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CD47: Target Therapy for Cancer

Author/Curator: Tilda Barliya

“A research team from Stanford University’s School of Medicine is now one step closer to uncovering a cancer treatment that could be applicable across the board in killing every kind of cancer tumor” (1). It appeared that their antibody-drug against the CD47 protein, enabled the shrinking of all tumor cells. After completing their animal studies the researchers now move into a human phase clinical trials. CD47 has been previously studied and evaluated for its role in multiple cells, some of this data however, is somewhat controversy. So where do we stand?

CD47

CD47 (originally named integrin-associated protein (IAP)) is a cell surface protein of the immunoglobulin (Ig) superfamily, which is heavily glycosylated and expressed by virtually all cells in the body and overexpressed in many types of cancer  including breast, ovarian, colon, prostate and others (3). CD47 was first recognized as a 50 kDa protein associated and copurified with the  Alpha-v-Beta-3 integrin in placenta and neutrophil granulocytes and later shown to have the capacity to regulate integrin function and the responsiveness of leukocytes to RGD-containing extracellular matrix proteins. CD47 has also been shown to be identical to the OA-3/OVTL3 antigen highly expressed on most ovarian carcinomas (4,5).

CD47 consists of an extracellular IgV domain, a five times transmembrane-spanning domain, and a short alternatively spliced cytoplasmic tail. In both humans and mice, the cytoplasmic tail can be found as four different splice isoforms ranging from 4 to 36 amino acids, showing different tissue expression patterns (3).

CD47 interactions (3, 6):

  • Thrombospondin-1 (TSP-1) – a secreted glycoprotein that plays a role in vascular development and angiogenesis. Binding of TSP-1 to CD47 influences several fundamental cellular functions including cell migration and adhesion, cell proliferation or apoptosis, and plays a role in the regulation of angiogenesis and inflammation.
  • Signal-regulatory protein-alpha (SIRPα) – an inhibitory transmembrane receptor present on myeloid cells. The CD47/SIRPα interaction leads to bidirectional signaling, resulting in different cell-to-cell responses including inhibition of phagocytosis, stimulation of cell-cell fusion, and T-cell activation.
  • Integrins – several membrane integrins, most commonly integrin avb3. These interactions result in CD47/integrin complexes that effect a range of cell functions including adhesion, spreading and migration

These interactions with multiple proteins and cells types create several important functions, which include:

  • Cell proliferation – cell proliferation is heavily dependent on cell type as both activation and loss of CD47 can result in enhanced proliferation. For example, activation of CD47 with TSP-1 in wild-type cells inhibits proliferation and reduces expression of stem cell transcription factors. In cancer cells however, activation of CD47 with TSP-1 increases proliferation of human U87 and U373 astrocytoma. it is likely that CD47 promotes proliferation via the PI3K/Akt pathway in cancerous cells but not normal cells (7).  Loss of CD47 allows sustained proliferation of primary murine endothelial cells and enables these cells to spontaneously reprogram to form multipotent embryoid body-like clusters (8).
  • Apoptosis – Ligation of CD47 by anti-CD47 mAbs was found to induce apoptosis in a number of different cell types (3). For example: Of the two SIRP-family members known to bind the CD47 IgV domain (SIRPα and SIRPγ), SIRPα as a soluble Fc-fusion protein does not induce CD47-dependent apoptosis, hile SIRPα or SIRPγ bound onto the surface of beads induces apoptosis through CD47 in Jurkat T cells and the myelomonocytic cell line U937.
  • Migration – CD47  role on cell migration was first demonstrated in neutrophils, these effects were shown to be dependent on avb3 integrins, which interact with and are activated by CD47 at the plasma membrane. In cancer, Blocking CD47 function has been shown to inhibit migration and metastasis in a variety of tumor models. Blockade of CD47 by neutralizing antibodies reduced migration and chemotaxis in response to collagen IV in melanomaprostate cancer and ovarian cancer-derived cells (9).
  • Angiogenesis – The mechanism of the anti-angiogenic activity of CD47 is not fully understood, but introduction of CD47 antibodies and TSP-1 have been shown to inhibit nitric oxide (NO)-stimulated responses in both endothelial and vascular smooth muscle cells (10). More so, CD47 signaling influences the SDF-1 chemokine pathway, which plays a role in angiogenesis (11). (12)
  • Inflammatory response – Interactions between endothelial cell CD47 and leukocyte SIRPγ regulate T cell transendothelial migration (TEM) at sites of inflammation. CD47 also functions as a marker of self on murine red blood cells which allows RBC to avoid phagocytosis. Tumor cells can also evade macrophage phagocytosis through the expression of CD47 (2, 13).

It appears that CD47 ligation induce different responses, depending on cell type and partner for ligation.

Therapeutic and clinical aspect of CD47 in human cancer:

CD47 is overexpressed in many types of human cancers  and its known function as a “don’t eat me” signal, suggests the potential for targeting the CD47-SIRPα pathway as a common therapy for human malignancies (2,13). Upregulation of CD47 expression in human cancers also appears to influence tumor growth and dissemination. First, increased expression of CD47 in several hematologic malignancies was found to be associated with a worse clinical prognosis, and in ALL to predict refractoriness to standard chemotherapies (13, 14-16). Second, CD47 was demonstrated to regulate tumor metastasis and dissemination in both MM and NHL (13, 17).

Efforts have been made to develop therapies inhibiting the CD47-SIRPα pathway, principally through blocking monoclonal antibodies directed against CD47, but also possibly with a recombinant SIRPα protein that can also bind and block CD47.

Figure 2

Chao MP et al. 2012 Combination strategies targeting CD47 in cancer

While monotherapies targeting CD47 were efficacious in several pre-clinical tumor models, combination strategies involving inhibition of the CD47-SIRPα pathway offer even greater therapeutic potential. Specifically, antibodies targeting CD47-SIRPα can be included in combination therapies with other therapeutic antibodies, macrophage-enhancing agents, chemo-radiation therapy, or as an adjuvant therapy to inhibit metastasis (13).

For example, anti-SIRPα antibody was found to potentiate  antibody-dependent cellular cytotoxicity (ADCC) mediated by the anti-Her2/Neu antibody trastuzumab against breast cancer cells (18).  CD47–SIRPα interactions and SIRPα signaling negatively regulate trastuzumab-mediated ADCC in vitro and antibody-dependent elimination of tumor cells in vivo

More so, chemo-radiation therapy-mediated upregulation of cell surface calreticulin may potentially augment the activity of anti-CD47 antibody. However, this approach may also lead to increased toxicity as cell surface calreticulin is expressed on non-cancerous cells undergoing apoptosis, a principle effect of chemo-radiation therapy (19).

Highlights:

  • Phagocytic cells, macrophages, regulate tumor growth through phagocytic clearance
  • CD47 binds SIRPα on phagocytes which delivers an inhibitory signal for phagocytosis
  • A blocking anti-CD47 antibody enabled phagocytic clearance of many human cancers
  • Phagocytosis depends on a balance of anti-(CD47) and pro-(calreticulin) signals
  • Anti-CD47 antibody synergized with an FcR-engaging antibody, such as rituximab

Summary

Evasion of immune recognition is a major mechanism by which cancers establish and propagate disease. Recent data has demonstrated that the innate immune system plays a key role in modulating tumor phagocytosis through the CD47-SIRPα pathway. Careful development of reagents that can block the CD47/SIRPα interaction may indeed be useful to treat many forms of cancer without having too much of a negative side effect in terms of inducing clearance of host cells. Therapeutic approaches inhibiting this pathway have demonstrated significant efficacy, leading to the reduction and elimination of multiple tumor types.

Dr. Weissman says: “We are now hopeful that the first human clinical trials of anti-CD47 antibody will take place at Stanford in mid-2014, if all goes wellClinical trials may also be done in the United Kingdom”. These clinical trials must be designed so that the data they generate will produce a valid scientific result!!!

REFERENCES

1. By Sara Gates:  Cancer Drug That Shrinks All Tumors Set To Begin Human Clinical Trials. http://www.huffingtonpost.com/2013/03/28/cancer-drug-shrinks-tumors_n_2972708.html

2. Willingham SB, Volkmer JP, Gentles AJ, Sahoo D, Dalerba P, Mitra SS, Wang J, Contreras-Trujillo H, Martin R, Cohen JD, Lovelace P, Scheeren FA, Chao MP, Weiskopf K, Tang C, Volkmer AK, Naik TJ, Storm TA, Mosley AR, Edris B, Schmid SM, Sun CK, Chua MS, Murillo O, Rajendran P, Cha AC, Chin RK, Kim D, Adorno M, Raveh T, Tseng D, Jaiswal S, Enger PØ, Steinberg GK, Li G, So SK, Majeti R, Harsh GR, van de Rijn M, Teng NN, Sunwoo JB, Alizadeh AA, Clarke MF, Weissman IL. The CD47-signal regulatory protein alpha (SIRPa) interaction is a therapeutic target for human solid tumors. Proc Natl Acad Sci U S A. 2012 Apr 24;109(17):6662-6667. http://www.pnas.org/content/early/2012/03/20/1121623109

3. Oldenborg PL. CD47: A Cell Surface Glycoprotein Which Regulates Multiple Functions of Hematopoietic Cells in Health and Disease. ISRN Hematology Volume 2013 (2013), Article ID 614619, 19 pages.  http://www.hindawi.com/isrn/hematology/2013/614619/

4. G. Campbell, P. S. Freemont, W. Foulkes, and J. Trowsdale, “An ovarian tumor marker with homology to vaccinia virus contains an IgV- like region and multiple transmembrane domains,”Cancer Research, vol. 52, no. 19, pp. 5416–5420, 1992. http://cancerres.aacrjournals.org/content/52/19/5416.long

5. L. G. Poels, D. Peters, Y. van Megen et al., “Monoclonal antibody against human ovarian tumor-associated antigens,” Journal of the National Cancer Institute, vol. 76, no. 5, pp. 781–791, 1986. http://www.ncbi.nlm.nih.gov/pubmed/3517452

6. CD47. Wikipedia. http://en.wikipedia.org/wiki/CD47

7. Sick E, Boukhari A, Deramaudt T, Rondé P, Bucher B, André P, Gies JP, Takeda K (February 2011). “Activation of CD47 receptors causes proliferation of human astrocytoma but not normal astrocytes via an Akt-dependent pathway”. Glia 59 (2): 308–319. http://www.ncbi.nlm.nih.gov/pubmed/21125662

8. Kaur S, Soto-Pantoja DR, Stein EV, Liu C, Elkahloun AG, Pendrak ML, Nicolae A, Singh SP, Nie Z, Levens D, Isenberg JS, Roberts DD.  “Thrombospondin-1 Signaling through CD47 Inhibits Self-renewal by Regulating c-Myc and Other Stem Cell Transcription Factors”Sci Rep 2013: 3: 1673. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3628113/

9. Shahan TA, Fawzi A, Bellon G, Monboisse JC, Kefalides NA. “Regulation of tumor cell chemotaxis by type IV collagen is mediated by a Ca(2+)-dependent mechanism requiring CD47 and the integrin alpha(V)beta(3)”. J. Biol. Chem 2000. 275 (7): 4796–4802. http://www.jbc.org/content/275/7/4796

10. Isenberg JS, Ridnour LA, Dimitry J, Frazier WA, Wink DA, Roberts DD. “CD47 is necessary for inhibition of nitric oxide-stimulated vascular cell responses by thrombospondin-1”. J. Biol. Chem  2006. 281 (36): 26069–26080.  http://www.jbc.org/content/281/36/26069

11. Smadja DM, d’Audigier C, Bièche I, Evrard S, Mauge L, Dias JV, Labreuche J, Laurendeau I, Marsac B, Dizier B, Wagner-Ballon O, Boisson-Vidal C, Morandi V, Duong-Van-Huyen JP, Bruneval P, Dignat-George F, Emmerich J, Gaussem P. “Thrombospondin-1 is a plasmatic marker of peripheral arterial disease that modulates endothelial progenitor cell angiogenic properties”. Arterioscler. Thromb. Vasc. Biol  2011. 31 (3): 551–559. http://atvb.ahajournals.org/content/31/3/551

12. G. D. Grossfeld, D. A. Ginsberg, J. P. Stein et al., “Thrombospondin-1 expression in bladder cancer: association with p53 alterations, tumor angiogenesis, and tumor progression,” Journal of the National Cancer Institute 1997 vol. 89, no. 3, pp. 219–227. http://www.scopus.com/record/display.url?eid=2-s2.0-18744423089&origin=inward&txGid=9C86356DDB0B6816ACCBF90F9CA44E92.WlW7NKKC52nnQNxjqAQrlA%3a2

13. Chao MP, Weissman IL, Majeti R. “The CD47-SIRPα pathway in cancer immune evasion and potential therapeutic implications”Curr. Opin. Immunol 2012. 24 (2): 225–32. http://www.sciencedirect.com/science/article/pii/S095279151200012Xhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3319521/

14. Majeti R, Chao MP, Alizadeh AA, Pang WW, Jaiswal S, Gibbs KD, Jr, van Rooijen N, Weissman IL. Cd47 is an adverse prognostic factor and therapeutic antibody target on human acute myeloid leukemia stem cells. Cell. 2009;138(2):286–299. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2726837/

15. Chao MP, Alizadeh AA, Tang C, Jan M, Weissman-Tsukamoto R, Zhao F, Park CY, Weissman IL, Majeti R. Therapeutic antibody targeting of cd47 eliminates human acute lymphoblastic leukemia.Cancer Res. 2011;71 (4):1374–1384. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041855/

16. Chao MP, Alizadeh AA, Tang C, Myklebust JH, Varghese B, Gill S, Jan M, Cha AC, Chan CK, Tan BT, Park CY, et al. Anti-cd47 antibody synergizes with rituximab to promote phagocytosis and eradicate non-hodgkin lymphoma. Cell. 2010;142(5):699–713. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2943345/

17. Chao MP, Tang C, Pachynski RK, Chin R, Majeti R, Weissman IL. Extranodal dissemination of non-hodgkin lymphoma requires cd47 and is inhibited by anti-cd47 antibody therapy. Blood.2011;118(18):4890–4901. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3208297/

18. Zhao XW, van Beek EM, Schornagel K, Van der Maaden H, Van Houdt M, Otten MA, Finetti P, Van Egmond M, Matozaki T, Kraal G, Birnbaum D, et al. Cd47-signal regulatory protein-alpha (sirpalpha) interactions form a barrier for antibody-mediated tumor cell destruction. Proc Natl Acad Sci U S A.2011;108(45):18342–18347. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3215076/

19. Obeid M, Tesniere A, Ghiringhelli F, Fimia GM, Apetoh L, Perfettini JL, Castedo M, Mignot G, Panaretakis T, Casares N, Metivier D, et al. Calreticulin exposure dictates the immunogenicity of cancer cell death. Nat Med. 2007;13(1):54–61. http://www.ncbi.nlm.nih.gov/pubmed/17187072

Other related articles on this Open Access Online Scientific Journal include the following:

I. By: Larry Bernstein MD. Treatment for Metastatic HER2 Breast Cancer https://pharmaceuticalintelligence.com/2013/03/03/treatment-for-metastatic-her2-breast-cancer/

II. By: Tilda Barliya PhD. Colon Cancer.  https://pharmaceuticalintelligence.com/2013/04/30/colon-cancer/

III. By: Ritu Saxena PhD. In focus: Triple Negative Breast Cancer. https://pharmaceuticalintelligence.com/2013/01/29/in-focus-triple-negative-breast-cancer/

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Curator: Aviva Lev-Ari, PhD, RN

First post published on 4/30/2012

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On 4/30/2013 – Great News to Share

News from the National Academy of Sciences

Date: April 30, 2013

FOR IMMEDIATE RELEASE

National Academy of Sciences Members and Foreign Associates Elected

The National Academy of Sciences announced today the election of 84 new members and 21 foreign associates from 14 countries in recognition of their distinguished and continuing achievements in original research.

Those elected today bring the total number of active members to 2,179 and the total number of foreign associates to 437. Foreign associates are nonvoting members of the Academy, with citizenship outside the United States.

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We congratulate OUR BOARD MEMBER for being elected 

Feldman, Marcus W.

Director, Morrison Institute for Population and Resource Studies, and Burnet C. and Mildred Finley Wohlford Professor of Biological Sciences, department of biological sciences, Stanford University, Stanford, Calif.

http://www.nasonline.org/news-and-multimedia/news/2013_04_30_NAS_Election.html

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Centers of Excellence in Genomic Sciences (CEGS): NHGRI to Fund New Center (CEGS) on the Brain: Mental Disorders and the Nervous System

April 16, 2013

NEW YORK (GenomeWeb News) – The National Human Genome Research Institute plans to fund new Centers of Excellence in Genomic Sciences, or CEGS, to create interdisciplinary teams that pursue innovative genome-based approaches to address biomedical problems and to understanding the basis of biological systems.

NHGRI, along with support from the National Institute of Mental Health, expects to provide up to $2 million per year for each of the new CEGS it funds, and plans to award up to four new awards each year.

Although these CEGS may pursue a wide range of research objectives, NIMH will support the program because it wants to fund research using novel genomic approaches that can accelerate the understanding of the genetic basis of mental disorders and the nervous systemNHGRI said on Friday.

The CEGS program was created to use the new knowledge and technologies that resulted from the Human Genome Project and subsequent genomics research to develop new tools, methods, and concepts that apply to human biology and disease.
CEGS grantees are expected to be innovative, to focus on a critical issue in genomic science, to use multiple investigators working under one leader, to work toward a specific outcome, and to tackle challenging aspects of problems that may have impeded previous research efforts.

Further, they are supposed to bolster the pool of professional scientists and engineers who are trained in genomics through offering educational programs, and they are expected to address the shortage of scientists from underrepresented minority communities by developing recruiting programs that encourage minority community members to become independent genomics investigators.

The technologies and methods the CEGS investigators develop should be applicable to a wide range of cell types and organisms, and they should be scalable and expandable so they may apply to other model systems, according to NHGRI’s funding opportunity announcement.

Recent CEGS centers include

  • Caltech’s Center for In Toto Genomic Analysis of Vertebrate Development;
  • Harvard University’s Center for Transcriptional Consequences of Human Genetic Variation;
  • Johns Hopkins University’s Center for the Epigenetics of Common Human Disease;
  • Stanford University’s Center for the Genomic Basis of Vertebrate Diversity;
  • Arizona State University’s Microscale Life Sciences Center;
  • Medical College of Wisconsin, Milwaukee’s Center of Excellence in Genomics Science;
  • The University of North Carolina at Chapel Hill‘s CISGen center;
  • The Broad Institute’s Center for Cell Circuits;
  • Yale University’s Center for the Analysis of Human Genome Using Integrated Technologies; and
  • Dana-Farber Cancer Institute‘s Center for Genomic Analysis of Network Perturbations in Human Disease.

 http://www.genomeweb.com/nhgri-fund-new-centers-excellence-genomic-sciences

Center for In Toto Genomic Analysis of Vertebrate Development

P50 HG004071
Marianne Bronner-Fraser
California Institute of Technology, Pasadena, Calif.

This Center of Excellence in Genomic Science (CEGS) assembles a multidisciplinary group of investigators to develop innovative technologies with the goal of imaging and mutating every developmentally important vertebrate gene. Novel “in toto imaging” tools make it possible to use a systems-based approach for analysis of gene function in developing vertebrate embryos in real time and space. These tools can digitize in vivo data in a systematic, high-throughput, and quantitative fashion. Combining in toto imaging with novel gene traps permits a means to rapidly screen for developmentally relevant expression patterns, followed by the ability to immediately mutagenize genes of interest. Initially, key technologies will be developed and tested in the zebrafish embryo due to its transparency and the ability to obtain rapid feedback. Once validated, these techniques will be applied to an amniote, the avian embryo, due to several advantages including accessibility and similarity to human embryogenesis. Finally, to monitor alterations in gene expression in normal and mutant embryos, we will develop new techniques for in situ hybridization that permit simultaneous analysis of multiple marker genes in a sensitive and potentially quantitative manner. Our goal is to combine real time analysis of gene expression on a genome-wide scale coupled with the ability to mutate genes of interest and examine global alterations in gene expression as a result of gene loss. Much of the value will come from the development of new and broadly applicable technologies. In contrast to a typical technology development grant, however, there will be experimental fruit emerging from at least two vertebrate systems (zebrafish and avian). The following aims will be pursued: Specific Aim 1: Real-time “in toto” image analysis of reporter gene expression; Specific Aim 2: Comprehensive spatiotemporal analysis of gene function of the developing vertebrate embryo using the FlipTrap approach for gene trapping; Specific Aim 3: Design of quantitative, multiplexed ‘hybridization chain reaction’ (HCR) amplifiers for in vivo imaging with active background suppression; Specific Aim 4: Data analysis and integration of data sets to produce a “digital” fish and a “digital” bird. The technologies and the resulting atlases will be made broadly available via electronic publication.

Center Web Site: California Institute of Technology Center of Excellence in Genomic Science

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Causal Transcriptional Consequences of Human Genetic Variation

P50 HG005550
George M. Church
Harvard University, Cambridge, Mass.

The Center for Transcriptional Consequences of Human Genetic Variation (CTCHGV) will develop innovative and powerful genetic engineering methods and use them to identify genetic variations that causally control gene transcription levels. Genome Wide Association Studies (GWAS) find many variations associated with disease and other phenotypes, but the variations that may actually cause these conditions are hard to identify because nearby variations in the same haplotype blocks consistently co-occur with them in human populations, so that specifically causative ones cannot be distinguished. About 95% of GWAS variations are not in gene coding regions, and many of these presumably associate with altered gene expression levels. CTCHGV will identify the variations that directly control gene expression by engineering precise combinations of changes to gene regulatory regions that break down the haplotype blocks, allowing each variations’ effect on gene expression to be discerned independently of the others. To perform this analysis, CTCHGV will extract ~100kbps gene regulatory regions from human cell samples, create precise variations in them in E. coli, and re-introduce the altered regions back into human cells, using zinc finger nucleases (ZFNs) to efficiently induce recombination. CTCHGV will target 1000 genes for this analysis (Aim 1), and will use human induced Pluripotent Stem cells (iPS) to study the effects of variations in diverse human cell types (Aim 2). To explore the effects of variations in complex human tissues, CTCHGV will develop methods of measuring gene expression at transcriptome-wide levels in many single cells, including in situ in structured tissues (Aim 3). Finally, CTCHGV will develop novel advanced technologies that integrate DNA sequencing and synthesis to construct thousands of large DNA constructs from oligonucleotides, that enable very precise targeting and highly efficient performance of ZFNs, and that enable cells to be sorted on the basis of morphology as well as fluorescence and labeling (Aim 4). CTCHGV will also develop direct oligo-mediated engineering of human cells, and create “marked allele” iPS that will enable easy ascertainment of complete exon distributions for many pairs of gene alleles in many cell types.

Center Web Site: Center for Causal Transcriptional Consequences of Human Genetic Variation (CTCHGV)

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Center for the Epigenetics of Common Human Disease

P50 HG003233
Andrew P. Feinberg
Johns Hopkins University, Baltimore
(co-funded by National Institute of Mental Health)

Epigenetics, the study of non-DNA sequence-related heredity, is at the epicenter of modern medicine because it can help to explain the relationship between an individual’s genetic background, the environment, aging, and disease. The Center for the Epigenetics of Common Human Disease was created in 2004 to begin to develop the interface between epigenetics and epidemiologic-based phenotype studies, recognizing that epigenetics requires new ways of thinking about disease. We created a highly interdisciplinary group of faculty and trainees, including molecular biologists, biostatisticians, epidemiologists, and clinical investigators. We developed novel approaches to genome-wide DNA methylation (DNAm) analysis, allele-specific expression, and new statistical epigenetic tools. Using these tools, we discovered that most variable DNAm is in neither CpG islands nor promoters, but in what we term “CpG island shores,” regions of lower CpG density up to several kb from islands, and we have found altered DNAm in these regions in cancer, depression and autism. In the renewal period, we will develop the novel field of epigenetic epidemiology, the relationship between epigenetic variation, genetic variation, environment and phenotype. We will continue to pioneer genome-wide epigenetic technology that is cost effective for large scale analysis of population-based samples, applying our knowledge from the current period to second-generation sequencing for epigenetic measurement, including DNAm and allele-specific methylation. We will continue to pioneer new statistical approaches for quantitative and binary DNAm assessment in populations, including an Epigenetic Barcode. We will develop Foundational Epigenetic Epidemiology, examining: time-dependence, heritability and environmental relationship of epigenetic marks; heritability in MZ and DZ twins; and develop an epigenetic transmission disequilibrium test. We will then pioneer Etiologic Epigenetic Epidemiology, by integrating novel genome-wide methylation scans (GWMs) with existing Genome-Wide Association Study (GWAS) and epidemiologic phenotype data, a design we term Genome-Wide Integrated Susceptibility (GWIS), focusing on bipolar disorder, aging, and autism as paradigms for epigenetic studies of family-based samples, longitudinal analyses, and parent-of-origin effects, respectively. This work will be critical to realizing the full value of previous genetic and phenotypic studies, by developing and applying molecular and statistical tools necessary to integrate DNA sequence with epigenetic and environmental causes of disease.

Center Web Site: Center of Excellence in Genomic Science at Johns Hopkins

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Genomic Basis of Vertebrate Diversity

P50 HG002568
David M. Kingsley
Stanford University, Stanford, Calif.

The long-term goal of this project is to understand the genomic mechanisms that generate phenotypic diversity in vertebrates. Rapid progress in genomics has provided nearly complete sequences for several organisms. Comparative analysis suggests many fundamental pathways and gene networks are conserved between organisms. And yet, the morphology, physiology, and behavior of different species are obviously and profoundly different. What are the mechanisms that generate these key differences? Are unique traits controlled by few or many genetic changes? What kinds of changes? Are there particular genes and mechanisms that are used repeatedly when organisms adapt to new environments? Can better understanding of these mechanisms help explain dramatic differences in disease susceptibility that also exist between groups? The Stanford CEGS will use an innovative combination of approaches in fish, mice, and humans to identify the molecular basis of major phenotypic change in natural populations of vertebrates. Specific aims include: 1) cross stickleback fish and develop a genome wide map of the chromosomes, genes, and mutations that control a broad range of new morphological, physiological, and behavioral traits in natural environments; 2) test which population genetic measures provide the most reliable “signatures of selection” surrounding genes that are known to have served as the basis of parallel adaptive change in many different natural populations around the world; 3) assemble the stickleback proto Y chromosome and test whether either sex or autosomal rearrangements play an important role in generating phenotypic diversity, or are enriched in genomic regions that control phenotypic change; 4) test whether particular genes and mechanisms are used repeatedly to control phenotypic change in many different vertebrates. Preliminary data suggests that mechanisms identified as the basis of adaptive change in natural fish populations may be broadly predictive of adaptive mechanisms across a surprisingly large range of animals, including humans. Genetic regions hypothesized to be under selection in humans will be compared to genetic regions under selection in fish. Regions predicted to play an important role in natural human variation and disease susceptibility will be modeled in mice, generating new model systems for confirming functional variants predicted from human population genetics and comparative genomics.

Center Web Site: Stanford Genome Evolution Center

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Microscale Life Sciences Center

P50 HG002360
Deirdre R. Meldrum
Arizona State University, Tempe

Increasingly, it is becoming apparent that understanding, predicting, and diagnosing disease states is confounded by the inherent heterogeneity of in situ cell populations. This variation in cell fate can be dramatic, for instance, one cell living while an adjacent cell dies. Thus, in order to understand fundamental pathways involved in disease states, it is necessary to link preexisting cell state to cell fate in the disease process at the individual cell level.

The Microscale Life Sciences Center (MLSC) at the University of Washington is focused on solving this problem, by developing cutting-edge microscale technology for high throughput genomic-level and multi-parameter single-cell analysis, and applying that technology to fundamental problems of biology and health. Our vision is to address pathways to disease states directly at the individual cell level, at increasing levels of complexity that progressively move to an in vivo understanding of disease. We propose to apply MLSC technological innovations to questions that focus on the balance between cell proliferation and cell death. The top three killers in the United States, cancer, heart disease and stroke, all involve an imbalance in this cellular decision-making process. Because of intrinsic cellular heterogeneity in the live/die decision, this fundamental cellular biology problem is an example of one for which analysis of individual cells is essential for developing the link between genomics, cell function, and disease. The specific systems to be studied are proinflammatory cell death (pyroptosis) in a mouse macrophage model, and neoplastic progression in the Barrett’s Esophagus (BE) precancerous model. In each case, diagnostic signatures for specific cell states will be determined by measuring both physiological (cell cycle, ploidy, respiration rate, membrane potential) and genomic (gene expression profiles by single-cell proteomics, qRT-PCR and transcriptomics; LOH by LATE-PCR) parameters. These will then be correlated with cell fate via the same sets of measurements after a challenge is administered, for instance, a cell death stimulus for pyroptosis or a predisposing risk factor challenge (acid reflux) for BE. Ultimately, time series will be taken to map out the pathways that underlie the live/die decision.

Finally, this information will be used as a platform to define cell-cell interactions at the single-cell level, to move information on disease pathways towards greater in vivo relevance. New technology will be developed and integrated into the existing MLSC Living Cell Analysis cassette system to support these ambitious biological goals including 1) automated systems for cell placement, off-chip device interconnects, and high throughput data analysis with user friendly interfaces; 2) new optical and electronic sensors based on a new detection platform, new dyes and nanowires; and 3) new micromodules for single-cell qRT-PCR, LATE-PCR for LOH including single-cell pyrosequencing, on-chip single-cell proteomics, and single-cell transcriptomics using barcoded nanobeads.

Collaborating InstitutionsFred Hutchison Cancer Research Center, Brandeis University, University of Washington.

Center Web Site: Microscale Life Sciences Center

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Wisconsin Center of Excellence in Genomics Science

P50 HG004952
Michael Olivier
Medical College of Wisconsin, Milwaukee

The successful completion of the human genome and model organism sequences has ushered in a new era in biological research, with attention now focused on understanding the way in which genome sequence information is expressed and controlled. The focus of this proposed Wisconsin Center of Excellence in Genomics Science is to facilitate understanding of the complex and integrated regulatory mechanisms affecting gene transcription by developing novel technology for the comprehensive characterization and quantitative analysis of proteins interacting with DNA. This new technology will help provide for a genome-wide functional interpretation of the underlying mechanisms by which gene transcriptional regulation is altered during biological processes, development, disease, and in response to physiological, pharmacological, or environmental stressors. The development of chromatin immunoprecipitation approaches has allowed identification of the specific DNA sequences bound by proteins of interest. We propose to reverse this strategy and develop an entirely novel technology that will use oligonucleotide capture to pull down DNA sequences of interest, and mass spectrometry to identify and characterize the proteins and protein complexes bound and associated with particular DNA regions. This new approach will create an invaluable tool for deciphering the critical control processes regulating an essential biological function. The proposed interdisciplinary and multi-institutional Center of Excellence in Genomics Science combines specific expertise at the Medical College of Wisconsin, the University of Wisconsin Madison, and Marquette University. Technological developments in four specific areas will be pursued to develop this new approach: (1) cross-linking of proteins to DNA and fragmentation of chromatin; (2) capture of the protein-DNA complexes in a DNA sequence-specific manner; (3) mass spectrometry analysis to identify and quantify bound proteins; and (4) informatics to develop tools enabling the global analysis of the relationship between changes in protein-DNA interactions and gene expression. The Center will use carefully selected biological systems to develop and test the technology in an integrated genome-wide analysis platform that includes efficient data management and analysis tools. As part of the Center mission, we will combine our technology development efforts with an interdisciplinary training program for students and fellows designed to train qualified scientists experienced in cutting-edge genomics technology. Data, technology, and software will be widely disseminated by multiple mechanisms including licensing and commercialization activities.

Collaborating InstitutionsUniversity of Wisconsin-Madison, Marquette University

Center Web Site: Wisconsin Center of Excellence in Genomic Science

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CISGen

P50 MH090338
Fernando Pardo-Manuel de Villena
University of North Carolina, Chapel Hill

p>In this application, we propose a highly ambitious yet realistically attainable goal: to align existing expertise at UNC-Chapel Hill into a CEGS called CISGen. The overarching purpose of CISGen is to develop as a resource and to exploit the utility of the murine Collaborative Cross (CC) mouse model of the heterogeneous human population to delineate genetic and environmental determinants of complex phenotypes drawn from psychiatry, which are among the most intractable set of problems in all of biomedicine. Psychiatric disorders present a paradox – the associated morbidity, mortality, and costs are enormous and yet, despite over a century of scientific study, there are few hard facts about the etiology of the core diseases. Although our GWAS meta- analyses are in progress, early results suggest that strong and replicable findings may be elusive. Therefore, our proposal provides a complementary approach to the study of fundamental psychiatric phenotypes.

We propose a particularly challenging definition of success – we will identify high probability etiological models (which can be realistically complex) and then prove the predictive capacity of these models by generating novel strains of mice predicted to be at very high risk for the phenotype. Once validated, these high confidence models can then be tested in subsequent human studies – we do not propose human extension studies in CISGen but this is achievable for the investigators and their colleagues. Data collected in CISGen would be a valuable resource to the wider scientific community and could be applied to a large set of biological problems and these data can rapidly add to the knowledge base for any new genomewide association study (GWAS) finding. Delivery of sophisticated and user-friendly databases are a key component of CISGen.

Accomplishing this overarching goal requires an exceptional diversity of scientific expertise – psychiatry, human genetics, mouse behavior, mouse genetics, statistical genetics, computational biology, and systems biology. Experts in these disciplines are deeply involved in CISGen and are committed to the projects described herein. Successful integration of these diverse fields is non-trivial; however, all scientists on this application have had extensive interactions over the past five years, already know how to work together, and have a working knowledge of their colleagues’ expertise. UNC-Chapel Hill has an intense commitment to inter- disciplinary genomics research and provides a fertile backdrop for 21st century projects like CISGen.

Collaborating InstitutionsThe Jackson Laboratory, North Carolina State University, University of Texas at Arlington

Center Web Site: Center for Integrated Systems Genomics at UNC (CISGen)

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Center for Cell Circuits

P50 HG006193
Aviv Regev
The Broad Institute, Inc., Cambridge, Mass.

Systematic reconstruction of genetic and molecular circuits in mammalian cells remains a significant, largescale and unsolved challenge in genomics. The urgency to address it is underscored by the sizeable number of GWAS-derived disease genes whose functions remain largely obscure, limiting our progress towards biological understanding and therapeutic intervention. Recent advances in probing and manipulating cellular circuits on a genomic scale open the way for the development of a systematic method for circuit reconstruction. Here, we propose a Center for Cell Circuits to develop the reagents, technologies, algorithms, protocols and strategies needed to reconstruct molecular circuits. Our preliminary studies chart an initial path towards a universal strategy, which we will fully implement by developing a broad and integrated experimental and computational toolkit. We will develop methods for comprehensive profiling, genetic perturbations and mesoscale monitoring of diverse circuit layers (Aim 1). In parallel, we will develop a computational framework to analyze profiles, derive provisional models, use them to determine targets for perturbation and monitoring, and evaluate, refine and validate circuits based on those experiments (Aim 2). We will develop, test and refine this strategy in the context of two distinct and complementary mammalian circuits. First, we will produce an integrated, multi-layer circuit of the transcriptional response to pathogens in dendritic cells (Aim 3) as an example of an acute environmental response. Second, we will reconstruct the circuit of chromatin factors and non-coding RNAs that control chromatin organization and gene expression in mouse embryonic stem cells (Aim 4) as an example of the circuitry underlying stable cell states. These detailed datasets and models will reveal general principles of circuit organization, provide a resource for scientists in these two important fields, and allow computational biologists to test and develop algorithms. We will broadly disseminate our tools and methods to the community, enabling researchers to dissect any cell circuit of interest at unprecedented detail. Our work will open the way for reconstructing cellular circuits in human disease and individuals, to improve the accuracy of both diagnosis and treatment.

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Analysis of Human Genome Using Integrated Technologies

P50 HG002357
Michael P. Snyder
Yale University, New Haven, Conn.

We propose to establish a center to build genomic DNA arrays and develop novel technologies that will use these arrays for the large-scale functional analysis of the human genome. 0.3-1.4 kb fragments of nonrepetitive DNA from each of chromosomes 22, 21, 20, 19,7, 17, and perhaps the X chromosome will be prepared by PCR and attached to microscope slides. The arrays will be used to develop technologies for the large-scale mapping of 1) Transcribed sequences. 2) Binding sites of chromosomal proteins. 3) Origins of replication. 4) Genetic mutation and variation. A web-accessible database will be constructed to house the information generated in this study; data from other studies will also be integrated into the database. The arrays and technologies will be made available throughout both the Yale University and the larger scientific community. They will be integrated into our training programs for postdoctoral fellows, graduate students and undergraduates at Yale. We expect these procedures to be applicable to the analysis of the entire human genome and the genomes of many other organisms.

Center Web Site: Yale University Center for Excellence in Genomic Science

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Genomic Analysis of the Genotype-Phenotype Map

P50 HG002790
Simon Tavaré
University of Southern California, Los Angeles

Our Center, which started in 2003, focused on implications of haplotype structure in the human genome. Since that time, there have been extraordinary advances in genomics: Genome-wide association studies using single nucleotide polymorphisms and copy number variants are now commonplace, and we are rapidly moving towards whole-genome sequence data for large samples of individuals. Our Center has undergone similar dramatic changes. While the underlying theme remains the same — making sense of genetic variation — our focus is now explicitly on how we can use the heterogeneous data produced by modern genomics technologies to achieve such an understanding. The overall goal of our proposal is to develop an intellectual framework, together with computational and statistical analysis tools, for illuminating the path from genotype to phenotype, and for predicting the latter from the former. We will address three broad questions related to this problem: 1) How do we infer mechanisms by which genetic variation leads to changes in phenotype? 2) How do we improve the design, understanding and interpretation of association studies by exploiting prior information? 3) How do we identify general principles about the genotype-phenotype map? We will approach these questions through a series of interrelated projects that combine computational and experimental methods, explored in Arabidopsis, Drosophila and human, and involve a wide range of researchers including molecular biologists, population geneticists, genetic epidemiologists, statisticians, computer scientists, and mathematicians.

Collaborating InstitutionsUniversity of Utah

Center Web Site: The USC Center of Excellence in Genomic Science

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Genomic Analysis of Network Perturbations in Human Disease

P50 HG004233
Marc Vidal
Dana-Farber Cancer Institute, Boston

Genetic differences between individuals can greatly influence their susceptibility to disease. The information originating from the Human Genome Project (HGP), including the genome sequence and its annotation, together with projects such as the HapMap and the Human Cancer Genome Project (HCGP) have greatly accelerated our ability to find genetic variants and associate genes with a wide range of human diseases. Despite these advances, linking individual genes and their variations to disease remains a daunting challenge. Even where a causal variant has been identified, the biological insight that must precede a strategy for therapeutic intervention has generally been slow in coming. The primary reason for this is that the phenotypic effects of functional sequence variants are mediated by a dynamic network of gene products and metabolites, which exhibit emergent properties that cannot be understood one gene at a time. Our central hypothesis is that both human genetic variations and pathogens such as viruses influence local and global properties of networks to induce “disease states.” Therefore, we propose a general approach to understanding cellular networks based on environmental and genetic perturbations of network structure and readout of the effects using interactome mapping, proteomic analysis, and transcriptional profiling. We have chosen a defined model system with a variety of disease outcomes: viral infection. We will explore the concept that one must understand changes in complex cellular networks to fully understand the link between genotype, environment, and phenotype. We will integrate observations from network-level perturbations caused by particular viruses together with genome-wide human variation datasets for related human diseases with the goal of developing general principles for data integration and network prediction, instantiation of these in open-source software tools, and development of testable hypotheses that can be used to assess the value of our methods. Our plans to achieve these goals are summarized in the following specific aims: 1. Profile all viral-host protein-protein interactions for a group of viruses with related biological properties. 2. Profile the perturbations that viral proteins induce on the transcriptome of their host cells. 3. Combine the resulting interaction and perturbation data to derive cellular network-based models. 4. Use the developed models to interpret genome-wide genetic variations observed in human disease, 5. Integrate the bioinformatics resources developed by the various CCSG members within a Bioinformatics Core for data management and dissemination. 6. Building on existing education and outreach programs, we plan to develop a genomic and network centered educational program, with particular emphasis on providing access for underrepresented minorities to internships, workshop and scientific meetings.

Center Web SiteCenter for Cancer Systems Biology (CCSB) Center of Excellence in Genomic Science

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Genomics & Genetics of Cardiovascular Disease Diagnoses: A Literature Survey of AHA’s Circulation Cardiovascular Genetics, 3/2010 – 3/2013

 

Curators: Aviva Lev-Ari, PhD, RN and Larry H. Bernstein, MD, FCAP

 

348 articles that appeared in AHA’s Circulation Cardiovascular Genetics, 3/2010 – 3/2013 were classified by the curators of this article into the following TEN categories. The first 9, represent DIAGNOSES of cardiovascular diseases, the last, deals with Pharmacogenomics.

The Cardiovascular Diagnoses that were covered in the period of 3/2010 – 3/2013, include the following:

  • Preventative Cardiology
  • MicroRNA in Serum as Bimarker for Cardiovascular Pathologies: acute myocardial infarction, viral myocarditis, diastolic dysfunction, and acute heart failure
  • Genetic Determinants of Potassium Sensitivity and Hypertension
  • Heart and Aging Research in Genomic Epidemiology: 1700 MIs and 2300 coronary heart disease events among about 29 000 eligible patients
  • Genetics of CVD and Hyperlipidemia, Hyper Cholesterolemia, Metabolic Syndrome
  • Genomics and Valvular Disease
  • Pharmacogenomics

Introductions

Larry H. Bernstein, MD, FCAP

 

The curation of this large amount of material in 10 categories begins with a first chapter on preventative cardiology, which has had much public attention for the last decade.  Much of the concern with preventive cardiology has emphasized diet and exercise.  There is much to be said about this in articles not yet written.  However, there are several decades of research on the amino acid composition of foods, and the essential fatty acids, that indicates an essential balance between proinflammatory and antiinflammatory fatty acids in polyunsaturated fatty acids, and of the harmful effects of saturated fats.  There is also much to be said of essential amino acids, and in particular, those essential for methylation processes, and sulfur metabolism.

The next eight chapters are all concerned with genomics in cardiovascular disease.  This is in no small part a follow up on the completion of the genetic code in 2003, a seminal event.  Let us look at these in clusters.

[1]   microRNA in serum is now considered for a biomarker for cardiovascular disease.  It can be measured at very low levels, but we don’t yet know where it fits.   It might be more revealing once we understand the adaptive mechanism in development of congestive heart failure, renal hypertension, and post-genomic events.

[2]  It appears to me that potassium sensitivity and hypertension approached from the genomic side is more complicate.  Why is that?   The kidney excretes a sodium load and in metabolic acidosis, the serum potassium rises with a metabolic acidemia that can’t be compensated by the respiratory loss of CO2 through the carbonic anhydrase mechanism.

[3]  Heart and aging research is a rich area for work on the long term post-genomic changes, and it involves a large population base.

[4][5]  The genomics of cardiac dysrrhytmias and cardiomyopathies will open new doors into our understanding of the mechanisms of these diseases, and perhaps find therapeutic targets.  There has been a large volume of work on lipid synthesis, the role of the liver in generating apolipoproteins, and this has new answers on the way.  The most important feature, not readily accepted is the measurement of particles, which has now been done by a monoclonal antibody.  Metabolic syndrome brings together adipose tissue metabolism, endocrine and changes in CRP and IL-1.

[6]   Vascular pathologies and coagulation, hyperviscosity has had an enormous increase in intensity of research.  The concept of plaque rupture to account for all AMIs is being modified, and the high sensitivity cardio-specific troponins have become the most widely use test.

[7]  The genomics of valvular disease fits with the increased surgical procedures for valvular disease related to atheroschlerosis and advent of minimally invasive surgical procedures for the reapir and replacement of valves, procedure called TAVR vs. Openhealrt surgery for valve replacement.

[8]  Inherited cardiovascular disease is an older family of disorders, going back to Victor McKusik, and also the “Blue Baby” operation, both at Johns Hopkins.

[9] Pharmacogenomics is a vary active field of investigation and has uncovered inter-individual differences in handling Warfarin as a starter.

 

 

Preventative Cardiology

 

Methods in Genetics and Clinical Interpretation Randomized Trial of Personal Genomics for Preventive Cardiology Design and Challenges

Joshua W. Knowles, MD, PhD, Themistocles L. Assimes, MD, PhD, Michaela Kiernan, PhD, Aleksandra Pavlovic, BS, Benjamin A. Goldstein, PhD, Veronica Yank, MD, Michael V. McConnell, MD, Devin Absher, PhD, Carlos Bustamante, PhD, Euan A. Ashley, MD, DPhil and John P.A. Ioannidis, MD, DSc

Author Affiliations

From the Division of Cardiovascular Medicine (J.W.K., T.L.A., A.P., M.V.M., E.A.A.), Stanford Prevention Research Center (M.K., V.Y., J.P.A.I.), Division of General Medical Disciplines (V.Y.), Department of Genetics (C.B.), Department of Health Research and Policy (J.P.A.I.), Stanford University School of Medicine, Stanford, CA; Quantitative Sciences Unit, Stanford University School of Medicine, Palo Alto, CA (B.A.G.); HudsonAlpha Institute for Biotechnology, Huntsville, AL (D.A.); Department of Statistics, Stanford University School of Humanities and Sciences, Stanford, CA (J.P.A.I.).

Correspondence to Joshua W. Knowles, MD, PhD, Stanford University School of Medicine, Division of Cardiovascular Medicine, Falk CVRC, 300 Pasteur Dr, Stanford, CA 94305. E-mail knowlej@stanford.edu

Background

Genome-wide association studies (GWAS) have identified more than 1500 disease-associated single nucleotide polymorphisms (SNPs), including many related to atherosclerotic cardiovascular disease (CVD). Associations have been found for most traditional risk factors (TRFs), including lipids,1,2 blood pressure/hypertension,3,4 weight/body mass index,5,6 smoking behavior,7 and diabetes.8–13 GWAS have also identified susceptibility variants for coronary heart disease (CHD). The first and, so far, strongest of these signals was found in the 9p21.3 locus, where common variants in this region increase the relative risk of CVD by 15% to 30% per risk allele in most race/ethnic groups.13–20 Subsequent large-scale GWAS meta-analyses and replication studies in largely white/European populations have led to the reliable identification of an additional 26 loci conferring susceptibility to CHD,2,20–23 all with substantially lower effects sizes compared with the 9p21 locus. Many of these CVD susceptibility loci appear to be conferring risk independent of TRFs and thus cannot currently be assessed by surrogate clinical measures (Table 1). Among the 27 independent loci identified in the most recent large meta-analyses of CVD, 21 were reported not to be associated with any of the TRFs.20,21

 SOURCE

Circulation: Cardiovascular Genetics 2012; 5: 368-376

doi: 10.1161/ CIRCGENETICS.112.962746

 

 

MicroRNA in Serum as Bimarker for Cardiovascular Pathologies: acute myocardial infarction, viral myocarditis,  diastolic dysfunction, and acute heart failure

Increased MicroRNA-1 and MicroRNA-133a Levels in Serum of Patients With Cardiovascular Disease Indicate Myocardial Damage

 

Yasuhide Kuwabara, MD, Koh Ono, MD, PhD, Takahiro Horie, MD, PhD, Hitoo Nishi, MD, PhD, Kazuya Nagao, MD, PhD, Minako Kinoshita, MD, PhD, Shin Watanabe, MD, PhD, Osamu Baba, MD, Yoji Kojima, MD, PhD, Satoshi Shizuta, MD, Masao Imai, MD, Toshihiro Tamura, MD, Toru Kita, MD, PhD and Takeshi Kimura, MD, PhD

Author Affiliations

From the Department of Cardiovascular Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan (Y. Kuwabara, K.O., T.H., H.N., K.N., M.K., S.W., O.B., Y. Kojima, S.S., M.I., T.T., T. Kimura); and Kobe City Medical Center General Hospital, Kobe, Japan (T. Kita).

Correspondence to Koh Ono, MD, PhD, Department of Cardiovascular Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-kawahara-cho, Sakyo-ku, Kyoto, Japan 606-8507. E-mail kohono@kuhp.kyoto-u.ac.jp

 

Abstract

Background—Recently, elevation of circulating muscle-specific microRNA (miRNA) levels has been reported in patients with acute myocardial infarction. However, it is still unclear from which part of the myocardium or under what conditions miRNAs are released into circulating blood. The purpose of this study was to identify the source of elevated levels of circulating miRNAs and their function in cardiovascular diseases.

Conclusions—These results suggest that elevated levels of circulating miR-133a in patients with cardiovascular diseases originate mainly from the injured myocardium. Circulating miR-133a can be used as a marker for cardiomyocyte death, and it may have functions in cardiovascular diseases.

SOURCE:

Circulation: Cardiovascular Genetics. 2011; 4: 446-454

Published online before print June 2, 2011,

doi: 10.1161/ CIRCGENETICS.110.958975

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Circulating MicroRNA-208b and MicroRNA-499 Reflect Myocardial Damage in Cardiovascular Disease

Maarten F. Corsten, MD, Robert Dennert, MD, Sylvia Jochems, BSc, Tatiana Kuznetsova, MD, PhD, Yvan Devaux, PhD, Leon Hofstra, MD, PhD, Daniel R. Wagner, MD, PhD, Jan A. Staessen, MD, PhD, Stephane Heymans, MD, PhD and Blanche Schroen, PhD

Author Affiliations

From the Center for Heart Failure Research (M.F.C., R.D., S.J., S.H., B.S.), Cardiovascular Research Institute, Maastricht, The Netherlands; the Division of Hypertension and Cardiovascular Rehabilitation (T.K., J.A.S.), Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium and Department of Epidemiology, Maastricht University Medical Center, Maastricht, The Netherlands; Centre de Recherche Public–Santé, Luxembourg (Y.D., D.R.W.), Luxembourg; Maastricht University Medical Center (L.H.), Maastricht, The Netherlands; and Centre Hospitalier Luxembourg (D.R.W.), Luxembourg.

Correspondence to Blanche Schroen, PhD, Center for Heart Failure Research, Cardiovascular Research Institute Maastricht, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands. E-mail b.schroen@cardio.unimaas.nl

Drs Heymans and Schroen contributed equally to this work.

Abstract

Background— Small RNA molecules, called microRNAs, freely circulate in human plasma and correlate with varying pathologies. In this study, we explored their diagnostic potential in a selection of prevalent cardiovascular disorders.

Methods and Results— MicroRNAs were isolated from plasmas from well-characterized patients with varying degrees of cardiac damage:

(1) acute myocardial infarction,

(2) viral myocarditis,

(3) diastolic dysfunction, and

(4) acute heart failure.

Plasma levels of selected microRNAs, including heart-associated (miR-1, -133a, -208b, and -499), fibrosis-associated (miR-21 and miR-29b), and leukocyte-associated (miR-146, -155, and -223) candidates, were subsequently assessed using real-time polymerase chain reaction. Strikingly, in plasma from acute myocardial infarction patients, cardiac myocyte–associated miR-208b and -499 were highly elevated, 1600-fold (P<0.005) and 100-fold (P<0.0005), respectively, as compared with control subjects. Receiver operating characteristic curve analysis revealed an area under the curve of 0.94 (P<1010) for miR-208b and 0.92 (P<109) for miR-499. Both microRNAs correlated with plasma troponin T, indicating release of microRNAs from injured cardiomyocytes. In viral myocarditis, we observed a milder but significant elevation of these microRNAs, 30-fold and 6-fold, respectively. Plasma levels of leukocyte-expressed microRNAs were not significantly increased in acute myocardial infarction or viral myocarditis patients, despite elevated white blood cell counts. In patients with acute heart failure, only miR-499 was significantly elevated (2-fold), whereas no significant changes in microRNAs studied could be observed in diastolic dysfunction. Remarkably, plasma microRNA levels were not affected by a wide range of clinical confounders, including age, sex, body mass index, kidney function, systolic blood pressure, and white blood cell count.

Conclusions— Cardiac damage initiates the detectable release of cardiomyocyte-specific microRNAs-208b and -499 into the circulation.

SOURCE:

Circulation: Cardiovascular Genetics. 2010; 3: 499-506

Published online before print October 4, 2010,

doi: 10.1161/ CIRCGENETICS.110.957415

 

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Genetic Determinants of Potassium Sensitivity and Hypertension

 

Integrated Computational and Experimental Analysis of the Neuroendocrine Transcriptome in Genetic Hypertension Identifies Novel Control Points for the Cardiometabolic Syndrome

Ryan S. Friese, PhD, Chun Ye, PhD, Caroline M. Nievergelt, PhD, Andrew J. Schork, BS, Nitish R. Mahapatra, PhD, Fangwen Rao, MD, Philip S. Napolitan, BS, Jill Waalen, MD, MPH, Georg B. Ehret, MD, Patricia B. Munroe, PhD, Geert W. Schmid-Schönbein, PhD, Eleazar Eskin, PhD and Daniel T. O’Connor, MD

Author Affiliations

From the Departments of Bioengineering (R.S.F., G.W.S.-S.), Medicine (R.S.F., A.J.S., F.R., P.S.N., D.T.O.), Pharmacology (D.T.O.), and Psychiatry (C.M.N.), the Bioinformatics Program (C.Y.), and the Institute for Genomic Medicine (D.T.O.), University of California at San Diego; the VA San Diego Healthcare System, San Diego, CA (D.T.O.); the Departments of Computer Science & Human Genetics, University of California at Los Angeles (E.E.); the Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India (N.R.M.); Clinical Pharmacology and The Genome Centre, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (P.B.M.); Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (G.B.E.); and Scripps Research Institute, La Jolla, CA (J.W.).

Correspondence to Daniel T. O’Connor, MD, Department of Medicine, University of California at San Diego School of Medicine, VASDHS (0838), Skaggs (SSPPS) Room 4256, 9500 Gilman Drive, La Jolla, CA 92093-0838. E-mail doconnor@ucsd.edu

Abstract

Background—Essential hypertension, a common complex disease, displays substantial genetic influence. Contemporary methods to dissect the genetic basis of complex diseases such as the genomewide association study are powerful, yet a large gap exists betweens the fraction of population trait variance explained by such associations and total disease heritability.

Methods and Results—We developed a novel, integrative method (combining animal models, transcriptomics, bioinformatics, molecular biology, and trait-extreme phenotypes) to identify candidate genes for essential hypertension and the metabolic syndrome. We first undertook transcriptome profiling on adrenal glands from blood pressure extreme mouse strains: the hypertensive BPH (blood pressure high) and hypotensive BPL (blood pressure low). Microarray data clustering revealed a striking pattern of global underexpression of intermediary metabolism transcripts in BPH. The MITRA algorithm identified a conserved motif in the transcriptional regulatory regions of the underexpressed metabolic genes, and we then hypothesized that regulation through this motif contributed to the global underexpression. Luciferase reporter assays demonstrated transcriptional activity of the motif through transcription factors HOXA3, SRY, and YY1. We finally hypothesized that genetic variation at HOXA3, SRY, and YY1 might predict blood pressure and other metabolic syndrome traits in humans. Tagging variants for each locus were associated with blood pressure in a human population blood pressure extreme sample with the most extensive associations for YY1 tagging single nucleotide polymorphism rs11625658 on systolic blood pressure, diastolic blood pressure, body mass index, and fasting glucose. Meta-analysis extended the YY1 results into 2 additional large population samples with significant effects preserved on diastolic blood pressure, body mass index, and fasting glucose.

Conclusions—The results outline an innovative, systematic approach to the genetic pathogenesis of complex cardiovascular disease traits and point to transcription factor YY1 as a potential candidate gene involved in essential hypertension and the cardiometabolic syndrome.

 SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 430-440

Published online before print June 5, 2012,

doi: 10.1161/ CIRCGENETICS.111.962415

Genome-Wide Linkage and Positional Candidate Gene Study of Blood Pressure Response to Dietary Potassium Intervention

The Genetic Epidemiology Network of Salt Sensitivity Study

Tanika N. Kelly, PhD, James E. Hixson, PhD, Dabeeru C. Rao, PhD, Hao Mei, MD, PhD, Treva K. Rice, PhD, Cashell E. Jaquish, PhD, Lawrence C. Shimmin, PhD, Karen Schwander, MS, Chung-Shuian Chen, MS, Depei Liu, PhD, Jichun Chen, MD, Concetta Bormans, PhD, Pramila Shukla, MS, Naveed Farhana, MS, Colin Stuart, BS, Paul K. Whelton, MD, MSc, Jiang He, MD, PhD and Dongfeng Gu, MD, PhD

Author Affiliations

From the Department of Epidemiology (T.N.K., H.M., C.-S.C., J.H.), Tulane University School of Public Health and Tropical Medicine, and Department of Medicine (J.H.), Tulane University School of Medicine, New Orleans, La; Department of Epidemiology (J.E.H., L.C.S., C.B., P.S., N.F., C.S.), University of Texas School of Public Health, Houston, Tex; Division of Biostatistics (D.C.R., T.K.R., K.S.), Washington University School of Medicine, St Louis, Mo; Division of Prevention and Population Sciences (C.E.J.), National Heart, Lung, Blood Institute, Bethesda, Md; National Laboratory of Medical Molecular Biology (D.L.), Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Cardiovascular Institute and Fuwai Hospital (J.C., D.G.), Chinese Academy of Medical Sciences and Peking Union Medical College and Chinese National Center for Cardiovascular Disease Control and Research, Beijing, China; and Office of the President (P.K.W.), Loyola University Health System and Medical Center, Maywood, Ill.

Correspondence to Dongfeng Gu, MD, PhD, Division of Population Genetics and Prevention, Cardiovascular Institute and Fuwai Hospital, 167 Beilishi Rd, Beijing 100037, China. E-mail gudongfeng@vip.sina.com

Abstract

Background— Genetic determinants of blood pressure (BP) response to potassium, or potassium sensitivity, are largely unknown. We conducted a genome-wide linkage scan and positional candidate gene analysis to identify genetic determinants of potassium sensitivity.

Conclusions— Genetic regions on chromosomes 3 and 11 may harbor important susceptibility loci for potassium sensitivity. Furthermore, the AGTR1 gene was a significant predictor of BP responses to potassium intake.

SOURCE:

Circulation: Cardiovascular Genetics. 2010; 3: 539-547

Published online before print September 22, 2010,

doi: 10.1161/ CIRCGENETICS.110.940635

 

Genome-Wide Association Study of Cardiac Structure and Systolic Function in African Americans

The Candidate Gene Association Resource (CARe) Study

Ervin R. Fox, MD*, Solomon K. Musani, PhD*, Maja Barbalic, PhD*, Honghuang Lin, PhD, Bing Yu, MS, Kofo O. Ogunyankin, MD, Nicholas L. Smith, PhD, Abdullah Kutlar, MD, Nicole L. Glazer, MD, Wendy S. Post, MD, MS, Dina N. Paltoo, PhD, MPH, Daniel L. Dries, MD, MPH, Deborah N. Farlow, PhD, Christine W. Duarte, PhD, Sharon L. Kardia, PhD, Kristin J. Meyers, PhD, Yan V. Sun, PhD, Donna K. Arnett, PhD, Amit A. Patki, MS, Jin Sha, MS, Xiangqui Cui, PhD, Tandaw E. Samdarshi, MD, MPH, Alan D. Penman, PhD, Kirsten Bibbins-Domingo, MD, PhD, Petra Bůžková, PhD, Emelia J. Benjamin, MD, David A. Bluemke, MD, PhD, Alanna C. Morrison, PhD, Gerardo Heiss, MD, J. Jeffrey Carr, MD, MSc, Russell P. Tracy, PhD, Thomas H. Mosley, PhD, Herman A. Taylor, MD, Bruce M. Psaty, MD, PhD, Susan R. Heckbert, MD, PhD, Thomas P. Cappola, MD, ScM and Ramachandran S. Vasan, MD

Author Affiliations

Guest Editor for this article was Barry London, MD, PhD.

Correspondence to Ervin Fox, MD MPH, FAHA, FACC, Professor of Medicine, Department of Medicine, University of Mississippi Medical Center, 2500 North State St, Jackson, MS 39216. E-mail efox@medicine.umsmed.edu

* These authors contributed equally as joint first authors.

Abstract

Background—Using data from 4 community-based cohorts of African Americans, we tested the association between genome-wide markers (single-nucleotide polymorphisms) and cardiac phenotypes in the Candidate-gene Association Resource study.

Methods and Results—Among 6765 African Americans, we related age, sex, height, and weight-adjusted residuals for 9 cardiac phenotypes (assessed by echocardiogram or magnetic resonance imaging) to 2.5 million single-nucleotide polymorphisms genotyped using Genome-wide Affymetrix Human SNP Array 6.0 (Affy6.0) and the remainder imputed. Within the cohort, genome-wide association analysis was conducted, followed by meta-analysis across cohorts using inverse variance weights (genome-wide significance threshold=4.0 ×107). Supplementary pathway analysis was performed. We attempted replication in 3 smaller cohorts of African ancestry and tested lookups in 1 consortium of European ancestry (EchoGEN). Across the 9 phenotypes, variants in 4 genetic loci reached genome-wide significance: rs4552931 in UBE2V2 (P=1.43×107) for left ventricular mass, rs7213314 in WIPI1 (P=1.68×107) for left ventricular internal diastolic diameter, rs1571099 in PPAPDC1A (P=2.57×108) for interventricular septal wall thickness, and rs9530176 in KLF5 (P=4.02×107) for ejection fraction. Associated variants were enriched in 3 signaling pathways involved in cardiac remodeling. None of the 4 loci replicated in cohorts of African ancestry was confirmed in lookups in EchoGEN.

Conclusions—In the largest genome-wide association study of cardiac structure and function to date in African Americans, we identified 4 genetic loci related to left ventricular mass, interventricular septal wall thickness, left ventricular internal diastolic diameter, and ejection fraction, which reached genome-wide significance. Replication results suggest that these loci may be unique to individuals of African ancestry. Additional large-scale studies are warranted for these complex phenotypes.

SOURCE:

Circulation: Cardiovascular Genetics. 2013; 6: 37-46

Published online before print December 28, 2012,

doi: 10.1161/ CIRCGENETICS.111.962365

 

Heart and Aging Research in Genomic Epidemiology: 1700 MIs and 2300 coronary heart disease events among about 29 000 eligible patients

 

Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium

Design of Prospective Meta-Analyses of Genome-Wide Association Studies From 5 Cohorts

Bruce M. Psaty, MD, PhD, Christopher J. O’Donnell, MD, MPH, Vilmundur Gudnason, MD, PhD, Kathryn L. Lunetta, PhD, Aaron R. Folsom, MD, Jerome I. Rotter, MD, André G. Uitterlinden, PhD, Tamara B. Harris, MD, Jacqueline C.M. Witteman, PhD, Eric Boerwinkle, PhD and on Behalf of the CHARGE Consortium

Author Affiliations

From the Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services (B.M.P.), University of Wash; Center for Health Studies, Group Health (B.M.P.), Seattle, Wash; the National Heart, Lung and Blood Institute and the Framingham Heart Study (C.J.O.D.), Framingham, Mass; Icelandic Heart Association and the Department of Cardiovascular Genetics (Y.G.), University of Iceland, Reykjavik, Iceland; Department of Biostatistics (K.L.), Boston University School of Public Health, Mass; Division of Epidemiology and Community Health (A.R.F.), University of Minnesota, Minneapolis; Medical Genetics Institute (J.I.R.), Cedars-Sinai Medical Center, Los Angeles, Calif; Departments of Internal Medicine (A.G.U.) and Epidemiology (A.G.U., J.C.M.W.), Erasmus Medical Center, Rotterdam, The Netherlands; Laboratory of Epidemiology, Demography, and Biometry (T.B.H.), Intramural Research Program, National Institute on Aging, Bethesda, Md; and Human Genetics Center and Division of Epidemiology (E.B.), University of Texas, Houston.

Guest editor for this article was Elizabeth R. Hauser, PhD.

Abstract

Background— The primary aim of genome-wide association studies is to identify novel genetic loci associated with interindividual variation in the levels of risk factors, the degree of subclinical disease, or the risk of clinical disease. The requirement for large sample sizes and the importance of replication have served as powerful incentives for scientific collaboration.

Methods— The Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium was formed to facilitate genome-wide association studies meta-analyses and replication opportunities among multiple large population-based cohort studies, which collect data in a standardized fashion and represent the preferred method for estimating disease incidence. The design of the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium includes 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility—Reykjavik Study, the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study. With genome-wide data on a total of about 38 000 individuals, these cohort studies have a large number of health-related phenotypes measured in similar ways. For each harmonized trait, within-cohort genome-wide association study analyses are combined by meta-analysis. A prospective meta-analysis of data from all 5 cohorts, with a properly selected level of genome-wide statistical significance, is a powerful approach to finding genuine phenotypic associations with novel genetic loci.

Conclusions— The Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and collaborating non-member studies or consortia provide an excellent framework for the identification of the genetic determinants of risk factors, subclinical-disease measures, and clinical events.

Example of Coronary Heart Disease

The cohort-study methods papers provide detail about many of the phenotypes listed in Table 2. For coronary heart disease, investigators knowledgeable about the phenotype in each study decided to focus on fatal and nonfatal myocardial infarction (MI) as the primary outcome because the MI criteria differed in only trivial ways among the studies. There were some minor differences in the definition of the composite outcome of MI, fatal coronary heart disease, and sudden death, which became the secondary outcome. Only subjects at risk for an incident event were included in the analysis. MI survivors whose DNA was drawn after the event were not eligible. The primary analysis was restricted to Europeans or European Americans. Patients entered the analysis at the time of the DNA blood draw, and were followed until an event, death, loss to follow up, or the last visit. The main recommendations of the Analysis Committee were adopted, and a threshold of 5×108 was selected for genome-wide statistical significance. Analyses in progress include about 1700 MIs and 2300 coronary heart disease events among about 29 000 eligible patients. Each cohort conducted its own analysis, and results were uploaded to a secure share site for the fixed-effects meta-analysis. Even with this number of events (Supplemental Figure 2), power is good for only for relatively high minor allele frequencies (>0.25) and large relative risks (>1.3).

The authors had full access to and take full responsibility for the integrity of the data. All authors have read and agree to the manuscript as written.

Discussion

In thousands of published papers, the 5 CHARGE cohort studies and many of the collaborating studies have already characterized the risk factors for and the incidence and prognosis of a variety of aging-related and cardiovascular conditions. The analysis of the incident MI, for instance, is free from the survival bias typically associated with cross-sectional or case-control studies. The methodologic advantages of the prospective population-based cohort design, the similarity of phenotypes across 5 studies, the availability of genome-wide genotyping data in each cohort, and the need for large sample sizes to provide reliable estimates of genotype-phenotype associations have served as the primary incentives for the formation of the CHARGE consortium, which includes GWAS data on about 38 000 individuals. The consortium effort relies on collaborative methods that are similar to those used by the individual contributing cohorts.

Phenotype experts who know the studies and the data well are responsible for phenotype-standardization across cohorts. The coordinated prospectively planned meta-analyses of CHARGE provide results that are virtually identical to a cohort-adjusted pooled analysis of individual level data. This approach–the within-study analysis followed by a between-study meta-analysis–avoids the human subjects issues associated with individual-level data sharing.

Editors, reviewers, and readers expect replication as the standard in science.6 The finding of a genetic association in one population with evidence for replication in multiple independent populations provides moderate assurance against false-positive reports and helps to establish the validity of the original finding. In a single experiment, the discovery-replication structure is traditionally embodied in a 2-stage design. The CHARGE consortium includes up to 5 independent replicate samples as well as additional collaborating studies for some phenotype working groups, so that it would have been possible to set up analysis plans within CHARGE to mimic the traditional 2-stage design for replication. For instance, the 2 largest cohorts could have served as the discovery set and the others as the replication set. However, attaining the extremely small probability values expected in GWAS requires large sample sizes. For any phenotype, a prospective meta-analysis of all participating cohorts, with a properly selected level of genome-wide statistical significance to minimize the chance of false-positives, is the most powerful approach to finding new genuine associations for genetic loci.25 When findings narrowly miss the prespecified significance threshold, genotyping individuals in other independent populations provides additional evidence about the association. For findings that substantially exceed pre-established significance thresholds, the results of a CHARGE meta-analysis effectively provide evidence of a multistudy replication.

The effort to assemble and manage the CHARGE consortium has provided some interesting and unanticipated challenges. Participating cohorts often had relationships with outside study groups that predated the formation of CHARGE. Timelines for genotyping and imputation have shifted. Purchases of new computer systems for the volume of work were sometimes necessary. Each cohort came to the consortium with their own traditions for methods of analysis, organization, and authorship policies that, while appropriate for their own work, were not always optimal for collaboration with multiple external groups. Within each cohort, the investigators had often formed working groups that divided up the large number of available phenotypes in ways that made sense locally but did not necessarily match the configuration that had been adopted by other cohorts. The Research Steering Committee has attempted to create a set of CHARGE working groups that accommodate the needs and the conventions of the various cohorts. Transparency, disclosure, and professional collaborative behavior by all participating investigators have been essential to the process.

Resource limitations are another challenge. Grant applications that funded the original single-study genome-wide genotyping effort typically imagined a much simpler design. The CHS whole-genome study had as its primary aim, for instance, the analysis of data on 3 endpoints, coronary disease, stroke and heart failure. With a score of active phenotype working groups, the CHARGE collaboration broadened the scope of the short-term work well beyond initial expectations for all the participating cohorts.

One of the premier challenges has been communications among scores of investigators at a dozen sites. CHS and ARIC are themselves multi-site studies. To be successful, the CHARGE collaboration has required effective communications: (1) within each cohort; (2) between cohorts; (3) within the CHARGE working groups; and (4) among the major CHARGE committees. In addition to the traditional methods of conference calls and email, the CHARGE “wiki,” set up by Dr J. Bis (Seattle, Wash), has provided a crucial and highly functional user-driven website for calendars, minutes, guidelines, working group analysis plans, manuscript proposals, and other documents. In the end, there is no substitute for face-to-face meetings, especially at the beginning of the collaboration, and this complex meta-organization has benefited from several CHARGE-wide meetings.

The major emerging opportunity is the collaboration with other studies and consortia. Many working groups have already incorporated nonmember studies into their efforts. Several working groups have coordinated submissions of initial manuscripts with the parallel submission of manuscripts from other studies or consortia. Several working groups have embarked on plans for joint meta-analyses between CHARGE and other consortia. CHARGE has tried to acknowledge and reward the efforts of champions, who assume leadership responsibility for moving these large complex projects forward and who are often hard-working young investigators, the key to the future success of population science.

The CHARGE Consortium represents an innovative model of collaborative research conducted by research teams that know well the strengths, the limitations, and the data from 5 prospective population-based cohort studies. By leveraging the dense genotyping, deep phenotyping and the diverse expertise, prospective meta-analyses are underway to identify and replicate the major common genetic determinants of risk factors, measures of subclinical disease, and clinical events for cardiovascular disease and aging.

SOURCE:

Circulation: Cardiovascular Genetics.2009; 2: 73-80

doi: 10.1161/ CIRCGENETICS.108.829747

 

 

Genomics of Ventricular arrhythmias, A-Fib, Right Ventricular Dysplasia, Cardiomyopathy

 

Comprehensive Desmosome Mutation Analysis in North Americans With Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy

A. Dénise den Haan, MD, Boon Yew Tan, MBChB, Michelle N. Zikusoka, MD, Laura Ibañez Lladó, MS, Rahul Jain, MD, Amy Daly, MS, Crystal Tichnell, MGC, Cynthia James, PhD, Nuria Amat-Alarcon, MS, Theodore Abraham, MD, Stuart D. Russell, MD, David A. Bluemke, MD, PhD, Hugh Calkins, MD, Darshan Dalal, MD, PhD and Daniel P. Judge, MD

Author Affiliations

From the Department of Medicine/Cardiology (A.D.d.H., B.Y.T., M.N.Z., L.I.L., R.J., A.D., C.T., C.J., N.A.-A., T.A., S.D.R., H.C., D.D., D.P.J.), Johns Hopkins University School of Medicine, Baltimore, Md; Department of Cardiology, Division of Heart and Lungs (A.D.d.H.), University Medical Center Utrecht, Utrecht, The Netherlands; and National Institutes of Health, Radiology and Imaging Sciences (D.A.B.), Bethesda, Md.

Correspondence to Daniel P. Judge, MD, Johns Hopkins University, Division of Cardiology, Ross 1049; 720 Rutland Avenue, Baltimore, MD 21205. E-mail djudge@jhmi.edu

Abstract

Background— Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD/C) is an inherited disorder typically caused by mutations in components of the cardiac desmosome. The prevalence and significance of desmosome mutations among patients with ARVD/C in North America have not been described previously. We report comprehensive desmosome genetic analysis for 100 North Americans with clinically confirmed or suspected ARVD/C.

Methods and Results— In 82 individuals with ARVD/C and 18 people with suspected ARVD/C, DNA sequence analysis was performed on PKP2, DSG2, DSP, DSC2, and JUP. In those with ARVD/C, 52% harbored a desmosome mutation. A majority of these mutations occurred in PKP2. Notably, 3 of the individuals studied have a mutation in more than 1 gene. Patients with a desmosome mutation were more likely to have experienced ventricular tachycardia (73% versus 44%), and they presented at a younger age (33 versus 41 years) compared with those without a desmosome mutation. Men with ARVD/C were more likely than women to carry a desmosome mutation (63% versus 38%). A mutation was identified in 5 of 18 patients (28%) with suspected ARVD. In this smaller subgroup, there were no significant phenotypic differences identified between individuals with a desmosome mutation compared with those without a mutation.

Conclusions— Our study shows that in 52% of North Americans with ARVD/C a mutation in one of the cardiac desmosome genes can be identified. Compared with those without a desmosome gene mutation, individuals with a desmosome gene mutation had earlier-onset ARVD/C and were more likely to have ventricular tachycardia.

SOURCE:

Circulation: Cardiovascular Genetics.2009; 2: 428-435

Published online before print June 3, 2009,

doi: 10.1161/ CIRCGENETICS.109.858217

 

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Large-Scale Candidate Gene Analysis in Whites and African Americans Identifies IL6R Polymorphism in Relation to Atrial Fibrillation

The National Heart, Lung, and Blood Institute’s Candidate Gene Association Resource (CARe) Project

Renate B. Schnabel, MD, MSc*, Kathleen F. Kerr, PhD*, Steven A. Lubitz, MD*, Ermeg L. Alkylbekova, MD*, Gregory M. Marcus, MD, MAS, Moritz F. Sinner, MD, Jared W. Magnani, MD, Philip A. Wolf, MD, Rajat Deo, MD, Donald M. Lloyd-Jones, MD, ScM, Kathryn L. Lunetta, PhD, Reena Mehra, MD, MS, Daniel Levy, MD, Ervin R. Fox, MD, MPH, Dan E. Arking, PhD, Thomas H. Mosley, PhD, Martina Müller-Nurasyid, MSc, PhD, Taylor R. Young, MA, H.-Erich Wichmann, MD, PhD, Sudha Seshadri, MD, Deborah N. Farlow, PhD, Jerome I. Rotter, MD, Elsayed Z. Soliman, MD, MSc, MS, Nicole L. Glazer, PhD, James G. Wilson, MD, Monique M.B. Breteler, MD, Nona Sotoodehnia, MD, MPH, Christopher Newton-Cheh, MD, MPH, Stefan Kääb, MD, PhD, Patrick T. Ellinor, MD, PhD*, Alvaro Alonso, MD*, Emelia J. Benjamin, MD, ScM*, Susan R. Heckbert, MD, PhD* and for the Candidate Gene Association Resource (CARe) Atrial Fibrillation/Electrocardiography Working Group

Correspondence to Susan R. Heckbert, MD, PhD, Cardiovascular Health Research Unit, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA 98101. E-mail heckbert@u.washington.edu; Emelia J. Benjamin, MD, ScM, Medicine and Epidemiology, Boston University Schools of Medicine and Public Health, The Framingham Heart Study, 73 Mount Wayte Ave, Framingham, MA 01702–5827. E-mail emelia@bu.edu; Renate B. Schnabel, MD, MSc, Department of Medicine 2, Cardiology, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Germany. E-mail schnabelr@gmx.de

* These authors contributed equally to the manuscript.

Abstract

Background—The genetic background of atrial fibrillation (AF) in whites and African Americans is largely unknown. Genes in cardiovascular pathways have not been systematically investigated.

Methods and Results—We examined a panel of approximately 50 000 common single-nucleotide polymorphisms (SNPs) in 2095 cardiovascular candidate genes and AF in 3 cohorts with participants of European (n=18 524; 2260 cases) or African American descent (n=3662; 263 cases) in the National Heart, Lung, and Blood Institute’s Candidate Gene Association Resource. Results in whites were followed up in the German Competence Network for AF (n=906, 468 cases). The top result was assessed in relation to incident ischemic stroke in the Cohorts for Heart and Aging Research in Genomic Epidemiology Stroke Consortium (n=19 602 whites, 1544 incident strokes). SNP rs4845625 in the IL6R gene was associated with AF (relative risk [RR] C allele, 0.90; 95% confidence interval [CI], 0.85–0.95; P=0.0005) in whites but did not reach statistical significance in African Americans (RR, 0.86; 95% CI, 0.72–1.03; P=0.09). The results were comparable in the German AF Network replication, (RR, 0.71; 95% CI, 0.57–0.89; P=0.003). No association between rs4845625 and stroke was observed in whites. The known chromosome 4 locus near PITX2 in whites also was associated with AF in African Americans (rs4611994; hazard ratio, 1.40; 95% CI, 1.16–1.69; P=0.0005).

Conclusions—In a community-based cohort meta-analysis, we identified genetic association in IL6R with AF in whites. Additionally, we demonstrated that the chromosome 4 locus known from recent genome-wide association studies in whites is associated with AF in African Americans.

 SOURCE:

Circulation: Cardiovascular Genetics.2011; 4: 557-564

Published online before print August 16, 2011,

doi: 10.1161/ CIRCGENETICS.110.959197

PITX2c Is Expressed in the Adult Left Atrium, and Reducing Pitx2c Expression Promotes Atrial Fibrillation Inducibility and Complex Changes in Gene Expression

Paulus Kirchhof, MD*, Peter C. Kahr*, Sven Kaese, Ilaria Piccini, PhD, Ismail Vokshi, BSc, Hans-Heinrich Scheld, MD, Heinrich Rotering, MD, Lisa Fortmueller, MD (vet), Sandra Laakmann, MD (vet), Sander Verheule, PhD, Ulrich Schotten, MD, PhD, Larissa Fabritz, MD and Nigel A. Brown, PhD

Author Affiliations

From the Department of Cardiology and Angiology (P.K., P.C.K., S.K., I.P., L.F., S.L., L.F.) and the Department of Thoracic and Cardiovascular Surgery (H.-H.S., H.R.), University Hospital Muenster, Germany; Division of Biomedical Sciences (P.C.K., I.V., N.A.B.), St. George’s, University of London, United Kingdom; and the Department of Physiology (S.V., U.S.), Maastricht University, The Netherlands.

Correspondence to Nigel A. Brown, PhD, Division of Biomedical Sciences, St George’s, University of London, Cranmer Terrace, London, SW17 0RE, UK. E-mail nbrown@sgul.ac.uk

* Drs Kirchhof and Kahr contributed equally to this work.

Abstract

Background— Intergenic variations on chromosome 4q25, close to the PITX2 transcription factor gene, are associated with atrial fibrillation (AF). We therefore tested whether adult hearts express PITX2 and whether variation in expression affects cardiac function.

Methods and Results— mRNA for PITX2 isoform c was expressed in left atria of human and mouse, with levels in right atrium and left and right ventricles being 100-fold lower. In mice heterozygous for Pitx2c (Pitx2c+/), left atrial Pitx2c expression was 60% of wild-type and cardiac morphology and function were not altered, except for slightly elevated pulmonary flow velocity. Isolated Pitx2c+/ hearts were susceptible to AF during programmed stimulation. At short paced cycle lengths, atrial action potential durations were shorter in Pitx2c+/ than in wild-type. Perfusion with the β-receptor agonist orciprenaline abolished inducibility of AF and reduced the effect on action potential duration. Spontaneous heart rates, atrial conduction velocities, and activation patterns were not affected in Pitx2c+/ hearts, suggesting that action potential duration shortening caused wave length reduction and inducibility of AF. Expression array analyses comparing Pitx2c+/ with wild-type, for left atrial and right atrial tissue separately, identified genes related to calcium ion binding, gap and tight junctions, ion channels, and melanogenesis as being affected by the reduced expression of Pitx2c.

Conclusions— These findings demonstrate a physiological role for PITX2 in the adult heart and support the hypothesis that dysregulation of PITX2 expression can be responsible for susceptibility to AF.

 SOURCE:

Circulation: Cardiovascular Genetics.2011; 4: 123-133

Published online before print January 31, 2011,

doi: 10.1161/ CIRCGENETICS.110.958058

 

Genetics of CVD and Hyperlipidemia, Hyper Cholesterolemia, Metabolic Syndrome

 

Genetic Loci Associated With Plasma Concentration of Low-Density Lipoprotein Cholesterol, High-Density Lipoprotein Cholesterol, Triglycerides, Apolipoprotein A1, and Apolipoprotein B Among 6382 White Women in Genome-Wide Analysis With Replication

Daniel I. Chasman, PhD*, Guillaume Paré, MD, MS*, Robert Y.L. Zee, PhD, MPH, Alex N. Parker, PhD, Nancy R. Cook, ScD, Julie E. Buring, ScD, David J. Kwiatkowski, MD, PhD, Lynda M. Rose, MS, Joshua D. Smith, BS, Paul T. Williams, PhD, Mark J. Rieder, PhD, Jerome I. Rotter, MD, Deborah A. Nickerson, PhD, Ronald M. Krauss, MD, Joseph P. Miletich, MD and Paul M Ridker, MD, MPH

Author Affiliations

From the Center for Cardiovascular Disease Prevention (D.I.C., G.P., R.Y.L.Z., N.R.C., J.E.B., L.M.R., P.M.R.) and Donald W. Reynolds Center for Cardiovascular Research (D.I.C., G.P., R.Y.L.Z., N.R.C., D.J.K., P.M.R.), Brigham and Women’s Hospital, Harvard Medical School, Boston, Mass; Amgen, Inc, Cambridge, Mass (A.N.P., J.M.P.); Department of Genome Sciences, University of Washington, Seattle, Wash (J.D.S., M.J.R., D.A.N.); Life Science Division, Lawrence Berkeley National Laboratory, Berkeley, Calif (P.T.W., R.M.K.); Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, Calif (J.I.R.); and Children’s Hospital Oakland Research Institute, Oakland, Calif (R.M.K.).

Correspondence to Daniel I. Chasman, Center for Cardiovascular Disease Prevention, Brigham and Women’s Hospital, 900 Commonwealth Ave E, Boston, MA 02215. E-mail dchasman@rics.bwh.harvard.edu

Abstract

Background— Genome-wide genetic association analysis represents an opportunity for a comprehensive survey of the genes governing lipid metabolism, potentially revealing new insights or even therapeutic strategies for cardiovascular disease and related metabolic disorders.

Methods and Results— We have performed large-scale, genome-wide genetic analysis among 6382 white women with replication in 2 cohorts of 970 additional white men and women for associations between common single-nucleotide polymorphisms and low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, apolipoprotein (Apo) A1, and ApoB. Genome-wide associations (P<5×108) were found at the PCSK9 gene, the APOB gene, the LPL gene, the APOA1-APOA5 locus, the LIPC gene, the CETP gene, the LDLR gene, and the APOE locus. In addition, genome-wide associations with triglycerides at the GCKR gene confirm and extend emerging links between glucose and lipid metabolism. Still other genome-wide associations at the 1p13.3 locus are consistent with emerging biological properties for a region of the genome, possibly related to the SORT1 gene. Below genome-wide significance, our study provides confirmatory evidence for associations at 5 novel loci with low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, or triglycerides reported recently in separate genome-wide association studies. The total proportion of variance explained by common variation at the genome-wide candidate loci ranges from 4.3% for triglycerides to 12.6% for ApoB.

Conclusion— Genome-wide associations at the GCKR gene and near the SORT1 gene, as well as confirmatory associations at 5 additional novel loci, suggest emerging biological pathways for lipid metabolism among white women.

 SOURCE:

Circulation: Cardiovascular Genetics.2008; 1: 21-30

doi: 10.1161/ CIRCGENETICS.108.773168

 

 

Integrated Computational and Experimental Analysis of the Neuroendocrine Transcriptome in Genetic Hypertension Identifies Novel Control Points for the Cardiometabolic Syndrome

Ryan S. Friese, PhD, Chun Ye, PhD, Caroline M. Nievergelt, PhD, Andrew J. Schork, BS, Nitish R. Mahapatra, PhD, Fangwen Rao, MD, Philip S. Napolitan, BS, Jill Waalen, MD, MPH, Georg B. Ehret, MD, Patricia B. Munroe, PhD, Geert W. Schmid-Schönbein, PhD, Eleazar Eskin, PhD and Daniel T. O’Connor, MD

Author Affiliations

From the Departments of Bioengineering (R.S.F., G.W.S.-S.), Medicine (R.S.F., A.J.S., F.R., P.S.N., D.T.O.), Pharmacology (D.T.O.), and Psychiatry (C.M.N.), the Bioinformatics Program (C.Y.), and the Institute for Genomic Medicine (D.T.O.), University of California at San Diego; the VA San Diego Healthcare System, San Diego, CA (D.T.O.); the Departments of Computer Science & Human Genetics, University of California at Los Angeles (E.E.); the Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India (N.R.M.); Clinical Pharmacology and The Genome Centre, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (P.B.M.); Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (G.B.E.); and Scripps Research Institute, La Jolla, CA (J.W.).

Correspondence to Daniel T. O’Connor, MD, Department of Medicine, University of California at San Diego School of Medicine, VASDHS (0838), Skaggs (SSPPS) Room 4256, 9500 Gilman Drive, La Jolla, CA 92093-0838. E-mail doconnor@ucsd.edu

Abstract

Background—Essential hypertension, a common complex disease, displays substantial genetic influence. Contemporary methods to dissect the genetic basis of complex diseases such as the genomewide association study are powerful, yet a large gap exists betweens the fraction of population trait variance explained by such associations and total disease heritability.

Methods and Results—We developed a novel, integrative method (combining animal models, transcriptomics, bioinformatics, molecular biology, and trait-extreme phenotypes) to identify candidate genes for essential hypertension and the metabolic syndrome. We first undertook transcriptome profiling on adrenal glands from blood pressure extreme mouse strains: the hypertensive BPH (blood pressure high) and hypotensive BPL (blood pressure low). Microarray data clustering revealed a striking pattern of global underexpression of intermediary metabolism transcripts in BPH. The MITRA algorithm identified a conserved motif in the transcriptional regulatory regions of the underexpressed metabolic genes, and we then hypothesized that regulation through this motif contributed to the global underexpression. Luciferase reporter assays demonstrated transcriptional activity of the motif through transcription factors HOXA3, SRY, and YY1. We finally hypothesized that genetic variation at HOXA3, SRY, and YY1 might predict blood pressure and other metabolic syndrome traits in humans. Tagging variants for each locus were associated with blood pressure in a human population blood pressure extreme sample with the most extensive associations for YY1 tagging single nucleotide polymorphism rs11625658 on systolic blood pressure, diastolic blood pressure, body mass index, and fasting glucose. Meta-analysis extended the YY1 results into 2 additional large population samples with significant effects preserved on diastolic blood pressure, body mass index, and fasting glucose.

Conclusions—The results outline an innovative, systematic approach to the genetic pathogenesis of complex cardiovascular disease traits and point to transcription factor YY1 as a potential candidate gene involved in essential hypertension and the cardiometabolic syndrome.

 SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 430-440

Published online before print June 5, 2012,

doi: 10.1161/ CIRCGENETICS.111.962415

 

Associations Between Incident Ischemic Stroke Events and Stroke and Cardiovascular Disease-Related Genome-Wide Association Studies Single Nucleotide Polymorphisms in the Population Architecture Using Genomics and Epidemiology Study

Cara L. Carty, PhD, Petra Bůžková, PhD, Myriam Fornage, PhD, Nora Franceschini, MD, Shelley Cole, PhD, Gerardo Heiss, MD, PhD, Lucia A. Hindorff, PhD, MPH, Barbara V. Howard, PhD, Sue Mann, MPH, Lisa W. Martin, MD, Ying Zhang, PhD, Tara C. Matise, PhD, Ross Prentice, PhD, Alexander P. Reiner, MD, MS and Charles Kooperberg, PhD

Author Affiliations

From the Public Health Sciences, Fred Hutchinson Cancer Research Center (C.L.C., S.M., R.P., C.K.); Department of Biostatistics, University of Washington, Seattle, WA (P.B.); Institute of Molecular Medicine, University of Texas Health Sciences Center at Houston, Houston, TX (M.F.); Division of Epidemiology, School of Public Health, University of Texas Health Sciences Center, Houston, TX (M.F.); Department of Epidemiology, University of North Carolina, Chapel Hill, NC (N.F., G.H.); Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX (S.C.); Office of Population Genomics, National Human Genome Research Institute, Bethesda, MD (L.A.H.); Medstar Health Research Institute, Washington, DC (B.V.H.); George Washington University School of Medicine, Washington, DC (B.V.H., L.W.M.); University of Oklahoma Health Sciences Center, Oklahoma City, OK (Y.Z.); Department of Genetics, Rutgers University, Piscataway, NJ (T.C.M.); Department of Epidemiology, University of Washington, Seattle, WA (A.P.R.).

Correspondence to Dr Cara L. Carty, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N./M3-A410, Seattle, WA 98109. E-mail ccarty@fhcrc.org

Abstract

Background—Genome-wide association studies (GWAS) have identified loci associated with ischemic stroke (IS) and cardiovascular disease (CVD) in European-descent individuals, but their replication in different populations has been largely unexplored.

Methods and Results—Nine single nucleotide polymorphisms (SNPs) selected from GWAS and meta-analyses of stroke, and 86 SNPs previously associated with myocardial infarction and CVD risk factors, including blood lipids (high density lipoprotein [HDL], low density lipoprotein [LDL], and triglycerides), type 2 diabetes, and body mass index (BMI), were investigated for associations with incident IS in European Americans (EA) N=26 276, African-Americans (AA) N=8970, and American Indians (AI) N=3570 from the Population Architecture using Genomics and Epidemiology Study. Ancestry-specific fixed effects meta-analysis with inverse variance weighting was used to combine study-specific log hazard ratios from Cox proportional hazards models. Two of 9 stroke SNPs (rs783396 and rs1804689) were associated with increased IS hazard in AA; none were significant in this large EA cohort. Of 73 CVD risk factor SNPs tested in EA, 2 (HDL and triglycerides SNPs) were associated with IS. In AA, SNPs associated with LDL, HDL, and BMI were significantly associated with IS (3 of 86 SNPs tested). Out of 58 SNPs tested in AI, 1 LDL SNP was significantly associated with IS.

Conclusions—Our analyses showing lack of replication in spite of reasonable power for many stroke SNPs and differing results by ancestry highlight the need to follow up on GWAS findings and conduct genetic association studies in diverse populations. We found modest IS associations with BMI and lipids SNPs, though these findings require confirmation.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 210-216

Published online before print March 8, 2012,

doi: 10.1161/ CIRCGENETICS.111.962191

 

Common Variation in Fatty Acid Genes and Resuscitation From Sudden Cardiac Arrest

Catherine O. Johnson, PhD, MPH, Rozenn N. Lemaitre, PhD, MPH, Carol E. Fahrenbruch, MSPH, Stephanie Hesselson, PhD, Nona Sotoodehnia, MD, MPH, Barbara McKnight, PhD, Kenneth M. Rice, PhD, Pui-Yan Kwok, MD, PhD, David S. Siscovick, MD, MPH and Thomas D. Rea, MD, MPH

Author Affiliations

From the Departments of Medicine (C.O.J., R.N.L., N.S., D.S.S., T.D.R.), Biostatistics (B.M., K.M.R.), and Epidemiology (D.S.S), University of Washington, Seattle; King County Emergency Medical Services, Seattle, WA (C.E.F.); and Institute of Human Genetics, University of California San Francisco (S.H., P.-Y.K.).

Correspondence to Catherine O. Johnson, PhD, MPH, Department of Medicine, University of Washington, CHRU 1730 Minor Ave, Suite 1360, Seattle, WA 98101. E-mail johnsoco@uw.edu

Abstract

Background—Fatty acids provide energy and structural substrates for the heart and brain and may influence resuscitation from sudden cardiac arrest (SCA). We investigated whether genetic variation in fatty acid metabolism pathways was associated with SCA survival.

Methods and Results—Subjects (mean age, 67 years; 80% male, white) were out-of-hospital SCA patients found in ventricular fibrillation in King County, WA. We compared subjects who survived to hospital admission (n=664) with those who did not (n=689), and subjects who survived to hospital discharge (n=334) with those who did not (n=1019). Associations between survival and genetic variants were assessed using logistic regression adjusting for age, sex, location, time to arrival of paramedics, whether the event was witnessed, and receipt of bystander cardiopulmonary resuscitation. Within-gene permutation tests were used to correct for multiple comparisons. Variants in 5 genes were significantly associated with SCA survival. After correction for multiple comparisons, single-nucleotide polymorphisms in ACSL1 and ACSL3 were significantly associated with survival to hospital admission. Single-nucleotide polymorphisms in ACSL3, AGPAT3, MLYCD, and SLC27A6 were significantly associated with survival to hospital discharge.

Conclusions—Our findings indicate that variants in genes important in fatty acid metabolism are associated with SCA survival in this population.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 422-429

Published online before print June 1, 2012,

doi: 10.1161/ CIRCGENETICS.111.961912

 

Genome-Wide Association Study Pinpoints a New Functional Apolipoprotein B Variant Influencing Oxidized Low-Density Lipoprotein Levels But Not Cardiovascular Events

AtheroRemo Consortium

Kari-Matti Mäkelä, BM, BSc, Ilkka Seppälä, MSc, Jussi A. Hernesniemi, MD, PhD, Leo-Pekka Lyytikäinen, MD, Niku Oksala, MD, PhD, DSc, Marcus E. Kleber, PhD, Hubert Scharnagl, PhD, Tanja B. Grammer, MD, Jens Baumert, PhD, Barbara Thorand, PhD, Antti Jula, MD, PhD, Nina Hutri-Kähönen, MD, PhD, Markus Juonala, MD, PhD, Tomi Laitinen, MD, PhD, Reijo Laaksonen, MD, PhD, Pekka J. Karhunen, MD, PhD, Kjell C. Nikus, MD, PhD, Tuomo Nieminen, MD, PhD, MSc, Jari Laurikka, MD, PhD, Pekka Kuukasjärvi, MD, PhD, Matti Tarkka, MD, PhD, Jari Viik, PhD, Norman Klopp, PhD, Thomas Illig, PhD, Johannes Kettunen, PhD, Markku Ahotupa, PhD, Jorma S.A. Viikari, MD, PhD, Mika Kähönen, MD, PhD, Olli T. Raitakari, MD, PhD, Mahir Karakas, MD, Wolfgang Koenig, MD, PhD, Bernhard O. Boehm, MD, Bernhard R. Winkelmann, MD, Winfried März, MD and Terho Lehtimäki, MD, PhD

Correspondence to Kari-Matti Mäkelä, Department of Clinical Chemistry, Finn-Medi 2, PO Box 2000, FI-33521 Tampere, Finland. E-mail kari-matti.makela@uta.fi

Abstract

Background—Oxidized low-density lipoprotein may be a key factor in the development of atherosclerosis. We performed a genome-wide association study on oxidized low-density lipoprotein and tested the impact of associated single-nucleotide polymorphisms (SNPs) on the risk factors of atherosclerosis and cardiovascular events.

Methods and Results—A discovery genome-wide association study was performed on a population of young healthy white individuals (N=2080), and the SNPs associated with a P<5×10–8 were replicated in 2 independent samples (A: N=2912; B: N=1326). Associations with cardiovascular endpoints were also assessed with 2 additional clinical cohorts (C: N=1118; and D: N=808). We found 328 SNPs associated with oxidized low-density lipoprotein. The genetic variant rs676210 (Pro2739Leu) in apolipoprotein B was the proxy SNP behind all associations (P=4.3×10–136, effect size=13.2 U/L per allele). This association was replicated in the 2 independent samples (A and B, P=2.5×10–47 and 1.1×10–11, effect sizes=10.3 U/L and 7.8 U/L, respectively). In the meta-analyses of cohorts A, C, and D (excluding cohort B without angiographic data), the top SNP did not associate significantly with the age of onset of angiographically verified coronary artery disease (hazard ratio=1.00 [0.94–1.06] per allele), 3-vessel coronary artery disease (hazard ratio=1.03 [0.94–1.13]), or myocardial infarction (hazard ratio=1.04 [0.96–1.12]).

Conclusions—This novel genetic marker is an important factor regulating oxidized low-density lipoprotein levels but not a major genetic factor for the studied cardiovascular endpoints.

 SOURCE:

Circulation: Cardiovascular Genetics.2013; 6: 73-81

Published online before print December 17, 2012,

doi: 10.1161/ CIRCGENETICS.112.964965

Genome-Wide Screen for Metabolic Syndrome Susceptibility Loci Reveals Strong Lipid Gene Contribution But No Evidence for Common Genetic Basis for Clustering of Metabolic Syndrome Traits

Kati Kristiansson, PhD, Markus Perola, MD, PhD, Emmi Tikkanen, MSc, Johannes Kettunen, PhD, Ida Surakka, MSc, Aki S. Havulinna, DSc (Tech.), Alena Stančáková, MD, PhD, Chris Barnes, PhD, Elisabeth Widen, MD, PhD, Eero Kajantie, MD, PhD, Johan G. Eriksson, MD, DMSc, Jorma Viikari, MD, PhD, Mika Kähönen, MD, PhD, Terho Lehtimäki, MD, PhD, Olli T. Raitakari, MD, PhD, Anna-Liisa Hartikainen, MD, PhD, Aimo Ruokonen, MD, PhD, Anneli Pouta, MD, PhD, Antti Jula, MD, PhD, Antti J. Kangas, MSc, Pasi Soininen, PhD, Mika Ala-Korpela, PhD, Satu Männistö, PhD, Pekka Jousilahti, MD, PhD, Lori L. Bonnycastle, PhD, Marjo-Riitta Järvelin, MD, PhD, Johanna Kuusisto, MD, PhD, Francis S. Collins, MD, PhD, Markku Laakso, MD, PhD, Matthew E. Hurles, PhD, Aarno Palotie, MD, PhD, Leena Peltonen, MD, PhD*, Samuli Ripatti, PhD and Veikko Salomaa, MD, PhD

Correspondence to Dr Kati Kristiansson, National Institute for Health and Welfare, University of Helsinki, Biomedicum, PL 104, FI-00251 Helsinki, Finland. E-mail kati.kristiansson@thl.fi

Abstract

Background—Genome-wide association (GWA) studies have identified several susceptibility loci for metabolic syndrome (MetS) component traits, but have had variable success in identifying susceptibility loci to the syndrome as an entity. We conducted a GWA study on MetS and its component traits in 4 Finnish cohorts consisting of 2637 MetS cases and 7927 controls, both free of diabetes, and followed the top loci in an independent sample with transcriptome and nuclear magnetic resonance-based metabonomics data. Furthermore, we tested for loci associated with multiple MetS component traits using factor analysis, and built a genetic risk score for MetS.

Methods and Results—A previously known lipid locus, APOA1/C3/A4/A5 gene cluster region (SNP rs964184), was associated with MetS in all 4 study samples (P=7.23×109 in meta-analysis). The association was further supported by serum metabolite analysis, where rs964184 was associated with various very low density lipoprotein, triglyceride, and high-density lipoprotein metabolites (P=0.024–1.88×105). Twenty-two previously identified susceptibility loci for individual MetS component traits were replicated in our GWA and factor analysis. Most of these were associated with lipid phenotypes, and none with 2 or more uncorrelated MetS components. A genetic risk score, calculated as the number of risk alleles in loci associated with individual MetS traits, was strongly associated with MetS status.

Conclusions—Our findings suggest that genes from lipid metabolism pathways have the key role in the genetic background of MetS. We found little evidence for pleiotropy linking dyslipidemia and obesity to the other MetS component traits, such as hypertension and glucose intolerance.

 SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 242-249

Published online before print March 7, 2012,

doi: 10.1161/ CIRCGENETICS.111.961482

 

Genetics and Vascular Pathologies and Platelet Aggregation, Cardiac Troponin T in Serum

 

 

TGFβRIIb Mutations Trigger Aortic Aneurysm Pathogenesis by Altering Transforming Growth Factor β2 Signal Transduction

Katharine J. Bee, PhD, David C. Wilkes, PhD, Richard B. Devereux, MD, Craig T. Basson, MD, PhD and Cathy J. Hatcher, PhD

Author Affiliations

From the Center for Molecular Cardiology, Greenberg Division of Cardiology, Weill Cornell Medical College, New York, NY.

Correspondence to Cathy J. Hatcher, PhD, Greenberg Division of Cardiology, Weill Cornell Medical College, 525 E. 68th St, New York, NY 10065. E-mail cjhatche@med.cornell.edu

Abstract

Background—Thoracic aortic aneurysm (TAA) is a common progressive disorder involving gradual dilation of the ascending and/or descending thoracic aorta that eventually leads to dissection or rupture. Nonsydromic TAA can occur as a genetically triggered, familial disorder that is usually transmitted in a monogenic autosomal dominant fashion and is known as familial TAA. Genetic analyses of families affected with TAA have identified several chromosomal loci, and further mapping of familial TAA genes has highlighted disease-causing mutations in at least 4 genes: myosin heavy chain 11 (MYH11), α-smooth muscle actin (ACTA2), and transforming growth factor β receptors I and II (TGFβRI and TGFβRII).

Methods and Results—We evaluated 100 probands to determine the mutation frequency in MYH11, ACTA2, TGFβRI, and TGFβRII in an unbiased population of individuals with genetically mediated TAA. In this study, 9% of patients had a mutation in one of the genes analyzed, 3% of patients had mutations in ACTA2, 3% in MYH11, 1% in TGFβRII, and no mutations were found in TGFβRI. Additionally, we identified mutations in a 75 base pair alternatively spliced TGFβRII exon, exon 1a that produces the TGFβRIIb isoform and accounted for 2% of patients with mutations. Our in vitro analyses indicate that the TGFβRIIb activating mutations alter receptor function on TGFβ2 signaling.

Conclusions—We propose that TGFβRIIb expression is a regulatory mechanism for TGFβ2 signal transduction. Dysregulation of the TGFβ2 signaling pathway, as a consequence of TGFβRIIb mutations, results in aortic aneurysm pathogenesis.

SOURCE: 

Circulation: Cardiovascular Genetics.2012; 5: 621-629

Published online before print October 24, 2012,doi: 10.1161/​CIRCGENETICS.112.964064

Matrix Metalloproteinase-9 Genotype as a Potential Genetic Marker for Abdominal Aortic Aneurysm

Tyler Duellman, BS, Christopher L. Warren, PhD, Peggy Peissig, PhD, Martha Wynn, MD and Jay Yang, MD, PhD

Author Affiliations

From the Molecular and Cellular Pharmacology Graduate Program (T.D., J.Y.) and Department of Anesthesiology (M.W., J.Y.), University of Wisconsin School of Medicine and Public Health, Madison; Illumavista Biosciences LLC, Madison, WI (C.L.W.); and Biomedical Informatics Research Center, Marshfield Clinics Research Foundation, Marshfield, WI (P.P.).

Correspondence to Jay Yang, MD, PhD, Department of Anesthesiology, University of Wisconsin SMPH, SMI 301, 1300 University Ave, Madison, WI 53706. E-mail Jyang75@wisc.edu

Abstract

Background—Degradation of extracellular matrix support in the large abdominal arteries contribute to abnormal dilation of aorta, leading to abdominal aortic aneurysms, and matrix metalloproteinase-9 (MMP-9) is the predominant enzyme targeting elastin and collagen present in the walls of the abdominal aorta. Previous studies have suggested a potential association between MMP-9 genotype and abdominal aortic aneurysm, but these studies have been limited only to the p-1562 and (CA) dinucleotide repeat microsatellite polymorphisms in the promoter region of the MMP-9 gene. We determined the functional alterations caused by 15 MMP-9 single-nucleotide polymorphisms (SNPs) reported to be relatively abundant in the human genome through Western blots, gelatinase, and promoter–reporter assays and incorporated this information to perform a logistic-regression analysis of MMP-9 SNPs in 336 human abdominal aortic aneurysm cases and controls.

Methods and Results—Significant functional alterations were observed for 6 exon SNPs and 4 promoter SNPs. Genotype analysis of frequency-matched (age, sex, history of hypertension, hypercholesterolemia, and smoking) cases and controls revealed significant genetic heterogeneity exceeding 20% observed for 6 SNPs in our population of mostly white subjects from Northern Wisconsin. A step-wise logistic-regression analysis with 6 functional SNPs, where weakly contributing confounds were eliminated using Akaike information criteria, gave a final 2 SNP (D165N and p-2502) model with an overall odds ratio of 2.45 (95% confidence interval, 1.06–5.70).

Conclusions—The combined approach of direct experimental confirmation of the functional alterations of MMP-9 SNPs and logistic-regression analysis revealed significant association between MMP-9 genotype and abdominal aortic aneurysm.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 529-537

Published online before print August 31, 2012,

doi: 10.1161/ CIRCGENETICS.112.963082

Common Genetic Variation in the 3BCL11B Gene Desert Is Associated With Carotid-Femoral Pulse Wave Velocity and Excess Cardiovascular Disease Risk

The AortaGen Consortium

Gary F. Mitchell, MD*, Germaine C. Verwoert, MSc*, Kirill V. Tarasov, MD, PhD*, Aaron Isaacs, PhD, Albert V. Smith, PhD, Yasmin, BSc, MA, PhD, Ernst R. Rietzschel, MD, PhD, Toshiko Tanaka, PhD, Yongmei Liu, MD, PhD, Afshin Parsa, MD, MPH, Samer S. Najjar, MD, Kevin M. O’Shaughnessy, MA, BM, DPhil, FRCP, Sigurdur Sigurdsson, MSc, Marc L. De Buyzere, MSc, Martin G. Larson, ScD, Mark P.S. Sie, MD, PhD, Jeanette S. Andrews, MS, Wendy S. Post, MD, MS, Francesco U.S. Mattace-Raso, MD, PhD, Carmel M. McEniery, BSc, PhD, Gudny Eiriksdottir, MSc, Patrick Segers, PhD, Ramachandran S. Vasan, MD, Marie Josee E. van Rijn, MD, PhD, Timothy D. Howard, PhD, Patrick F. McArdle, PhD, Abbas Dehghan, MD, PhD, Elizabeth S. Jewell, MS, Stephen J. Newhouse, MSc, PhD, Sofie Bekaert, PhD, Naomi M. Hamburg, MD, Anne B. Newman, MD, MPH, Albert Hofman, MD, PhD, Angelo Scuteri, MD, PhD, Dirk De Bacquer, PhD, Mohammad Arfan Ikram, MD, PhD†, Bruce M. Psaty, MD, PhD†, Christian Fuchsberger, PhD‡, Matthias Olden, PhD‡, Louise V. Wain, PhD§, Paul Elliott, MB, PhD§, Nicholas L. Smith, PhD‖, Janine F. Felix, MD, PhD‖, Jeanette Erdmann, PhD¶, Joseph A. Vita, MD, Kim Sutton-Tyrrell, PhD, Eric J.G. Sijbrands, MD, PhD, Serena Sanna, PhD, Lenore J. Launer, MS, PhD, Tim De Meyer, PhD, Andrew D. Johnson, MD, Anna F.C. Schut, MD, PhD, David M. Herrington, MD, MHS, Fernando Rivadeneira, MD, PhD, Manuela Uda, PhD, Ian B. Wilkinson, MA, BM, FRCP, Thor Aspelund, PhD, Thierry C. Gillebert, MD, PhD, Luc Van Bortel, MD, PhD, Emelia J. Benjamin, MD, MSc, Ben A. Oostra, PhD, Jingzhong Ding, MD, PhD, Quince Gibson, MBA, André G. Uitterlinden, PhD, Gonçalo R. Abecasis, PhD, John R. Cockcroft, BSc, MB, ChB, FRCP, Vilmundur Gudnason, MD, PhD, Guy G. De Backer, MD, PhD, Luigi Ferrucci, MD, Tamara B. Harris, MD, MS, Alan R. Shuldiner, MD, Cornelia M. van Duijn, PhD, Daniel Levy, MD*, Edward G. Lakatta, MD* and Jacqueline C.M. Witteman, PhD*

Correspondence to Gary F. Mitchell, MD, Cardiovascular Engineering, Inc, 1 Edgewater Dr, Suite 201A, Norwood, MA 02062. E-mail GaryFMitchell@mindspring.com

* These authors contributed equally.

Abstract

Background—Carotid-femoral pulse wave velocity (CFPWV) is a heritable measure of aortic stiffness that is strongly associated with increased risk for major cardiovascular disease events.

Methods and Results—We conducted a meta-analysis of genome-wide association data in 9 community-based European ancestry cohorts consisting of 20 634 participants. Results were replicated in 2 additional European ancestry cohorts involving 5306 participants. Based on a preliminary analysis of 6 cohorts, we identified a locus on chromosome 14 in the 3′-BCL11B gene desert that is associated with CFPWV (rs7152623, minor allele frequency=0.42, β=−0.075±0.012 SD/allele, P=2.8×1010; replication β=−0.086±0.020 SD/allele, P=1.4×106). Combined results for rs7152623 from 11 cohorts gave β=−0.076±0.010 SD/allele, P=3.1×1015. The association persisted when adjusted for mean arterial pressure (β=−0.060±0.009 SD/allele, P=1.0×1011). Results were consistent in younger (<55 years, 6 cohorts, n=13 914, β=−0.081±0.014 SD/allele, P=2.3×109) and older (9 cohorts, n=12 026, β=−0.061±0.014 SD/allele, P=9.4×106) participants. In separate meta-analyses, the locus was associated with increased risk for coronary artery disease (hazard ratio=1.05; confidence interval=1.02–1.08; P=0.0013) and heart failure (hazard ratio=1.10, CI=1.03–1.16, P=0.004).

Conclusions—Common genetic variation in a locus in the BCL11B gene desert that is thought to harbor 1 or more gene enhancers is associated with higher CFPWV and increased risk for cardiovascular disease. Elucidation of the role this novel locus plays in aortic stiffness may facilitate development of therapeutic interventions that limit aortic stiffening and related cardiovascular disease events.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 81-90

Published online before print November 8, 2011,

doi: 10.1161/ CIRCGENETICS.111.959817

Genetic Variation in PEAR1 is Associated with Platelet Aggregation and Cardiovascular Outcomes

Joshua P. Lewis1, Kathleen Ryan1, Jeffrey R. O’Connell1, Richard B. Horenstein1, Coleen M. Damcott1, Quince Gibson1, Toni I. Pollin1, Braxton D. Mitchell1, Amber L. Beitelshees1, Ruth Pakzy1, Keith Tanner1, Afshin Parsa1, Udaya S. Tantry2, Kevin P. Bliden2, Wendy S. Post3, Nauder Faraday3, William Herzog4, Yan Gong5, Carl J. Pepine6, Julie A. Johnson5, Paul A. Gurbel2 and Alan R. Shuldiner7*

Author Affiliations

1University of Maryland School of Medicine, Baltimore, MD

2Sinai Hospital of Baltimore, Baltimore, MD

3Johns Hopkins University School of Medicine, Baltimore, MD

4Sinai Hospital of Baltimore & Johns Hopkins University School of Medicine, Baltimore, MD

5University of Florida College of Pharmacy, Gainesville, FL

6University of Florida College of Medicine, Gainesville, FL

7University of Maryland School of Medicine & Veterans Administration Medical Center, Baltimore, MD

* University of Maryland School of Medicine & Veterans Administration Medical Center, Baltimore, MD ashuldin@medicine.umaryland.edu

Abstract

Background-Aspirin or dual antiplatelet therapy (DAPT) with aspirin and clopidogrel is standard therapy for patients at increased risk for cardiovascular events. However, the genetic determinants of variable response to aspirin (alone and in combination with clopidogrel) are not known.

Methods and Results-We measured ex-vivo platelet aggregation before and after DAPT in individuals (n=565) from the Pharmacogenomics of Antiplatelet Intervention (PAPI) Study and conducted a genome-wide association study (GWAS) of drug response. Significant findings were extended by examining genotype and cardiovascular outcomes in two independent aspirin-treated cohorts: 227 percutaneous coronary intervention (PCI) patients, and 1,000 patients of the International VErapamil SR/trandolapril Study (INVEST) GENEtic Substudy (INVEST-GENES). GWAS revealed a strong association between single nucleotide polymorphisms on chromosome 1q23 and post-DAPT platelet aggregation. Further genotyping revealed rs12041331 in the platelet endothelial aggregation receptor-1 (PEAR1) gene to be most strongly associated with DAPT response (P=7.66×10-9). In Caucasian and African American patients undergoing PCI, A-allele carriers of rs12041331 were more likely to experience a cardiovascular event or death compared to GG homozygotes (hazard ratio = 2.62, 95%CI 0.96-7.10, P=0.059 and hazard ratio = 3.97, 95%CI 1.10-14.31, P=0.035 respectively). In aspirin-treated INVEST-GENES patients, rs12041331 A-allele carriers had significantly increased risk of myocardial infarction compared to GG homozygotes (OR=2.03, 95%CI 1.01-4.09, P=0.048).

Conclusions-Common genetic variation in PEAR1 may be a determinant of platelet response and cardiovascular events in patients on aspirin, alone and in combination with clopidogrel.

Clinical Trial Registration Information-clinicaltrials.gov; Identifiers: NCT00799396 and NCT00370045

SOURCE:

CIRCGENETICS.112.964627

Published online before print February 7, 2013,

doi: 10.1161/ CIRCGENETICS.111.964627

Association of Genome-Wide Variation With Highly Sensitive Cardiac Troponin-T Levels in European Americans and Blacks

A Meta-Analysis From Atherosclerosis Risk in Communities and Cardiovascular Health Studies

Bing Yu, MD, MSc, Maja Barbalic, PhD, Ariel Brautbar, MD, Vijay Nambi, MD, Ron C. Hoogeveen, PhD, Weihong Tang, PhD, Thomas H. Mosley, PhD, Jerome I. Rotter, MD, Christopher R. deFilippi, MD, Christopher J. O’Donnell, MD, Sekar Kathiresan, MD, Ken Rice, PhD, Susan R. Heckbert, MD, PhD, Christie M. Ballantyne, MD, Bruce M. Psaty, MD, PhD and Eric Boerwinkle, PhD on behalf of the CARDIoGRAM Consortium

Author Affiliations

From the Human Genetic Center, University of Texas Health Science Center at Houston, Houston, TX (B.Y., M.B., E.B.); Deptartment of Medicine (A.B., V.N., R.C.H., C.M.B.), and Human Genome Sequencing Center (E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology, University of Minnesota, Minneapolis, MN (W.T.); Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS (T.H.M.); Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA (J.I.R.); School of Medicine, University of Maryland, Baltimore, MD (C.R.D.); National Heart, Lung, and Blood Institute and Framingham Heart Study, National Institutes of Health, Bethesda, MD (C.J.O.D.); Center for Human Genetic Research & Cardiovascular Research Center, Massachusetts General Hospital and Department of Medicine, Harvard Medical School, Boston, MA (S.K.); Department of Biostatistics (K.R.), and Cardiovascular Health Research Unit & Department of Epidemiology (S.R.H.), University of Washington, Seattle, WA; and Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington & Group Health Research Institute, Group Health Cooperative, Seattle, WA (B.M.P.).

Correspondence to Eric Boerwinkle, PhD, Human Genetic Center, University of Texas School of Public Health, 1200 Herman Pressler E-447, Houston, TX 77030. E-mail Eric.Boerwinkle@uth.tmc.edu

Abstract

Background—High levels of cardiac troponin T, measured by a highly sensitive assay (hs-cTnT), are strongly associated with incident coronary heart disease and heart failure. To date, no large-scale genome-wide association study of hs-cTnT has been reported. We sought to identify novel genetic variants that are associated with hs-cTnT levels.

Methods and Results—We performed a genome-wide association in 9491 European Americans and 2053 blacks free of coronary heart disease and heart failure from 2 prospective cohorts: the Atherosclerosis Risk in Communities Study and the Cardiovascular Health Study. Genome-wide association studies were conducted in each study and race stratum. Fixed-effect meta-analyses combined the results of linear regression from 2 cohorts within each race stratum and then across race strata to produce overall estimates and probability values. The meta-analysis identified a significant association at chromosome 8q13 (rs10091374; P=9.06×109) near the nuclear receptor coactivator 2 (NCOA2) gene. Overexpression of NCOA2 can be detected in myoblasts. An additional analysis using logistic regression and the clinically motivated 99th percentile cut point detected a significant association at 1q32 (rs12564445; P=4.73×108) in the gene TNNT2, which encodes the cardiac troponin T protein itself. The hs-cTnT-associated single-nucleotide polymorphisms were not associated with coronary heart disease in a large case-control study, but rs12564445 was significantly associated with incident heart failure in Atherosclerosis Risk in Communities Study European Americans (hazard ratio=1.16; P=0.004).

Conclusions—We identified 2 loci, near NCOA2 and in the TNNT2 gene, at which variation was significantly associated with hs-cTnT levels. Further use of the new assay should enable replication of these results.

 SOURCE:

Circulation: Cardiovascular Genetics.2013; 6: 82-88

Published online before print December 16, 2012,

doi: 10.1161/ CIRCGENETICS.112.963058

 

Genomics and Valvular Disease

 

Supravalvular Aortic Stenosis Elastin Arteriopathy

 

Giuseppe Merla, PhD, Nicola Brunetti-Pierri, MD, Pasquale Piccolo, PhD, Lucia Micale, PhD and Maria Nicla Loviglio, PhD, MSc

Author Affiliations

From the Medical Genetics Unit, IRCCS Casa Sollievo Della Sofferenza Hospital, San Giovanni Rotondo, Italy (G.M., L.M., M.N.L.); Telethon Institute of Genetics and Medicine, Napoli, Italy (N.B-P., P.P.); Department of Pediatrics, Federico II University of Naples, Naples, Italy (N.B-P.); and CIG Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland (M.N.L.).

Correspondence to Giuseppe Merla, PhD, Medical Genetics Unit, IRCCS Casa Sollievo della Sofferenza, viale Cappuccini, 71013 San Giovanni Rotondo, Italy. E-mail g.merla@operapadrepio.it

Abstract

Supravalvular aortic stenosis is a systemic elastin (ELN) arteriopathy that disproportionately affects the supravalvular aorta. ELN arteriopathy may be present in a nonsyndromic condition or in syndromic conditions such as Williams–Beuren syndrome. The anatomic findings include congenital narrowing of the lumen of the aorta and other arteries, such as branches of pulmonary or coronary arteries. Given the systemic nature of the disease, accurate evaluation is recommended to establish the degree and extent of vascular involvement and to plan appropriate interventions, which are indicated whenever hemodynamically significant stenoses occur. ELN arteriopathy is genetically heterogeneous and occurs as a consequence of haploinsufficiency of the ELN gene on chromosome 7q11.23, owing to either microdeletion of the entire chromosomal region or ELN point mutations. Interestingly, there is a prevalence of premature termination mutations resulting in null alleles among ELN point mutations. The identification of the genetic defect in patients with supravalvular aortic stenosis is essential for a definitive diagnosis, prognosis, and genetic counseling.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 692-696

doi: 10.1161/ CIRCGENETICS.112.962860

Genetic Loci for Coronary Calcification and Serum Lipids Relate to Aortic and Carotid Calcification

Daniel Bos, MD, M. Arfan Ikram, MD, PhD, Aaron Isaacs, PhD, Benjamin F.J. Verhaaren, MD, Albert Hofman, MD, PhD, Cornelia M. van Duijn, PhD, Jacqueline C.M. Witteman, PhD, Aad van der Lugt, MD, PhD and Meike W. Vernooij, MD, PhD

Author Affiliations

From the Departments of Radiology (D.B., M.A.I., B.F.J.V., A.v.d.L., M.W.V), Epidemiology (D.B., M.A.I., A.I., B.F.J.V., A.H., C.M.v.D., J.C.M.W., M.W.V.), and Genetic Epidemiology Unit (A.I., C.M.v.D.), Erasmus MC, Rotterdam, the Netherlands.

Correspondence to Meike W. Vernooij, MD, PhD, Department of Radiology, Erasmus MC, Gravendijkwal 230, PO Box 2040, 3000CA Rotterdam, the Netherlands. E-mail m.vernooij@erasmusmc.nl

Abstract

Background—Atherosclerosis in different vessel beds shares lifestyle and environmental risk factors. It is unclear whether this holds for genetic risk factors. Hence, for the current study genetic loci for coronary artery calcification and serum lipid levels, one of the strongest risk factors for atherosclerosis, were used to assess their relation with atherosclerosis in different vessel beds.

Methods and Results—From 1987 persons of the population-based Rotterdam Study, 3 single-nucleotide polymorphisms (SNPs) for coronary artery calcification and 132 SNPs for total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides were used. To quantify atherosclerotic calcification as a marker of atherosclerosis, all participants underwent nonenhanced computed tomography of the aortic arch and carotid arteries. Associations between genetic risk scores of the joint effect of the SNPs and of all calcification were investigated. The joint effect of coronary artery calcification–SNPs was associated with larger calcification volumes in all vessel beds (difference in calcification volume per SD increase in genetic risk score: 0.15 [95% confidence interval, 0.11–0.20] in aorta, 0.14 [95% confidence interval, 0.10–0.18] in extracranial carotids, and 0.11 [95% confidence interval, 0.07–0.16] in intracranial carotids). The joint effect of total cholesterol SNPs, low-density lipoprotein SNPs, and of all lipid SNPs together was associated with larger calcification volumes in both the aortic arch and the carotid arteries but attenuated after adjusting for the lipid fraction and lipid-lowering medication.

Conclusions—The genetic basis for aortic arch and carotid artery calcification overlaps with the most important loci of coronary artery calcification. Furthermore, serum lipids share a genetic predisposition with both calcification in the aortic arch and the carotid arteries, providing novel insights into the cause of atherosclerosis.

 SOURCE:

Circulation: Cardiovascular Genetics.2013; 6: 47-53

Published online before print December 16, 2012,

doi: 10.1161/ CIRCGENETICS.112.963934

 

Joint Associations of 61 Genetic Variants in the Nicotinic Acetylcholine Receptor Genes with Subclinical Atherosclerosis in American Indians

A Gene-Family Analysis

Jingyun Yang, PhD*, Yun Zhu, MS*, Elisa T. Lee, PhD, Ying Zhang, PhD, Shelley A. Cole, PhD, Karin Haack, PhD, Lyle G. Best, BS MD, Richard B. Devereux, MD, Mary J. Roman, MD, Barbara V. Howard, PhD and Jinying Zhao, MD, PhD

Author Affiliations

From the Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (J.Y., Y. Zhu, J.Z.); Center for American Indian Health Research, University of Oklahoma Health Sciences Center, Oklahoma City, OK (E.T.L., Y. Zhang); Texas Biomedical Research Institute, San Antonio, TX (S.A.C., K.H.); Missouri Breaks Industries Research Inc, Timber Lake, SD (L.G.B.); The New York Hospital-Cornell Medical Center, New York, NY (R.B.D., M.J.R.); MedStar Health Research Institute, Hyattsville, MD (B.V.H.); and Georgetown and Howard Universities Centers for Translational Sciences, Washington, DC (B.V.H.).

Correspondence to Jinying Zhao, MD, PhD, Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal St, SL18, New Orleans, LA 70112. E-mail jzhao5@tulane.edu

* These authors contributed equally to this work.

Abstract

Background—Atherosclerosis is the underlying cause of cardiovascular disease, the leading cause of morbidity and mortality in all American populations, including American Indians. Genetic factors play an important role in the pathogenesis of atherosclerosis. Although a single-nucleotide polymorphism (SNP) may explain only a small portion of variability in disease, the joint effect of multiple variants in a pathway on disease susceptibility could be large.

Methods and Results—Using a gene-family analysis, we investigated the joint associations of 61 tag SNPs in 7 nicotinic acetylcholine receptor genes with subclinical atherosclerosis, as measured by carotid intima-media thickness and plaque score, in 3665 American Indians from 94 families recruited by the Strong Heart Family Study (SHFS). Although multiple SNPs showed marginal association with intima-media thickness and plaque score individually, only a few survived adjustments for multiple testing. However, simultaneously modeling of the joint effect of all 61 SNPs in 7 nicotinic acetylcholine receptor genes revealed significant association of the nicotinic acetylcholine receptor gene family with both intima-media thickness and plaque score independent of known coronary risk factors.

Conclusions—Genetic variants in the nicotinic acetylcholine receptor gene family jointly contribute to subclinical atherosclerosis in American Indians who participated in the SHFS. These variants may influence the susceptibility of atherosclerosis through pathways other than cigarette smoking per se.

SOURCE:

Circulation: Cardiovascular Genetics.2013; 6: 89-96

Published online before print December 22, 2012,

doi: 10.1161/ CIRCGENETICS.112.963967

 

 

Heredity of Cardiovascular Disorders Inheritance

 

A Clinical Approach to Common Cardiovascular Disorders When There Is a Family History

The Implications of Inheritance for Clinical Management

Srijita Sen-Chowdhry, MBBS, MD, FESC, Daniel Jacoby, MD and William J. McKenna, MD, DSc, FESC

Author Affiliations

From the Institute of Cardiovascular Science, University College London, London, United Kingdom (S.S-C., W.J.M.); Department of Epidemiology, Imperial College, London, London, United Kingdom (S.S-C.); Division of Cardiology, Yale School of Medicine, New Haven, CT (D.J., W.J.M.).

Correspondence to Professor William J. McKenna, MD, DSc, FESC, Institute of Cardiovascular Science, University College London, The Heart Hospital, 16-18 Westmoreland Street, London, E-mail william.mckenna@uclh.nhs.uk

Introduction

Since the advent of genotyping, recognition of heritable disease has been perceived as an opportunity for genetic diagnosis or new gene identification studies to advance understanding of pathogenesis. Until recently, however, clinical application of DNA-based testing was confined largely to Mendelian disorders. Even within this remit, predictive testing of relatives is cost-effective only in diseases in which the majority of families harbor mutations in known causal genes, such as adult polycystic kidney disease and hypertrophic cardiomyopathy, but not dilated cardiomyopathy. Confirmatory genetic testing of index cases with borderline clinical features may be economic in the still smaller subset of diseases with limited locus heterogeneity, such as Marfan syndrome. Furthermore, Mendelian diseases account for ≈5% of total disease burden.1 Genome-wide association studies have made headway in elucidating the genetic contribution to the more common, complex diseases, and high throughput techniques promise to facilitate integration of genetic analysis into clinical practice. Nevertheless, many genes remain to be identified and implementation of genomic profiling as a population screening tool would not be cost-effective at present. The implications of heredity, however, extend beyond serving as a platform for genetic analysis, influencing diagnosis, prognostication, and treatment of both index cases and relatives, and enabling rational targeting of genotyping resources. This review covers acquisition of a family history, evaluation of heritability and inheritance patterns, and the impact of inheritance on subsequent components of the clinical pathway.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 467-476

doi: 10.1161/ CIRCGENETICS.110.959361

Clinical Considerations of Heritable Factors in Common Heart Failure

Thomas P. Cappola, MD, ScM and Gerald W. Dorn II, MD

Author Affiliations

From the Department of Medicine, University of Pennsylvania, Philadelphia, PA (T.P.C.), and Center for Pharmacogenomics, Washington University School of Medicine, St Louis, MO (G.W.D.II.).

Correspondence to Gerald W. Dorn II, MD, Center for Pharmacogenomics, Washington University, 660 S Euclid Ave, Campus Box 8220, St Louis, MO 63110. E-mail gdorn@dom.wustl.edu

 

Introduction

Heart failure is a common condition responsible for at least 290 000 deaths each year in the United States alone.1 A small minority of heart failure cases are attributed to Mendelian or familial cardiomyopathies. The majority of systolic heart failure cases are not familial but represent the end result of 1 or many conditions that primarily injure the myocardium sufficiently to diminish cardiac output in the absence of compensatory mechanisms. Paradoxically, because they also injure the myocardium, it is the chronic actions of the compensatory mechanisms that in many instances contribute to the progression from simple cardiac injury to dilated cardiomyopathy and overt heart failure. Thus, the epidemiology of common heart failure appears to be just as sporadic as its major antecedent conditions (atherosclerosis, diabetes, hypertension, and viral myocarditis).

Familial trends in preclinical cardiac remodeling2 and risk of developing heart failure3 reveal an important role for genetic modifiers in addition to clinical and environmental factors. Candidate gene studies performed over the past 10 years have identified a few polymorphic gene variants that modify risk or progression of common heart failure.4 Whole-genome sequencing will lead to the discovery of other genetic modifiers that were not candidates.5 The imminent availability of individual whole-genome sequences at a cost competitive with available genetic tests for familial cardiomyopathy will no doubt further expand the list of putative genetic heart failure modifiers. Heart failure risk alleles along with traditional clinical factors will need to be considered by clinical cardiologists in their design of optimal disease surveillance and prevention programs and in individually tailoring heart failure management.

The use of individual genetic make-up is likely to have the earliest and greatest impact on managing patients with heart failure by tailoring available pharmacotherapeutics to optimize patient response and minimize adverse effects (ie, the area of pharmacogenetics). Modern heart failure management has been derived and directed by the results of large, randomized, multicenter clinical trials. When standard therapies are applied according to the selection criteria used in these trials, they prolong average survival across affected populations or decrease the incidence of heart failure in populations at risk.6 For this reason, standardized treatment guidelines prescribe heart failure therapies according to trial designs, aiming for the same target doses and general treatment approaches,7 and largely ignore individual characteristics. In this article, we review established and emerging knowledge of genetic influence on common heart failure and try to anticipate how these genetic factors may be best used to eschew the cookie-cutter approach to heart failure management and move toward implementing a personalized medicine approach for the treatment and prevention of this important and prevalent disease.

The Concept of Genotype-Directed Personal Medical Management in Heart Failure

Variation in clinical heart failure progression and therapeutic response (either benefits or side effects) supports the need for a more individualized approach to disease management. On the basis of clinical stratification (eg, by etiology of heart failure as ischemic versus nonischemic, functional status, comorbid disease), physicians try to match each patient’s specific heart failure syndrome with a therapeutic regime devised to provide the most benefit. Standard heart failure pharmacotherapy currently comprises a minimum of 3 medications (angiotensin-converting enzyme [ACE] inhibitors, β-blockers, and aldosterone antagonists), with consideration of additional medications (hydralazine/isosorbide, angiotensin receptor blockers) and diuretics. The recommended target dosages for these agents, derived from their respective clinical trials, is rarely achieved,8 partly because of untoward clinical side effects such as low blood pressure or renal dysfunction. Accordingly, the published guidelines most often are applied in each individual patient using ad hoc approaches derived from personal experience and the “art of medicine.”

Technological advances in human genomics promise a different approach and are bringing cardiology into an era of clinically applied pharmacogenetics9 (whether we want to or not). As sequencing costs decline, it is not hard to envision that patients will present having had their entire genome already sequenced. The imperative to apply genome information in clinical settings will increase, as demonstrated by recent proof-of-concept studies.10 Our field seems poorly prepared for this type of evolution in care; Roden et al9 identified 3 major barriers: First is the absence of rapidly available genotype information in the clinical workflow. This barrier is being overcome with whole-genome sequencing, which (with proper analysis) promises a permanent and largely immutable genetic roadmap for individual disease risk and drug response at a cost comparable to many other clinical tests.11 Second, we must have the knowledge to properly apply information on genetic variants for the diseases we are managing and the drugs we are using. As we describe, this knowledge is accumulating for heart failure and for other cardiac conditions, and the rate at which we are gaining additional information and developing further expertise appears to be accelerating.

The third and perhaps most formidable barrier is the lack of clinical evidence showing how real-time application of genetic information can best benefit patients. As has been broadly communicated to the medical community and lay public, common functional gene variants in CYP2C19 can impair the transformation of clopidogrel into its active metabolite, leading to increased risk of stent thrombosis after percutaneous coronary intervention.12 The relevant question thus becomes the following: If physicians have this information at the time of clinical care and reacted by adjusting clopidogrel dose or substituting prasugrel, which is unaffected by CYP2C19 genotype,13 would there be any improvement in clinical outcome? It is also important to consider whether any observed benefits justify the additional costs of genetic testing and for the alternate drug. Studies are currently examining these questions, and similar clinical trials will prospectively examine whether a genotype-guided strategy of warfarin dosing will be superior to the standard genotype-blinded approach in reaching target anticoagulation goals. At this time, there are no similar prospective, randomized, blinded trials of genotype-guided care for common heart failure.

Emerging Variants

The variants described here are established, but new ones are emerging. Although findings in heart failure genome-wide association studies have been limited, we can expect additional common heart failure variants to emerge as sample sizes increase.65 The CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium published a genome-wide association study of incident heart failure that tested for associations between >2.4 million HapMap-imputed polymorphisms in >20 000 subjects.7 They identified 2 loci associated with heart failure, rs10519210 (15q22, containing USP3 encoding a ubiquitin-specific protease) in subjects of European ancestry and rs11172782 (12q14, containing LRIG3 encoding a leucine-rich, immunoglobulin-like domain-containing protein of uncertain function) in subjects of African ancestry.66 In a companion study using the same population and genotyping results, mortality analysis of the subgroup of individuals who developed heart failure implicated an intronic SNP in CMTM7 (CKLF-like MARVEL transmembrane domain-containing 7).67 These genetic associations require independent replication and further study to identify the underlying biological mechanisms.

A recently published genome-wide association study by a European consortium on dilated cardiomyopathy identified common variants in BAG3 (BCL2-associated athanogene 3) associated with heart failure57 and identified rare BAG3 missense and truncation mutations that segregate with familial cardiomyopathy. These findings were consistent with an earlier exome-sequencing study that identified BAG3 as a familial dilated cardiomyopathy gene and showed recapitulation of cardiomyopathy with BAG3 morpholino knockdown in zebra fish.68 Together, these studies convincingly support variation in BAG3 as a genetic risk factor of cardiomyopathy and heart failure. It is noteworthy that both common and rare functional variations were identified at this locus. A unifying hypothesis for these findings, which needs to be formally tested, is that common variants in BAG3 serve as proxies for rare functional BAG3 mutations with large effects. In this situation, the underlying genetic lesion is a rare variant with a large functional effect. This has recently been described for common variants in MYH6 that correlated with rare functional MYH6 variants to cause sick sinus syndrome.69 It is premature to speculate on the clinical applications of these newer findings.

Moving Knowledge to Practice

A small number of genomic variants have been identified that modify heart failure by affecting well-understood physiological systems. The principal barrier preventing their adoption in practice may be lack of evidence showing how application of this information can best be used for clinical benefit. Trials testing genotype targeting of antiplatelet therapy and anticoagulation will be completed in the coming years. The findings from these studies will likely determine the level of enthusiasm for conducting genotype-guided trials of β-blockers and RAAS antagonists in heart failure. Given that the lifetime risk of heart failure in the United States is estimated at 1 in 5, even a small favorable effect on heart failure prevention or outcome through use of genome-guided therapy has the potential for a large public health impact. We therefore believe that a near-term goal should be to conduct pharmacogenomic trials in heart failure based on our current understanding of heart failure variants.

Looking ahead, unbiased approaches will continue to reveal a large number heart failure-modifying variants (both common and rare). Based on experience in other complex phenotypes, such has height70 and plasma lipid levels,71 the underlying genetic mechanisms for many new heart failure variants will be completely unknown, and their sheer number will preclude detailed experimentation using murine models to figure them out. Leveraging these variants for clinical application is a challenge that we will be forced to confront.

As our ability to identify rare, disease-causing variants improves through personal genome sequencing, we will be faced with the additional problem of how best to estimate the disease risk conferred by a sequence variant for which there has been no biological validation. In probabilistic terms, because there are 3 billion nucleotides in the human genome and over twice that many humans on the planet, it is likely that a nucleotide substitution for every position is represented in someone. Obviously, it will be impossible to recombinantly express and functionally characterize every DNA variant that is going to be implicated in heart failure. Bioinformatics filters have been used to try and separate functionally significant from insignificant variants based on the likelihood of changing transcript expression or protein function. These tools are limited but will improve if we tailor their results to the known characteristics of each gene product. For example, current approaches to categorize amino acid substitutions as conservative or nonconservative based only on charge or side chains can be improved by molecular modeling that incorporates protein-specific structure-function information. This approach has been used to estimate the pathogenicity of myosin heavy chain (MHC) mutations in an effort to determine which mutations are likely to cause familial cardiomyopathy when linkage analysis is not feasible.72 In concept, this approach can be applied to any protein for which structure-function activities have been finely mapped to distinct domains.

A promising extension of this approach may be to use evolutionary genetics to infer disease causality. Again, using the MHC genes as examples, human genome data show a greater prevalence of nonsynonymous gene variants in MYH6, which encodes the minor cardiac α-MHC isoform, compared with the adjacent MYH7, which encodes the major β-MHC isoform. This disparity suggests a greater tolerance for protein changes in the α-MHC isoform and negative selection against these in β-MHC. We can infer, therefore, that amino acid changes are more likely to have adverse impacts in MYH7-encoded β-MHC. If this paradigm survives prospective testing, then the forthcoming explosion of individual genetic data not only will present a massive problem in interpretation, but also will provide the genetic information by which analyses of rare sequence variants across large unaffected populations can help to differentiate the tolerable variants from those that are more likely to alter disease risk.

Each Reference above is found in:

http://circgenetics.ahajournals.org/content/4/6/701.full

SOURCE: 

Circulation: Cardiovascular Genetics.2011; 4: 701-709

doi: 10.1161/ CIRCGENETICS.110.959379

 

Pharmacogenomics

 

Hypertension Susceptibility Loci and Blood Pressure Response to Antihypertensives

Results From the Pharmacogenomic Evaluation of Antihypertensive Responses Study

Yan Gong, PhD, Caitrin W. McDonough, PhD, Zhiying Wang, MS, Wei Hou, PhD, Rhonda M. Cooper-DeHoff, PharmD, MS, Taimour Y. Langaee, PhD, Amber L. Beitelshees, PharmD, MPH, Arlene B. Chapman, MD, John G. Gums, PharmD, Kent R. Bailey, PhD, Eric Boerwinkle, PhD, Stephen T. Turner, MD and Julie A. Johnson, PharmD

Author Affiliations

From the Department of Pharmacotherapy and Translational Research (Y.G., C.W.M., R.M.C.-D., T.Y.L., J.G.G., J.A.J.), Department of Biostatistics, College of Medicine (W.H.), Division of Cardiovascular Medicine, College of Medicine (R.M.C.-D., J.A.J.), and Department of Community Health and Family Medicine (J.G.G.), University of Florida, Gainesville, FL; Division of Epidemiology, University of Texas at Houston, Houston, TX (Z.W., E.B.); Division of Endocrinology, Diabetes and Nutrition, University of Maryland, Baltimore, MD (A.L.B.); Renal Division, Emory University, Atlanta, GA (A.B.C.); and Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN (S.T.T.).

Correspondence to Yan Gong, PhD, Department of Pharmacotherapy and Translational Research, University of Florida, PO Box 100486, 1600 SW Archer Rd, Gainesville, FL 32610. E-mail gong@cop.ufl.edu.

Abstract

Background—To date, 39 single nucleotide polymorphisms (SNPs) have been associated with blood pressure (BP) or hypertension in genome-wide association studies in whites. Our hypothesis is that the loci/SNPs associated with BP/hypertension are also associated with BP response to antihypertensive drugs.

Methods and Results—We assessed the association of these loci with BP response to atenolol or hydrochlorothiazide monotherapy in 768 hypertensive participants in the Pharmacogenomics Responses of Antihypertensive Responses study. Linear regression analysis was performed on whites for each SNP in an additive model adjusting for baseline BP, age, sex, and principal components for ancestry. Genetic scores were constructed to include SNPs with nominal associations, and empirical P values were determined by permutation test. Genotypes of 37 loci were obtained from Illumina 50K cardiovascular or Omni1M genome-wide association study chips. In whites, no SNPs reached Bonferroni-corrected α of 0.0014, 6 reached nominal significance (P<0.05), and 3 were associated with atenolol BP response at P<0.01. The genetic score of the atenolol BP-lowering alleles was associated with response to atenolol (P=3.3×10–6 for systolic BP; P=1.6×10–6 for diastolic BP). The genetic score of the hydrochlorothiazide BP-lowering alleles was associated with response to hydrochlorothiazide (P=0.0006 for systolic BP; P=0.0003 for diastolic BP). Both risk score P values were <0.01 based on the empirical distribution from the permutation test.

Conclusions—These findings suggest that selected signals from hypertension genome-wide association studies may predict BP response to atenolol and hydrochlorothiazide when assessed through risk scoring.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 686-691

Published online before print October 19, 2012,

doi: 10.1161/ CIRCGENETICS.112.964080

 

Genetic Determinants of Statin-Induced Low-Density Lipoprotein Cholesterol Reduction

The Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER) Trial

Daniel I. Chasman, PhD, Franco Giulianini, PhD, Jean MacFadyen, BA, Bryan J. Barratt, PhD, Fredrik Nyberg, MD, PhD, MPH and Paul M Ridker, MD, MPH

Author Affiliations

From the Center for Cardiovascular Disease Prevention (D.I.C., F.G., J.M., P.M.R.), JUPITER Trial Coordinating Center (D.I.C., F.G., J.M., P.M.R.), Brigham and Women’s Hospital and Harvard Medical School (D.I.C., P.M.R.), Boston, MA; Personalised Healthcare and Biomarkers, AstraZeneca Research and Development, Alderley Park, United Kingdom (B.J.B.); AstraZeneca Research and Development, Mölndal, Sweden (F.N.); and Unit of Occupational and Environmental Medicine, Department of Public Health and Community Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden (F.N.).

Correspondence to Daniel I. Chasman, PhD, Center for Cardiovascular Disease Prevention, Brigham and Women’s Hospital, 900 Commonwealth Ave E, Boston, MA 02215. E-mail dchasman@rics.bwh.harvard.edu

Abstract

Background—In statin trials, each 20 mg/dL reduction in cholesterol results in a 10–15% reduction of annual incidence rates for vascular events. However, interindividual variation in low-density lipoprotein cholesterol (LDL-C) response to statins is wide and may partially be determined on a genetic basis.

Methods and Results—A genome-wide association study of LDL-C response was performed among a total of 6989 men and women of European ancestry who were randomly allocated to either rosuvastatin 20 mg daily or placebo. Single nucleotide polymorphisms (SNPs) for genome-wide association (P<5×108) with LDL-C reduction on rosuvastatin were identified at ABCG2, LPA, and APOE, and a further association at PCSK9 was genome-wide significant for baseline LDL-C and locus-wide significant for LDL-C reduction. Median LDL-C reductions on rosuvastatin were 40, 48, 51, 55, 60, and 64 mg/dL, respectively, among those inheriting increasing numbers of LDL-lowering alleles for SNPs at these 4 loci (P trend=6.2×1020), such that each allele approximately doubled the odds of percent LDL-C reduction greater than the trial median (odds ratio, 1.9; 95% confidence interval, 1.8–2.1; P=5.0×1041). An intriguing additional association with sub–genome-wide significance (P<1×10-6) was identified for statin related LDL-C reduction at IDOL, which mediates posttranscriptional regulation of the LDL receptor in response to intracellular cholesterol levels. In candidate analysis, SNPs in SLCO1B1 and LDLR were confirmed as associated with LDL-C lowering, and a significant interaction was observed between SNPs in PCSK9 and LDLR.

Conclusions—Inherited polymorphisms that predominantly relate to statin pharmacokinetics and endocytosis of LDL particles by the LDL receptor are common in the general population and influence individual patient response to statin therapy.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 257-264

Published online before print February 13, 2012,

doi: 10.1161/ CIRCGENETICS.111.961144

Genetic Variation in the β2 Subunit of the Voltage-Gated Calcium Channel and Pharmacogenetic Association With Adverse Cardiovascular Outcomes in the INternational VErapamil SR-Trandolapril STudy GENEtic Substudy (INVEST-GENES)

Yuxin Niu, PhD*, Yan Gong, PhD*, Taimour Y. Langaee, PhD, Heather M. Davis, PharmD, Hazem Elewa, PhD, Amber L. Beitelshees, PharmD, MPH, James I. Moss, PhD, Rhonda M. Cooper-DeHoff, PharmD, Carl J. Pepine, MD and Julie A. Johnson, PharmD

Author Affiliations

From the Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics (Y.N., Y.G., T.Y.L., H.M.D., H.E., J.I.M., R.M.C.-D., J.A.J.), College of Pharmacy, University of Florida, Gainesville, Fla; Division of Endocrinology, Diabetes and Nutrition (A.L.B.), University of Maryland School of Medicine, Baltimore, Md; and Division of Cardiovascular Medicine (R.M.C.-D., C.J.P., J.A.J.), University of Florida College of Medicine, Gainesville, Fla.

Correspondence to Julie A. Johnson, PharmD, Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, PO Box 100486, Gainesville, FL 32610. E-mail Johnson@cop.ufl.edu

* Drs Niu and Gong contributed equally to this work.

Abstract

Background— Single-nucleotide polymorphisms (SNPs) within the regulatory β2 subunit of the voltage-gated calcium channel (CACNB2) may contribute to variable treatment response to antihypertensive drugs and adverse cardiovascular outcomes.

Methods and Results— SNPs in CACNB2 from 60 ethnically diverse individuals were identified and characterized. Three common SNPs (rs2357928, rs7069292, and rs61839258) and a genome-wide association study-identified intronic SNP (rs11014166) were genotyped for a clinical association study in 5598 hypertensive patients with coronary artery disease randomized to a β-blocker (BB) or a calcium channel blocker (CCB) treatment strategy in the INternational VErapamil SR-Trandolapril STudy GENEtic Substudy (INVEST-GENES). Reporter gene assays were conducted on the promoter SNP, showing association with clinical outcomes. Twenty-one novel SNPs were identified. A promoter A>G SNP (rs2357928) was found to have significant interaction with treatment strategy for adverse cardiovascular outcomes (P for interaction, 0.002). In whites, rs2357928 GG patients randomized to CCB were more likely to experience an adverse outcome than those randomized to BB treatment strategy, with adjusted hazard ratio (HR) (CCB versus BB) of 2.35 (95% CI, 1.19 to 4.66; P=0.014). There was no evidence for such treatment difference in AG (HR, 1.16; 95% CI, 0.75 to 1.79; P=0.69) and AA (HR, 0.63; 95% CI, 0.36 to 1.11; P=0.11) patients. This finding was consistent in Hispanics and blacks. CACNB2 rs11014166 showed similar pharmacogenetic effect in Hispanics, but not in whites or blacks. Reporter assay analysis of rs2357928 showed a significant increase in promoter activity for the G allele compared to the A allele.

Conclusions— These data suggest that genetic variation within CACNB2 may influence treatment-related outcomes in high-risk patients with hypertension.

Clinical Trial Registration— URL: http://www.clinicaltrials.gov. Unique identifier: NCT00133692.

SOURCE:

Circulation: Cardiovascular Genetics.2010; 3: 548-555

doi: 10.1161/ CIRCGENETICS.110.957654

 

Hepatic Metabolism and Transporter Gene Variants Enhance Response to Rosuvastatin in Patients With Acute Myocardial Infarction

The GEOSTAT-1 Study

Kristian M. Bailey, MBChB, Simon P.R. Romaine, BSc, Beryl M. Jackson, RGN, Amanda J. Farrin, MSc, Maria Efthymiou, MSc, Julian H. Barth, MD, Joanne Copeland, BSc, Terry McCormack, MBBS, Andrew Whitehead, MSc, Marcus D. Flather, MBBS, Nilesh J. Samani, MD, FMedSci, Jane Nixon, PhD, Alistair S. Hall, MD, PhD, Anthony J. Balmforth, PhD and on behalf of the SPACE ROCKET Trial Group

Author Affiliations

From the Division of Cardiovascular and Diabetes Research (K.M.B., S.P.R.R., B.M.J., A.J.B.), and Division of Cardiovascular and Neuronal Remodelling (A.S.H.), Multidisciplinary Cardiovascular Research Centre, Leeds Institute of Genetics, Health and Therapeutics, University of Leeds, Leeds, United Kingdom; Clinical Trials Research Unit (A.J.F., M.E., J.C., J.N.), University of Leeds, Leeds, United Kingdom; Clinical Biochemistry (J.H.B.), Leeds General Infirmary, Leeds, United Kingdom; Whitby Group Practice (T.M.), Spring Vale Medical Centre, Whitby, North Yorkshire, United Kingdom; Pharmacy Department (A.W.), Leeds General Infirmary, Leeds, United Kingdom; Clinical Trials and Evaluation Unit (M.D.F.), Royal Brompton and Harefield NHS Trust and Imperial College, London, United Kingdom; and Department of Cardiovascular Sciences (N.J.S.), University of Leicester, Leicester, United Kingdom.

Correspondence to Alistair S. Hall, Clinical Cardiology, Multidisciplinary Cardiovascular Research Centre (MCRC), G Floor, Jubilee Building, Leeds General Infirmary, Leeds, LS1 3EX, United Kingdom. E-mail A.S.Hall@leeds.ac.uk

* Dr Bailey, Mr Romaine, Dr Hall, and Dr Balmforth contributed equally to this study.

Abstract

Background— Pharmacogenetics aims to maximize benefits and minimize risks of drug treatment. Our objectives were to examine the influence of common variants of hepatic metabolism and transporter genes on the lipid-lowering response to statin therapy.

Methods and Results— The Genetic Effects On STATins (GEOSTAT-1) Study was a genetic substudy of Secondary Prevention of Acute Coronary Events—Reduction of Cholesterol to Key European Targets (SPACE ROCKET) (a randomized, controlled trial comparing 40 mg of simvastatin and 10 mg of rosuvastatin) that recruited 601 patients after myocardial infarction. We genotyped the following functional single nucleotide polymorphisms in the genes coding for the cytochrome P450 (CYP) metabolic enzymes, CYP2C9*2 (430C>T), CYP2C9*3 (1075A>C), CYP2C19*2 (681G>A), CYP3A5*1 (6986A>G), and hepatic influx and efflux transporters SLCO1B1 (521T>C) and breast cancer resistance protein (BCRP; 421C>A). We assessed 3-month LDL cholesterol levels and the proportion of patients reaching the current LDL cholesterol target of <70 mg/dL (<1.81 mmol/L). An enhanced response to rosuvastatin was seen for patients with variant genotypes of either CYP3A5 (P=0.006) or BCRP (P=0.010). Furthermore, multivariate logistic-regression analysis revealed that patients with at least 1 variant CYP3A5 and/or BCRP allele (n=186) were more likely to achieve the LDL cholesterol target (odds ratio: 2.289; 95% CI: 1.157, 4.527; P=0.017; rosuvastatin 54.0% to target vs simvastatin 33.7%). There were no differences for patients with variants of CYP2C9, CYP2C19, or SLCO1B1 in comparison with their respective wild types, nor were differential effects on statin response seen for patients with the most common genotypes for CYP3A5 and BCRP (n=415; odds ratio: 1.207; 95% CI: 0.768, 1.899; P=0.415).

Conclusion— The LDL cholesterol target was achieved more frequently for the 1 in 3 patients with CYP3A5 and/or BCRP variant genotypes when prescribed rosuvastatin 10 mg, compared with simvastatin 40 mg.

Clinical Trial Registration— URL: http://isrctn.org. Unique identifier: ISRCTN 89508434.

SOURCE:

Circulation: Cardiovascular Genetics.2010; 3: 276-285

Published online before print March 5, 2010,

doi: 10.1161/ CIRCGENETICS.109.898502

 

Comprehensive Whole-Genome and Candidate Gene Analysis for Response to Statin Therapy in the Treating to New Targets (TNT) Cohort

John F. Thompson, PhD, Craig L. Hyde, PhD, Linda S. Wood, MS, Sara A. Paciga, MA, David A. Hinds, PhD, David R. Cox, MD, PhD, G. Kees Hovingh, MD, PhD and John J.P. Kastelein, MD, PhD

Author Affiliations

From the Helicos BioSciences (J.F.T.), Cambridge, Mass; Molecular Medicine (J.F.T., L.S.W., S.A.P.) and Statistical Applications (C.L.H.), Pfizer Global Research and Development, Groton, Conn; Perlegen Sciences (D.A.H., D.R.C.), Mountain View, Calif; and Department of Vascular Medicine (G.K.H., J.J.P.K.), Academic Medical Center, Amsterdam, The Netherlands.

Correspondence to John J.P. Kastelein, MD, PhD, Department of Vascular Medicine, Academic Medical Center, Meibergdreef 9, Room F4-159.2, 1105 AZ Amsterdam, The Netherlands. E-mail j.j.kastelein@amc.uva.nl or j.s.jansen@amc.uva.nl

Abstract

Background— Statins are effective at lowering low-density lipoprotein cholesterol and reducing risk of cardiovascular disease, but variability in response is not well understood. To address this, 5745 individuals from the Treating to New Targets (TNT) trial were genotyped in a combination of a whole-genome and candidate gene approach to identify associations with response to atorvastatin treatment.

Methods and Results— A total of 291 988 single-nucleotide polymorphisms (SNPs) from 1984 individuals were analyzed for association with statin response, followed by genotyping top hits in 3761 additional individuals. None was significant at the whole-genome level in either the initial or follow-up test sets for association with low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, or triglyceride response. In addition to the whole-genome platform, 23 candidate genes previously associated with statin response were analyzed in these 5745 individuals. Three SNPs in apoE were most highly associated with low-density lipoprotein cholesterol response, followed by 1 in PCSK9 with a similar effect size. At the candidate gene level, SNPs in HMGCR were also significant though the effect was less than with those in apoE and PCSK9. rs7412/apoE had the most significant association (P=6×1030), and its high significance in the whole-genome study (P=4×109) confirmed the suitability of this population for detecting effects. Age and gender were found to influence low-density lipoprotein cholesterol response to a similar extent as the most pronounced genetic effects.

Conclusions— Among SNPs tested with an allele frequency of at least 5%, only SNPs in apoE are found to influence statin response significantly. Less frequent variants in PCSK9 and smaller effect sizes in SNPs in HMGCR were also revealed.

SOURCE:

Circulation: Cardiovascular Genetics.2009; 2: 173-181

Published online before print February 12, 2009,

doi: 10.1161/ CIRCGENETICS.108.818062

Summary

Larry H. Bernstein, MD, FCAP

This review has examined a compendium of well regarded documents drawn from 248 articles in Circulation Cardiovascular Genetics from March 2010 to March 2013. The large amount of evidence obtained from large population studies identifying Genome Wide Analysis Studies (GWAS) examines a host of cardiac and vascular diseases in which there is association between specific single nucleotide peptides (SNPs), and gene loci, that may play or have no significant role in developing heart disease. It certainly is evidence of the role that the American Heart Association has is in supporting the leading research today for tomorrow’s patients.   It is too early to sort them out, but it speaks to a large volume of discovery in this area.

It raises another issue that we have been confronted with mostly since the second half of the 20th century.  What is that issue?  The issue, it appears to me, is the vast improvements in analytical technology so that “imprecision” is far less likely to be a confounder in biological measurements and this lends access to far better accuracy?  But from that question arises another! Accuracy only refers to what is measured, but does it give us better ability to explain a complex and dynamic process?  In other words, what is what we are looking at representative of in manageable events?   I think that this is the most important idea that should come out of the recent criticism of the trajectory that molecular genetics been on in the last 5 years.

It was still in an era that “BIG’ science was not the normal.  One could spend an enormous effort at stepwise purification of a protein or enzyme, or other biomolecule starting with a slurry made from 100 lbs of “chicken heart”, for example.  These separations were based on negative charges on the molecules and positive charges on the column, and the molecules of no interest were eluted by gradient elution.  Much was learned about large scale preparation from small scale trials.  But this work was not undertaken without the intent to carry out a number of investigations to understand the “functionality” of a link in a metabolic pathway.  The studies that followed the purification required kinetic investigation with a coenzyme, or with a synthetically modified coenzyme, amino acid sequencing, NMR studies, etc.  You could not put together a “mechanism” without having the minimum amount of necessary information for a reliable account.  It is probably this requirement that led to today’s “BIG” science, that is founded upon multiple methods, now large data bases, and teams of investigators across institutions and continents.  The acquisition of knowledge has been astounding, but the integration of knowledge has not caught up.

However, let’s see if we can sort out the most meaningful signals from what I too am beginning to call the “noisy channel”.  As often happens, important areas of research are opened up that are followed by significant discovery and, in the long run, many other dead end publications that have no lasting significance.  In order to do justice to the work, I’ll pick through documents I find interesting, keeping in mind there is a hidden layer of complexity of which only sufficient information leads to a better understanding.  As much literature calls attention to, much of what ails us has nothing to do with classical Mendelian genetics, and has a postgenomic component.

The most fascinating aspect of this is the withering “dark matter” of the genome. While that component may be silent or expressed, the understanding comes at a higher observed order.  The dark became light! The expression became subtle, like weak bond interactions. The underlying organization is a component of the adaptive ability of an organism or individual in an environment with plants and animals in a changing climate, at particular altitudes, with given water supplies, with disease vectors, and with endogenous sources of essential nutrients.  This brings into focus the regulatory role of the genome as just as important a factor as transmission of the genetic code, especially in somatic cell populations.

The remainder of this discussion deals specifically with my observations on cardiovascular genomics. The following conclusion is appropriate, if incomplete, at this time on circulating miRNAs, particularly miR-133a:

  • elevated levels of circulating miR-133a in patients with cardiovascular diseases originate mainly from the injured myocardium.
  • Circulating miR-133a can be used as a marker for cardiomyocyte death, and

A number of articles that cite this article suggest that it may be useful for following disease progression:
Plasma microRNAs serve as biomarkers of therapeutic efficacy and disease progression in hypertension-induced heart failure  Eur J Heart Fail  2013

MicroRNAs Within the Continuum of Postgenomics Biomarker Discovery Arterio. Thromb. Vasc. Bio. 2013;33:206-214

“Need for Rigor in Design, Reporting, and Interpretation of Transcriptomic Biomarker Studies”  J. Clin. Microbiol.. 2012;50:4192-4193

Circulating microRNAs as diagnostic biomarkers for cardiovascular diseases. Am. J. Physiol. Heart Circ. Physiol.. 2012;303:H1085-H1095,

Circulating MicroRNAs: Novel Biomarkers and Extracellular Communicators in Cardiovascular Disease? Circ. Res.. 2012;110:483-495

Circulating MicroRNAs: Biomarkers or Mediators of Cardiovascular Diseases?  Arterioscler. Thromb. Vasc. Bio. 2011;31:2383-2390,

Circulating MicroRNA-208b and MicroRNA-499 Reflect Myocardial Damage in Cardiovascular Disease MF Corsten, R Dennert, S Jochem, T Kuznetsova,  et al.

The finding refers to an association that is related to the appearance of a miRNA in the circulation of patients with acute cardiac ischemia, and particular released into the circulation of patients from injured myocardium.  This finding has to be distinguished from a finding of another miRNA released with acute injury.  In the case of miR499 (and miR208b), there is a comparison with plasma cTnT, and an ROC curve is produced.

The List of this follows:

Circulation: Cardiovascular Genetics 2010; 3: 499-506

Strikingly, in plasma from

  • acute myocardial infarction patients, cardiac myocyte–associated miR-208b and -499 were highly elevated, 1600-fold (P<0.005) and 100-fold (P<0.0005), respectively, as compared with control subjects. Receiver operating characteristic curve analysis revealed an area under the curve of 0.94 (P<10−10) for miR-208b and 0.92 (P<10−9) for miR-499. Both microRNAs correlated with plasma troponin T, indicating release of microRNAs from injured cardiomyocytes.
  • In patients with acute heart failure, only miR-499 was significantly elevated (2-fold), whereas
  • no significant changes in microRNAs studied could be observed in diastolic dysfunction.

Remarkably, plasma microRNA levels were not affected by a wide range of clinical confounders, including

  • age,
  • sex,
  • body mass index,
  • kidney function,
  • systolic blood pressure, and
  • white blood cell count.

This is miRNA with a different twist.  It appears that there are 3 types found in AMI (133a, 208b, 409).  But type 499 alone is increased with acute heart failure (no mention of chronic cardiomyopathy and no effect of estimated GFR, or of age).

If the problem was just of AMI, then we have to know what this brings to the table.  As it is the hs-troponins have yet to be shown to effectively not only increase the high sensitivity of the tests, but to decrease the confusion generated by the elevation.  The enormous improvement of a test that may be superior to the hs-ctn’s is for the patient with very indeterminiate shortness of breath, a nondefinitive ECG, and in a prodromal phase of AMI.  This happened in the past, and it may happen now, and it may account for many cases of silent MI that were found at autopsy.

Cited by
Plasma microRNAs serve as biomarkers of therapeutic efficacy and disease progression in hypertension-induced heart failure Eur J Heart Fail. 2013;0:hft018v1-hft018,
Circulating microRNAs as diagnostic biomarkers for cardiovascular diseases Am. J. Physiol. Heart Circ. Physiol.. 2012;303:H1085-H1095,

Circulation Editors’ Picks: Most Read Articles in Cardiovascular Genetics Circulation. 2012;126:e163-e169,
MicroRNAs in Patients on Chronic Hemodialysis (MINOS Study) CJASN. 2012;7:619-623,

Novel techniques and targets in cardiovascular microRNA research Cardiovasc Res. 2012;93:545-554,

Microparticles: major transport vehicles for distinct microRNAs in circulation Cardiovasc Res. 2012;93:633-644,

Profiling of circulating microRNAs: from single biomarkers to re-wired networks Cardiovasc Res. 2012;93:555-562,

Small but smart–microRNAs in the centre of inflammatory processes during cardiovascular diseases, the metabolic syndrome, and ageing   Cardiovasc Res. 2012;93:605-613,

Circulation: Heart Failure Editors’ Picks: Most Important Papers in Pathophysiology and Genetics Circ Heart Fail. 2012;5:e32-e49

Use of Circulating MicroRNAs to Diagnose Acute Myocardial Infarction   Clin. Chem. 2012;58:559-567,

Circulating microRNAs to identify human heart failure   Eur J Heart Fail. 2012;14:118-119,

Next Steps in Cardiovascular Disease Genomic Research–Sequencing, Epigenetics, and Transcriptomics  Clin. Chem. 2012;58:113-126,

Most Read in Cardiovascular Genetics on Biomarkers, Inherited Cardiomyopathies and Arrhythmias, Metabolomics, and Genomics Circ Cardiovasc Genet. 2011;4:e24-e30,

MicroRNA-126 modulates endothelial SDF-1 expression and mobilization of Sca-1+/Lin- progenitor cells in ischaemia  Cardiovasc Res. 2011;92:449-455,

The use of genomics for treatment is another matter, and has several factors, e.g., age, residual function after AMI, comorbidities

This is a lot of interesting work that opens as many questions as it answers. The observations are real, and they lead to questions relating to the heart and the circulation.  Maybe it will generate answers to very tough issues concerning hypertension, renal disease and the heart.  It is far too early to tell.  It appears that we are about to hear a cacophony of miR’s in a symphony on cardiac and circulatory diseases not be be pieced together soon. But we have many more tools at our disposal than we did when Karmen discovered and made a distinction between

  • Aspartate and Alanine aminotransferases in the late 1950s, followed in the 1960s by
  • Creatine phosphokinase, the
  • MB-isoenzyme of CK by Sobel, Shell and Kjeckshus,
  • isoenzyme-1 of lactate dehydrogenase, and later the
  • Troponins,

leading to the programs to “reduce the extent of infarct damage”.  Then came the

  • a- and b-type natriuretic peptides,

which are still not fully understood in their role in congestive heart failure and in renal disease.

One item strikes the imagination as a fruitful area of further study.   Genetic Determinants of Potassium Sensitivity and Hypertension.    Integrated Computational and Experimental Analysis of the Neuroendocrine Transcriptome in Genetic Hypertension Identifies Novel Control Points for the Cardiometabolic Syndrome

Essential hypertension, a common complex disease, displays substantial genetic influence. Contemporary methods to dissect the genetic basis of complex diseases such as the genomewide association study are powerful, yet a large gap exists betweens the fraction of population trait variance explained by such associations and total disease heritability.

The researchers

  • developed a novel, integrative method (combining animal models, transcriptomics, bioinformatics, molecular biology, and trait-extreme phenotypes)
  • to identify candidate genes for essential hypertension and the metabolic syndrome.

Method  …  transcriptome profiling on adrenal glands from blood pressure extreme mouse strains:

  1. the hypertensive BPH (blood pressure high) and
  2. hypotensive BPL (blood pressure low).

Results….   Microarray data clustering revealed

  • underexpression of intermediary metabolism transcripts in HIGH BLOOD PRESSURE.
  • The MITRA algorithm identified a conserved motif in the transcriptional regulatory regions of the underexpressed metabolic genes,
  • They decide that regulation through this motif contributed to the global underexpression.
  • Luciferase reporter assays demonstrated transcriptional activity of the motif through transcription factors
    • HOXA3,
    • SRY, and
    •  YY1.

They finally hypothesized that genetic variation at HOXA3, SRY, and YY1 might predict blood pressure and other metabolic syndrome traits in humans. Tagging variants for each locus were associated with

  • blood pressure in a human population blood pressure extreme sample with
  • the most extensive associations for YY1 tagging single nucleotide polymorphism rs11625658 on
  1. systolic blood pressure,
  2. diastolic blood pressure,
  3. body mass index, and
  4. fasting glucose.

Meta-analysis extended the YY1 results into 2 additional large population samples with significant effects preserved on diastolic blood pressure, body mass index, and fasting glucose.

It will take much more of this beautiful integrative work to open up our imagination as to what physiological processes are occurring.

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Reporter: Aviva Lev-Ari, PhD, RN

Engineers work to help biologists cope with big data

Tue, 01/08/2013 – 10:15am

Liang Dong is developing an instrument that will allow plant scientists to simultaneously study thousands of plants grown in precisely controlled condition. Photo: Bob ElbertLiang Dong is developing an instrument that will allow plant scientists to simultaneously study thousands of plants grown in precisely controlled condition. Photo: Bob ElbertLiang Dong held up a clear plastic cube, an inch or so across, just big enough to hold 10 to 20 tiny seeds.

Using sophisticated sensors and software, researchers can precisely control the light, temperature, humidity, and carbon dioxide inside that cube.

Dong—an Iowa State University assistant professor of electrical and computer engineering and of chemical and biological engineering—calls it a “microsystem instrument.” Put hundreds of those cubes together and researchers can simultaneously grow thousands of seeds and seedlings in different conditions and see what happens. How, for example, do the plants react when it is hot and dry? Or carbon dioxide levels change? Or light intensity is adjusted very slightly?

The instrument designed and built by Dong’s research group will keep track of all that by using a robotic arm to run a camera over the cubes and take thousands of images of the growing seeds and seedlings.

Plant scientists will use the images to analyze the plants’ observable characteristics—the leaf color, the root development, the shoot size. All those observations are considered a plant’s phenotype. And while plant scientists understand plant genetics very well, Dong says they don’t have a lot of data about how genetics and environment combine to influence phenotype.

Dong’s instrument will provide researchers with lots of data—too much for scientists to easily sort and analyze. That’s a problem known as big data. And it’s increasingly common in the biological sciences.

“We’re seeing a proliferation of new instruments in the biological sciences,” says Srinivas Aluru, the Ross Martin Mehl and Marylyne Munas Mehl Professor of Computer Engineering at Iowa State. “And the rate of data collection is increasing. So we have to have a solution to analyze all this data.”

Aluru is leading a College of Engineering initiative to build research teams capable of solving big data problems in next-generation DNA sequencing, systems biology, and phenomics. The researchers are developing computing solutions that take advantage of emerging technologies such as cloud computing and high-performance computers. They’re also building partnerships with technology companies such as IBM, Micron, NVIDIA, Illumina Inc., Life Technologies Corp., Monsanto Co., and Roche.

The project is one of the three Dean’s Research Initiatives launched by Jonathan Wickert, former dean of the College of Engineering and currently Iowa State’s senior vice president and provost. The initiatives in high-throughput computational biology, wind energy, and a carbon-negative economy were launched in March 2011 with $500,000 each over three years. That money is to build interdisciplinary, public-private research teams ready to compete for multi-million dollar grants and projects.

Patrick Schnable, Iowa State’s Baker Professor of Agronomy and director of the centers for Plant Genomics and Carbon Capturing Crops, remembers when biologists had no interest in working with computer specialists. That was before they tried to work with billions of data points to, say, accurately predict harvests based on plant genotype, soil type and weather conditions.

“Now we’re getting huge, absolutely huge, data sets,” Schnable says. “There is no way to analyze these data sets without extraordinary computer resources. There’s no way we could do this without the collaboration of engineers.”

To date, the computational biology initiative has attracted $5.5 million for four major research projects. One of the latest grants is a three-year, $2 million award from the BIGDATA program of the National Science Foundation and the National Institutes of Health. The grant will allow Aluru and researchers from Iowa State, Stanford University, Virginia Tech, and the University of Michigan to work together to develop a computing toolbox that helps scientists manage all the data from today’s DNA sequencing instruments.

Aluru says the research initiative helped prepare Iowa State researchers to go after that grant.

“When the BIGDATA call came in, we had the credibility to compete,” he says. “We were already working on leading edge problems and had established relationships with companies.”

The initiative, the grants and the industry partnerships are helping Iowa State faculty and students move to the front of the developing field.

“One computing company wanted to set up a life science research group and it came here for advice,” Aluru says. “Iowa State is known as a big data leader in the biosciences.”

Source: Iowa State University

SOURCE:

http://www.rdmag.com/news/2013/01/engineers-work-help-biologists-cope-big-data?et_cid=3031227&et_rid=461755519&linkid=http%3a%2f%2fwww.rdmag.com%2fnews%2f2013%2f01%2fengineers-work-help-biologists-cope-big-data

 

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Reporter: Aviva Lev-Ari, PhD, RN

 

Stanford Launches Computational Genomics Center

December 03, 2012

NEW YORK (GenomeWeb News) – Stanford University has launched a new genomics research center that will foster collaboration across its seven schools and harness new computational technologies, it said today.

The Stanford Center for Computational, Evolutionary and Human Genomics, headed by the university’s School of Medicine and School of Humanities and Sciences, has been authorized for five years of funding, the university said.

Created with the goal of spurring and nurturing cross-cutting research collaborations, the new center will be open to all university faculty and labs. It will provide support for small project grants and computational genomics analysis services for member labs, faculty, students, and staff.

The center also will consult with academic institutions, industry, government, and research organizations on collaborations, will support graduate and postdoctoral students, and in its first year will launch public outreach programs in three areas – genomics and social systems, medical genomics, and agricultural, ecological, and environmental genomics. The center’s focus, regardless of the particulars of the project at hand, will be on using expertise and methods for sorting through, integrating, and analyzing large-scale data sets.

Stanford Professor Carlos Bustamante, who also is one of the center’s two founding directors, told GenomeWeb Daily News today that the university has not yet set the funding amount for the center but has committed to five years and will be “sufficient to catalyze all of the programs that we want to get started.” Ultimately, the center will seek funding from beyond the university, he noted.

“The incredible thing about a place like Stanford is that we’ve got the medical school co-located with the main campus, the traditional arts and sciences and humanities programs, and an exceptional engineering school, so we really are looking to create interdisciplinary programs that cut across traditional academic boundaries,” Bustamante said.

He explained that the new center will pursue and support projects that cut a broad swath across Stanford’s academic research areas, including paleo-anthropology, population genetics, agriculture, climate science, and biomedicine, as well as pursue bioethical questions that have arisen alongside human genomic science.

For example, Bustamante said, the research may involve integrating genetics and history studies.

“How can we use technologies from genomics to improve our understanding of the great human diaspora? That’s an area that [Founding Director and Stanford Biology Professor] Mark Feldman and I have been interested in for years.

“But now we can begin to do things that are cross-cutting in, say, funding archaeology students that want to study ancient DNA, or beginning to do projects that have to do with race, genetics, and ethnicity,” he said. “Now we can fund graduate students and post-docs to really work on interdisciplinary issues that are very hard to fund through traditional mechanisms.”

Bustamante pointed out that Stanford has “a tremendous amount of expertise in machine learning and statistical learning,” and the center will try to bring people and projects together with clinicians who are pursuing cutting-edge projects in a wide array of fields, such as cancer genomics.

“Traditionally, these people would know about each other but they haven’t necessarily had the mechanisms to initiative [joint] pilot projects and collaborations,” Bustamante said, and that is where the new center might fit in.

One of the key aims of the center also is to forge collaborations between biomedical researchers with those in the humanities and social sciences.

For example, one of the center’s executive committee members, Stanford Biology Professor Noah Rosenberg, is co-directing a program focused on Jewish genetics and Jewish history. Another executive member, Professor Dmitri Petrov, will head a year-long project focused on ecological genetics.

Bustamante, who previously was a researcher at Cornell University, said he expects that the center will branch out into agricultural genomics as well.

“Genomics is transforming agriculture. It is probably where genomics is having some of its biggest impacts,” he said.

Aside from the wide range of research areas that the new center may support, it will have one core mission, Bustamante told GWDN.

“It really is, first and foremost, a center focused on computational analysis, both in terms of developing methods and computing on big data. That is a particular expertise of those of us involved in launching the center.”

 

 

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Reporter: Aviva Lev-Ari, PhD, RN

Stanford’s Mike Snyder is Showing the Way With Personalized Medicine

 

11/19/12
Follow @ldtimmerman

Say the words “personalized medicine” to people from various walks of life, and you’re likely to get one of about four different reactions.

A. “Personalized medicine? What’s that?” (Usually spoken by 99 percent of patients.)

B. “Personalized medicine will bankrupt the country with expensive new diagnostic tests, and overrated targeted drugs.” (Usually spoken by health economists.)

C. “Personalized medicine is overhyped, a load of bunk.” (Usually spoken by grizzled pharma industry vets who remember the genomics crash of a decade ago, and have a financial interest in preserving the status quo.)

D. “Personalized medicine will revolutionize healthcare, moving us away from reactive sick-care and more toward predictive and preventive strategies focused on wellness.” (Usually spoken by the subset of true believers in science and the biotech industry.)

You can make arguments, buttressed with data, to support any of the last three positions. But none of these positions quite captures the truth. We are in the early days of the personalized medicine movement, and don’t know how the story will unfold. As a journalist who’s followed many different threads of this story for thelast decade, I keep getting the feeling that we’re moving further away from one-size-fits-all medicine, and more toward treatment based on extremely detailed molecular readouts on your state of health or disease. People may havesnickered at Internet pioneer Larry Smarr and his friends in the “Quantified Self” movement for being weird a couple years ago, but I can easily envision people jumping on this bandwagon sometime not too far out.

I was fascinated this past week when I had a chance to talk with Mike Snyder, a geneticist who has turned himself into a poster child for personalized medicine through his work at Stanford University. After talking with him for about a half hour last week, I hung up thinking his experience today could seem mainstream in another 10 or 20 years.

Stanford geneticist Mike Snyder

Snyder, for those who are unfamiliar, was the guy at the center of an important paper published in the journal Cell back in March. This paper described how researchers sequenced Snyder’s genome, and then really got rolling in their quest to understand his biochemical state of being at 20 different snapshots in time over a 14-month period. The scientists took blood samples from him when he was feeling fine, and a few times when he was sick with viral infections. They then ran the samples through instruments that captured an extremely detailed look at 40,000 molecular parameters in his blood. These were metabolites, proteins, RNA transcripts, self-directed antibodies. This hard-core genomic, transcriptomic, metabolomic and proteomic approach (which the scientists called an integrative personal ‘omics profile) could have been just a demonstration of technological overkill, offering very little information that could lead anyone to make better decisions about their health.

But that’s not what happened. It turned out that the results, surprisingly, showed this healthy white guy in his mid-50s was at high risk of getting Type 2 diabetes—which if it’s not controlled, it can lead down the path to blindness, amputations, stroke, or heart attack.

At the time the molecular analysis revealed this trend, it was hard to believe. Snyder had no family history of the disease, and most everybody in his family is thin. His genome said he was at low risk of obesity, and at a shade under 5-foot-10, and 160 pounds, Snyder’s general practitioner thought the idea of him becoming diabetic was far-fetched.

But just as the pan-‘omics tests had predicted, researchers saw over time that something was amiss with Snyder’s ability to control his blood sugar—especially, and oddly, when he had viral infections. When looking at two traditional blood measurements of diabetes—blood sugar concentration levels and hemoglobin A1C counts—both of those numbers progressively climbed into worrisome territory. As the sweeping ‘omics-driven analysis had predicted, Snyder was diagnosed with diabetes.

He remembers the day that word came, April 11, 2011. He decided it was time to change his health habits.

“Up until that point, I had been eating lots of sweets. I’d have ice cream all the time after dinner. It really was a pretty bad diet,” Snyder says. After the diagnosis, it took him six months to get his blood sugar levels back to normal. “I completely cut out all dessert, and have had one bite of wedding cake since,” he says. That one exception came when one of his postdocs got married, he says.

That might be how anybody in this situation would react to a diabetes diagnosis, with enough self-discipline. But what makes this story even more interesting is that when Snyder changed his diet, and ramped up his daily exercise routines, he could see how his biochemical profile changed when his behavior changed. The scientists have kept looking at measurements of 40,000 different molecules in Snyder’s blood, before, during, and after his diagnosis. Suddenly, you can see not only that bicycling 40-50 miles a week instead of 20-30 miles has helped him lose 15 pounds. You can also see the molecular warning signs of diabetes have returned roughly to normal, along with his blood sugar and hemoglobin A1c scores.

“This study is a landmark for personalized medicine,” Eric Topol, a professor of genomics at the Scripps Research Institute in San Diego, told the New York Times.

Months later, Snyder reports that even though he’s not technically cured of diabetes, he’s been able to keep it in remission through these behavior changes, without taking any drugs. That doesn’t mean he’s completely in the clear. He knows his risk will go up again as he gets older. He also knows from his genome that if he gets diabetes, and needs to take the generic drug metformin, he should take a lower-than-usual dose. But most importantly, because he’s a scientist willing to make himself a laboratory subject, he’s more likely to catch diabetes or some other ailment at an early and treatable stage.

After giving 50 samples to his research team over the past 34 months, Snyder says he expects much more interesting data to come. This wasn’t just a case of a single paper which generates some buzz, maybe a few new research ideas, and then fades into the ether. It’s really just the first step in a long-range study of Snyder at the molecular level, and what that means for his health. “I’m sure I’ll be doing this the rest of my life,” Snyder says.

No question, this is all still very much at a research stage. This kind of hard-core data-gathering approach is many years away from being reduced to practical use, or lending itself to new products for diagnosis or treatment. The Stanford team used a next-generation gene sequencing machine, and two different mass spectrometers, which are expensive pieces of equipment. The first study of Snyder’s ‘omics profile generated 50 terabytes of data, and he says the next phase of research will probably double the amount of data. It cost tens of thousands of dollars, and he doesn’t really have a full accounting that includes computer analysis and staff time. And the costs keep recurring. While the team only had to sequence his genome once—because his unique DNA signature doesn’t change over time—the battery of other ‘omic tests will probably cost at least $2,000 each time he gives blood, just for the chemical reagents required, not counting costs for analysis and staff time.

Still, every day as the costs come down, more research ideas become feasible. Snyder’s story, which got a fair bit of media attention in the spring, has inspired a number of volunteers who want to help. The Stanford team is broadening the scope of their personalized medicine vision by looking to analyze the microbes in Snyder’s gut—the microbiome—and his epigenome, which will show how his genes get expressed. Those extra analyses will add cost, but Snyder says he believes it will be soon be possible to capture a simple version of the molecular analysis for maybe $600 each time he gives blood. Once the costs get down into that range, it will be feasible to do one continuous study of 10 volunteers like Snyder, who are willing to subject themselves to all these regular blood draws, when they’re feeling well and when they’re not.

Beyond that study, Snyder says he and his team are exploring a 250-person study of people at high risk for diabetes, or who are pre-diabetic. The idea will be to take these regular personal ‘omic snapshots, connect it with a detailed picture of the person’s environmental stimuli (particularly their diet/exercise habits), and watch over a 5-year period to see whether certain biochemical pathways are truly predictive of whether a person will get diabetes. That kind of study would be clearly more informative to the practice of medicine than just one man’s experience, which could be a fluke.

Certainly, there are going to be experiments that fail, or just give us vague ideas of where an individual’s health is headed. People, being human, won’t always follow their doctor’s advice, even if they know they can stop themselves from getting diabetes. Insurance companies may use this data to their own advantage, and to the disadvantage of the individual. (In fact, Snyder says his life insurance premiums went up once he told his insurer about his diabetes diagnosis. That action is perfectly legal, he notes, because life insurance firms aren’t subject to theGenetic Information Non-Discrimination Act of 2008.)

The whole march of science, the business implications, and the ethics of this movement will surely lurch along in fits and starts over the coming decades. It will be messy. It won’t happen overnight.

But I do believe we’re going to learn amazing things that will change our behavior. And I think that within the next decade, a whole lot more people in the U.S. will have the same kind of visibility Snyder got into his individual health, because it really ought to save the whole system money if it scares people into leading healthier lives. The 99 percent of patients will no longer say “Personalized Medicine? What’s that?” People will want this information, they’ll demand it, and many will act on it. Some of today’s skeptics will turn into believers, and they’ll find ways to profit from this movement, by helping people prevent bad things from happening. As Snyder puts it, “This is what personalized medicine is all about. You can look at your altered biochemical state, and you can change things when you catch them early. It’s the name of the game.”

Luke Timmerman is the National Biotech Editor of Xconomy. E-mail him at

ltimmerman@xconomy.com Follow @ldtimmerman

SOURCE:

http://www.xconomy.com/national/2012/11/19/stanfords-mike-snyder-starts-living-the-personalized-medicine-story/2/

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