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Posts Tagged ‘Single-nucleotide polymorphism’

Proteomics, Metabolomics, Signaling Pathways, and Cell Regulation: a Compilation of Articles in the Journal http://pharmaceuticalintelligence.com


Compilation of References by Leaders in Pharmaceutical Business Intelligence in the Journal http://pharmaceuticalintelligence.com about
Proteomics, Metabolomics, Signaling Pathways, and Cell Regulation

Curator: Larry H Bernstein, MD, FCAP

Proteomics

  1. The Human Proteome Map Completed

Reporter and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/08/28/the-human-proteome-map-completed/

  1. Proteomics – The Pathway to Understanding and Decision-making in Medicine

Author and Curator, Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/06/24/proteomics-the-pathway-to-
understanding-and-decision-making-in-medicine/

3. Advances in Separations Technology for the “OMICs” and Clarification of Therapeutic Targets

Author and Curator, Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/10/22/advances-in-separations-technology-for-the-omics-and-clarification-         of-therapeutic-targets/

  1. Expanding the Genetic Alphabet and Linking the Genome to the Metabolome

Author and Curator, Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/09/24/expanding-the-genetic-alphabet-and-linking-the-genome-to-the-                metabolome/

5. Genomics, Proteomics and standards

Larry H Bernstein, MD, FCAP, Author and Curator

https://pharmaceuticalintelligence.com/2014/07/06/genomics-proteomics-and-standards/

6. Proteins and cellular adaptation to stress

Larry H Bernstein, MD, FCAP, Author and Curator

https://pharmaceuticalintelligence.com/2014/07/08/proteins-and-cellular-adaptation-to-stress/

 

Metabolomics

  1. Extracellular evaluation of intracellular flux in yeast cells

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

https://pharmaceuticalintelligence.com/2014/08/25/extracellular-evaluation-of-intracellular-flux-in-yeast-cells/

  1. Metabolomic analysis of two leukemia cell lines. I.

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

https://pharmaceuticalintelligence.com/2014/08/23/metabolomic-analysis-of-two-leukemia-cell-lines-_i/

  1. Metabolomic analysis of two leukemia cell lines. II.

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

https://pharmaceuticalintelligence.com/2014/08/24/metabolomic-analysis-of-two-leukemia-cell-lines-ii/

  1. Metabolomics, Metabonomics and Functional Nutrition: the next step in nutritional metabolism and biotherapeutics

Reviewer and Curator, Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/08/22/metabolomics-metabonomics-and-functional-nutrition-the-next-step-          in-nutritional-metabolism-and-biotherapeutics/

  1. Buffering of genetic modules involved in tricarboxylic acid cycle metabolism provides homeomeostatic regulation

Larry H. Bernstein, MD, FCAP, Reviewer and curator

https://pharmaceuticalintelligence.com/2014/08/27/buffering-of-genetic-modules-involved-in-tricarboxylic-acid-cycle-              metabolism-provides-homeomeostatic-regulation/

Metabolic Pathways

  1. Pentose Shunt, Electron Transfer, Galactose, more Lipids in brief

Reviewer and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/08/21/pentose-shunt-electron-transfer-galactose-more-lipids-in-brief/

  1. Mitochondria: More than just the “powerhouse of the cell”

Ritu Saxena, PhD

https://pharmaceuticalintelligence.com/2012/07/09/mitochondria-more-than-just-the-powerhouse-of-the-cell/

  1. Mitochondrial fission and fusion: potential therapeutic targets?

Ritu saxena

https://pharmaceuticalintelligence.com/2012/10/31/mitochondrial-fission-and-fusion-potential-therapeutic-target/

4.  Mitochondrial mutation analysis might be “1-step” away

Ritu Saxena

https://pharmaceuticalintelligence.com/2012/08/14/mitochondrial-mutation-analysis-might-be-1-step-away/

  1. Selected References to Signaling and Metabolic Pathways in PharmaceuticalIntelligence.com

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/08/14/selected-references-to-signaling-and-metabolic-pathways-in-                     leaders-in-pharmaceutical-intelligence/

  1. Metabolic drivers in aggressive brain tumors

Prabodh Kandal, PhD

https://pharmaceuticalintelligence.com/2012/11/11/metabolic-drivers-in-aggressive-brain-tumors/

  1. Metabolite Identification Combining Genetic and Metabolic Information: Genetic association links unknown metabolites to functionally related genes

Writer and Curator, Aviva Lev-Ari, PhD, RD

https://pharmaceuticalintelligence.com/2012/10/22/metabolite-identification-combining-genetic-and-metabolic-                        information-genetic-association-links-unknown-metabolites-to-functionally-related-genes/

  1. Mitochondria: Origin from oxygen free environment, role in aerobic glycolysis, metabolic adaptation

Larry H Bernstein, MD, FCAP, author and curator

https://pharmaceuticalintelligence.com/2012/09/26/mitochondria-origin-from-oxygen-free-environment-role-in-aerobic-            glycolysis-metabolic-adaptation/

  1. Therapeutic Targets for Diabetes and Related Metabolic Disorders

Reporter, Aviva Lev-Ari, PhD, RD

https://pharmaceuticalintelligence.com/2012/08/20/therapeutic-targets-for-diabetes-and-related-metabolic-disorders/

10.  Buffering of genetic modules involved in tricarboxylic acid cycle metabolism provides homeomeostatic regulation

Larry H. Bernstein, MD, FCAP, Reviewer and curator

https://pharmaceuticalintelligence.com/2014/08/27/buffering-of-genetic-modules-involved-in-tricarboxylic-acid-cycle-              metabolism-provides-homeomeostatic-regulation/

11. The multi-step transfer of phosphate bond and hydrogen exchange energy

Larry H. Bernstein, MD, FCAP, Curator:

https://pharmaceuticalintelligence.com/2014/08/19/the-multi-step-transfer-of-phosphate-bond-and-hydrogen-                          exchange-energy/

12. Studies of Respiration Lead to Acetyl CoA

https://pharmaceuticalintelligence.com/2014/08/18/studies-of-respiration-lead-to-acetyl-coa/

13. Lipid Metabolism

Author and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/08/15/lipid-metabolism/

14. Carbohydrate Metabolism

Author and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/08/13/carbohydrate-metabolism/

15. Update on mitochondrial function, respiration, and associated disorders

Larry H. Bernstein, MD, FCAP, Author and Curator

https://pharmaceuticalintelligence.com/2014/07/08/update-on-mitochondrial-function-respiration-and-associated-                   disorders/

16. Prologue to Cancer – e-book Volume One – Where are we in this journey?

Author and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/04/13/prologue-to-cancer-ebook-4-where-are-we-in-this-journey/

17. Introduction – The Evolution of Cancer Therapy and Cancer Research: How We Got Here?

Author and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/04/04/introduction-the-evolution-of-cancer-therapy-and-cancer-research-          how-we-got-here/

18. Inhibition of the Cardiomyocyte-Specific Kinase TNNI3K

Author and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/11/01/inhibition-of-the-cardiomyocyte-specific-kinase-tnni3k/

19. The Binding of Oligonucleotides in DNA and 3-D Lattice Structures

Author and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/05/15/the-binding-of-oligonucleotides-in-dna-and-3-d-lattice-structures/

20. Mitochondrial Metabolism and Cardiac Function

Author and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/04/14/mitochondrial-metabolism-and-cardiac-function/

21. How Methionine Imbalance with Sulfur-Insufficiency Leads to Hyperhomocysteinemia

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/04/04/sulfur-deficiency-leads_to_hyperhomocysteinemia/

22. AMPK Is a Negative Regulator of the Warburg Effect and Suppresses Tumor Growth In Vivo

Author and Curator: Stephen J. Williams, PhD

https://pharmaceuticalintelligence.com/2013/03/12/ampk-is-a-negative-regulator-of-the-warburg-effect-and-suppresses-         tumor-growth-in-vivo/

23. A Second Look at the Transthyretin Nutrition Inflammatory Conundrum

Author and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/12/03/a-second-look-at-the-transthyretin-nutrition-inflammatory-                         conundrum/

24. Mitochondrial Damage and Repair under Oxidative Stress

Author and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/10/28/mitochondrial-damage-and-repair-under-oxidative-stress/

25. Nitric Oxide and Immune Responses: Part 2

Author and Curator: Aviral Vatsa, PhD, MBBS

https://pharmaceuticalintelligence.com/2012/10/28/nitric-oxide-and-immune-responses-part-2/

26. Overview of Posttranslational Modification (PTM)

Writer and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/07/29/overview-of-posttranslational-modification-ptm/

27. Malnutrition in India, high newborn death rate and stunting of children age under five years

Writer and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/07/15/malnutrition-in-india-high-newborn-death-rate-and-stunting-of-                   children-age-under-five-years/

28. Update on mitochondrial function, respiration, and associated disorders

Writer and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/07/08/update-on-mitochondrial-function-respiration-and-associated-                  disorders/

29. Omega-3 fatty acids, depleting the source, and protein insufficiency in renal disease

Larry H. Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/2014/07/06/omega-3-fatty-acids-depleting-the-source-and-protein-insufficiency-         in-renal-disease/

30. Introduction to e-Series A: Cardiovascular Diseases, Volume Four Part 2: Regenerative Medicine

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

https://pharmaceuticalintelligence.com/2014/04/27/larryhbernintroduction_to_cardiovascular_diseases-                                  translational_medicine-part_2/

31. Epilogue: Envisioning New Insights in Cancer Translational Biology
Series C: e-Books on Cancer & Oncology

Author & Curator: Larry H. Bernstein, MD, FCAP, Series C Content Consultant

https://pharmaceuticalintelligence.com/2014/03/29/epilogue-envisioning-new-insights/

32. Ca2+-Stimulated Exocytosis:  The Role of Calmodulin and Protein Kinase C in Ca2+ Regulation of Hormone                         and Neurotransmitter

Writer and Curator: Larry H Bernstein, MD, FCAP and
Curator and Content Editor: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/12/23/calmodulin-and-protein-kinase-c-drive-the-ca2-regulation-of-                    hormone-and-neurotransmitter-release-that-triggers-ca2-stimulated-exocy

33. Cardiac Contractility & Myocardial Performance: Therapeutic Implications of Ryanopathy (Calcium Release-                           related Contractile Dysfunction) and Catecholamine Responses

Author, and Content Consultant to e-SERIES A: Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC
Author and Curator: Larry H Bernstein, MD, FCAP
and Article Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/08/28/cardiac-contractility-myocardium-performance-ventricular-arrhythmias-      and-non-ischemic-heart-failure-therapeutic-implications-for-cardiomyocyte-ryanopathy-calcium-release-related-                    contractile/

34. Role of Calcium, the Actin Skeleton, and Lipid Structures in Signaling and Cell Motility

Author and Curator: Larry H Bernstein, MD, FCAP Author: Stephen Williams, PhD, and Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/08/26/role-of-calcium-the-actin-skeleton-and-lipid-structures-in-signaling-and-cell-motility/

35. Identification of Biomarkers that are Related to the Actin Cytoskeleton

Larry H Bernstein, MD, FCAP, Author and Curator

https://pharmaceuticalintelligence.com/2012/12/10/identification-of-biomarkers-that-are-related-to-the-actin-                           cytoskeleton/

36. Advanced Topics in Sepsis and the Cardiovascular System at its End Stage

Author: Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/08/18/advanced-topics-in-Sepsis-and-the-Cardiovascular-System-at-its-              End-Stage/

37. The Delicate Connection: IDO (Indolamine 2, 3 dehydrogenase) and Cancer Immunology

Demet Sag, PhD, Author and Curator

https://pharmaceuticalintelligence.com/2013/08/04/the-delicate-connection-ido-indolamine-2-3-dehydrogenase-and-               immunology/

38. IDO for Commitment of a Life Time: The Origins and Mechanisms of IDO, indolamine 2, 3-dioxygenase

Demet Sag, PhD, Author and Curator

https://pharmaceuticalintelligence.com/2013/08/04/ido-for-commitment-of-a-life-time-the-origins-and-mechanisms-of-             ido-indolamine-2-3-dioxygenase/

39. Confined Indolamine 2, 3 dioxygenase (IDO) Controls the Homeostasis of Immune Responses for Good and Bad

Curator: Demet Sag, PhD, CRA, GCP

https://pharmaceuticalintelligence.com/2013/07/31/confined-indolamine-2-3-dehydrogenase-controls-the-hemostasis-           of-immune-responses-for-good-and-bad/

40. Signaling Pathway that Makes Young Neurons Connect was discovered @ Scripps Research Institute

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/06/26/signaling-pathway-that-makes-young-neurons-connect-was-                     discovered-scripps-research-institute/

41. Naked Mole Rats Cancer-Free

Writer and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/06/20/naked-mole-rats-cancer-free/

42. Late Onset of Alzheimer’s Disease and One-carbon Metabolism

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

https://pharmaceuticalintelligence.com/2013/05/06/alzheimers-disease-and-one-carbon-metabolism/

43. Problems of vegetarianism

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

https://pharmaceuticalintelligence.com/2013/04/22/problems-of-vegetarianism/

44.  Amyloidosis with Cardiomyopathy

Writer and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/03/31/amyloidosis-with-cardiomyopathy/

45. Liver endoplasmic reticulum stress and hepatosteatosis

Larry H Bernstein, MD, FACP

https://pharmaceuticalintelligence.com/2013/03/10/liver-endoplasmic-reticulum-stress-and-hepatosteatosis/

46. The Molecular Biology of Renal Disorders: Nitric Oxide – Part III

Curator and Author: Larry H Bernstein, MD, FACP

https://pharmaceuticalintelligence.com/2012/11/26/the-molecular-biology-of-renal-disorders/

47. Nitric Oxide Function in Coagulation – Part II

Curator and Author: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/11/26/nitric-oxide-function-in-coagulation/

48. Nitric Oxide, Platelets, Endothelium and Hemostasis

Curator and Author: Larry H Bernstein, MD, FACP

https://pharmaceuticalintelligence.com/2012/11/08/nitric-oxide-platelets-endothelium-and-hemostasis/

49. Interaction of Nitric Oxide and Prostacyclin in Vascular Endothelium

Curator and Author: Larry H Bernstein, MD, FACP

https://pharmaceuticalintelligence.com/2012/09/14/interaction-of-nitric-oxide-and-prostacyclin-in-vascular-endothelium/

50. Nitric Oxide and Immune Responses: Part 1

Curator and Author:  Aviral Vatsa PhD, MBBS

https://pharmaceuticalintelligence.com/2012/10/18/nitric-oxide-and-immune-responses-part-1/

51. Nitric Oxide and Immune Responses: Part 2

Curator and Author:  Aviral Vatsa PhD, MBBS

https://pharmaceuticalintelligence.com/2012/10/28/nitric-oxide-and-immune-responses-part-2/

52. Mitochondrial Damage and Repair under Oxidative Stress

Curator and Author: Larry H Bernstein, MD, FACP

https://pharmaceuticalintelligence.com/2012/10/28/mitochondrial-damage-and-repair-under-oxidative-stress/

53. Is the Warburg Effect the cause or the effect of cancer: A 21st Century View?

Curator and Author: Larry H Bernstein, MD, FACP

https://pharmaceuticalintelligence.com/2012/10/17/is-the-warburg-effect-the-cause-or-the-effect-of-cancer-a-21st-                 century-view/

54. Ubiquinin-Proteosome pathway, autophagy, the mitochondrion, proteolysis and cell apoptosis

Curator and Author: Larry H Bernstein, MD, FACP

https://pharmaceuticalintelligence.com/2012/10/30/ubiquinin-proteosome-pathway-autophagy-the-mitochondrion-                  proteolysis-and-cell-apoptosis/

55. Ubiquitin-Proteosome pathway, Autophagy, the Mitochondrion, Proteolysis and Cell Apoptosis: Part III

Curator and Author: Larry H Bernstein, MD, FACP

https://pharmaceuticalintelligence.com/2013/02/14/ubiquinin-proteosome-pathway-autophagy-the-mitochondrion-                   proteolysis-and-cell-apoptosis-reconsidered/

56. Nitric Oxide and iNOS have Key Roles in Kidney Diseases – Part II

Curator and Author: Larry H Bernstein, MD, FACP

https://pharmaceuticalintelligence.com/2012/11/26/nitric-oxide-and-inos-have-key-roles-in-kidney-diseases/

57. New Insights on Nitric Oxide donors – Part IV

Curator and Author: Larry H Bernstein, MD, FACP

https://pharmaceuticalintelligence.com/2012/11/26/new-insights-on-no-donors/

58. Crucial role of Nitric Oxide in Cancer

Curator and Author: Ritu Saxena, Ph.D.

https://pharmaceuticalintelligence.com/2012/10/16/crucial-role-of-nitric-oxide-in-cancer/

59. Nitric Oxide has a ubiquitous role in the regulation of glycolysis -with a concomitant influence on mitochondrial function

Curator and Author: Larry H Bernstein, MD, FACP

https://pharmaceuticalintelligence.com/2012/09/16/nitric-oxide-has-a-ubiquitous-role-in-the-regulation-of-glycolysis-with-         a-concomitant-influence-on-mitochondrial-function/

60. Targeting Mitochondrial-bound Hexokinase for Cancer Therapy

Curator and Author: Ziv Raviv, PhD, RN 04/06/2013

https://pharmaceuticalintelligence.com/2013/04/06/targeting-mitochondrial-bound-hexokinase-for-cancer-therapy/

61. Biochemistry of the Coagulation Cascade and Platelet Aggregation – Part I

Curator and Author: Larry H Bernstein, MD, FACP

https://pharmaceuticalintelligence.com/2012/11/26/biochemistry-of-the-coagulation-cascade-and-platelet-aggregation/

Genomics, Transcriptomics, and Epigenetics

  1. What is the meaning of so many RNAs?

Writer and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/08/06/what-is-the-meaning-of-so-many-rnas/

  1. RNA and the transcription the genetic code

Larry H. Bernstein, MD, FCAP, Writer and Curator

https://pharmaceuticalintelligence.com/2014/08/02/rna-and-the-transcription-of-the-genetic-code/

  1. A Primer on DNA and DNA Replication

Writer and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/07/29/a_primer_on_dna_and_dna_replication/

4. Synthesizing Synthetic Biology: PLOS Collections

Reporter: Aviva Lev-Ari

https://pharmaceuticalintelligence.com/2012/08/17/synthesizing-synthetic-biology-plos-collections/

5. Pathology Emergence in the 21st Century

Author and Curator: Larry Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/08/03/pathology-emergence-in-the-21st-century/

6. RNA and the transcription the genetic code

Writer and Curator, Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/08/02/rna-and-the-transcription-of-the-genetic-code/

7. A Great University engaged in Drug Discovery: University of Pittsburgh

Larry H. Bernstein, MD, FCAP, Reporter and Curator

https://pharmaceuticalintelligence.com/2014/07/15/a-great-university-engaged-in-drug-discovery/

8. microRNA called miRNA-142 involved in the process by which the immature cells in the bone  marrow give                              rise to all the types of blood cells, including immune cells and the oxygen-bearing red blood cells

Aviva Lev-Ari, PhD, RN, Author and Curator

https://pharmaceuticalintelligence.com/2014/07/24/microrna-called-mir-142-involved-in-the-process-by-which-the-                   immature-cells-in-the-bone-marrow-give-rise-to-all-the-types-of-blood-cells-including-immune-cells-and-the-oxygen-             bearing-red-blood-cells/

9. Genes, proteomes, and their interaction

Larry H. Bernstein, MD, FCAP, Writer and Curator

https://pharmaceuticalintelligence.com/2014/07/28/genes-proteomes-and-their-interaction/

10. Regulation of somatic stem cell Function

Larry H. Bernstein, MD, FCAP, Writer and Curator    Aviva Lev-Ari, PhD, RN, Curator

https://pharmaceuticalintelligence.com/2014/07/29/regulation-of-somatic-stem-cell-function/

11. Scientists discover that pluripotency factor NANOG is also active in adult organisms

Larry H. Bernstein, MD, FCAP, Reporter

https://pharmaceuticalintelligence.com/2014/07/10/scientists-discover-that-pluripotency-factor-nanog-is-also-active-in-           adult-organisms/

12. Bzzz! Are fruitflies like us?

Larry H Bernstein, MD, FCAP, Author and Curator

https://pharmaceuticalintelligence.com/2014/07/07/bzzz-are-fruitflies-like-us/

13. Long Non-coding RNAs Can Encode Proteins After All

Larry H Bernstein, MD, FCAP, Reporter

https://pharmaceuticalintelligence.com/2014/06/29/long-non-coding-rnas-can-encode-proteins-after-all/

14. Michael Snyder @Stanford University sequenced the lymphoblastoid transcriptomes and developed an
allele-specific full-length transcriptome

Aviva Lev-Ari, PhD, RN, Author and Curator

https://pharmaceuticalintelligence.com/014/06/23/michael-snyder-stanford-university-sequenced-the-lymphoblastoid-            transcriptomes-and-developed-an-allele-specific-full-length-transcriptome/

15. Commentary on Biomarkers for Genetics and Genomics of Cardiovascular Disease: Views by Larry H                                     Bernstein, MD, FCAP

Author: Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/07/16/commentary-on-biomarkers-for-genetics-and-genomics-of-                        cardiovascular-disease-views-by-larry-h-bernstein-md-fcap/

16. Observations on Finding the Genetic Links in Common Disease: Whole Genomic Sequencing Studies

Author an curator: Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/05/18/observations-on-finding-the-genetic-links/

17. Silencing Cancers with Synthetic siRNAs

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

https://pharmaceuticalintelligence.com/2013/12/09/silencing-cancers-with-synthetic-sirnas/

18. Cardiometabolic Syndrome and the Genetics of Hypertension: The Neuroendocrine Transcriptome Control Points

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/12/12/cardiometabolic-syndrome-and-the-genetics-of-hypertension-the-neuroendocrine-transcriptome-control-points/

19. Developments in the Genomics and Proteomics of Type 2 Diabetes Mellitus and Treatment Targets

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

https://pharmaceuticalintelligence.com/2013/12/08/developments-in-the-genomics-and-proteomics-of-type-2-diabetes-           mellitus-and-treatment-targets/

20. Loss of normal growth regulation

Larry H Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/2014/07/06/loss-of-normal-growth-regulation/

21. CT Angiography & TrueVision™ Metabolomics (Genomic Phenotyping) for new Therapeutic Targets to Atherosclerosis

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/11/15/ct-angiography-truevision-metabolomics-genomic-phenotyping-for-           new-therapeutic-targets-to-atherosclerosis/

22.  CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics

Genomics Curator, Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/08/30/cracking-the-code-of-human-life-the-birth-of-bioinformatics-                      computational-genomics/

23. Big Data in Genomic Medicine

Author and Curator, Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/12/17/big-data-in-genomic-medicine/

24. From Genomics of Microorganisms to Translational Medicine

Author and Curator: Demet Sag, PhD

https://pharmaceuticalintelligence.com/2014/03/20/without-the-past-no-future-but-learn-and-move-genomics-of-                      microorganisms-to-translational-medicine/

25. Summary of Genomics and Medicine: Role in Cardiovascular Diseases

Author and Curator, Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/01/06/summary-of-genomics-and-medicine-role-in-cardiovascular-diseases/

 26. Genomic Promise for Neurodegenerative Diseases, Dementias, Autism Spectrum, Schizophrenia, and Serious                      Depression

Author and Curator, Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/02/19/genomic-promise-for-neurodegenerative-diseases-dementias-autism-        spectrum-schizophrenia-and-serious-depression/

 27.  BRCA1 a tumour suppressor in breast and ovarian cancer – functions in transcription, ubiquitination and DNA repair

Sudipta Saha, PhD

https://pharmaceuticalintelligence.com/2012/12/04/brca1-a-tumour-suppressor-in-breast-and-ovarian-cancer-functions-         in-transcription-ubiquitination-and-dna-repair/

28. Personalized medicine gearing up to tackle cancer

Ritu Saxena, PhD

https://pharmaceuticalintelligence.com/2013/01/07/personalized-medicine-gearing-up-to-tackle-cancer/

29. Differentiation Therapy – Epigenetics Tackles Solid Tumors

Stephen J Williams, PhD

      https://pharmaceuticalintelligence.com/2013/01/03/differentiation-therapy-epigenetics-tackles-solid-tumors/

30. Mechanism involved in Breast Cancer Cell Growth: Function in Early Detection & Treatment

     Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/01/17/mechanism-involved-in-breast-cancer-cell-growth-function-in-early-          detection-treatment/

31. The Molecular pathology of Breast Cancer Progression

Tilde Barliya, PhD

https://pharmaceuticalintelligence.com/2013/01/10/the-molecular-pathology-of-breast-cancer-progression

32. Gastric Cancer: Whole-genome reconstruction and mutational signatures

Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2012/12/24/gastric-cancer-whole-genome-reconstruction-and-mutational-                   signatures-2/

33. Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine –                                                       Part 1 (pharmaceuticalintelligence.com)

Aviva  Lev-Ari, PhD, RN

http://pharmaceuticalntelligence.com/2013/01/13/paradigm-shift-in-human-genomics-predictive-biomarkers-and-personalized-medicine-part-1/

34. LEADERS in Genome Sequencing of Genetic Mutations for Therapeutic Drug Selection in Cancer                                         Personalized Treatment: Part 2

A Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/01/13/leaders-in-genome-sequencing-of-genetic-mutations-for-therapeutic-       drug-selection-in-cancer-personalized-treatment-part-2/

35. Personalized Medicine: An Institute Profile – Coriell Institute for Medical Research: Part 3

Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/01/13/personalized-medicine-an-institute-profile-coriell-institute-for-medical-        research-part-3/

36. Harnessing Personalized Medicine for Cancer Management, Prospects of Prevention and Cure: Opinions of                           Cancer Scientific Leaders @http://pharmaceuticalintelligence.com

Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/01/13/7000/Harnessing_Personalized_Medicine_for_ Cancer_Management-      Prospects_of_Prevention_and_Cure/

37.  GSK for Personalized Medicine using Cancer Drugs needs Alacris systems biology model to determine the in silico
effect of the inhibitor in its “virtual clinical trial”

Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2012/11/14/gsk-for-personalized-medicine-using-cancer-drugs-needs-alacris-             systems-biology-model-to-determine-the-in-silico-effect-of-the-inhibitor-in-its-virtual-clinical-trial/

38. Personalized medicine-based cure for cancer might not be far away

Ritu Saxena, PhD

  https://pharmaceuticalintelligence.com/2012/11/20/personalized-medicine-based-cure-for-cancer-might-not-be-far-away/

39. Human Variome Project: encyclopedic catalog of sequence variants indexed to the human genome sequence

Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2012/11/24/human-variome-project-encyclopedic-catalog-of-sequence-variants-         indexed-to-the-human-genome-sequence/

40. Inspiration From Dr. Maureen Cronin’s Achievements in Applying Genomic Sequencing to Cancer Diagnostics

Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/01/10/inspiration-from-dr-maureen-cronins-achievements-in-applying-                genomic-sequencing-to-cancer-diagnostics/

41. The “Cancer establishments” examined by James Watson, co-discoverer of DNA w/Crick, 4/1953

Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/01/09/the-cancer-establishments-examined-by-james-watson-co-discover-         of-dna-wcrick-41953/

42. What can we expect of tumor therapeutic response?

Author and curator: Larry H Bernstein, MD, FACP

https://pharmaceuticalintelligence.com/2012/12/05/what-can-we-expect-of-tumor-therapeutic-response/

43. Directions for genomics in personalized medicine

Author and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/01/27/directions-for-genomics-in-personalized-medicine/

44. How mobile elements in “Junk” DNA promote cancer. Part 1: Transposon-mediated tumorigenesis.

Stephen J Williams, PhD

https://pharmaceuticalintelligence.com/2012/10/31/how-mobile-elements-in-junk-dna-prote-cancer-part1-transposon-            mediated-tumorigenesis/

45. mRNA interference with cancer expression

Author and Curator, Larry H. Bernstein, MD, FCAP

 https://pharmaceuticalintelligence.com/2012/10/26/mrna-interference-with-cancer-expression/

46. Expanding the Genetic Alphabet and linking the genome to the metabolome

Aviva Lev-Ari, PhD, RD

https://pharmaceuticalintelligence.com/2012/09/24/expanding-the-genetic-alphabet-and-linking-the-genome-to-the-               metabolome/

47. Breast Cancer, drug resistance, and biopharmaceutical targets

Author and Curator: Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/09/18/breast-cancer-drug-resistance-and-biopharmaceutical-targets/

48.  Breast Cancer: Genomic profiling to predict Survival: Combination of Histopathology and Gene Expression                            Analysis

Aviva Lev-Ari, PhD, RD

https://pharmaceuticalintelligence.com/2012/12/24/breast-cancer-genomic-profiling-to-predict-survival-combination-of-           histopathology-and-gene-expression-analysis

49. Gastric Cancer: Whole-genome reconstruction and mutational signatures

Aviva  Lev-Ari, PhD, RD

https://pharmaceuticalintelligence.com/2012/12/24/gastric-cancer-whole-genome-reconstruction-and-mutational-                   signatures-2/

50. Genomic Analysis: FLUIDIGM Technology in the Life Science and Agricultural Biotechnology

Aviva Lev-Ari, PhD, RD

https://pharmaceuticalintelligence.com/2012/08/22/genomic-analysis-fluidigm-technology-in-the-life-science-and-                   agricultural-biotechnology/

51. 2013 Genomics: The Era Beyond the Sequencing Human Genome: Francis Collins, Craig Venter, Eric Lander, et al.

Aviva Lev-Ari, PhD, RD

https://pharmaceuticalintelligence.com/2013_Genomics

52. Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine – Part 1

Aviva Lev-Ari, PhD, RD

https://pharmaceuticalintelligence.com/Paradigm Shift in Human Genomics_/

Signaling Pathways

  1. Proteins and cellular adaptation to stress

Larry H Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/2014/07/08/proteins-and-cellular-adaptation-to-stress/

  1. A Synthesis of the Beauty and Complexity of How We View Cancer:
    Cancer Volume One – Summary

Author and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/03/26/a-synthesis-of-the-beauty-and-complexity-of-how-we-view-cancer/

  1. Recurrent somatic mutations in chromatin-remodeling and ubiquitin ligase complex genes in
    serous endometrial tumors

Sudipta Saha, PhD

https://pharmaceuticalintelligence.com/2012/11/19/recurrent-somatic-mutations-in-chromatin-remodeling-ad-ubiquitin-           ligase-complex-genes-in-serous-endometrial-tumors/

4.  Prostate Cancer Cells: Histone Deacetylase Inhibitors Induce Epithelial-to-Mesenchymal Transition

Stephen J Williams, PhD

https://pharmaceuticalintelligence.com/2012/11/30/histone-deacetylase-inhibitors-induce-epithelial-to-mesenchymal-              transition-in-prostate-cancer-cells/

5. Ubiquinin-Proteosome pathway, autophagy, the mitochondrion, proteolysis and cell apoptosis

Author and Curator: Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/10/30/ubiquinin-proteosome-pathway-autophagy-the-mitochondrion-                   proteolysis-and-cell-apoptosis/

6. Signaling and Signaling Pathways

Larry H. Bernstein, MD, FCAP, Reporter and Curator

https://pharmaceuticalintelligence.com/2014/08/12/signaling-and-signaling-pathways/

7.  Leptin signaling in mediating the cardiac hypertrophy associated with obesity

Larry H. Bernstein, MD, FCAP, Reporter and Curator

https://pharmaceuticalintelligence.com/2013/11/03/leptin-signaling-in-mediating-the-cardiac-hypertrophy-associated-            with-obesity/

  1. Sensors and Signaling in Oxidative Stress

Larry H. Bernstein, MD, FCAP, Reporter and Curator

https://pharmaceuticalintelligence.com/2013/11/01/sensors-and-signaling-in-oxidative-stress/

  1. The Final Considerations of the Role of Platelets and Platelet Endothelial Reactions in Atherosclerosis and Novel
    Treatments

Larry H. Bernstein, MD, FCAP, Reporter and Curator

https://pharmaceuticalintelligence.com/2013/10/15/the-final-considerations-of-the-role-of-platelets-and-platelet-                      endothelial-reactions-in-atherosclerosis-and-novel-treatments

10.   Platelets in Translational Research – Part 1

Larry H. Bernstein, MD, FCAP, Reporter and Curator

https://pharmaceuticalintelligence.com/2013/10/07/platelets-in-translational-research-1/

11.  Disruption of Calcium Homeostasis: Cardiomyocytes and Vascular Smooth Muscle Cells: The Cardiac and
Cardiovascular Calcium Signaling Mechanism

Author and Curator: Larry H Bernstein, MD, FCAP, Author, and Content Consultant to e-SERIES A:
Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC and Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/09/12/disruption-of-calcium-homeostasis-cardiomyocytes-and-vascular-             smooth-muscle-cells-the-cardiac-and-cardiovascular-calcium-signaling-mechanism/

12. The Centrality of Ca(2+) Signaling and Cytoskeleton Involving Calmodulin Kinases and
Ryanodine Receptors in Cardiac Failure, Arterial Smooth Muscle, Post-ischemic Arrhythmia,
Similarities and Differences, and Pharmaceutical Targets

     Author and Curator: Larry H Bernstein, MD, FCAP, Author, and Content Consultant to
e-SERIES A: Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC and
Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/09/08/the-centrality-of-ca2-signaling-and-cytoskeleton-involving-calmodulin-       kinases-and-ryanodine-receptors-in-cardiac-failure-arterial-smooth-muscle-post-ischemic-arrhythmia-similarities-and-           differen/

13.  Nitric Oxide Signalling Pathways

Aviral Vatsa, PhD, MBBS

https://pharmaceuticalintelligence.com/2012/08/22/nitric-oxide-signalling-pathways/

14. Immune activation, immunity, antibacterial activity

Larry H. Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/2014/07/06/immune-activation-immunity-antibacterial-activity/

15.  Regulation of somatic stem cell Function

Larry H. Bernstein, MD, FCAP, Writer and Curator    Aviva Lev-Ari, PhD, RN, Curator

https://pharmaceuticalintelligence.com/2014/07/29/regulation-of-somatic-stem-cell-function/

16. Scientists discover that pluripotency factor NANOG is also active in adult organisms

Larry H. Bernstein, MD, FCAP, Reporter

https://pharmaceuticalintelligence.com/2014/07/10/scientists-discover-that-pluripotency-factor-nanog-is-also-active-in-adult-organisms/

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Blood Pressure Response to Antihypertensives: Hypertension Susceptibility Loci Study

Reporter: Aviva Lev-Ari, PhD, RN

 

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 Pvalues 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

 

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

Reporter: Aviva Lev-Ari, PhD, RN

 

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-mailJyang75@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

 

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Genomics of Incident Ischemic Stroke Events, Stroke and Cardiovascular Disease

Reporter: Aviva Lev-Ari, PhD, RN

 

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 Genomicsand 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

 

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

Reporter: Aviva Lev-Ari, PhD, RN

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

 

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Nicotinic Acetylcholine Receptor Genes with Subclinical Atherosclerosis in American Indians: Genetic Variants Study and Gene-Family Analysis

Reporter: Aviva Lev-Ari, PhD, RN

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

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Reporter: Aviva Lev-Ari, PhD, RN

Genome.gov National Human Genome Research Institute National Institutes of Health

Online Research Resources

Contents

From NHGRI
Online Research Resources Developed at NHGRI
NHGRI Reports and Publications
The NHGRI Genome Sequencing Program (GSP)
Beyond NHGRI
The Completed Human Sequence
Other Federal Agencies Involved in Genomics
Human Genome Sequence Assemblies and Other Genomic Data Resources
Underlying Map Information
Sequencing Centers of the International Human Genome Sequencing Consortium
Model Organism Genome Projects
Archaea and Bacteria
Eukaryotes
Databases
National Center for Biotechnology Information (NCBI) Databases and Tools
Nucleotide Sequence Databases
Trace Archives (Raw Sequence Data Repositories)
Single Nucleotide Polymorphisms (SNPs)
cDNAs and Expressed Sequence Tags (ESTs)
Model Organism Databases
Additional Sequence, Gene and Protein Databases
Ethical, Legal and Social Implications (ELSI) Information
Funding Agencies
Additional Genome Resources
Biology Resources
Selected Journals

From NHGRI

Online Research Resources Developed at NHGRI
Software, databases and research project Web sites from NHGRI’s Division of Intramural Research (DIR).

NHGRI Reports and Publications

The NHGRI Genome Sequencing Program (GSP) 
Genome sequencing projects currently in production and funded by NHGRI.

Beyond NHGRI

The Completed Human Sequence:
Other Federal Agencies Involved in Genomics
Human Genome Sequence Assemblies and Other Genomic Data Resources

 

Underlying Map Information
Sequencing Centers of the International Human Genome Sequencing Consortium

(Listed in order of total sequence contributed to the draft human sequence published February 15, 2001, Nature, 409:860-921)

Model Organism Genome Projects

Archaea and Bacteria

Eukaryotes

Databases

National Center for Biotechnology Information (NCBI) Databases and Tools

Nucleotide Sequence Databases

Trace Archives (Raw Sequence Data Repositories)

Single Nucleotide Polymorphisms (SNPs)

cDNAs and Expressed Sequence Tags (ESTs)

Model Organism Databases

Additional Sequence, Gene and Protein Databases

  • InterPro protein sequence analysis & classification [ebi.ac.uk]
    An integrated database of predictive protein signatures used for the classification and automatic annotation of proteins and genomes.
  • Eukaryotic Promoter Database [epd.isb-sib.ch]
  • PROSITE [expasy.org]
    A database of protein families and domains.
  • SWISS-PROT [web.expasy.org]
    A protein knowledgebase.
  • BioMagResBank [bmrb.wisc.edu]
    NMR spectroscopy data on proteins, peptides, and nucleic acids.
  • Protein Data Bank (PDB) [rcsb.org]
    The repository for 3-D biological macromolecular structure data.
  • DSSP [swift.cmbi.ru.nl]
    A database of secondary structure protein assignments.
  • FSSP [biocenter.helsinki.fi]
    A database of fold classifications based on structure-structure alignment of proteins.
  • HSSP [cmbi.kun.nl]
    A database of homology-derived secondary structure of proteins.
  • Nucleic Acid Database Project (NDB) [ndbserver.rutgers.edu]
    Structural information about nucleic acids.
  • The I.M.A.G.E. Consortium [image.hudsonalpha.org]
    A public collection of genes.
Ethical, Legal and Social Implications (ELSI) Research Program
Funding Agencies
Additional Genome Resources
Biology Resources
Selected Journals

Last Updated: October 16, 2012

SOURCE:

http://www.genome.gov/10000375

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Observations on Finding the Genetic Links in Common Disease: Whole Genomic Sequencing Studies

Author: Larry H Bernstein, MD, FCAP

In this article I will address the following article by Dr. SJ Williams.

Finding the Genetic Links in Common Disease:  Caveats of Whole Genome Sequencing Studies

 

In the November 23, 2012 issue of Science, Jocelyn Kaiser reports (Genetic Influences On Disease  Remain Hidden in News and  Analysis) on the difficulties that many genomic studies are encountering correlating genetic variants to high risk of type 2 diabetes and heart disease. American Society of  Human Genetics annual 2012 meeting, results of DNA sequencing studies reporting on genetic variants and links to high risk type 2 diabetes and heart disease, part of an international effort to determine the genetic events contributing to complex, common diseases like diabetes.
The key point is that these disease links are challenged by the identification of genetic determinants that do not follow Mendelian Genetics.  There are many disease associated gene variants, and they have not been deleted as a result of natural selection.  In the case of diabetes (type 2), the genetic risk is a low as 26%.

Gene-wide-association studies (GAWS) have identified single nucleotide polymorphisms (SNPs) with associations for common diseases, most of these individually carry only only 20-40% of risk. This is not sufficient for prediction
and use in personalized  treatment.

What is the implication of this.  Researchers have gone to exome-sequencing and  to whole genome sequencing for answers. SNPs can be easily done  by microarray, and in a clinic setting. GWAS is difficult and has inherent complexity, and it has had high cost of use. But the cost of the technology has been dropping precipitously. Technology is being redesigned for more rapid diagnosis and use in clinical research and personalized medicine.  It appears that this is not  yet a game changer.

My own thinking is that the answer doesn’t  fully lie in the genome sequencing, but that it must turn on the very large weight of importance in the regulatory function in the genome, that which was once “considered” dark matter.  In the regulatory function you have a variety of interactions and adaptive changes to the proximate environment, and this is a key to the nascent study of metabolomics.

Three projects highlighted are:
1.  National Heart, Lung and Blood Institute Exome Sequencing Project (ESP)[2]: heart, lung, blood

  • A majority of variants linked to any disease are rare
  • Groups of variants in the same gene confirmed a link between
    APOC3 and risk for early-onset heart attack

2.  T2D-GENES Consortium
3.  GoT2D

  • SNP and PAX4 gene association for type 2 diabetes in East Asians
  • No new rare variants above 1.5% frequency for diabetes

http://www.phgfoundation.org/news/5164/

The unsupported conclusion from this has been

  1. the common disease-common variant hypothesis, which predicts that common disease-causing genetic variants exist in all human populations, but   (common unexplained complexity?) each individual variant will necessarily only have a small effect on disease susceptibility (i.e. a low associated relative risk).
  1. the common disease, many rare variants hypothesis, which postulates that disease is caused by multiple strong-effect variants, (an alternative complexity situation?) Dickson et al. (2010)  PLoS Biol 2010 8(1):e1000294

The reality is that it has been difficult to associate any variant with prediction of risk, but an alternative approach appears to be intron sequencing and missing information on gene-gene interactions.

Jocelyn Kaiser’s Science article notes this in a brief interview with Harry Dietz of Johns Hopkins University where he suspects that “much of the missing heritability lies in gene-gene interactions”.

Oliver Harismendy and Kelly Frazer and colleagues’ recent publication in Genome Biology  http://genomebiology.com/content/11/11/R118 support this notion.  The authors used targeted resequencing
of two endocannabinoid metabolic enzyme genes (fatty-acid-amide hydrolase (FAAH) and monoglyceride lipase (MGLL) in 147 normal weight and 142 extremely obese patients.

English: The human genome, categorized by func...

English: The human genome, categorized by function of each gene product, given both as number of genes and as percentage of all genes. (Photo credit: Wikipedia)

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Finding the Genetic Links in Common Disease:  Caveats of Whole Genome Sequencing Studies

Writer and Reporter: Stephen J. Williams, Ph.D.

In the November 23, 2012 issue of Science, Jocelyn Kaiser reports (Genetic Influences On Disease Remain Hidden in News and Analysis)[1] on the difficulties that many genomic studies are encountering correlating genetic variants to high risk of type 2 diabetes and heart disease.  At the recent American Society of Human Genetics annual 2012 meeting, results of several DNA sequencing studies reported difficulties in finding genetic variants and links to high risk type 2 diabetes and heart disease.  These studies were a part of an international effort to determine the multiple genetic events contributing to complex, common diseases like diabetes.  Unlike Mendelian inherited diseases (like ataxia telangiectasia) which are characterized by defects mainly in one gene, finding genetic links to more complex diseases may pose a problem as outlined in the article:

  • Variants may be so rare that massive number of patient’s genome would need to be analyzed
  • For most diseases, individual SNPs (single nucleotide polymorphisms) raise risk modestly
  • Hard to find isolated families (hemophilia) or isolated populations (Ashkenazi Jew)
  • Disease-influencing genes have not been weeded out by natural selection after human population explosion (~5000 years ago) resulted in numerous gene variants
  • What percentage variants account for disease heritability (studies have shown this is as low as 26% for diabetes with the remaining risk determined by environment)

Although many genome-wide-associations studies have found SNPs that have causality to increasing risk diseases such as cancer, diabetes, and heart disease, most individual SNPs for common diseases raise risk by about only 20-40% and would be useless for predicting an individual’s chance they will develop disease and be a candidate for a personalized therapy approach.  Therefore, for common diseases, investigators are relying on direct exome sequencing and whole-genome sequencing to detect these medium-rare risk variants, rather than relying on genome-wide association studies (which are usually fine for detecting the higher frequency variants associated with common diseases).

Three of the many projects (one for heart risk and two for diabetes risk) are highlighted in the article:

1.  National Heart, Lung and Blood Institute Exome Sequencing Project (ESP)[2]: heart, lung, blood

  • Sequenced 6,700 exomes of European or African descent
  • Majority of variants linked to disease too rare (as low as one variant)
  • Groups of variants in the same gene confirmed link between APOC3 and higher risk for early-onset heart attack
  • No other significant gene variants linked with heart disease

2.  T2D-GENES Consortium: diabetes

Sequenced 5,300 exomes of type 2 diabetes patients and controls from five ancestry groups
SNP in PAX4 gene associated with disease in East Asians
No low-frequency variant with large effect though

3.  GoT2D: diabetes

  • After sequencing 2700 patient’s exomes and whole genome no new rare variants above 1.5% frequency with a strong effect on diabetes risk

A nice article by Dr. Sowmiya Moorthie entitled Involvement of rare variants in common disease can be found at the PGH Foundation site http://www.phgfoundation.org/news/5164/ further discusses this conundrum,  and is summarized below:

“Although GWAs have identified many SNPs associated with common disease, they have as yet had little success in identifying the causative genetic variants. Those that have been identified have only a weak effect on disease risk, and therefore only explain a small proportion of the heritable, genetic component of susceptibility to that disease. This has led to the common disease-common variant hypothesis, which predicts that common disease-causing genetic variants exist in all human populations, but each individual variant will necessarily only have a small effect on disease susceptibility (i.e. a low associated relative risk).

An alternative hypothesis is the common disease, many rare variants hypothesis, which postulates that disease is caused by multiple strong-effect variants, each of which is only found in a few individuals. Dickson et al. in a paper in PLoS Biology postulate that these rare variants can be indirectly associated with common variants; they call these synthetic associations and demonstrate how further investigation could help explain findings from GWA studies [Dickson et al. (2010) PLoS Biol. 8(1):e1000294][3].  In simulation experiments, 30% of synthetic associations were caused by the presence of rare causative variants and furthermore, the strength of the association with common variants also increased if the number of rare causative variants increased. “

one_of_many rare variants

Figure from Dr. Moorthie’s article showing the problem of “finding one in many”.

(please   click to enlarge)

Indeed, other examples of such issues concerning gene variant association studies occur with other common diseases such as neurologic diseases and obesity, where it has been difficult to clearly and definitively associate any variant with prediction of risk.

For example, Nuytemans et. al.[4] used exome sequencing to find variants in the vascular protein sorting 3J (VPS35) and eukaryotic transcription initiation factor 4  gamma1 (EIF4G1) genes, tow genes causally linked to Parkinson’s Disease (PD).  Although they identified novel VPS35 variants none of these variants could be correlated to higher risk of PD.   One EIF4G1 variant seemed to be a strong Parkinson’s Disease risk factor however there was “no evidence for an overall contribution of genetic variability in VPS35 or EIF4G1 to PD development”.

These negative results may have relevance as companies such as 23andme (www.23andme.com) claim to be able to test for Parkinson’s predisposition.  To see a description of the LLRK2 mutational analysis which they use to determine risk for the disease please see the following link: https://www.23andme.com/health/Parkinsons-Disease/. This company and other like it have been subjects of posts on this site (Personalized Medicine: Clinical Aspiration of Microarrays)

However there seems to be more luck with strategies focused on analyzing intronic sequence rather than exome sequence. Jocelyn Kaiser’s Science article notes this in a brief interview with Harry Dietz of Johns Hopkins University where he suspects that “much of the missing heritability lies in gene-gene interactions”.  Oliver Harismendy and Kelly Frazer and colleagues’ recent publication in Genome Biology  http://genomebiology.com/content/11/11/R118 support this notion[5].  The authors used targeted resequencing of two endocannabinoid metabolic enzyme genes (fatty-acid-amide hydrolase (FAAH) and monoglyceride lipase (MGLL) in 147 normal weight and 142 extremely obese patients.

These patients were enrolled in the CRESCENDO trial and patients analyzed were of European descent. However, instead of just exome sequencing, the group resequenced exome AND intronic sequence, especially focusing on promoter regions.   They identified 1,448 single nucleotide variants but using a statistical filter (called RareCover which is referred to as a collapsing method) they found 4 variants in the promoters and intronic areas of the FAAH and MGLL genes which correlated to body mass index.  It should be noted that anandamide, a substrate for FAAH, is elevated in obese patients. The authors did note some issues though mentioning that “some other loci, more weakly or inconsistently associated in the original GWASs, were not replicated in our samples, which is not too surprising given the sample size of our cohort is inadequate to replicate modest associations”.

PLEASE WATCH VIDEO on the National Heart, Lung and Blood Institute Exome Sequencing Project

https://www.youtube.com/watch?v=-Qr5ahk1HEI

REFERENCES

http://www.phgfoundation.org/news/5164/  PHG Foundation

1.            Kaiser J: Human genetics. Genetic influences on disease remain hidden. Science 2012, 338(6110):1016-1017.

2.            Tennessen JA, Bigham AW, O’Connor TD, Fu W, Kenny EE, Gravel S, McGee S, Do R, Liu X, Jun G et al: Evolution and functional impact of rare coding variation from deep sequencing of human exomes. Science 2012, 337(6090):64-69.

3.            Dickson SP, Wang K, Krantz I, Hakonarson H, Goldstein DB: Rare variants create synthetic genome-wide associations. PLoS biology 2010, 8(1):e1000294.

4.            Nuytemans K, Bademci G, Inchausti V, Dressen A, Kinnamon DD, Mehta A, Wang L, Zuchner S, Beecham GW, Martin ER et al: Whole exome sequencing of rare variants in EIF4G1 and VPS35 in Parkinson disease. Neurology 2013, 80(11):982-989.

5.            Harismendy O, Bansal V, Bhatia G, Nakano M, Scott M, Wang X, Dib C, Turlotte E, Sipe JC, Murray SS et al: Population sequencing of two endocannabinoid metabolic genes identifies rare and common regulatory variants associated with extreme obesity and metabolite level. Genome biology 2010, 11(11):R118.

Other posts on this site related to Genomics include:

Cancer Biology and Genomics for Disease Diagnosis

Diagnosis of Cardiovascular Disease, Treatment and Prevention: Current & Predicted Cost of Care and the Promise of Individualized Medicine Using Clinical Decision Support Systems

Ethical Concerns in Personalized Medicine: BRCA1/2 Testing in Minors and Communication of Breast Cancer Risk

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

Genomics-based cure for diabetes on-the-way

Personalized Medicine: Clinical Aspiration of Microarrays

Late Onset of Alzheimer’s Disease and One-carbon Metabolism

Genetics of Disease: More Complex is How to Creating New Drugs

Genetics of Conduction Disease: Atrioventricular (AV) Conduction Disease (block): Gene Mutations – Transcription, Excitability, and Energy Homeostasis

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

Cancer Genomic Precision Therapy: Digitized Tumor’s Genome (WGSA) Compared with Genome-native Germ Line: Flash-frozen specimen and Formalin-fixed paraffin-embedded Specimen Needed

Mitochondrial Metabolism and Cardiac Function

Pancreatic Cancer: Genetics, Genomics and Immunotherapy

Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

Quantum Biology And Computational Medicine

Personalized Cardiovascular Genetic Medicine at Partners HealthCare and Harvard Medical School

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

LEADERS in Genome Sequencing of Genetic Mutations for Therapeutic Drug Selection in Cancer Personalized Treatment: Part 2

Consumer Market for Personal DNA Sequencing: Part 4

Personalized Medicine: An Institute Profile – Coriell Institute for Medical Research: Part 3

Whole-Genome Sequencing Data will be Stored in Coriell’s Spin off For-Profit Entity

 

Read Full Post »


Reporter: Aviva Lev-Ari, PhD, RN

 

Track 5

Next-Gen Sequencing Informatics

NGS, Genome-Scale Screening, and HTP Proteomics

Track 5 is dedicated to advances in analysis and intepretation of next-gen data. Topics to be covered include analysis of

sequence variants related to cancer research from NGS data, instruments facilitate a cloud approach for NGS, analysis tools

and workflows, and network biology/network medicine.

TUESDAY, APRIL 9

7:00 am Workshop Registration and Morning Coffee

8:00 Pre-Conference Workshops*

*Separate Registration Required

2:00 – 7:00 pm Main Conference Registration

4:00 Event Chairperson’s Opening Remarks

Cindy Crowninshield, RD, LDN, Conference Director, Cambridge

Healthtech Institute

4:05 Keynote Introduction

Kevin Brode, Senior Director, Health & Life Sciences, Americas Hitachi

Data Systems

»»4:15 PLENARY KEYNOTE

Do Network Pharmacologists Need Robot Chemists?

Andrew L. Hopkins, DPhil, FRSC, FSB, Division of Biological Chemistry

and Drug Design, College of Life Sciences, University of Dundee

5:00 Welcome Reception in the Exhibit Hall with Poster Viewing

Drop off a business card at the CHI Sales booth for a chance to win 1 of 2

iPads® or 1 of 2 Kindle Fires®!*

*Apple ® and Amazon are not sponsors or participants in this program

WEDNESDAY, APRIL 10

7:00 am Registration and Morning Coffee

8:00 Chairperson’s Opening Remarks

Phillips Kuhl, Co-Founder and President, Cambridge Healthtech Institute

8:05 Keynote Introduction

Sanjay Joshi, CTO, Life Sciences, EMC Isilon

»»8:15 PLENARY KEYNOTE

Atul Butte, M.D., Ph.D., Division Chief and Associate Professor,

Stanford University School of Medicine; Director, Center for Pediatric

Bioinformatics, Lucile Packard Children’s Hospital; Co-founder,

Personalis and Numedii

8:55 Benjamin Franklin Award & Laureate Presentation

9:15 Best Practices Award Program

9:45 Coffee Break in the Exhibit Hall with Poster Viewing

Best Practices for Genomic Data Interpretation & Analysis

10:50 Chairperson’s Remarks

Steve Dickman, Founder & CEO, CBT Advisors, Inc.

11:00 CLARITY Challenge

Shamil Sunyaev, Ph.D., Associate Professor, Division of Genetics,

Department of Medicine, Brigham and Women’s Hospital/Harvard

Medical School

11:30 HLA and KIR Typing from NGS Reads with

Omixon Target

Attila Berces, Ph.D., CEO, Omixon

HLA is the most polymorphic region of the human genome

with several segmental duplications and its analysis is a computational

challenge. In this presentation I will show examples including validation

studies of HLA typing from various sources of genomic data: whole genome,

whole exome, targeted amplicon sequencing with Illumina, Ion Torrent and

Roche sequencer.

11:45 Comparison of Genome Analysis Tools

Jason Wang, Co-founder & CTO, Arpeggi, Inc.

A major impediment to clinical sequencing is the paucity of

analysis standards and comparison metrics. We present our

progress towards developing analysis standards, as well an open-access

collaborative tool that enables anyone to define comparison metrics and

compare tool performance. We hope that in making available this resource

we can help fuel a community-driven solution for standardizing genome

analysis pipelines.

12:00 Case Study: Sequencing Informatics System to Profile Genetic

Changes in Tumors

Long Phi Le, M.D., Ph.D., Department of Pathology, Massachusetts

General Hospital

This presentation will discuss the development of a sequencing informatics

system to profile genetic changes in tumors that is in collaboration between

PerkinElmer with Massachusetts General Hospital. This system, based on

PerkinElmer’s Geospiza platforms, will allow genotype analysis to define

key targets.

12:30 Ion Torrent Informatics Enables

Semiconductor Sequencing

Darryl León , Ph.D., Associate Director, Product

Management, Ion Torrent, Life Technologies

Data generated by the Ion Torrent Personal Genome Machine Sequencer or

the Ion Torrent Proton Sequencer are analyzed by Torrent Suite Software.

An overview of the data analysis steps will be provided. Torrent Suite offers

a flexible plug-in system allowing software developers the ability to deliver

custom analysis solutions using the compute resources associated with the

local Torrent Server. For researchers with need for either rich annotations

or controlled data analysis, the Ion Reporter Software offers a streamlined

data analysis and decision engine for use with amplicons, exomes,

or genomes.

1:40 Chairperson’s Remarks

Jeffrey Rosenfeld, Ph.D., IST/High Performance & Research Computing,

University of Medicine & Dentistry of New Jersey (UMDNJ)

Sponsored by

Sponsored by

Sponsored by

Bio-ITWorldExpo.com 18

1:45 Data Intensive Academic Grid (DIAG): A Free Computational Cloud

Infrastructure Designed for Bioinformatics Analysis

Anup Mahurkar, Executive Director, Software Engineering and IT, Institute

for Genome Sciences, University of Maryland School of Medicine

We have deployed the NSF funded Data Intensive Academic Grid (DIAG),

a free computational cloud designed to meet the analytical needs of

the bioinformatics community. DIAG has 200+ registered users from 130

institutions worldwide who conduct large-scale genomics, transcriptomics,

and metagenomics data analysis. Learn about the grid’s architecture, how

to access this free resource, and success stories.

2:15 Performance Comparison of Variant Detection Tools for Next

Generation Sequencing (NGS) Data: An Assessment Using a Pedigree-

Based NGS Dataset and SNP Array

Ming Yi, Ph.D. IT Manager, Functional Genomic Group, Advanced

Biomedical Computing Center, SAIC-Frederick at Frederick National

Laboratory for Cancer Research (formerly National Cancer Institute)

There is an urgent need for the NGS community to be able to make the

right choice out of a large collection of available SNP detection tools. Our

methodology offers a great example of comparing SNP discovery tools and

paving a way to expand such methods in more global scope for comparison.

2:45 Informatics in the Cloud

Karan Bhatia, Ph.D., Solutions Architect, Amazon

Web Services

Learn about how to easily create sophisticated, scalable,

secure pipelines to accelerate life science research with Amazon Web

Services. In this presentation, you will learn how to drive scale out, tightly

coupled and Hadoop based workflows on Amazon EC2, a utility computing

platform that provides a perfect fit for data management and collaboration.

3:15 Refreshment Break in the Exhibit Hall with Poster Viewing

Gene Mapping & Expression

3:45 InSilico DB Genomic Datasets Hub: An Efficient Starting Point for

Managing and Analyzing Genomewide Studies in GenePattern, Integrative

Genomics Viewer, and R/Bioconductor

David Weiss, Ph.D., CEO, InSilico Genomics

Alain Coletta, Ph.D., Co-Founder and CTO, InSilico Genomics

The InSilico DB platform is a powerful collaborative environment, with

advanced capabilities for biocuration, datasets subsetting and combination,

and datasets sharing. InSIlico DB solution architecture will be presented

along with a live demo of the InSilico DB online platform. Learn how more

than 1000 users from top academic and research institutions are using

InSilico DB in their daily research.

4:15 Constructing a Comprehensive Map for Molecules Implicated in

Obesity and Its Induced Disorders

Kamal Rawal, Ph.D., Faculty, Biotechnology and Bioinformatics, Jaypee

Institute of Information Technology

We have constructed a comprehensive map of all the molecules (genes,

proteins, and metabolites) reported to be implicated in obesity. This map

paves the way to understanding the pathophysiology of obesity and identify

drug targets and off-targets for existing drugs. This talk discusses the

integrated approach we used in combining public resources, abstracts, and

research articles to construct this map.

4:45 Quality Assurance: An Essential Step for Gene

Expression Analysis Using Deep Sequencing

Dan Kearns, Director, Software Development, Maverix

Biomics, Inc.

Dave Mandelkern, CEO & Co-Founder, Maverix Biomics, Inc.

With the advancement of deep sequencing technologies, researchers

expect to obtain high quality results from their studies. However, this cannot

be obtained solely by successful sequencing runs. Multiple data checks

and pre-processing must be performed before downstream analysis. In this

case study, we will present an automated quality assurance pipeline that

helps improve gene expression analysis results.

5:00 DDN LS Appliance – Simple Platform for NGS

Analysis, Data Distribution and Collaboration

Jose L. Alvarez, WW Director Life Sciences,

DataDirect Networks

With this unique approach the DDN LS appliance can deliver flexible data

ingest options, optimized data analysis resources, a policy based data

tiering/archive solution and a geo-distributed secure collaboration platform.

The appliance delivers 1.46X better performance on popular LS applications

like Bowtie when compared to NFS based solutions.

5:15 Best of Show Awards Reception in the Exhibit Hall

6:15 Exhibit Hall Closes

THURSDAY, APRIL 11

7:00 am Breakfast Presentation (Sponsorship Opportunity Available) or

Morning Coffee

Gene Mapping & Expression

8:45 Chairperson’s Opening Remarks

8:50 Network Biology and Personalized Medicine in Multiple Sclerosis

Mark Chance, Ph.D., Vice Dean for Research, Proteomics, Case Western

Reserve University

Almost nothing is known about biological factors underlying the remarkable

disease heterogeneity observed across multiple sclerosis (MS) patients,

and there are no accurate biological predictors of disease severity that

can be used for guiding clinical treatment options. Learn about the network

biology methods we are using to analyze blood cell gene expression and

understand good and poor responders to therapy.

9:20 GeneSeer: A Flexible, Easy-to-Use Tool to Aid Drug Discovery by

Exploring Evolutionary Relationships between Genes across Genomes

Philip Cheung, Bioinformatics Group Leader, Scientific Computing,

Dart Neuroscience

GeneSeer is a publicly available tool that leverages public sequence data,

gene metadata information, and other publicly available data to calculate

and display orthologous and paralogous gene relationships for all genes

from several species, including yeasts, insects, worms, vertebrates,

mammals, and primates such as human. This talk describes GeneSeer’s

underlying methods and the user-friendly interface.

9:50 Sponsored Presentations (Opportunities Available)

10:20 Coffee Break in the Exhibit Hall and Poster Competition

Winners Announced

10:45 Plenary Keynote Panel Chairperson’s Remarks

Kevin Davies, Ph.D., Editor-in-Chief, Bio-IT World

10:50 Plenary Keynote Panel Introduction

Yury Rozenman, Head of BT for Life Sciences, BT Global Services

Niven R. Narain, President & CTO, Berg Pharma

»»Plenary Keynote Panel

11:05 The Life Sciences CIO Panel

Panelists:

Remy Evard, CIO, Novartis Institutes for BioMedical Research

Martin Leach, Ph.D., Vice President, R&D IT, Biogen Idec

Andrea T. Norris, Director, Center for Information Technology (CIT)

and Chief Information Officer, NIH

Gunaretnam (Guna) Rajagopal, Ph.D., VP & CIO – R&D IT, Research,

Bioinformatics & External Innovation, Janssen Pharmaceuticals

Cris Ross, Chief Information Officer, Mayo Clinic

Matthew Trunnell, CIO, Broad Institute of MIT and Harvard

Sponsored by

Sponsored by

Sponsored by

19 Bio-ITWorldExpo.com

12:15 Luncheon in the Exhibit Hall with Poster Viewing

Panel Session: Building the IT Archetecture of the New York

Genome Center

2:00 Panel Session: Building the IT Architecture of the New York

Genome Center

Moderator: Kevin Davies, Ph.D., Editor-in-Chief, Bio-IT World

Christopher Dwan, Acting Senior Vice President, IT, New York

Genome Center

Kevin Shianna, Senior Vice President, Sequencing Operations, New York

Genome Center

Sanjay Joshi, CTO, Life Sciences, EMC Isilon Storage Division

Robert B. Darnell, M.D., Ph.D., President & Scientific Director, New York

Genome Center

George Gosselin, CTO, Computer Design & Integration LLC

In 2011, a consortium of 11 major academic and medical organizations in

and around New York announced the creation of the New York Genome

Center (NYGC). Under the direction of Nancy Kelley, the NYGC aspires to

be a world-class genomics and medical research center, and is currently

undergoing construction in the heart of Manhattan. NYGC management

has the opportunity to design and create a state-of-the-art IT and data

management infrastructure to handle, store and share the output from

what will rapidly become one of the world’s foremost genome sequencing

facilities. This series of talks will describe the thinking that went into the

design, creation and construction of the NYGC’s IT infrastructure and entire

data management strategy.

4:00 Conference Adjourns

 

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