Advertisements
Feeds:
Posts
Comments

Posts Tagged ‘population variation’


Icelandic Population Genomic Study Results by deCODE Genetics come to Fruition: Curation of Current genomic studies

Reporter/Curator: Stephen J. Williams, Ph.D.

 

UPDATED on 9/6/2017

On 9/6/2017, Aviva Lev-Ari, PhD, RN had attend a talk by Paul Nioi, PhD, Amgen, at HMS, Harvard BioTechnology Club (GSAS).

Nioi discussed his 2016 paper in NEJM, 2016, 374:2131-2141

Variant ASGR1 Associated with a Reduced Risk of Coronary Artery Disease

Paul Nioi, Ph.D., Asgeir Sigurdsson, B.Sc., Gudmar Thorleifsson, Ph.D., Hannes Helgason, Ph.D., Arna B. Agustsdottir, B.Sc., Gudmundur L. Norddahl, Ph.D., Anna Helgadottir, M.D., Audur Magnusdottir, Ph.D., Aslaug Jonasdottir, M.Sc., Solveig Gretarsdottir, Ph.D., Ingileif Jonsdottir, Ph.D., Valgerdur Steinthorsdottir, Ph.D., Thorunn Rafnar, Ph.D., Dorine W. Swinkels, M.D., Ph.D., Tessel E. Galesloot, Ph.D., Niels Grarup, Ph.D., Torben Jørgensen, D.M.Sc., Henrik Vestergaard, D.M.Sc., Torben Hansen, Ph.D., Torsten Lauritzen, D.M.Sc., Allan Linneberg, Ph.D., Nele Friedrich, Ph.D., Nikolaj T. Krarup, Ph.D., Mogens Fenger, Ph.D., Ulrik Abildgaard, D.M.Sc., Peter R. Hansen, D.M.Sc., Anders M. Galløe, Ph.D., Peter S. Braund, Ph.D., Christopher P. Nelson, Ph.D., Alistair S. Hall, F.R.C.P., Michael J.A. Williams, M.D., Andre M. van Rij, M.D., Gregory T. Jones, Ph.D., Riyaz S. Patel, M.D., Allan I. Levey, M.D., Ph.D., Salim Hayek, M.D., Svati H. Shah, M.D., Muredach Reilly, M.B., B.Ch., Gudmundur I. Eyjolfsson, M.D., Olof Sigurdardottir, M.D., Ph.D., Isleifur Olafsson, M.D., Ph.D., Lambertus A. Kiemeney, Ph.D., Arshed A. Quyyumi, F.R.C.P., Daniel J. Rader, M.D., William E. Kraus, M.D., Nilesh J. Samani, F.R.C.P., Oluf Pedersen, D.M.Sc., Gudmundur Thorgeirsson, M.D., Ph.D., Gisli Masson, Ph.D., Hilma Holm, M.D., Daniel Gudbjartsson, Ph.D., Patrick Sulem, M.D., Unnur Thorsteinsdottir, Ph.D., and Kari Stefansson, M.D., Ph.D.

N Engl J Med 2016; 374:2131-2141June 2, 2016DOI: 10.1056/NEJMoa1508419

Abstract
Article
References
Citing Articles (22)
Metrics

BACKGROUND

Several sequence variants are known to have effects on serum levels of non–high-density lipoprotein (HDL) cholesterol that alter the risk of coronary artery disease.

METHODS

We sequenced the genomes of 2636 Icelanders and found variants that we then imputed into the genomes of approximately 398,000 Icelanders. We tested for association between these imputed variants and non-HDL cholesterol levels in 119,146 samples. We then performed replication testing in two populations of European descent. We assessed the effects of an implicated loss-of-function variant on the risk of coronary artery disease in 42,524 case patients and 249,414 controls from five European ancestry populations. An augmented set of genomes was screened for additional loss-of-function variants in a target gene. We evaluated the effect of an implicated variant on protein stability.

RESULTS

We found a rare noncoding 12-base-pair (bp) deletion (del12) in intron 4 of ASGR1, which encodes a subunit of the asialoglycoprotein receptor, a lectin that plays a role in the homeostasis of circulating glycoproteins. The del12 mutation activates a cryptic splice site, leading to a frameshift mutation and a premature stop codon that renders a truncated protein prone to degradation. Heterozygous carriers of the mutation (1 in 120 persons in our study population) had a lower level of non-HDL cholesterol than noncarriers, a difference of 15.3 mg per deciliter (0.40 mmol per liter) (P=1.0×10−16), and a lower risk of coronary artery disease (by 34%; 95% confidence interval, 21 to 45; P=4.0×10−6). In a larger set of sequenced samples from Icelanders, we found another loss-of-function ASGR1 variant (p.W158X, carried by 1 in 1850 persons) that was also associated with lower levels of non-HDL cholesterol (P=1.8×10−3).

CONCLUSIONS

ASGR1 haploinsufficiency was associated with reduced levels of non-HDL cholesterol and a reduced risk of coronary artery disease. (Funded by the National Institutes of Health and others.)

 

Amgen’s deCODE Genetics Publishes Largest Human Genome Population Study to Date

Mark Terry, BioSpace.com Breaking News Staff reported on results of one of the largest genome sequencing efforts to date, sequencing of the genomes of 2,636 people from Iceland by deCODE genetics, Inc., a division of Thousand Oaks, Calif.-based Amgen (AMGN).

Amgen had bought deCODE genetics Inc. in 2012, saving the company from bankruptcy.

There were a total of four studies, published on March 25, 2015 on the online version of Nature Genetics; titled “Large-scale whole-genome sequencing of the Icelandic population[1],” “Identification of a large set of rare complete human knockouts[2],” “The Y-chromosome point mutation rate in humans[3]” and “Loss-of-function variants in ABCA7 confer risk of Alzheimer’s disease[4].”

The project identified some new genetic variants which increase risk of Alzheimer’s disease and confirmed some variants known to increase risk of diabetes and atrial fibrillation. A more in-depth post will curate these findings but there was an interesting discrete geographic distribution of certain rare variants located around Iceland. The dataset offers a treasure trove of meaningful genetic information not only about the Icelandic population but offers numerous new targets for breast, ovarian cancer as well as Alzheimer’s disease.

View Mark Terry’s article here on Biospace.com.

“This work is a demonstration of the unique power sequencing gives us for learning more about the history of our species,” said Kari Stefansson, founder and chief executive officer of deCode and one of the lead authors in a statement, “and for contributing to new means of diagnosing, treating and preventing disease.”

The scale and ambition of the study is impressive, but perhaps more important, the research identified a new genetic variant that increases the risk of Alzheimer’s disease and already had identified an APP variant that is associated with decreased risk of Alzheimer’s Disease. It also confirmed variants that increase the risk of diabetes and a variant that results in atrial fibrillation.
The database of human genetic variation (dbSNP) contained over 50 million unique sequence variants yet this database only represents a small proportion of single nucleotide variants which is thought to exist. These “private” or rare variants undoubtedly contribute to important phenotypes, such as disease susceptibility. Non-SNV variants, like indels and structural variants, are also under-represented in public databases. The only way to fully elucidate the genetic basis of a trait is to consider all of these types of variants, and the only way to find them is by large-scale sequencing.

Curation of Population Genomic Sequencing Programs/Corporate Partnerships

Click on “Curation of genomic studies” below for full Table

Curation of genomic studies
Study Partners Population Enrolled Disease areas Analysis
Icelandic Genome

Project

deCODE/Amgen Icelandic 2,636 Variants related to: Alzheimer’s, cardiovascular, diabetes WES + EMR; blood samples
Genome Sequencing Study Geisinger Health System/Regeneron Northeast PA, USA 100,000 Variants related to hypercholestemia, autism, obesity, other diseases WES +EMR +MyCode;

– Blood samples

The 100,000 Genomes Project National Health Service/NHS Genome Centers/ 10 companies forming Gene Consortium including Abbvie, Alexion, AstraZeneca, Biogen, Dimension, GSK, Helomics, Roche,   Takeda, UCB Rare disorders population UK Starting to recruit 100,000 Initially rare diseases, cancer, infectious diseases WES of blood, saliva and tissue samples

Ref paper

Saudi Human Genome Program 7 centers across Saudi Arabia in conjunction with King Abdulaziz City Science & Tech., King Faisal Hospital & Research Centre/Life Technologies General population Saudi Arabia 20,000 genomes over three years First focus on rare severe early onset diseases: diabetes, deafness, cardiovascular, skeletal deformation Whole genome sequence blood samples + EMR
Genome of the Netherlands (GoNL) Consortium consortium of the UMCG,LUMCErasmus MCVU university and UMCU. Samples where contributed by LifeLinesThe Leiden Longevity StudyThe Netherlands Twin Registry (NTR), The Rotterdam studies, and The Genetic Research in Isolated Populations program. All the sequencing work is done by BGI Hong Kong. Families in Netherlands 769 Variants, SNV, indels, deletions from apparently healthy individuals, family trios Whole genome NGS of whole blood no EMR

Ref paper in Nat. Genetics

Ref paper describing project

Faroese FarGen project Privately funded Faroe Islands Faroese population 50,000 Small population allows for family analysis Combine NGS with EMR and genealogy reports
Personal Genome Project Canada $4000.00 fee from participants; collaboration with University of Toronto and SickKids Organization; technical assistance with Harvard Canadian Health System Goal: 100,000 ? just started no defined analysis goals yet Whole exome and medical records
Singapore Sequencing Malay Project (SSMP) Singapore Genome Variation Project

Singapore Pharmacogenomics Project

Malaysian 100 healthy Malays from Singapore Pop. Health Study Variant analysis Deep whole genome sequencing
GenomeDenmark four Danish universities (KU, AU, DTU and AAU), two hospitals (Herlev and Vendsyssel) and two private firms (Bavarian Nordic and BGI-Europe). 150 complete genomes; first 30 published in Nature Comm. ? See link
Neuromics Consortium University of Tübingen and 18 academic and industrial partners (see link for description) European and Australian 1,100 patients with neuro-

degenerative and neuro-

muscular disease

Moved from SNP to whole exome analysis Whole Exome, RNASeq

References

  1. Gudbjartsson DF, Helgason H, Gudjonsson SA, Zink F, Oddson A, Gylfason A, Besenbacher S, Magnusson G, Halldorsson BV, Hjartarson E et al: Large-scale whole-genome sequencing of the Icelandic population. Nature genetics 2015, advance online publication.
  2. Sulem P, Helgason H, Oddson A, Stefansson H, Gudjonsson SA, Zink F, Hjartarson E, Sigurdsson GT, Jonasdottir A, Jonasdottir A et al: Identification of a large set of rare complete human knockouts. Nature genetics 2015, advance online publication.
  3. Helgason A, Einarsson AW, Gumundsdottir VB, Sigursson A, Gunnarsdottir ED, Jagadeesan A, Ebenesersdottir SS, Kong A, Stefansson K: The Y-chromosome point mutation rate in humans. Nature genetics 2015, advance online publication.
  4. Steinberg S, Stefansson H, Jonsson T, Johannsdottir H, Ingason A, Helgason H, Sulem P, Magnusson OT, Gudjonsson SA, Unnsteinsdottir U et al: Loss-of-function variants in ABCA7 confer risk of Alzheimer’s disease. Nature genetics 2015, advance online publication.

Other post related to DECODE, population genomics, and NGS on this site include:

Illumina Says 228,000 Human Genomes Will Be Sequenced in 2014

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

CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics and Computational Genomics – Part IIB

Human genome: UK to become world number 1 in DNA testing

Synthetic Biology: On Advanced Genome Interpretation for Gene Variants and Pathways: What is the Genetic Base of Atherosclerosis and Loss of Arterial Elasticity with Aging

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

Sequencing the exomes of 1,100 patients with neurodegenerative and neuromuscular diseases: A consortium of 18 European and Australian institutions

University of California Santa Cruz’s Genomics Institute will create a Map of Human Genetic Variations

Three Ancestral Populations Contributed to Modern-day Europeans: Ancient Genome Analysis

Impact of evolutionary selection on functional regions: The imprint of evolutionary selection on ENCODE regulatory elements is manifested between species and within human populations

Advertisements

Read Full Post »


1:00PM 11/13/2014 – 10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

REAL TIME Coverage of this Conference by Dr. Aviva Lev-Ari, PhD, RN – Director and Founder of LEADERS in PHARMACEUTICAL BUSINESS INTELLIGENCE, Boston http://pharmaceuticalintelligence.com

1:00 p.m. Panel Discussion Genomics in Prenatal and Childhood Disorders

Genomics in Prenatal and Childhood Disorders

     Moderator:

David Sweetser, M.D., Ph.D.
Unit Chief, Division of Medical Genetics; Attending Physician in Pediatric Hematology/Oncology,
Massachusetts General Hospital for Children

Genomics revolutionized medicine and genetic variation in a larger scale

Cases one on Causing Autism – mutations in a gene of synapse formation, clinical trials

Treatment: IGF1

Genetics: embryo – implant only the healthy embryo – newborn comprehensive genetics testing in the medical record integrated – Standard language of GENE-DRUG interaction not only drug-drug interaction

Potential Harms: May or may not happen disease – stigma issues

Explaining to parents the conditions is very difficult for MDs

Panelists:

3. Diana Bianchi, M.D.
Executive Director, Mother Infant Research Institute;
Vice Chair for Research and Academic Affairs,
Department of Pediatrics; Attending Geneticists and Neonatologist;
Natalie V. Zucker Professor, Tufts University School of Medicine

Medical Geneticist – Pediatrics

  • Prenatal screening and diagnosis – chromosomal abnormality – Down Syndrome, testing is more precise 70% fewer procedures to correct defects due to screening prenatally.
  • Prenatal diagnostics — patient is not in front of us, ultrasound examination, options to terminate pregnancies, genetic counseling — changed due to Genomics
  • Prenatal treatment to down syndrome before the birth – Transcriptomic approach, treat the fetus prebirth
  • Standard of care – all pregnant women – must receive from MD the option for screening for down syndrome, it is a test positive or negative
  • NOW – DNA allows to test for  fetal sex, chromosome in maternal circulation fetal and maternal genetics — Mother may have chromosomal variation
  • high false positive – DNA for Down Syndrome, 97% effective Micro duplication only 5%
  • genetics information protection act – sue prospective employer using Genome, life insurance issues
  • most data available is on Down Syndrome, of all parents informed of a fetus with Down Syndrome – 40% continues the pregnancy
  • accuracy in testing, offering choice and treatment are LEADING principles NOT elimination of a disease (i.e. down syndromes)
  • in ten years — GENOME OF EVERY FETUS TO BE SEQUENCE

for reference see Prenatal Treatment of Down’s Syndrome: a Reality?

and ref list by Dr. Bianchi

2. Holmes Morton, M.D. @ClinicSpecChild
Medical Director, Clinic for Special Children

Small population in Lancaster, PA – risk for untreatable disease 52,000 screens 4.2 millions in US are screened Target mutation analysis, diagnosis very effectively. Harrisburg, PA – small scale natural history studies

Carrier testing offered in 70s. Discourages  from marriage, culture reaction is different. Working in the community, clinical practice using exon sequencing, combine population genetics and molecular biology.Translate Genomics to Clinical, small number of risk factors

History of genetics in population important to establish treatment

Upon birth, affected newborns get matching bone marrow transplant, thus, bypass stem cells – Gene therapy is another thing

1. Benjamin Solomon, Ph.D., M.D.
Chief, Division of Medical Genomics,
Inova Translational Medicine Institute

Longer term, statistical model in asthma research,  rigorous process on patient consent, life insurance, mutation that parents also have. Consequences: actionable findings are communicated
135 Genes – sequencing for some conditions
100,000 deliveries 10% ENTER THE STUDY, CASE BY CASE BASIS O PARTICIPATE, WHO SHOULD BE TESTED

Questions from the Podium

– See more at: http://personalizedmedicine.partners.org/Education/Personalized-Medicine-Conference/Program.aspx#sthash.qGbGZXXf.dpuf

@HarvardPMConf

#PMConf

@SachsAssociates

@MGH

@MassGeneral

@TuftsMedicalCtr

@MedscapePeds

@ClinicSpecChild

@InovaHealth

Read Full Post »


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

https://pharmaceuticalintelligence.com/12-2-2013/larryhbern/Stabilizers that prevent transthyretin-mediated cardiomyocyte amyloidotic toxicity

Transthyretin is a small protein with a half-life of < 48 hours, synthesized by the liver, and a major transport protein for thyroxin.  There are 80 variants known, and some variants that occur in the Portuguese, a small section of Japan, Sweden, and Brazil, are associated will primary amyloidosis, the only cure for which is liver transplantation.  It causes fibrillary inclusions in the heart, but also affects the autonomic nervous system.  Some of the major work on this has been done for many years in the laboratory of   Jeffery W. Kelly, at the Skaggs Institue for Chemical Biology, the Scripps Research Institute.  A recent publication is of considerable interest.

Potent Kinetic Stabilizers that Prevent Transthyretin-mediated Cardiomyocyte Proteotoxicity

 Mamoun M. Alhamadsheh1,6,7, Stephen Connelly2,7, Ahryon Cho1, Natàlia Reixach3, Evan T. Powers3,4,5, Dorothy W. Pan1, Ian A. Wilson2,5, Jeffery W. Kelly3,4,5, and Isabella A. Graef1,*
Sci Transl Med. Author manuscript; available in PMC 2012 August 24.
1Department of Pathology, Stanford University Medical School, Stanford, California, USA
2Department of Molecular Biology, The Scripps Research Institute, La Jolla, California, USA
3Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, California, USA
4Department of Chemistry, The Scripps Research Institute, La Jolla, California, USA
5The Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, California, USA
6Department of Pharmaceutics & Medicinal Chemistry, University of the Pacific, Stockton, California, USA

Abstract

The V122I mutation that alters the stability of transthyretin (TTR) affects 3–4% of African Americans and leads to amyloidogenesis and development of cardiomyopathy. In addition, 10–15% of individuals over the age of 65 develop senile systemic amyloidosis (SSA) and cardiac
TTR deposits due to wild-type TTR amyloidogenesis. As no approved therapies for TTR amyloid cardiomyopathy are available, the development of drugs that prevent amyloid-mediated cardiotoxicity is desired. To this aim, we developed a fluorescence polarization-based HTS screen,
which identified several new chemical scaffolds targeting TTR. These novel compounds were potent kinetic stabilizers of TTR and
  • prevented tetramer dissociation,
  • unfolding and aggregation of both wild type and the most common cardiomyopathy-associated TTR mutant, V122I-TTR.
High-resolution co-crystal structures and characterization of the binding energetics revealed how these diverse structures bound to tetrameric TTR. Our study also showed that these compounds effectively inhibited the proteotoxicity of V122I-TTR towards human cardiomyocytes.
Several of these ligands stabilized TTR in human serum more effectively than diflunisal, which is one of the best known inhibitors of TTR aggregation, and may be promising leads for the treatment and/or prevention of TTR-mediated cardiomyopathy.

Author Contributions:

M.M.A. designed and performed most experiments, S.C. performed crystallographic structure determination, A.C peformed the serum TTR stabilization. N.R. performed the cell-based assays.   E.T.P. analyzed the ITC data. D.W.P. helped with probe synthesis. I.A.W. supervised the crystallographic work. J.W.K. supervised the work, S.C., N.R., I.A.W. and J.W.K. edited the paper. I.A.G supervised the work, M.M.A. and I.A.G prepared the manuscript.

 INTRODUCTION

The misassembly of soluble proteins into toxic amyloid aggregates underlies a large number of human degenerative diseases (1–3). TTR is one of more than 30 human amyloidogenic proteins whose misassembly can cause
  • a variety of degenerative gain-of-toxic-function diseases.
TTR is a tetrameric protein (54 kDa), secreted from the liver into the blood where, using orthogonal sites,
  • it transports thyroxine (T4) and
  • holo-retinol binding protein (4).
However, 99% of the TTR T4 binding sites remain unoccupied in humans
  • owing to the presence of two other T4 transport proteins in blood (3).
Familial TTR amyloid diseases, which are associated with one of more than 80 mutations in the TTR gene, include
  • the systemic neuropathies (familial amyloid polyneuropathy [FAP]),
  • cardiomyopathies (familial amyloid cardiomyopathy [FAC]), and
  • central nervous system amyloidoses (CNSA) (5–8).
Cardiac amyloidosis is most commonly caused by
  • deposition of immunoglobulin light chains or
  • TTR in the cardiac interstitium and conducting system.
It is a chronic and progressive condition, which can lead to arrhythmias, biventricular heart failure, and death (8–10). Two types of TTR-associated amyloid cardiomyopathies are clinically important.
  1. Wild-type (WT) TTR aggregation underlies the development of senile systemic amyloidosis (SSA). Cardiac TTR deposits can be found in 10 to 15% of the population over the age of 65 at autopsy (10,11). Many of these patients are asymptomatic, but there is little doubt that SSA is an underdiagnosed disease.
  2. In addition, a number of TTR mutations, including V122I, lead to amyloidogenesis and familial amyloid cardiomyopathy (FAC) (12–15). Population studies show that the V122I mutation is found in 3–4% of African Americans (~1.3 million people) and contributes to the increased prevalence of heart failure among this population segment (14,15).

The mutant TTR allele behaves as an autosomal dominant allele with age-dependent penetrance and

  • the frequency of cardiac amyloidosis from TTR in African-American individuals above age 60 is four times that seen in Caucasian-Americans of comparable age.
All of the TTR mutations associated with familial amyloidosis decrease tetramer stability, and
  • some decrease the kinetic barrier for tetramer dissociation (3, 16).
  • The latter is important because tetramer dissociation is the rate-limiting step in the TTR amyloidogenesis cascade (3).

Kinetic stabilization of the native, tetrameric structure of TTR by

  • interallelic trans suppression (incorporation of mutant subunits that raise the dissociative transition state energy) prevents
    1. post-secretory dissociation and aggregation, as well as the related disease 
    2. familial amyloid polyneuropathy (FAP), by slowing TTR tetramer dissociation (17).
Occupancy of the TTR T4 binding sites with rationally designed small molecules is known to stabilize the native tetrameric state of TTR over the dissociative transition state,
  • raising the kinetic barrier,
  • imposing kinetic stabilization on the tetramer and
  • preventing amyloidogenesis (3, 16, 18).
Previous studies have focused on rational ligand design and as a result
  • most of the TTR stabilizers reported to date are halogenated biaryl analogues of T4,
  • many resembling non-steroidal anti-inflammatory drugs (NSAIDs).
Some of these compounds, such as the NSAID diflunisal, which is currently tested in clinical trials in FAP patients for its efficacy to ameliorate
  • peripheral neuropathy resulting from TTR deposition, (19) have anti-inflammatory activity (20, 21).
The pharmacological effects of NSAIDs are due to inhibition of cyclo-oxygenase (COX) enzymes (22). Inhibition of COX-1 can produce side effects such as
  • gastrointestinal irritation, leading to ulcers and bleeding (23).
Inhibition of COX-2 has been associated with an
  • increased risk of severe cardiovascular events, including heart failure,
  • particularly in patients with preexisting cardiorenal dysfunction (20, 21, 24, 25).
Therefore, heart and kidney impairment are exclusion criteria for participation of patients in the diflunisal clinical trials to treat TTR-mediated FAP (19). Genomic variations can
  • increase the sensitivity of individuals to adverse side effects of NSAIDs.
Serum concentrations of NSAIDs depend on CYP2C9 and/or CYP2C8 activity. CYP2C9 polymorphism might play a significant role in the profile of adverse side effects of NSAID and alleles that affect the activity of CYP2C9 are found at different frequency in subjects of Caucasian, African or Asian descent (26, 27). Hence, the long-term therapy with drugs that have inhibitory effect on COX activity to prevent TTR aggregation is especially problematic in patients who suffer from TTR-mediated cardiomyopathy. The design and development of drugs to treat/prevent FAC or SSA thus presents the challenge
  1. not only to find compounds with a greater variety of chemical scaffolds that accomplish stabilization, but
  2. do so without the adverse side effects due to inhibition of COX activity.
 For these reasons, the development of a rapid and robust screen for compounds that bind to and stabilize TTR could be useful. To date, no high-throughput screening (HTS) methodology is available for the discovery of TTR ligands (28,29). Therefore, we developed a versatile
  • fluorescence polarization (FP) based HTS assay that can detect
  • binding of small molecules to the T4 binding pocket of TTR under physiological conditions.

RESULTS

Design and synthesis of the TTR FP probe

FP is used to study molecular interactions by monitoring changes in the apparent size of a fluorescently labeled molecule. Binding is measured by an increase in the FP signal, which is proportional to the decrease in the rate of tumbling of a fluorescent ligand upon association with macromolecules such as proteins (Fig. 1A). To synthesize a fluorescent TTR ligand 1, we initially started with the NSAID diflunisal analogue 2 (Fig. 1B) (30). The product of attaching a linker to 2, compound 3, had very low binding affinity to TTR (Kd1 >3290 nM, fig. S1A and fig. S1B).
The crystal structure of the diclofenac analog 4 showed that
  • the phenolic hydroxyl flanked by the two chlorine atoms is oriented out of the binding pocket into the solvent (31).
  • We reasoned that attaching a PEG amine linker to the phenol group of 4 would generate compound 5 which would bind to TTR (Fig. 1B and fig. S1C)

5 was coupled to fluorescein isothiocyanate (FITC) to produce the FITC-coupled TTR FP probe (1, Fig. 1B). The binding characteristics of the probe (Kd1 = 13 nM and Kd2 = 100 nM) were assessed with ITC (Fig. 2A).

Evaluation of the FP assay

The binding of 1 to TTR was evaluated to test its suitability for the FP assay with a standard saturation binding experiment. A fixed concentration of probe 1 (0.1 μM) was incubated with increasing concentrations of TTR (0.005 μM to 10 μM) and the formation of 1•TTR complex was quantified by the increase in FP signal (excitation λ 485 nm, emission λ 525 nm) relative to the concentration of TTR (Fig. 2B). The fluorescence polarization increased with the concentration of TTR until saturation was reached. A large dynamic range (70 – 330 mP) was measured for the assay. To validate the FP assay, we tested known TTR binders in a displacement assay (for detailed information see Supplemental Material). Compound 2 (Kapp = 231 nM, R2 = 0.997), Thyroxine (T4) (Kapp = 186 nM, R2 = 0.998) and diclofenac (Kapp = 4660 nM, R2 = 0.999) decreased the FP signal in a dose- dependent  manner  (Fig. 2C,  fig. S2B and S2C). The FP assay is a competitive displacement assay and therefore it provides apparent binding constants (Kapp). However, these apparent binding constants correlate well with the data obtained by ITC which measures direct interactions in solution and gives an actual (Kd) value.

  Adaptation of the FP assay for HTS

Next, we optimized the FP assay for HTS and screened a ~130,000 small molecule library for compounds that displaced probe 1 from the T4 binding sites of TTR. The FP assay was performed in 384-well plates with low concentrations of probe 1 (1.5 nM) and TTR (50 nM) in a 10  μL assay volume.  Detergent (0.01% Triton X-100) was added to the assay buffer to avoid false positive hits from aggregation of the small molecules. The assay demonstrated robust performance, with a, large dynamic range (~70–230 mP) and a Z′ factor (32, 33) in the range of 0.57–0.78 (fig. S3A and S3B).

Hits were defined as compounds, which resulted in at least 50% decrease in FP and demonstrated relative fluorescence between 70 and 130%. Many fluorescence quenchers and enhancers, which have less than 70% and greater than 130% total fluorescence relative to a control (compound without TTR), were excluded from the hit list. The excluded compounds have native fluorescence that is similar to fluorescein, which would interfere with the FP measurements and result in false positive hits. Two hundred compounds were designated as positive hits (0.167% hit rate). The top 33 compounds (compounds with lowest FP IC50) were assayed in a 10-point duplicate dose-response FP assay and displayed an IC50 (concentration that resulted in 50% decrease in the FP signal) between 0.277 and 10.957 μM (table S2).

Validation of the HTS hits

The top 33 compounds were retested with the FP assay (table S2) and with surface plasmon resonance (SPR) as another independent biophysical method. Solutions of the 33 hits were passed over immobilized, biotinylated TTR on a streptavidin coated chip. The binding of a small molecule to TTR on the sensor chip produces a SPR response signal (RU). The RU signal after addition of the top 33 compounds was measured and compared to a negative, solvent only, control. All compounds identified by the screen as hits were confirmed as TTR binders using SPR (fig. S4). We also found known TTR binders, such as NSAIDs (diclofenac, meclofenamic acid, and niflumic acid) and isoflavones (apigenin) in our screen (3, 34) (table S2). Among the best ligands (Fig. 2D) were the NSAID, niflumic acid, two catechol-O-methyl-tranferase (COMT) inhibitors, 3,5-dintrocatechol and Ro 41-0960 (35) and a number  of compounds   not previously known to bind to TTR. The chemical structures of these ligands were confirmed by 1H NMR and high-resolution mass spectrometry(HRMS) and the chemical purity was determined to be >95% (fig. S5).

Inhibition of TTR amyloidogenesis by the HTS hits

To test whether the new TTR ligands (7.2 μM) could function as kinetic stabilizers, we measured their ability to inhibit TTR (3.6 μM) amyloidogenesis at 72 hrs at pH 4.4 (fig. S6) (29). All 33 compounds inhibited TTR aggregation (<50% fibril formation, table S2). Of these, 23 were very good (<20% fibril formation) and 11 were excellent (<2% fibril formation) TTR kinetic stabilizers (Fig. 3A). All of the potent TTR stabilizers, except niflumic acid, and the two COMT inhibitors 3,5-dintrocatechol and Ro 41-0960, were chemical entities with no previously reported biological activity. Since occupancy of only
one T4 binding site within TTR is sufficient for kinetic stabilization of the tetramer (3), we tested the most potent ligands at substoichiometric concentrations (2.4 fold molar excess of TTR relative to ligand) in a kinetic aggregation assay monitored over 5 days (Fig. 3B). Under these conditions ligands 7, 14, 15 and Ro 41-0960 dramatically slowed fibril formation and outperformed the known TTR stabilizer, diclofenac, which blocked only ~55% of TTR aggregation.

Evaluating the TTR ligands for COX-1 enzymatic inhibition and binding to thyroid hormone receptor

A successful clinical candidate against TTR amyloid cardiomyopathy should have minimal off-target toxicity due to the potential need for life-long use of these drugs. Specifically, the TTR ligands should exhibit minimal binding to COX and the nuclear thyroid hormone receptor (THR). Inhibition of COX is contraindicated for treating FAC patients, since COX inhibition can not only lead to renal dysfunction and blood pressure elevation, but may precipitate heart failure in vulnerable individuals (20, 21, 24, 25). Therefore, the most potent TTR ligands were evaluated for their ability to inhibit COX-1 activity, as well as, for binding to THR, in comparison with the NSAID niflumic acid. Although niflumic acid exhibited substantial (94%) COX-1 inhibition, three of the 12 new compounds evaluated (7, 6 and 10) displayed less than 1% inhibition of COX-1. Only one ligand (compound 8) showed significant (58%) and two compounds (6 and 10) minor (5%) binding to THR (Fig. 3C).

Characterization of the binding energetics to TTR

Many reported TTR ligands, including T4, bind TTR with negative cooperativity, which appears to arise from subtle conformational changes in TTR upon ligand binding to the first T4 site (3, 16, 36). We used ITC to determine the binding constants and to evaluate cooperativity between the two TTR T4 sites (Fig. 2A, Fig. 4A, Fig. 4B and fig. S1 and fig. S7). The ITC data for compounds 1, 7, 14, and Ro 41-0906 binding to TTR were fit to a two-site binding model and show that these potent ligands bind TTR with low nanomolar affinity. The dissociation constants for these ligands indicated that they bound TTR with negative cooperativity (table S3). Analysis of the free energies associated with ligand binding to TTR indicates that binding was driven both by burial of the hydrophobic ligand in the TTR binding site (which leads to the favorable binding entropies) and specific ligand-TTR interactions (which leads to the favorable binding enthalpies) (Fig. 2A, Fig. 4A, Fig.4B, and fig. S7B) (37). The binding of compounds 7 (Kd1 = 58 nM and Kd2 = 500 nM) and 14 (Kd1 = 26 nM and Kd2 = 1800 nM) to TTR did not cause major conformational changes to the TTR tetramer structure (Fig. 5).
Remainder of document is found at publication site, including Figures.

Read Full Post »