GWAS as a Driver of Gene Discovery in Cardiometabolic Diseases

Cardiometabolic diseases represent a common complex disorder with a strong genetic component. Currently, genome-wide association studies (GWAS) have yielded some 755 single-nucleotide polymorphisms (SNPs) encompassing 366 independent loci that may help to decipher the molecular basis of cardiometabolic diseases. Going from a disease SNP to the underlying disease mechanisms is a huge challenge because the associated SNPs rarely disrupt protein function. Many disease SNPs are located in noncoding regions, and therefore attention is now focused on linking genetic SNP variation to effects on gene expression levels. By integrating genetic information with large-scale gene expression data, and with data from epigenetic roadmaps revealing gene regulatory regions, we expect to be able to identify candidate disease genes and the regulatory potential of disease SNPs.

[1]  Manolis Kellis,et al.  FTO Obesity Variant Circuitry and Adipocyte Browning in Humans. , 2015, The New England journal of medicine.

[2]  Christian Gieger,et al.  New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk , 2010, Nature Genetics.

[3]  D. Balding,et al.  A Genome-Wide Association Study of the Metabolic Syndrome in Indian Asian Men , 2010, PloS one.

[4]  Peter Kraft,et al.  Replication in genome-wide association studies. , 2009, Statistical science : a review journal of the Institute of Mathematical Statistics.

[5]  J. Weissenbach,et al.  Mutations in PCSK9 cause autosomal dominant hypercholesterolemia , 2003, Nature Genetics.

[6]  Daphne Koller,et al.  Polarization of the Effects of Autoimmune and Neurodegenerative Risk Alleles in Leukocytes , 2014, Science.

[7]  R. Hegele,et al.  Mining the genome for lipid genes. , 2014, Biochimica et biophysica acta.

[8]  Y. Moreau,et al.  Computational tools for prioritizing candidate genes: boosting disease gene discovery , 2012, Nature Reviews Genetics.

[9]  He Zhang,et al.  Loss-of-function mutations in APOC3, triglycerides, and coronary disease. , 2014, The New England journal of medicine.

[10]  Jingyuan Fu,et al.  Human Disease-Associated Genetic Variation Impacts Large Intergenic Non-Coding RNA Expression , 2013, PLoS genetics.

[11]  Jingyuan Fu,et al.  Calling genotypes from public RNA-sequencing data enables identification of genetic variants that affect gene-expression levels , 2014, Genome Medicine.

[12]  Tanya M. Teslovich,et al.  Discovery and refinement of loci associated with lipid levels , 2013, Nature Genetics.

[13]  C. Gieger,et al.  Genetic variants primarily associated with type 2 diabetes are related to coronary artery disease risk. , 2015, Atherosclerosis.

[14]  G. Francis,et al.  Targeted next-generation sequencing to diagnose disorders of HDL cholesterol[S] , 2015, Journal of Lipid Research.

[15]  L. Wilkins.  Functional Analysis of the TRIB1 Associated Locus Linked to Plasma Triglycerides and Coronary Artery Disease , 2016, Journal of the American Heart Association.

[16]  J. Danesh,et al.  Large-scale association analysis identifies new risk loci for coronary artery disease , 2013 .

[17]  John Spertus,et al.  Inactivating mutations in NPC1L1 and protection from coronary heart disease. , 2014, The New England journal of medicine.

[18]  John Spertus,et al.  Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study , 2012, The Lancet.

[19]  R. Xavier,et al.  Genetics of immune-mediated disorders: from genome-wide association to molecular mechanism. , 2014, Current opinion in immunology.

[20]  J. Danesh,et al.  Genetically determined height and coronary artery disease. , 2015, The New England journal of medicine.

[21]  Tamara S. Roman,et al.  New genetic loci link adipose and insulin biology to body fat distribution , 2014, Nature.

[22]  Tanya M. Teslovich,et al.  Re-sequencing Expands Our Understanding of the Phenotypic Impact of Variants at GWAS Loci , 2014, PLoS genetics.

[23]  D. MacArthur,et al.  Negligible impact of rare autoimmune-locus coding-region variants on missing heritability , 2013, Nature.

[24]  Pieter B. T. Neerincx,et al.  Supplementary Information Whole-genome sequence variation , population structure and demographic history of the Dutch population , 2022 .

[25]  Mingyao Li,et al.  Tissue-Specific RNA-Seq in Human Evoked Inflammation Identifies Blood and Adipose LincRNA Signatures of Cardiometabolic Diseases , 2014, Arteriosclerosis, thrombosis, and vascular biology.

[26]  H. Lähdesmäki,et al.  Systematic annotation of celiac disease loci refines pathological pathways and suggests a genetic explanation for increased interferon-gamma levels. , 2015, Human molecular genetics.

[27]  D. Ingber,et al.  Microfluidic organs-on-chips , 2014, Nature Biotechnology.

[28]  Tanya M. Teslovich,et al.  Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility , 2014, Nature Genetics.

[29]  A. Chakravarti,et al.  Understanding cardiovascular disease through the lens of genome-wide association studies. , 2009, Trends in genetics : TIG.

[30]  Heorhiy Byelas,et al.  Improved imputation quality of low-frequency and rare variants in European samples using the ‘Genome of The Netherlands' , 2014, European Journal of Human Genetics.

[31]  Chun Jimmie Ye,et al.  Intersection of population variation and autoimmunity genetics in human T cell activation , 2014, Science.

[32]  Toshihiro Tanaka.  The International HapMap Project , 2003, Nature.

[33]  Tanya M. Teslovich,et al.  Biological, Clinical, and Population Relevance of 95 Loci for Blood Lipids , 2010, Nature.

[34]  Claude Bouchard,et al.  Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders , 2014 .

[35]  Benjamin J. Raphael,et al.  Network analysis of GWAS data. , 2013, Current opinion in genetics & development.

[36]  J. Ordovás,et al.  Lipoprotein(a) levels in familial hypercholesterolemia: an important predictor of cardiovascular disease independent of the type of LDL receptor mutation. , 2014, Journal of the American College of Cardiology.

[37]  A. Tanay,et al.  Single cell Hi-C reveals cell-to-cell variability in chromosome structure , 2013, Nature.

[38]  P. Chambon,et al.  Diabetes Risk Gene and Wnt Effector Tcf7l2/TCF4 Controls Hepatic Response to Perinatal and Adult Metabolic Demand , 2012, Cell.

[39]  Jun S. Liu,et al.  The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans , 2015, Science.

[40]  S. Batzoglou,et al.  Linking disease associations with regulatory information in the human genome , 2012, Genome research.

[41]  J. Oram.  Tangier disease and ABCA1. , 2000, Biochimica et biophysica acta.

[42]  Laura J. Scott,et al.  Stratifying Type 2 Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean Compared to Obese Cases , 2012, PLoS genetics.

[43]  J. Hirschhorn,et al.  Biological interpretation of genome-wide association studies using predicted gene functions , 2015, Nature Communications.

[44]  Rahul C. Deo,et al.  Exome Sequencing in Suspected Monogenic Dyslipidemias , 2015, Circulation. Cardiovascular genetics.

[45]  Bronwen L. Aken,et al.  GENCODE: The reference human genome annotation for The ENCODE Project , 2012, Genome research.

[46]  Shane J. Neph,et al.  Systematic Localization of Common Disease-Associated Variation in Regulatory DNA , 2012, Science.

[47]  Olle Melander,et al.  From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus , 2010, Nature.

[48]  Neville E. Sanjana,et al.  High-throughput functional genomics using CRISPR–Cas9 , 2015, Nature Reviews Genetics.

[49]  R. Ophoff,et al.  Unraveling the Regulatory Mechanisms Underlying Tissue-Dependent Genetic Variation of Gene Expression , 2012, PLoS genetics.

[50]  M. Peters,et al.  Systematic identification of trans eQTLs as putative drivers of known disease associations , 2013, Nature Genetics.

[51]  Ying Wang,et al.  Genomewide association study of leprosy. , 2009, The New England journal of medicine.

[52]  Jean-Baptiste Michel,et al.  The vascular smooth muscle cell in arterial pathology: a cell that can take on multiple roles. , 2012, Cardiovascular research.

[53]  Simon C. Potter,et al.  Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls , 2007, Nature.

[54]  Jingyuan Fu,et al.  Pleiotropic Effects of Lipid Genes on Plasma Glucose, HbA1c, and HOMA-IR Levels , 2014, Diabetes.

[55]  N. Cox,et al.  Obesity-associated variants within FTO form long-range functional connections with IRX3 , 2014, Nature.

[56]  Roby Joehanes,et al.  Identification of common genetic variants controlling transcript isoform variation in human whole blood , 2015, Nature Genetics.

[57]  Kenny Q. Ye,et al.  An integrated map of genetic variation from 1,092 human genomes , 2012, Nature.

[58]  Tanya M. Teslovich,et al.  The Metabochip, a Custom Genotyping Array for Genetic Studies of Metabolic, Cardiovascular, and Anthropometric Traits , 2012, PLoS genetics.

[59]  John P. Overington,et al.  An atlas of genetic influences on human blood metabolites , 2014, Nature Genetics.

[60]  C. Bouchard,et al.  Are there genetic paths common to obesity, cardiovascular disease outcomes, and cardiovascular risk factors? , 2015, Circulation research.

[61]  David M. Herrington,et al.  Multiple rare alleles at LDLR and APOA5 confer risk for early-onset myocardial infarction , 2014, Nature.

[62]  B. Staels,et al.  Functional genomics of the CDKN2A/B locus in cardiovascular and metabolic disease: what have we learned from GWASs? , 2015, Trends in Endocrinology & Metabolism.

[63]  Ayellet V. Segrè,et al.  Analysis of Genome-Wide Association Study Reveals Novel Associations Between Key Biological Processes and Coronary Artery Disease , 2015 .

[64]  Wei Sun,et al.  eQTL Mapping Using RNA-seq Data , 2012, Statistics in Biosciences.

[65]  Oznur Tastan,et al.  Integromic Analysis of Genetic Variation and Gene Expression Identifies Networks for Cardiovascular Disease Phenotypes , 2015, Circulation.

[66]  M. Daly,et al.  Identifying Relationships among Genomic Disease Regions: Predicting Genes at Pathogenic SNP Associations and Rare Deletions , 2009, PLoS genetics.

[67]  Inactivating Mutations in NPC 1 L 1 and Protection from Coronary Heart Disease , 2014 .

[68]  Jingyuan Fu,et al.  Trans-eQTLs Reveal That Independent Genetic Variants Associated with a Complex Phenotype Converge on Intermediate Genes, with a Major Role for the HLA , 2011, PLoS genetics.

[69]  Ross M. Fraser,et al.  Genetic studies of body mass index yield new insights for obesity biology , 2015, Nature.

[70]  L. Solin,et al.  Palliative radiotherapy for metastatic malignant melanoma: brain metastases, bone metastases, and spinal cord compression. , 1988, International journal of radiation oncology, biology, physics.