GWAS as a Driver of Gene Discovery in Cardiometabolic Diseases

Trends in Endocrinology and Metabolism

Volumn 26, Issue 12, 2015, Pages 722-732

  Atanasovska, Biljana ^a   Kumar, Vinod ^a   Fu, Jingyuan ^a   Wijmenga, Cisca ^a   Hofker, Marten H ^a  

^a UNIVERSITY MEDICAL CENTER GRONINGEN   (Netherlands)

Author keywords

Cardiovascular disease; Complex disease; Expression QTL; Gene prioritization; SNPs

Indexed keywords

CARDIOMETABOLIC DISEASE; CARDIOVASCULAR DISEASE; GENE EXPRESSION; GENE IDENTIFICATION; GENE MAPPING; GENETIC ASSOCIATION; GENETIC PREDISPOSITION; HUMAN; METABOLIC DISORDER; NONHUMAN; PRIORITY JOURNAL; QUANTITATIVE TRAIT LOCUS; REVIEW; SINGLE NUCLEOTIDE POLYMORPHISM; GENETIC VARIATION; GENETICS; GENOME-WIDE ASSOCIATION STUDY;

CARDIOVASCULAR DISEASES; GENETIC VARIATION; GENOME-WIDE ASSOCIATION STUDY; HUMANS; METABOLIC DISEASES;

EID: 84949627443     PISSN: 10432760     EISSN: 18793061     Source Type: Journal    
DOI: 10.1016/j.tem.2015.10.004     Document Type: Review

References (67)

1. Crosby J., et al. Loss-of-function mutations in APOC3, triglycerides, and coronary disease. N. Engl. J. Med. 2014, 371:22-31.
2. Abifadel M., et al. Mutations in PCSK9 cause autosomal dominant hypercholesterolemia. Nat. Genet. 2003, 34:154-156.
3. Alonso R., et al. Lipoprotein(a) levels in familial hypercholesterolemia: An important predictor of cardiovascular disease independent of the type of LDL receptor mutation. J. Am. Coll. Cardiol. 2014, 63:1982-1989.
4. Sadananda S.N., et al. Targeted next-generation sequencing to diagnose disorders of HDL cholesterol. J. Lipid Res. 2015, 56:1992-2001.
5. Kuivenhoven J.A., Hegele R.a. Mining the genome for lipid genes. Biochim. Biophys. Acta 2014, 1842:1993-2009.
6. Kraft P., et al. Replication in genome-wide association studies. Stat. Sci. 2009, 24:561-573.
7. Tanaka T. The International HapMap Project. Nature 2003, 426:789-796.
8. Arking D.E., Chakravarti A. Understanding cardiovascular disease through the lens of genome-wide association studies. Trends Genet. 2009, 25:387-394.
9. Burton P.R., et al. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 2007, 447:661-678.
10. Teslovich T.M., et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 2010, 466:707-713.
11. Boj S.F., et al. Diabetes risk gene and wnt effector Tcf7l2/TCF4 controls hepatic response to perinatal and adult metabolic demand. Cell 2012, 151:1595-1607.
12. Locke A.E., et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 2015, 518:197-206.
13. Shungin D., et al. New genetic loci link adipose and insulin biology to body fat distribution. Nature 2015, 518:187-196.
14. Willer C.J., et al. Discovery and refinement of loci associated with lipid levels. Nat. Genet. 2013, 45:1274-1283.
15. Mahajan A., et al. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat. Genet. 2014, 46:234-244.
16. The Cardi.D.C., et al. Large-scale association analysis identifies new risk loci for coronary artery disease. Nat. Genet. 2012, 45:25-33.
17. Voight B.F., et al. The metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits. PLoS Genet. 2012, 8:1-12.
18. Jansen H., et al. Genetic variants primarily associated with type 2 diabetes are related to coronary artery disease risk. Atherosclerosis 2015, 241:419-426.
19. Li N., et al. Pleiotropic effects of lipid genes on plasma glucose, HbA1c and HOMA-IR levels. Diabetes 2014, 63:1-47.
20. Rankinen T., et al. Are there genetic paths common to obesity, cardiovascular disease outcomes, and cardiovascular risk factors?. Circ. Res. 2015, 116:909-922.
21. Hannou S.A., et al. Functional genomics of the CDKN2A/B locus in cardiovascular and metabolic disease: what have we learned from GWASs?. Trends Endocrinol. Metab. 2015, 26:176-184.
22. Nagano T., et al. Single-cell Hi-C reveals cell-to-cell variability in chromosome structure. Nature 2013, 502:59-64.
23. Oram J.F. Tangier disease and ABCA1. Biochim. Biophys. Acta 2000, 1529:321-330.
24. Service S.K., et al. Re-sequencing expands our understanding of the phenotypic impact of variants at GWAS loci. PLoS Genet. 2014, 10:e1004147.
25. Hunt K., a, et al. Negligible impact of rare autoimmune-locus coding-region variants on missing heritability. Nature 2013, 498:232-235.
26. Do R., et al. Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction. Nature 2015, 518:102-106.
27. Stitziel N.O., et al. Exome sequencing in suspected monogenic dyslipidemias. Circ. Cardiovasc. Genet. 2015, 8:343-350.
28. Maurano M.T., et al. Systematic localization of common disease-associated variation in regulatory DNA. Science 2012, 337:1190-1195.
29. Fehrmann R.S.N., 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. PLoS Genet. 2011, 7:e1002197.
30. Kumar V., et al. Genetics of immune-mediated disorders: from genome-wide association to molecular mechanism. Curr. Opin. Immunol. 2014, 31:51-57.
31. Musunuru K., et al. From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus. Nature 2010, 466:714-719.
32. Westra H-J., et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat. Genet. 2013, 45:1238-1243.
33. Fu J., et al. Unraveling the regulatory mechanisms underlying tissue-dependent genetic variation of gene expression. PLoS Genet. 2012, 8:e1002431.
34. Raj T., et al. Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes. Science 2014, 344:519-523.
35. Jimmie C., et al. Intersection of population variation and autoimmunity genetics in human T cell activation. Science 2014, 345:1254665.
36. Rate W.R., et al. Palliative radiotherapy for metastatic malignant melanoma: brain metastases, bone metastases, and spinal cord compression. Int. J. Radiat. Oncol. Biol. Phys. 1988, 15:859-864.
37. GTEx Consortium The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 2015, 348:648-660.
38. Smemo S., et al. Obesity-associated variants within FTO form long-range functional connections with IRX3. Nature 2014, 507:371-375.
39. Zabaneh D., Balding D.J. A genome-wide association study of the metabolic syndrome in Indian Asian men. PLoS ONE 2010, 5:538-543.
40. Shin S-Y., et al. An atlas of genetic influences on human blood metabolites. Nat. Genet. 2014, 46:543-550.
41. Dupuis J., et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat. Genet. 2010, 42:105-116.
42. Den Hoed M., et al. Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders. Nat. Genet. 2013, 45:621-631.
43. Yao C., et al. Integromic analysis of genetic variation and gene expression identifies networks for cardiovascular disease phenotypes. Circulation 2015, 131:536-549.
44. Harrow J., et al. GENCODE: The reference human genome annotation for the ENCODE project. Genome Res. 2012, 22:1760-1774.
45. Liu Y., et al. Tissue-specific RNA-Seq in human evoked inflammation identifies blood and adipose LincRNA signatures of cardiometabolic diseases. Arterioscler. Thromb. Vasc. Biol. 2014, 34:902-912.
46. Douvris A., et al. Functional analysis of the TRIB1 associated locus linked to plasma triglycerides and coronary artery disease. J. Am. Heart Assoc. 2014, 3:e000884.
47. Kumar V., et al. Human disease-associated genetic variation impacts large intergenic non-coding RNA expression. PLoS Genet. 2013, 9:1296-1300.
48. Sun W., Hu Y. eQTL mapping using RNA-seq data. Stat. Biosci. 2013, 5:198-219.
49. Deelen P., et al. Calling genotypes from public RNA-sequencing data enables identification of genetic variants that affect gene-expression levels. Genome Med. 2015, 7:30.
50. Zhang X., et al. Identification of common genetic variants controlling transcript isoform variation in human whole blood. Nat. Genet. 2015, 47:345-352.
51. Lacolley P., et al. The vascular smooth muscle cell in arterial pathology: A cell that can take on multiple roles. Cardiovasc. Res. 2012, 95:194-204.
52. Moreau Y., Tranchevent L-C. Computational tools for prioritizing candidate genes: boosting disease gene discovery. Nat. Rev. Genet. 2012, 13:523-536.
53. Raychaudhuri S., et al. Identifying relationships among genomic disease regions: Predicting genes at pathogenic SNP associations and rare deletions. PLoS Genet. 2009, 5:419-431.
54. Leiserson M.D.M., et al. Network analysis of GWAS data. Curr. Opin. Genet. Dev. 2013, 23:602-610.
55. Kumar V., et al. Systematic annotation of celiac disease loci refines pathological pathways and suggests a genetic explanation for increased interferon-gamma levels. Hum. Mol. Genet. 2014, 61:1-13.
56. Pers T.H., et al. Biological interpretation of genome-wide association studies using predicted gene functions. Nat. Commun. 2015, 6:5890.
57. Voight B.F., et al. Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study. Lancet 2012, 380:572-580.
58. Nelson C.P., et al. Genetically determined height and coronary artery disease. N. Engl. J. Med. 2015, 372:1608-1618.
59. Myocardial Infarction Genetics Consortium Investigators, et al. Inactivating mutations in NPC1L1 and protection from coronary heart disease. N. Engl. J. Med. 2014, 371:2072-2082.
60. Claussnitzer M., et al. FTO obesity variant circuitry and adipocyte browning in humans. N. Engl. J. Med. 2015, 7:508-519.
61. Ghosh S., et al. Systems genetics analysis of genome-wide association study reveals novel associations between key biological processes and coronary artery disease. Arterioscler. Thromb. Vasc. Biol. 2015, 35:1712-1722.
62. Shalem O., et al. High-throughput functional genomics using CRISPR-Cas9. Nat. Rev. Genet. 2015, 509:487-491.
63. Bhatia S.N., Ingber D.E. Microfluidic organs-on-chips. Nat. Biotechnol. 2014, 32:760-772.
64. Schaub M.A., et al. Linking disease associations with regulatory information in the human genome. Genome Res. 2012, 22:1748-1759.
65. Altshuler D.M., et al. An integrated map of genetic variation from 1,092 human genomes. Nature 2012, 491:56-65.
66. Francioli L.C., et al. Whole-genome sequence variation, population structure and demographic history of the Dutch population. Nat. Genet. 2014, 46:818-825.
67. Deelen P., et al. Improved imputation quality of low-frequency and rare variants in European samples using the 'Genome of The Netherlands'. Eur. J. Hum. Genet. 2014, 22:1321-1326.