Adiponectin GWAS loci harboring extensive allelic heterogeneity exhibit distinct molecular consequences
Autoři:
Cassandra N. Spracklen aff001; Apoorva K. Iyengar aff001; Swarooparani Vadlamudi aff001; Chelsea K. Raulerson aff001; Anne U. Jackson aff003; Sarah M. Brotman aff001; Ying Wu aff001; Maren E. Cannon aff001; James P. Davis aff001; Aaron T. Crain aff001; Kevin W. Currin aff001; Hannah J. Perrin aff001; Narisu Narisu aff004; Heather M. Stringham aff003; Christian Fuchsberger aff003; Adam E. Locke aff003; Ryan P. Welch aff003; Johanna K. Kuusisto aff007; Päivi Pajukanta aff008; Laura J. Scott aff003; Yun Li aff001; Francis S. Collins aff004; Michael Boehnke aff003; Markku Laakso aff007; Karen L. Mohlke aff001
Působiště autorů:
Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
aff001; Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, Massachusetts, United States of America
aff002; Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
aff003; National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
aff004; Center for Biomedicine, European Academy of Bolzano/Bozen, University of Lübeck, Bolzano/Bozen, Italy
aff005; McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri, United States of America
aff006; Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
aff007; Department of Human Genetics, University of California, Los Angeles, California, United States of America
aff008; Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
aff009
Vyšlo v časopise:
Adiponectin GWAS loci harboring extensive allelic heterogeneity exhibit distinct molecular consequences. PLoS Genet 16(9): e1009019. doi:10.1371/journal.pgen.1009019
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1009019
Souhrn
Loci identified in genome-wide association studies (GWAS) can include multiple distinct association signals. We sought to identify the molecular basis of multiple association signals for adiponectin, a hormone involved in glucose regulation secreted almost exclusively from adipose tissue, identified in the Metabolic Syndrome in Men (METSIM) study. With GWAS data for 9,262 men, four loci were significantly associated with adiponectin: ADIPOQ, CDH13, IRS1, and PBRM1. We performed stepwise conditional analyses to identify distinct association signals, a subset of which are also nearly independent (lead variant pairwise r2<0.01). Two loci exhibited allelic heterogeneity, ADIPOQ and CDH13. Of seven association signals at the ADIPOQ locus, two signals colocalized with adipose tissue expression quantitative trait loci (eQTLs) for three transcripts: trait-increasing alleles at one signal were associated with increased ADIPOQ and LINC02043, while trait-increasing alleles at the other signal were associated with decreased ADIPOQ-AS1. In reporter assays, adiponectin-increasing alleles at two signals showed corresponding directions of effect on transcriptional activity. Putative mechanisms for the seven ADIPOQ signals include a missense variant (ADIPOQ G90S), a splice variant, a promoter variant, and four enhancer variants. Of two association signals at the CDH13 locus, the first signal consisted of promoter variants, including the lead adipose tissue eQTL variant for CDH13, while a second signal included a distal intron 1 enhancer variant that showed ~2-fold allelic differences in transcriptional reporter activity. Fine-mapping and experimental validation demonstrated that multiple, distinct association signals at these loci can influence multiple transcripts through multiple molecular mechanisms.
Klíčová slova:
Adiponectin – Alleles – DNA transcription – Genetic loci – Genome-wide association studies – Genomic signal processing – Haplotypes – Introns
Zdroje
1. MacArthur J, Bowler E, Cerezo M, Gil L, Hall P, Hastings E, et al. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). Nucleic acids research. 2017;45(D1):D896–d901. Epub 2016/12/03. doi: 10.1093/nar/gkw1133 27899670.
2. Visscher PM, Wray NR, Zhang Q, Sklar P, McCarthy MI, Brown MA, et al. 10 Years of GWAS Discovery: Biology, Function, and Translation. American journal of human genetics. 2017;101(1):5–22. Epub 2017/07/08. doi: 10.1016/j.ajhg.2017.06.005 28686856.
3. Gallagher MD, Chen-Plotkin AS. The Post-GWAS Era: From Association to Function. American journal of human genetics. 2018;102(5):717–30. Epub 2018/05/05. doi: 10.1016/j.ajhg.2018.04.002 29727686.
4. Cannon ME, Mohlke KL. Deciphering the Emerging Complexities of Molecular Mechanisms at GWAS Loci. American journal of human genetics. 2018;103(5):637–53. Epub 2018/11/06. doi: 10.1016/j.ajhg.2018.10.001 30388398.
5. Wood AR, Hernandez DG, Nalls MA, Yaghootkar H, Gibbs JR, Harries LW, et al. Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association. Human molecular genetics. 2011;20(20):4082–92. Epub 2011/07/30. doi: 10.1093/hmg/ddr328 21798870.
6. Castel SE, Cervera A, Mohammadi P, Aguet F, Reverter F, Wolman A, et al. Modified penetrance of coding variants by cis-regulatory variation contributes to disease risk. Nature genetics. 2018;50(9):1327–34. Epub 2018/08/22. doi: 10.1038/s41588-018-0192-y 30127527.
7. Mahajan A, Taliun D, Thurner M, Robertson NR, Torres JM, Rayner NW, et al. Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps. Nature genetics. 2018;50(11):1505–13. Epub 2018/10/10. doi: 10.1038/s41588-018-0241-6 30297969.
8. Rivas MA, Beaudoin M, Gardet A, Stevens C, Sharma Y, Zhang CK, et al. Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease. Nature genetics. 2011;43(11):1066–73. Epub 2011/10/11. doi: 10.1038/ng.952 21983784.
9. Hugot JP, Chamaillard M, Zouali H, Lesage S, Cezard JP, Belaiche J, et al. Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn’s disease. Nature. 2001;411(6837):599–603. Epub 2001/06/01. doi: 10.1038/35079107 11385576.
10. Nejentsev S, Walker N, Riches D, Egholm M, Todd JA. Rare variants of IFIH1, a gene implicated in antiviral responses, protect against type 1 diabetes. Science (New York, NY). 2009;324(5925):387–9. Epub 2009/03/07. doi: 10.1126/science.1167728 19264985.
11. Chatterjee S, Kapoor A, Akiyama JA, Auer DR, Lee D, Gabriel S, et al. Enhancer Variants Synergistically Drive Dysfunction of a Gene Regulatory Network In Hirschsprung Disease. Cell. 2016;167(2):355–68.e10. Epub 2016/10/04. doi: 10.1016/j.cell.2016.09.005 27693352.
12. Roman TS, Marvelle AF, Fogarty MP, Vadlamudi S, Gonzalez AJ, Buchkovich ML, et al. Multiple Hepatic Regulatory Variants at the GALNT2 GWAS Locus Associated with High-Density Lipoprotein Cholesterol. American journal of human genetics. 2015;97(6):801–15. Epub 2015/12/08. doi: 10.1016/j.ajhg.2015.10.016 26637976.
13. Spracklen CN, Horikoshi M, Kim YJ, Lin K, Bragg F, Moon S, et al. Identification of type 2 diabetes loci in 433,540 East Asian individuals. Nature. 2020;582(7811):240–5. Epub 2020/06/06. doi: 10.1038/s41586-020-2263-3 32499647.
14. Willer CJ, Sanna S, Jackson AU, Scuteri A, Bonnycastle LL, Clarke R, et al. Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nature genetics. 2008;40(2):161–9. Epub 2008/01/15. doi: 10.1038/ng.76 18193043.
15. Bojesen SE, Pooley KA, Johnatty SE, Beesley J, Michailidou K, Tyrer JP, et al. Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer. Nature genetics. 2013;45(4):371–84, 84e1–2. Epub 2013/03/29. doi: 10.1038/ng.2566 23535731.
16. Dunning AM, Michailidou K, Kuchenbaecker KB, Thompson D, French JD, Beesley J, et al. Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170. Nature genetics. 2016;48(4):374–86. Epub 2016/03/02. doi: 10.1038/ng.3521 26928228.
17. Woodward L, Akoumianakis I, Antoniades C. Unravelling the adiponectin paradox: novel roles of adiponectin in the regulation of cardiovascular disease. British journal of pharmacology. 2017;174(22):4007–20. Epub 2016/10/21. doi: 10.1111/bph.13619 27629236.
18. Laakso M, Kuusisto J, Stancakova A, Kuulasmaa T, Pajukanta P, Lusis AJ, et al. METabolic Syndrome In Men (METSIM) Study: a resource for studies of metabolic and cardiovascular diseases. Journal of lipid research. 2017. Epub 2017/01/26. doi: 10.1194/jlr.O072629
19. Ghaben AL, Scherer PE. Adipogenesis and metabolic health. Nature reviews Molecular cell biology. 2019;20(4):242–58. Epub 2019/01/06. doi: 10.1038/s41580-018-0093-z 30610207.
20. Dastani Z, Hivert MF, Timpson N, Perry JR, Yuan X, Scott RA, et al. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals. PLoS genetics. 2012;8(3):e1002607. Epub 2012/04/06. doi: 10.1371/journal.pgen.1002607
21. Jungtrakoon P, Plengvidhya N, Tangjittipokin W, Chimnaronk S, Salaemae W, Chongjaroen N, et al. Novel adiponectin variants identified in type 2 diabetic patients reveal multimerization and secretion defects. PloS one. 2011;6(10):e26792. Epub 2011/11/03. doi: 10.1371/journal.pone.0026792 22046359.
22. Lee BP, Lloyd-Laney HO, Locke JM, McCulloch LJ, Knight B, Yaghootkar H, et al. Functional characterisation of ADIPOQ variants using individuals recruited by genotype. Molecular and cellular endocrinology. 2016;428:49–57. Epub 2016/03/22. doi: 10.1016/j.mce.2016.03.020 26996131.
23. Raulerson CK, Ko A, Kidd JC, Currin KW, Brotman SM, Cannon ME, et al. Adipose Tissue Gene Expression Associations Reveal Hundreds of Candidate Genes for Cardiometabolic Traits. American journal of human genetics. 2019;105(4):773–87. Epub 2019/10/01.
24. Cai R, Sun Y, Qimuge N, Wang G, Wang Y, Chu G, et al. Adiponectin AS lncRNA inhibits adipogenesis by transferring from nucleus to cytoplasm and attenuating Adiponectin mRNA translation. Biochimica et biophysica acta Molecular and cell biology of lipids. 2018;1863(4):420–32. Epub 2018/02/08. doi: 10.1016/j.bbalip.2018.01.005 29414510.
25. Gamazon ER, Segre AV, van de Bunt M, Wen X, Xi HS, Hormozdiari F, et al. Using an atlas of gene regulation across 44 human tissues to inform complex disease- and trait-associated variation. Nature genetics. 2018;50(7):956–67. Epub 2018/06/30. doi: 10.1038/s41588-018-0154-4 29955180.
26. Hug C, Wang J, Ahmad NS, Bogan JS, Tsao TS, Lodish HF. T-cadherin is a receptor for hexameric and high-molecular-weight forms of Acrp30/adiponectin. Proceedings of the National Academy of Sciences of the United States of America. 2004;101(28):10308–13. Epub 2004/06/24. doi: 10.1073/pnas.0403382101 15210937.
27. Matsuda K, Fujishima Y, Maeda N, Mori T, Hirata A, Sekimoto R, et al. Positive feedback regulation between adiponectin and T-cadherin impacts adiponectin levels in tissue and plasma of male mice. Endocrinology. 2015;156(3):934–46. Epub 2014/12/17. doi: 10.1210/en.2014-1618 25514086.
28. Goddeke S, Knebel B, Fahlbusch P, Horbelt T, Poschmann G, van de Velde F, et al. CDH13 abundance interferes with adipocyte differentiation and is a novel biomarker for adipose tissue health. International journal of obesity (2005). 2018;42(5):1039–50. Epub 2018/02/23. doi: 10.1038/s41366-018-0022-4 29467502.
29. Hormozdiari F, Zhu A, Kichaev G, Ju CJ, Segrè AV, Joo JWJ, et al. Widespread Allelic Heterogeneity in Complex Traits. American journal of human genetics. 2017;100(5):789–802. Epub 2017/05/06. doi: 10.1016/j.ajhg.2017.04.005 28475861.
30. Peterson RE, Kuchenbaecker K, Walters RK, Chen CY, Popejoy AB, Periyasamy S, et al. Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations. Cell. 2019;179(3):589–603. Epub 2019/10/15. doi: 10.1016/j.cell.2019.08.051 31607513.
31. Valdar W, Sabourin J, Nobel A, Holmes CC. Reprioritizing genetic associations in hit regions using LASSO-based resample model averaging. Genetic epidemiology. 2012;36(5):451–62. Epub 2012/05/03. doi: 10.1002/gepi.21639 22549815.
32. Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. American journal of human genetics. 2011;88(1):76–82. Epub 2010/12/21. doi: 10.1016/j.ajhg.2010.11.011
33. Wang X, Bao W, Liu J, Ouyang YY, Wang D, Rong S, et al. Inflammatory markers and risk of type 2 diabetes: a systematic review and meta-analysis. Diabetes care. 2013;36(1):166–75. Epub 2012/12/25. doi: 10.2337/dc12-0702 23264288.
34. Achari AE, Jain SK. Adiponectin, a Therapeutic Target for Obesity, Diabetes, and Endothelial Dysfunction. Int J Mol Sci. 2017;18(6). Epub 2017/06/22. doi: 10.3390/ijms18061321 28635626.
35. Jee SH, Sull JW, Lee JE, Shin C, Park J, Kimm H, et al. Adiponectin concentrations: a genome-wide association study. American journal of human genetics. 2010;87(4):545–52. Epub 2010/10/05. doi: 10.1016/j.ajhg.2010.09.004 20887962.
36. Menzaghi C, Trischitta V, Doria A. Genetic influences of adiponectin on insulin resistance, type 2 diabetes, and cardiovascular disease. Diabetes. 2007;56(5):1198–209. Epub 2007/02/17. doi: 10.2337/db06-0506 17303804.
37. Hivert MF, Manning AK, McAteer JB, Florez JC, Dupuis J, Fox CS, et al. Common variants in the adiponectin gene (ADIPOQ) associated with plasma adiponectin levels, type 2 diabetes, and diabetes-related quantitative traits: the Framingham Offspring Study. Diabetes. 2008;57(12):3353–9. Epub 2008/09/09. doi: 10.2337/db08-0700 18776141.
38. Wu Y, Gao H, Li H, Tabara Y, Nakatochi M, Chiu YF, et al. A meta-analysis of genome-wide association studies for adiponectin levels in East Asians identifies a novel locus near WDR11-FGFR2. Hum Mol Genet. 2014;23(4):1108–19. Epub 2013/10/10. doi: 10.1093/hmg/ddt488 24105470.
39. Walter K, Min JL, Huang J, Crooks L, Memari Y, McCarthy S, et al. The UK10K project identifies rare variants in health and disease. Nature. 2015;526(7571):82–90. Epub 2015/09/15. doi: 10.1038/nature14962 26367797.
40. Waki H, Yamauchi T, Kamon J, Ito Y, Uchida S, Kita S, et al. Impaired multimerization of human adiponectin mutants associated with diabetes. Molecular structure and multimer formation of adiponectin. The Journal of biological chemistry. 2003;278(41):40352–63. Epub 2003/07/25. doi: 10.1074/jbc.M300365200 12878598.
41. Kottyan LC, Woo JG, Keddache M, Banach W, Crimmins NA, Dolan LM, et al. Novel variations in the adiponectin gene (ADIPOQ) may affect distribution of oligomeric complexes. SpringerPlus. 2012;1(1):66. Epub 2013/02/12. doi: 10.1186/2193-1801-1-66 23396303.
42. Font-Cunill B, Arnes L, Ferrer J, Sussel L, Beucher A. Long Non-coding RNAs as Local Regulators of Pancreatic Islet Transcription Factor Genes. Frontiers in genetics. 2018;9:524. Epub 2018/11/22. doi: 10.3389/fgene.2018.00524 30459811.
43. Kopp F, Mendell JT. Functional Classification and Experimental Dissection of Long Noncoding RNAs. Cell. 2018;172(3):393–407. Epub 2018/01/27. doi: 10.1016/j.cell.2018.01.011 29373828.
44. Pang WJ, Lin LG, Xiong Y, Wei N, Wang Y, Shen QW, et al. Knockdown of PU.1 AS lncRNA inhibits adipogenesis through enhancing PU.1 mRNA translation. Journal of cellular biochemistry. 2013;114(11):2500–12. Epub 2013/06/12. doi: 10.1002/jcb.24595 23749759.
45. Davis JP, Huyghe JR, Locke AE, Jackson AU, Sim X, Stringham HM, et al. Common, low-frequency, and rare genetic variants associated with lipoprotein subclasses and triglyceride measures in Finnish men from the METSIM study. PLoS genetics. 2017;13(10):e1007079. Epub 2017/10/31. doi: 10.1371/journal.pgen.1007079 29084231.
46. McCarthy S, Das S, Kretzschmar W, Delaneau O, Wood AR, Teumer A, et al. A reference panel of 64,976 haplotypes for genotype imputation. Nature genetics. 2016. Epub 2016/08/23. doi: 10.1038/ng.3643 27548312.
47. Kang HM, Sul JH, Service SK, Zaitlen NA, Kong SY, Freimer NB, et al. Variance component model to account for sample structure in genome-wide association studies. Nature genetics. 2010;42(4):348–54. Epub 2010/03/09. doi: 10.1038/ng.548 20208533.
48. Pruim RJ, Welch RP, Sanna S, Teslovich TM, Chines PS, Gliedt TP, et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics (Oxford, England). 2010;26(18):2336–7. Epub 2010/07/17. doi: 10.1093/bioinformatics/btq419 20634204.
49. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489(7414):57–74. Epub 2012/09/08. doi: 10.1038/nature11247 22955616.
50. Ernst J, Kheradpour P, Mikkelsen TS, Shoresh N, Ward LD, Epstein CB, et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature. 2011;473(7345):43–9. Epub 2011/03/29. doi: 10.1038/nature09906 21441907.
51. Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, Heravi-Moussavi A, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518(7539):317–30. Epub 2015/02/20. doi: 10.1038/nature14248 25693563.
52. Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, et al. The human genome browser at UCSC. Genome research. 2002;12(6):996–1006. Epub 2002/06/05. doi: 10.1101/gr.229102 12045153.
53. Allum F, Shao X, Guenard F, Simon MM, Busche S, Caron M, et al. Characterization of functional methylomes by next-generation capture sequencing identifies novel disease-associated variants. Nat Commun. 2015;6:7211. Epub 2015/05/30. doi: 10.1038/ncomms8211 26021296.
54. Cannon ME, Currin KW, Young KL, Perrin HJ, Vadlamudi S, Safi A, et al. Open Chromatin Profiling in Adipose Tissue Marks Genomic Regions with Functional Roles in Cardiometabolic Traits. G3 (Bethesda, Md). 2019. Epub 2019/06/13. doi: 10.1534/g3.119.400294 31186305.
55. Fogarty MP, Cannon ME, Vadlamudi S, Gaulton KJ, Mohlke KL. Identification of a regulatory variant that binds FOXA1 and FOXA2 at the CDC123/CAMK1D type 2 diabetes GWAS locus. PLoS genetics. 2014;10(9):e1004633. Epub 2014/09/12. doi: 10.1371/journal.pgen.1004633 25211022.
Článek vyšel v časopise
PLOS Genetics
2020 Číslo 9
- Antibiotika na nachlazení nezabírají! Jak můžeme zpomalit šíření rezistence?
- FDA varuje před selfmonitoringem cukru pomocí chytrých hodinek. Jak je to v Česku?
- Prof. Jan Škrha: Metformin je bezpečný, ale je třeba jej bezpečně užívat a léčbu kontrolovat
- Ibuprofen jako alternativa antibiotik při léčbě infekcí močových cest
- Jak a kdy u celiakie začíná reakce na lepek? Možnou odpověď poodkryla čerstvá kanadská studie
Nejčtenější v tomto čísle
- Alleviating chronic ER stress by p38-Ire1-Xbp1 pathway and insulin-associated autophagy in C. elegans neurons
- Cocoonase is indispensable for Lepidoptera insects breaking the sealed cocoon
- A mega-analysis of expression quantitative trait loci in retinal tissue
- Adiponectin GWAS loci harboring extensive allelic heterogeneity exhibit distinct molecular consequences