First genome-wide association study in an Australian Aboriginal population provides insights into genetic risk factors for body mass index and type 2 diabetes

PLoS ONE

Volumn 10, Issue 3, 2015, Pages

  Anderson, Denise ^a   Cordell, Heather J ^b   Fakiola, Michaela ^a,c   Francis, Richard W ^a   Syn, Genevieve ^a   Scaman, Elizabeth S H ^a   Davis, Elizabeth ^a,d   Miles, Simon J ^e   McLeay, Toby ^e   Jamieson, Sarra E ^a   Blackwell, Jenefer M ^a,c  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

^b NEWCASTLE UNIVERSITY   (United Kingdom)

^c UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^d PRINCESS MARGARET HOSPITAL FOR CHILDREN   (Australia)

^e Ngangganawili Aboriginal Health Service   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN DERIVED NEUROTROPHIC FACTOR RECEPTOR; MELANOCORTIN 4 RECEPTOR;

5' UNTRANSLATED REGION; ADULT; AFRICAN AMERICAN; ARTICLE; AUSTRALIAN ABORIGINE; BCL9 GENE; BODY MASS; CNTNAP2 GENE; CONTROLLED STUDY; DOWNSTREAM PROCESSING; ETHNICITY; FEMALE; GABRR1 GENE; GENE; GENETIC ASSOCIATION; GENETIC RISK; GENETIC TRANSCRIPTION; GENOME; GENOTYPING TECHNIQUE; HUMAN; IGF2BP2 GENE; KCNA1 GENE; KCNJ6 GENE; MALE; MC4R GENE; NON INSULIN DEPENDENT DIABETES MELLITUS; PANCREAS FUNCTION; PATHOGENESIS; REGULATORY MECHANISM; SIGNAL TRANSDUCTION; SINGLE NUCLEOTIDE POLYMORPHISM; TCF7L2 GENE; WNT SIGNALING PATHWAY; AGED; AUSTRALIA; ETHNOLOGY; GENETIC PREDISPOSITION; GENETICS; MIDDLE AGED; OCEANIC ANCESTRY GROUP; PEDIGREE; PROCEDURES; RISK FACTOR; VERY ELDERLY;

ADULT; AGED; AGED, 80 AND OVER; AUSTRALIA; BODY MASS INDEX; DIABETES MELLITUS, TYPE 2; FEMALE; GENETIC PREDISPOSITION TO DISEASE; GENOME-WIDE ASSOCIATION STUDY; HUMANS; MALE; MIDDLE AGED; OCEANIC ANCESTRY GROUP; PEDIGREE; POLYMORPHISM, SINGLE NUCLEOTIDE; RISK FACTORS;

EID: 84924365865     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0119333     Document Type: Article

References (105)

1. Donnelly P. Genome-sequencing anniversary. Making sense of the data. Science. 2011; 331 (6020):1024-5. doi: 331/6020/1024-c[pii]10.1126/science.1204089 PMID: 21350161
2. Fesinmeyer MD, North KE, Lim U, Buzkova P, Crawford DC, Haessler J, et al. Effects of smoking on the genetic risk of obesity: the population architecture using genomics and epidemiology study. BMC Med Genet. 2013; 14:6. doi: 10.1186/1471-2350-14-6 1471-2350-14-6[pii] PMID: 23311614
3. McCarthy MI. Genomics, type 2 diabetes, and obesity. N Engl J Med. 2010; 363(24):2339-50. doi: 10. 1056/NEJMra0906948 PMID: 21142536
4. Morris AP, Voight BF, Teslovich TM, Ferreira T, Segre AV, Steinthorsdottir V, et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet. 2012; 44(9):981-90. doi: ng.2383 [pii] 10.1038/ng.2383 PMID: 22885922
5. Scott RA, Lagou V, Welch RP, Wheeler E, Montasser ME, Luan J, et al. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat Genet. 2012; 44(9):991-1005. doi: ng.2385 [pii] 10.1038/ng.2385 PMID: 22885924
6. Xi B, Takeuchi F, Meirhaeghe A, Kato N, Chambers JC, Morris AP, et al. Associations of genetic variants in/near body mass index-associated genes with type 2 diabetes: a systematic meta-analysis. Clin Endocrinol (Oxf). 2014; 81(5):702-10. doi: 10.1111/cen.12428 PMID: 24528214
7. Gillett G, McKergow F. Genes, ownership, and indigenous reality. Social science & medicine. 2007; 65(10):2093-104. doi: 10.1016/j.socscimed.2007.06.024.
8. McInnes RR. 2010 Presidential Address: Culture: the silent language geneticists must learn-genetic research with indigenous populations. Am J Hum Genet. 2011; 88(3):254-61. PMID: 21516613
9. Kowal E, Anderson I. Difficult conversations: talking about Indigenous genetic research in Australia. In: Berthier S, Tolazzi S, Whittick S, editors. Biomapping-Indigenous Identities. Amsterdam: Rodopi; 2012.
10. Kowal E, Pearson G, Peacock CS, Jamieson SE, Blackwell JM. Genetic research and aboriginal and Torres Strait Islander Australians. J Bioeth Inq. 2012; 9(4):419-32. doi: 10.1007/s11673-012-9391-x PMID: 23188401
11. Kowal EE. Genetic research in Indigenous health: significant progress, substantial challenges. Comment. Med J Aust. 2012; 197(7):384. doi: 10.5694/mja.12.11113 [pii] PMID: 23025733
12. Kowal EE. Genetic research in Indigenous health: significant progress, substantial challenges. Med J Aust. 2012; 197(1):19-20. doi: 10.5694/mja12.10531 [pii] PMID: 22762219
13. Dodson M, Williamson R. Indigenous peoples and the morality of the Human Genome Diversity Project. J Med Ethics. 1999; 25(2):204-8. PMID: 10226929
14. Kowal E, Anderson I. Genetic research in Aboriginal and Torres Strait Islander communities: Continuing the conversation: http://www.lowitja.org.au/files/docs/Genetics-report2012.pdf; 2012. Available from: http://www.lowitja.org.au/files/docs/Genetics-report2012.pdf.
15. Rotimi CN, Jorde LB. Ancestry and disease in the age of genomic medicine. N Engl J Med. 2010; 363 (16):1551-8. doi: 10.1056/NEJMra0911564 PMID: 20942671
16. Daniel M, Rowley KG, McDermott R, O'Dea K. Diabetes and impaired glucose tolerance in Aboriginal Australians: prevalence and risk. Diabetes Res Clin Pract. 2002; 57(1):23-33. PMID: 12007727
17. Tonkinson R. The Mardu Aborigines, living the dream in Australia's desert. New York: Holt, Reinhart & Winston; 1991.
18. Davenport S, Johnson PC, Yuwali. Cleared Out: First Contract in the Western Desert: Aboriginal Studies Press; 2005.
19. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med. 1998; 15(7):539-53. doi: 10.1002/(SICI)1096-9136(199807)15:7<539::AIDDIA668> 3.0.CO;2-S PMID: 9686693
20. Patterson N, Price AL, Reich D. Population structure and eigenanalysis. PLoS Genet. 2006; 2(12): e190. doi: 06-PLGE-RA-0101R3 [pii] 10.1371/journal.pgen.0020190 PMID: 17194218
21. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006; 38(8):904-9. doi: ng1847 [pii] 10.1038/ng1847 PMID: 16862161
22. Delaneau O, Marchini J, Zagury JF. A linear complexity phasing method for thousands of genomes. Nat Methods. 2012; 9(2):179-81. doi: 10.1038/nmeth.1785 nmeth.1785 [pii].
23. Howie B, Marchini J, Stephens M. Genotype imputation with thousands of genomes. G3 (Bethesda). 2011; 1(6):457-70. doi: 10.1534/g3.111.001198 GGG-001198 [pii].
24. Marchini J, Howie B. Genotype imputation for genome-wide association studies. Nat Rev Genet. 2010; 11(7):499-511. doi: 10.1038/nrg2796 nrg2796 [pii] PMID: 20517342
25. Lin P, Hartz SM, Zhang Z, Saccone SF, Wang J, Tischfield JA, et al. A new statistic to evaluate imputation reliability. PLoS ONE. 2010; 5(3):e9697. doi: 10.1371/journal.pone.0009697 PMID: 20300623
26. Liu EY, Buyske S, Aragaki AK, Peters U, Boerwinkle E, Carlson C, et al. Genotype imputation of Metabochip SNPs using a study-specific reference panel of ∼4,000 haplotypes in African Americans from the Women's Health Initiative. Genet Epidemiol. 2012; 36(2):107-17. doi: 10.1002/gepi.21603 PMID: 22851474
27. Abecasis GR, Cardon LR, Cookson WO. A general test of association for quantitative traits in nuclear families. Am J Hum Genet. 2000; 66:279-92. PMID: 10631157
28. Aulchenko YS, Ripke S, Isaacs A, van Duijn CM. GenABEL: an R library for genome-wide association analysis. Bioinformatics. 2007; 23(10):1294-6. doi: btm108 [pii] 10.1093/ bioinformatics/btm108 PMID: 17384015
29. Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet. 2011; 88(1):76-82. doi: 10.1016/j.ajhg.2010.11.011 S0002-9297(10)00598-7 [pii] PMID: 21167468
30. Paradis E, Claude J, Strimmer K. APE: Analyses of Phylogenetics and Evolution in R language. Bioinformatics. 2004; 20(2):289-90. PMID: 14734327
31. Chen WM, Abecasis GR. Family-based association tests for genomewide association scans. Am J Hum Genet. 2007; 81(5):913-26. doi: S0002-9297(07)63869-5 [pii] 10.1086/521580 PMID: 17924335
32. Lippert C, Listgarten J, Liu Y, Kadie CM, Davidson RI, Heckerman D. FaST linear mixed models for genome-wide association studies. Nat Methods. 2011; 8(10):833-5. doi: nmeth.1681 [pii] 10.1038/ nmeth.1681 PMID: 21892150
33. 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. Nat Genet. 2010; 42(4):348-54. doi: ng.548 [pii] 10.1038/ng.548 PMID: 20208533
34. Gauderman WJ. Sample size requirements for association studies of gene-gene interaction. Am J Epidemiol. 2002; 155(5):478-84. PMID: 11867360
35. Pruim RJ, Welch RP, Sanna S, Teslovich TM, Chines PS, Gliedt TP, et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics. 2010; 26(18):2336-7. doi: btq419 [pii] 10.1093/bioinformatics/btq419 PMID: 20634204
36. Brudno M, Do CB, Cooper GM, Kim MF, Davydov E, Green ED, et al. LAGAN and Multi-LAGAN: efficient tools for large-scale multiple alignment of genomic DNA. Genome Res. 2003; 13(4):721-31. doi: 10.1101/gr.926603 GR-9266R [pii] PMID: 12654723
37. Brudno M, Chapman M, Gottgens B, Batzoglou S, Morgenstern B. Fast and sensitive multiple alignment of large genomic sequences. BMC Bioinformatics. 2003; 4:66. doi: 10.1186/1471-2105-4-66 1471-2105-4-66 [pii] PMID: 14693042
38. Gottgens B, Gilbert JG, Barton LM, Grafham D, Rogers J, Bentley DR, et al. Long-range comparison of human and mouse SCL loci: localized regions of sensitivity to restriction endonucleases correspond precisely with peaks of conserved noncoding sequences. Genome Res. 2001; 11(1):87-97. PMID: 11156618
39. Messeguer X, Escudero R, Farre D, Nunez O, Martinez J, Alba MM. PROMO: detection of known transcription regulatory elements using species-tailored searches. Bioinformatics. 2002; 18(2):333-4. PMID: 11847087
40. Grabe N. AliBaba2: context specific identification of transcription factor binding sites. In Silico Biol. 2002; 2(1):S1-15. PMID: 11808873
41. Cartharius K, Frech K, Grote K, Klocke B, Haltmeier M, Klingenhoff A, et al. MatInspector and beyond: promoter analysis based on transcription factor binding sites. Bioinformatics. 2005; 21(13):2933-42. PMID: 15860560
42. Takai D, Jones PA. Comprehensive analysis of CpG islands in human chromosomes 21 and 22. Proc Natl Acad Sci U S A. 2002; 99(6):3740-5. PMID: 11891299
43. Cole TJ, Donaldson MD, Ben-Shlomo Y. SITAR-a useful instrument for growth curve analysis. Int J Epidemiol. 2010; 39(6):1558-66. doi: 10.1093/ije/dyq115 PMID: 20647267
44. Kuczmarski RJ, Flegal KM. Criteria for definition of overweight in transition: background and recommendations for the United States. Am J Clin Nutr. 2000; 72(5):1074-81. PMID: 11063431
45. Haslam DW, James WP. Obesity. The Lancet. 2005; 366:1197-209. PMID: 16198769
46. van Dongen J, Willemsen G, Chen WM, de Geus EJ, Boomsma DI. Heritability of metabolic syndrome traits in a large population-based sample. J Lipid Res. 2013; 54(10):2914 -23. doi: 10.1194/jlr. P041673 PMID: 23918046
47. Ning F, Silventoinen K, Pang ZC, Kaprio J, Wang SJ, Zhang D, et al. Genetic and environmental correlations between body mass index and waist circumference in China: the Qingdao adolescent twin study. Behav Genet. 2013; 43(4):340-7. doi: 10.1007/s10519-013-9597-7 PMID: 23756614
48. Johnson W, Choh AC, Lee M, Towne B, Czerwinski SA, Demerath EW. Characterization of the infant BMI peak: sex differences, birth year cohort effects, association with concurrent adiposity, and heritability. Am J Hum Biol. 2013; 25(3):378-88. doi: 10.1002/ajhb.22385 PMID: 23606227
49. Devlin B, Roeder K. Genomic control for association studies. Biometrics. 1999; 55(4):997-1004. PMID: 11315092
50. Eu-Ahsunthornwattana J, Miller EN, Fakiola M, Wellcome Trust Case Control C, Jeronimo SM, Blackwell JM, et al. Comparison of methods to account for relatedness in genome-wide association studies with family-based data. PLoS Genet. 2014; 10(7):e1004445. doi: 10.1371/journal.pgen.1004445 PMID: 25033443
51. Dudbridge F, Gusnanto A. Estimation of significance thresholds for genomewide association scans. Genet Epidemiol. 2008; 32:227-34. doi: 10.1002/gepi.20297 PMID: 18300295
52. Hindorff LA, Junkins HA, Mehta JP, Manolio TA. A Catalog of Published Genome-Wide Association Studies. Available at: www.genome.gov/26525384. Accessed [25 October 2014]. 2009.
53. Harb G, Vasavada RC, Cobrinik D, Stewart AF. The retinoblastoma protein and its homolog p130 regulate the G1/S transition in pancreatic beta-cells. Diabetes. 2009; 58(8):1852-62. doi: 10.2337/db08-0759 PMID: 19509021
54. Daimon M, Sato H, Oizumi T, Toriyama S, Saito T, Karasawa S, et al. Association of the PIK3C2G gene polymorphisms with type 2 DM in a Japanese population. Biochem Biophys Res Commun. 2008; 365(3):466-71. doi: 10.1016/j.bbrc.2007.10.180 PMID: 17991425
55. Alsmadi O, Al-Rubeaan K, Mohamed G, Alkayal F, Al-Saud H, Al-Saud NA, et al. Weak or no association of TCF7L2 variants with Type 2 diabetes risk in an Arab population. BMC Med Genet. 2008; 9:72. doi: 1471-2350-9-72 [pii] 10.1186/1471-2350-9-72 PMID: 18655717
56. Chandak GR, Janipalli CS, Bhaskar S, Kulkarni SR, Mohankrishna P, Hattersley AT, et al. Common variants in the TCF7L2 gene are strongly associated with type 2 diabetes mellitus in the Indian population. Diabetologia. 2007; 50(1):63-7. doi: 10.1007/s00125-006-0502-2 PMID: 17093941
57. Ereqat S, Nasereddin A, Cauchi S, Azmi K, Abdeen Z, Amin R. Association of a common variant in TCF7L2 gene with type 2 diabetes mellitus in the Palestinian population. Acta Diabetol. 2010; 47 (Suppl 1):195-8. doi: 10.1007/s00592-009-0161-0 PMID: 19885641
58. Lyssenko V, Lupi R, Marchetti P, Del Guerra S, Orho-Melander M, Almgren P, et al. Mechanisms by which common variants in the TCF7L2 gene increase risk of type 2 diabetes. J Clin Invest. 2007; 117 (8):2155-63. doi: 10.1172/JCI30706 PMID: 17671651
59. Saadi H, Nagelkerke N, Carruthers SG, Benedict S, Abdulkhalek S, Reed R, et al. Association of TCF7L2 polymorphism with diabetes mellitus, metabolic syndrome, and markers of beta cell function and insulin resistance in a population-based sample of Emirati subjects. Diabetes Res Clin Pract. 2008; 80(3):392-8. doi: S0168-8227(08)00018-1 [pii] 10.1016/j.diabres.2008.01.008 PMID: 18282631
60. Qin LJ, Lv Y, Huang QY. Meta-analysis of association of common variants in the KCNJ11-ABCC8 region with type 2 diabetes. Genet Mol Res. 2013; 12(3):2990-3002. doi: 10.4238/2013.August.20.1 PMID: 24065655
61. Sakura H, Bond C, Warren-Perry M, Horsley S, Kearney L, Tucker S, et al. Characterization and variation of a human inwardly-rectifying-K-channel gene (KCNJ6): a putative ATP-sensitive K-channel subunit. FEBS Lett. 1995; 367(2):193-7. PMID: 7796919
62. Ma Z, Lavebratt C, Almgren M, Portwood N, Forsberg LE, Branstrom R, et al. Evidence for presence and functional effects of Kv1.1 channels in beta-cells: general survey and results from mceph/mceph mice. PLoS ONE. 2011; 6(4):e18213. doi: 10.1371/journal.pone.0018213 PMID: 21483673
63. Lin HJ, Huang YC, Lin JM, Liao WL, Wu JY, Chen CH, et al. Novel susceptibility genes associated with diabetic cataract in a Taiwanese population. Ophthalmic Genet. 2013; 34(1-2):35-42. doi: 10. 3109/13816810.2012.736590.
64. Herson PS, Virk M, Rustay NR, Bond CT, Crabbe JC, Adelman JP, et al. A mouse model of episodic ataxia type-1. Nature neuroscience. 2003; 6(4):378-83. doi: 10.1038/nn1025 PMID: 12612586
65. Howie BN, Donnelly P, Marchini J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 2009; 5(6):e1000529. doi: 10.1371/ journal.pgen.1000529 PMID: 19543373
66. Pugach I, Delfin F, Gunnarsdottir E, Kayser M, Stoneking M. Genome-wide data substantiate Holocene gene flow from India to Australia. Proc Natl Acad Sci U S A. 2013; 110(5):1803-8. doi: 1211927110 [pii] 10.1073/pnas.1211927110 PMID: 23319617
67. Rasmussen M, Guo X, Wang Y, Lohmueller KE, Rasmussen S, Albrechtsen A, et al. An Aboriginal Australian genome reveals separate human dispersals into Asia. Science. 2011; 334(6052):94-8. doi: science.1211177 [pii] 10.1126/science.1211177 PMID: 21940856
68. Carlsson S, Ahlbom A, Lichtenstein P, Andersson T. Shared genetic influence of BMI, physical activity and type 2 diabetes: a twin study. Diabetologia. 2013; 56(5):1031-5. doi: 10.1007/s00125-013-2859-3 PMID: 23404445
69. Gunther T, Schmitt AO, Bortfeldt RH, Hinney A, Hebebrand J, Brockmann GA. Where in the genome are significant single nucleotide polymorphisms from genome-wide association studies located? Omics: a journal of integrative biology. 2011; 15(7- 8):507-12. doi: 10.1089/omi.2010.0154.
70. Gruber CJ, Gruber DM, Gruber IM, Wieser F, Huber JC. Anatomy of the estrogen response element. Trends Endocrinol Metab. 2004; 15(2):73-8. doi: 10.1016/j.tem.2004.01.008 S1043276004000098 [pii] PMID: 15036253
71. Hughes MJ, Liang HM, Jiricny J, Jost JP. Purification and characterization of a protein from HeLa cells that binds with high affinity to the estrogen response element, GGTCAGCGTGACC. Biochemistry. 1989; 28(23):9137-42. PMID: 2605247
72. Naciff JM, Hess KA, Overmann GJ, Torontali SM, Carr GJ, Tiesman JP, et al. Gene expression changes induced in the testis by transplacental exposure to high and low doses of 17{alpha}-ethynyl estradiol, genistein, or bisphenol A. Toxicol Sci. 2005; 86(2):396-416. doi: kfi198 [pii] 10.1093/toxsci/ kfi198 PMID: 15901920
73. Yang N, Kazazian HH Jr, L1 retrotransposition is suppressed by endogenously encoded small interfering RNAs in human cultured cells. Nat Struct Mol Biol. 2006; 13(9):763-71. doi: nsmb1141 [pii] 10. 1038/nsmb1141 PMID: 16936727
74. Ikeno M, Suzuki N, Kamiya M, Takahashi Y, Kudoh J, Okazaki T. LINE1 family member is negative regulator of HLA-G expression. NucleicAcidsRes. 2012; 40(21):10742-52. doi: 10.1093/nar/gks874. gks874 [pii] PMID: 23002136
75. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012; 491(7422):56-65. http://www.nature.com/nature/journal/v491/n7422/abs/nature11632.html#supplementaryinformation. doi: 10.1038/nature11632 PMID: 23128226
76. Nelson SC, Doheny KF, Pugh EW, Romm JM, Ling H, Laurie CA, et al. Imputation-based genomic coverage assessments of current human genotyping arrays. G3 (Bethesda). 2013; 3(10):1795-807. doi: 10.1534/g3.113.007161 g3.113.007161 [pii] PMID: 23979933
77. Guo T, Hanson RL, Traurig M, Muller YL, Ma L, Mack J, et al. TCF7L2 is not a major susceptibility gene for type 2 diabetes in Pima Indians: analysis of 3,501 individuals. Diabetes. 2007; 56(12):3082-8. doi: db07-0621 [pii] 10.2337/db07-0621 PMID: 17909099
78. Replication DIG, Meta-analysis C. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat Genet. 2014; 46(3):234-44. doi: 10. 1038/ng.2897 PMID: 24509480
79. Coventry A, Bull-Otterson LM, Liu X, Clark AG, Maxwell TJ, Crosby J, et al. Deep resequencing reveals excess rare recent variants consistent with explosive population growth. Nat Commun. 2010; 1:131. doi: ncomms1130 [pii] 10.1038/ncomms1130 PMID: 21119644
80. Dickson SP, Wang K, Krantz I, Hakonarson H, Goldstein DB. Rare variants create synthetic genomewide associations. PLoS Biol. 2010; 8(1):e1000294. doi: 10.1371/journal.pbio.1000294 PMID: 20126254
81. Kramps T, Peter O, Brunner E, Nellen D, Froesch B, Chatterjee S, et al. Wnt/wingless signaling requires BCL9/legless-mediated recruitment of pygopus to the nuclear beta-catenin-TCF complex. Cell. 2002; 109(1):47-60. PMID: 11955446
82. Wagner R, Staiger H, Ullrich S, Stefan N, Fritsche A, Haring HU. Untangling the interplay of genetic and metabolic influences on beta-cell function: Examples of potential therapeutic implications involving TCF7L2 and FFAR1. Molecular metabolism. 2014; 3(3):261-7. doi: 10.1016/j.molmet.2014.01. 001 PMID: 24749055
83. Okamoto K, Iwasaki N, Nishimura C, Doi K, Noiri E, Nakamura S, et al. Identification of KCNJ15 as a susceptibility gene in Asian patients with type 2 diabetes mellitus. Am J Hum Genet. 2010; 86 (1):54-64. doi: 10.1016/j.ajhg.2009.12.009 PMID: 20085713
84. Robbins CA, Tempel BL. Kv1.1 and Kv1.2: similar channels, different seizure models. Epilepsia. 2012; 53 Suppl 1:134-41. doi: 10.1111/j.1528-1167.2012.03484.x PMID: 22612818
85. Al Safar HS, Cordell HJ, Jafer O, Anderson D, Jamieson SE, Fakiola M, et al. A genome-wide search for type 2 diabetes susceptibility genes in an extended Arab family. AnnHumGenet. 2013; 77 (6):488-503. doi: 10.1111/ahg.12036 PMID: 23937595
86. Rorsman P, Berggren PO, Bokvist K, Ericson H, Mohler H, Ostenson CG, et al. Glucose-inhibition of glucagon secretion involves activation of GABAA-receptor chloride channels. Nature. 1989; 341 (6239):233-6. doi: 10.1038/341233a0 PMID: 2550826
87. Taneera J, Jin Z, Jin Y, Muhammed SJ, Zhang E, Lang S, et al. gamma-Aminobutyric acid (GABA) signalling in human pancreatic islets is altered in type 2 diabetes. Diabetologia. 2012; 55(7):1985-94. doi: 10.1007/s00125-012-2548-7 PMID: 22538358
88. Ho LK, Liu D, Rozycka M, Brown RA, Fry MJ. Identification of four novel human phosphoinositide 3-kinases defines a multi-isoform subfamily. Biochem Biophys Res Commun. 1997; 235(1):130-7. doi: S0006-291X(97)96747-4 [pii] 10.1006/bbrc.1997.6747 PMID: 9196049
89. Shia WC, Ku TH, Tsao YM, Hsia CH, Chang YM, Huang CH, et al. Genetic copy number variants in myocardial infarction patients with hyperlipidemia. BMC Genomics. 2011; 12 Suppl 3:S23. doi: 10. 1186/1471-2164-12-S3-S23 1471-2164-12-S3-S23 [pii] PMID: 22369086
90. Poliak S, Gollan L, Martinez R, Custer A, Einheber S, Salzer JL, et al. Caspr2, a new member of the neurexin superfamily, is localized at the juxtaparanodes of myelinated axons and associates with K+ channels. Neuron. 1999; 24(4):1037-47. PMID: 10624965
91. Buchner DA, Geisinger JM, Glazebrook PA, Morgan MG, Spiezio SH, Kaiyala KJ, et al. The juxtaparanodal proteins CNTNAP2 and TAG1 regulate diet-induced obesity. Mamm Genome. 2012; 23(7-8):431-42. doi: 10.1007/s00335-012-9400-8 PMID: 22961258
92. Velez Edwards DR, Naj AC, Monda K, North KE, Neuhouser M, Magvanjav O, et al. Gene-environment interactions and obesity traits among postmenopausal African-American and Hispanic women in the Women' s Health Initiative SHARe Study. Hum Genet. 2013; 132(3):323-36. doi: 10.1007/ s00439-012-1246-3 PMID: 23192594
93. Vuillaume ML, Naudion S, Banneau G, Diene G, Cartault A, Cailley D, et al. New candidate loci identified by array-CGH in a cohort of 100 children presenting with syndromic obesity. Am J Med Genet A. 2014; 164A(8):1965-75. doi: 10.1002/ajmg.a.36587 PMID: 24782328
94. Ritzel MW, Ng AM, Yao SY, Graham K, Loewen SK, Smith KM, et al. Molecular identification and characterization of novel human and mouse concentrative Na+-nucleoside cotransporter proteins (hCNT3 and mCNT3) broadly selective for purine and pyrimidine nucleosides (system cib). J Biol Chem. 2001; 276(4):2914-27. doi: 10.1074/jbc.M007746200 PMID: 11032837
95. Loos RJ, Lindgren CM, Li S, Wheeler E, Zhao JH, Prokopenko I, et al. Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nat Genet. 2008; 40(6):768-75. doi: ng.140 [pii] 10.1038/ng.140 PMID: 18454148
96. Willer CJ, Speliotes EK, Loos RJ, Li S, Lindgren CM, Heid IM, et al. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet. 2009; 41(1):25-34. doi: ng.287 [pii] 10.1038/ng.287 PMID: 19079261
97. Chambers JC, Elliott P, Zabaneh D, Zhang W, Li Y, Froguel P, et al. Common genetic variation near MC4R is associated with waist circumference and insulin resistance. Nat Genet. 2008; 40(6):716-8. doi: ng.156 [pii] 10.1038/ng.156 PMID: 18454146
98. Wen W, Cho YS, Zheng W, Dorajoo R, Kato N, Qi L, et al. Meta-analysis identifies common variants associated with body mass index in east Asians. Nat Genet. 2012; 44(3):307-11. doi: 10.1038/ng. 1087 ng.1087 [pii] PMID: 22344219
99. Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU, et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet. 2010; 42 (11):937-48. doi: ng.686 [pii] 10.1038/ng.686 PMID: 20935630
100. Guo Y, Lanktree MB, Taylor KC, Hakonarson H, Lange LA, Keating BJ, et al. Gene-centric meta-analyses of 108 912 individuals confirm known body mass index loci and reveal three novel signals. Hum Mol Genet. 2013; 22(1):184-201. doi: 10.1093/hmg/dds396 PMID: 23001569
101. Xu B, Goulding EH, Zang K, Cepoi D, Cone RD, Jones KR, et al. Brain-derived neurotrophic factor regulates energy balance downstream of melanocortin-4 receptor. Nature neuroscience. 2003; 6 (7):736-42. doi: 10.1038/nn1073 PMID: 12796784
102. McCaffery JM, Papandonatos GD, Peter I, Huggins GS, Raynor HA, Delahanty LM, et al. Obesity susceptibility loci and dietary intake in the Look AHEAD Trial. Am J Clin Nutr. 2012; 95(6):1477-86. doi: 10.3945/ajcn.111.026955 PMID: 22513296
103. Murphy R, Carroll RW, Krebs JD. Pathogenesis of the metabolic syndrome: insights from monogenic disorders. Mediators of inflammation. 2013; 2013:920214. doi: 10.1155/2013/920214 PMID: 23766565
104. Skowronski AA, Morabito MV, Mueller BR, Lee S, Hjorth S, Lehmann A, et al. Effects of a novel MC4R agonist on maintenance of reduced body weight in diet-induced obese mice. Obesity (Silver Spring). 2014; 22(5):1287-95. doi: 10.1002/oby.20678 PMID: 24318934
105. Olney JJ, Sprow GM, Navarro M, Thiele TE. The protective effects of the melanocortin receptor (MCR) agonist, melanotan-II (MTII), against binge-like ethanol drinking are facilitated by deletion of the MC3 receptor in mice. Neuropeptides. 2014; 48(1):47-51. doi: 10.1016/j.npep.2013.11.001 PMID: 24290566