A flexible likelihood framework for detecting associations with secondary phenotypes in genetic studies using selected samples: Application to sequence data

European Journal of Human Genetics

Volumn 20, Issue 4, 2012, Pages 449-456

  Liu, Dajiang J ^a,b   Leal, Suzanne M ^a,b  

^a BAYLOR COLLEGE OF MEDICINE   (United States)

^b Rice University   (United States)

Author keywords

multiple phenotypes; next generation sequencing; pleiotropy; rare variants; secondary trait; selective sampling

Indexed keywords

ARTICLE; CASE CONTROL STUDY; CONCEPTUAL FRAMEWORK; CONTROLLED STUDY; GENE LOCUS; GENETIC ANALYSIS; GENETIC ASSOCIATION; GENETIC PARAMETERS; GENETIC PROCEDURES; GENETIC SUSCEPTIBILITY; GENETIC TRAIT; HUMAN; PHENOTYPE; POPULATION GENETICS; PRIORITY JOURNAL; RANDOM SAMPLE; SEQUENCE ANALYSIS; SEQUENCE DATABASE;

COMPUTER SIMULATION; GENOME-WIDE ASSOCIATION STUDY; GENOTYPE; HUMANS; LIKELIHOOD FUNCTIONS; PHENOTYPE;

EID: 84858337563     PISSN: 10184813     EISSN: 14765438     Source Type: Journal    
DOI: 10.1038/ejhg.2011.211     Document Type: Article

References (40)

1. Cohen JC, Kiss RS, Pertsemlidis A, Marcel YL, McPherson R, Hobbs HH: Multiple rare alleles contribute to low plasma levels of HDL cholesterol. Science 2004; 305: 869-872.
2. JiW, Foo JN, O'Roak BJ et al: Rare independent mutations in renal salt handling genes contribute to blood pressure variation. Nat Genet 2008; 40: 592-599.
3. Romeo S, Pennacchio LA, Fu Y et al: Population-based resequencing of ANGPTL4 uncovers variations that reduce triglycerides and increase HDL. Nat Genet 2007; 39: 513-516.
4. Bodmer W, Bonilla C: Common and rare variants in multifactorial susceptibility to common diseases. Nat Genet 2008; 40: 695-701.
5. Kryukov GV, Shpunt A, Stamatoyannopoulos JA, Sunyaev SR: Power of deep, all-exon resequencing for discovery of human trait genes. Proc Natl Acad Sci USA 2009; 106: 3871-3876.
6. Cohen JC, Pertsemlidis A, Fahmi S et al: Multiple rare variants in NPC1L1 associated with reduced sterol absorption and plasma low-density lipoprotein levels. Proc Natl Acad Sci USA 2006; 103: 1810-1815.
7. Cauchi S, Nead KT, Choquet H et al: The genetic susceptibility to type 2 diabetes may be modulated by obesity status: Implications for association studies. BMC Med Genet 2008; 9: 45.
8. Cauchi S, Meyre D, Dina C et al: Transcription factor TCF7L2 genetic study in the French population: Expression in human beta-cells and adipose tissue and strong association with type 2 diabetes. Diabetes 2006; 55: 2903-2908.
9. Lin DY, Zeng D: Proper analysis of secondary phenotype data in case-control association studies. Genet Epidemiol 2009; 33: 256-265.
10. Richardson DB, Rzehak P, Klenk J, Weiland SK: Analyses of case-control data for additional outcomes. Epidemiology 2007; 18: 441-445.
11. Ioannidis JP, Thomas G, Daly MJ: Validating, augmenting and refining genome-wide association signals. Nat Rev Genet 2009; 10: 318-329.
12. McCarthy MI, Abecasis GR, Cardon LR et al: Genome-wide association studies for complex traits: Consensus, uncertainty and challenges. Nat Rev Genet 2008; 9: 356-369.
13. Cirulli ET, Goldstein DB: Uncovering the roles of rare variants in common disease through whole-genome sequencing. Nat Rev Genet 2010; 11: 415-425.
14. Plomin R, Haworth CM, Davis OS: Common disorders are quantitative traits. Nat Rev Genet 2009; 10: 872-878.
15. Lange C, Silverman EK, Xu X, Weiss ST, Laird NM: A multivariate family-based association test using generalized estimating equations: FBAT-GEE. Biostatistics 2003; 4: 195-206.
16. Liu J, Pei Y, Papasian CJ, Deng HW: Bivariate association analyses for the mixture of continuous and binary traits with the use of extended generalized estimating equations. Genet Epidemiol 2009; 33: 217-227.
17. Allison DB, Thiel B, St Jean P, Elston RC, Infante MC, Schork NJ: Multiple phenotype modeling in gene-mapping studies of quantitative traits: Power advantages. Am J Hum Genet 1998; 63: 1190-1201.
18. Boyko AR, Williamson SH, Indap AR et al: Assessing the evolutionary impact of amino acid mutations in the human genome. PLoS Genet 2008; 4: E1000083.
19. Liu DJ, Leal SM: A novel adaptive method for the analysis of next-generation sequencing data to detect complex trait associations with rare variants due to gene main effects and interactions. PLoS Genet 2010; 6: E1001156.
20. Madsen BE, Browning SR: A groupwise association test for rare mutations using a weighted sum statistic. PLoS Genet 2009; 5: E1000384.
21. Price AL, Kryukov GV, de Bakker PI et al: Pooled association tests for rare variants in exon-resequencing studies. Am J Hum Genet 2010; 86: 832-838.
22. Morris AP, Zeggini E: An evaluation of statistical approaches to rare variant analysis in genetic association studies. Genet Epidemiol 2009; 34: 188-193.
23. Li B, Leal SM: Methods for detecting associations with rare variants for common diseases: Application to analysis of sequence data. Am J Hum Genet 2008; 83: 311-321.
24. Neale BM, Rivas MA, Voight BF et al: Testing for an unusual distribution of rare variants. PLoS Genet 2010; 7: E1001322.
25. Bhatia G, Bansal V, Harismendy O et al: A covering method for detecting genetic associations between rare variants and common phenotypes. PLoS Comput Biol 2010; 6: E1000954.
26. Aitken AC: Notes on selection from a multivariate normal population. Proc Edin Math Soc 1934; 4: 106-110.
27. Munafo MR, Flint J: Meta-analysis of genetic association studies. Trends Genet 2004; 20: 439-444.
28. Skol AD, Scott LJ, Abecasis GR, Boehnke M: Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies. Nat Genet 2006; 38: 209-213.
29. Mailman MD, Feolo M, Jin Y et al: The NCBI dbGaP database of genotypes and phenotypes. Nat Genet 2007; 39: 1181-1186.
30. Bouatia-Naji N, Rocheleau G, Van Lommel L et al: A polymorphism within the G6PC2 gene is associated with fasting plasma glucose levels. Science 2008; 320: 1085-1088.
31. Elliott P, Chambers JC, Zhang W et al: Genetic loci associated with C-reactive protein levels and risk of coronary heart disease. JAMA 2009; 302: 37-48.
32. Sladek R, Rocheleau G, Rung J et al: A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 2007; 445: 881-885.
33. Webster RJ, Warrington NM, Weedon MN et al: The association of common genetic variants in the APOA5, LPL and GCK genes with longitudinal changes in metabolic and cardiovascular traits. Diabetologia 2009; 52: 106-114.
34. Koster A, Chao YB, Mosior M et al: Transgenic angiopoietin-like (angptl)4 overexpression and targeted disruption of angptl4 and angptl3: Regulation of triglyceride metabolism. Endocrinology 2005; 146: 4943-4950.
35. Li B, Ge D, Wang Y et al: Lipoprotein lipase gene polymorphisms and blood pressure levels in the Northern Chinese Han population. Hypertens Res 2004; 27: 373-378.
36. Romeo S, Yin W, Kozlitina J et al: Rare loss-of-function mutations in ANGPTL family members contribute to plasma triglyceride levels in humans. J Clin Invest 2009; 119: 70-79.
37. Li M, Li C: Assessing departure from Hardy-Weinberg equilibrium in the presence of disease association. Genet Epidemiol 2008; 32: 589-599.
38. Garner C: Confounded by sequencing depth in association studies of rare alleles. Genet Epidemiol 2011; 35: 261-268.
39. Nyholt DR: A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other. Am J Hum Genet 2004; 74: 765-769.
40. Liu DJ, Leal SM: Replication strategies for rare variant complex trait association studies via next-generation sequencing. Am J Hum Genet 2010; 87: 790-801.