Statistical analysis strategies for association studies involving rare variants

Nature Reviews Genetics

Volumn 11, Issue 11, 2010, Pages 773-785

  Bansal, Vikas ^a   Libiger, Ondrej ^a,b,c   Torkamani, Ali ^a,b   Schork, Nicholas J ^a,b  

^a SCRIPPS TRANSLATIONAL SCIENCE INSTITUTE   (United States)

^b SCRIPPS RESEARCH INSTITUTE   (United States)

^c CHARLES UNIVERSITY   (Czech Republic)

Author keywords

[No Author keywords available]

Indexed keywords

DNA;

DNA SEQUENCE; GENE EXPRESSION; GENE IDENTIFICATION; GENE LOCUS; GENETIC ANALYSIS; GENETIC ASSOCIATION; GENETIC TRAIT; GENETIC VARIABILITY; GENOTYPE; HUMAN GENETICS; ONLINE SYSTEM; PHENOTYPE; PRIORITY JOURNAL; QUANTITATIVE TRAIT; REVIEW; SINGLE NUCLEOTIDE POLYMORPHISM; SOMATIC HYPERMUTATION; STATISTICAL ANALYSIS; CASE CONTROL STUDY; COPY NUMBER VARIATION; EVALUATION STUDY; GENE FREQUENCY; HUMAN; STATISTICS AND NUMERICAL DATA;

CASE-CONTROL STUDIES; DATA INTERPRETATION, STATISTICAL; DNA COPY NUMBER VARIATIONS; GENE FREQUENCY; GENOME-WIDE ASSOCIATION STUDY; HUMANS; PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 77958102016     PISSN: 14710056     EISSN: 14710064     Source Type: Journal    
DOI: 10.1038/nrg2867     Document Type: Review

References (150)

1. Manolio, T. A., Brooks, L. D. & Collins, F. S. A HapMap harvest of insights into the genetics of common disease. J. Clin. Invest. 118, 1590-1605 (2008).
2. Manolio, T. A. et al. Finding the missing heritability of complex diseases. Nature 461, 747-753 (2009).
3. Pinto, D. et al. Functional impact of global rare copy number variation in autism spectrum disorders. Nature 466, 368-372 (2010).
4. Frazer, K. A., Murray, S. S., Schork, N. J. & Topol, E. J. Human genetic variation and its contribution to complex traits. Nature Rev. Genet. 10, 241-251 (2009).
5. Tycko, B. Mapping allele-specific DNA methylation: a new tool for maximizing information from GWAS. Am. J. Hum. Genet. 86, 109-112 (2010).
6. Kong, A. et al. Parental origin of sequence variants associated with complex diseases. Nature 462, 868-874 (2009).
7. Eichler, E. E. et al. Completing the map of human genetic variation. Nature 447, 161-165 (2007).
8. Hunter, D. J. Gene-environment interactions in human diseases. Nature Rev. Genet. 6, 287-298 (2005).
9. Cordell, H. J. Detecting gene-gene interactions that underlie human diseases. Nature Rev. Genet. 10, 392-404 (2009).
10. Bodmer, W. & Bonilla, C. Common and rare variants in multifactorial susceptibility to common diseases. Nature Genet. 40, 695-701 (2008).
11. Schork, N. J., Murray, S. S., Frazer, K. A. & Topol, E. J. Common vs. rare allele hypotheses for complex diseases. Curr. Opin. Genet. Dev. 19, 212-219 (2009).
12. Cirulli, E. T. et al. Common genetic variation and performance on standardized cognitive tests. Eur. J. Hum. Genet. 18, 815-820 (2010).
13. Asimit, J. & Zeggini, E. Rare variant association analysis methods for complex traits. Annu. Rev. Genet. 44, 293-308 (2010).
14. Gorlov, I. P., Gorlova, O. Y., Sunyaev, S. R., Spitz, M. R. & Amos, C. I. Shifting paradigm of association studies: value of rare single-nucleotide polymorphisms. Am. J. Hum. Genet. 82, 100-112 (2008).
15. Pritchard, J. K. Are rare variants responsible for susceptibility to complex diseases? Am. J. Hum. Genet. 69, 124-137 (2001).
16. Wood, L. D. et al. The genomic landscapes of human breast and colorectal cancers. Science 318, 1108-1113 (2007).
17. Lahiry, P., Torkamani, A., Schork, N. J. & Hegele, R. A. Kinase mutations in human disease: interpreting genotype-phenotype relationships. Nature Rev. Genet. 11, 60-74 (2010).
18. Bobadilla, J. L., Macek, M., Jr, Fine, J. P. & Farrell, P. M. Cystic fibrosis: a worldwide analysis of CFTR mutations\ correlation with incidence data and application to screening. Hum. Mutat. 19, 575-606 (2002).
19. Easton, D. F. et al. A systematic genetic assessment of 1,433 sequence variants of unknown clinical significance in the BRCA1 and BRCA2 breast cancer-predisposition genes. Am. J. Hum. Genet. 81, 873-883 (2007).
20. Schork, N. J., Wessel, J. & Malo, N. DNA sequence-based phenotypic association analysis. Adv. Genet. 60, 195-217 (2008).
21. Metzker, M. L. Sequencing technologies\ the next generation. Nature Rev. Genet. 11, 31-46 (2010).
22. Nejentsev, S., Walker, N., Riches, D., Egholm, M. & Todd, J. A. Rare variants of IFIH1, a gene implicated in antiviral responses, protect against type 1 diabetes. Science 324, 387-389 (2009).
23. Ng, S. B. et al. Exome sequencing identifies the cause of a Mendelian disorder. Nature Genet. 42, 30-35 (2010).
24. Roach, J. C. et al. Analysis of genetic inheritance in a family quartet by whole-genome sequencing. Science 328, 636-639 (2010).
25. Schork, N. J., Nath, S. K., Fallin, D. & Chakravarti, A. Linkage disequilibrium analysis of biallelic DNA markers, human quantitative trait loci, and threshold-defined case and control subjects. Am. J. Hum. Genet. 67, 1208-1218 (2000).
26. Lanktree, M. B., Hegele, R. A., Schork, N. J. & Spence, J. D. Extremes of unexplained variation as a phenotype: an efficient approach for genome-wide association studies of cardiovascular disease. Circ. Cardiovasc. Genet. 3, 215-221 (2010).
27. Gilad, Y., Pritchard, J. K. & Thornton, K. Characterizing natural variation using next-generation sequencing technologies. Trends Genet. 25, 463-471 (2009).
28. Li, B. & Leal, S. M. Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. Am. J. Hum. Genet. 83, 311-321 (2008).
29. Altshuler, D., Daly, M. J. & Lander, E. S. Genetic mapping in human disease. Science 322, 881-888 (2008).
30. Morgenthaler, S. & Thilly, W. G. A strategy to discover genes that carry multi-allelic or mono-allelic risk for common diseases: a cohort allelic sums test (CAST). Mutat Res. 615, 28-56 (2007).
31. McClellan, J. & King, M. C. Genetic heterogeneity in human disease. Cell 141, 210-217 (2010).
32. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559-575 (2007).
33. Morris, A. P. & Zeggini, E. An evaluation of statistical approaches to rare variant analysis in genetic association studies. Genet. Epidemiol. 34, 188-193 (2010).
34. Madsen, B. E. & Browning, S. R. A groupwise association test for rare mutations using a weighted sum statistic. PLoS Genet. 5, e1000384 (2009).
35. Price, A. L. et al. Pooled association tests for rare variants in exon-resequencing studies. Am. J. Hum. Genet. 86, 832-838 (2010).
36. Ng, S. B. et al. Targeted capture and massively parallel sequencing of 12 human exomes. Nature 461, 272-276 (2009).
37. Sebat, J., Levy, D. & McCarthy, S. E. Rare structural variants in schizophrenia: one disorder, multiple mutations; one mutation, multiple disorders. Trends Genet. 25, 528-535 (2009).
38. Xiong, M., Zhao, J. & Boerwinkle, E. Generalized T2 test for genome association studies. Am. J. Hum. Genet. 70, 1257-1268 (2002).
39. Lehmann, E. L. Nonparametric Statistical Methods Based on Ranks (McGraw-Hill, New York, 1975).
40. Han, F & Pan, W. A data-adaptive sum test for disease association with multiple common or rare variants. Hum. Hered. 70, 42-54 (2010).
41. Hoh, J. & Ott, J. Scan statistics to scan markers for susceptibility genes. Proc. Natl Acad. Sci. USA 97, 9615-9617 (2000).
42. Pan, W., Han, F & Shen, X. Test selection with application to detecting disease association with multiple SNPs. Hum. Hered. 69, 120-130 (2010).
43. Fallin, D. et al. Genetic analysis of case/control data using estimated haplotype frequencies: application to APOE locus variation and Alzheimer's disease. Genome Res. 11, 143-151 (2001).
44. Zhao, J. H., Curtis, D. & Sham, P. C. Model-free analysis and permutation tests for allelic associations. Hum. Hered. 50, 133-139 (2000).
45. Zhu, X., Fejerman, L., Luke, A., Adeyemo, A. & Cooper, R. S. Haplotypes produced from rare variants in the promoter and coding regions of angiotensinogen contribute to variation in angiotensinogen levels. Hum. Mol. Genet. 14, 639-643 (2005).
46. Zhu, X., Feng, T., Li, Y., Lu, Q. & Elston, R. C. Detecting rare variants for complex traits using family and unrelated data. Genet. Epidemiol. 34, 171-187 (2010).
47. Hartl, D. L. & Clark, A. G. Principles of Population Genetics (Sinauer Associates, Sunderland, Massachusetts, 2007).
48. ST. Nature Rev. Genet. 10, 639-650 (2009)
49. Nei, M. Molecular Evolutionary Genetics (Columbia Univ. Press, New York, 1987).
50. ST and its relatives do not measure differentiation. Mol. Ecol. 17, 4015-4026 (2008).
51. Mount, D. W. Bioinformatics: Sequence and Genome Analysis (Cold Spring Harbor Laboratory Press, New York, 2001).
52. Qian, D. & Thomas, D. C. Genome scan of complex traits by haplotype sharing correlation. Genet. Epidemiol. 21 (Suppl. 1), S582-S587 (2001).
53. Tzeng, J. Y., Devlin, B., Wasserman, L. & Roeder, K. On the identification of disease mutations by the analysis of haplotype similarity and goodness of fit. Am. J. Hum. Genet. 72, 891-902 (2003).
54. Wessel, J. & Schork, N. J. Generalized genomic distance-based regression methodology for multilocus association analysis. Am. J. Hum. Genet. 79, 792-806 (2006).
55. Mukhopadhyay, I., Feingold, E., Weeks, D. E. & Thalamuthu, A. Association tests using kernel-based measures of multi-locus genotype similarity between individuals. Genet. Epidemiol. 34, 213-221 (2009).
56. Clayton, D., Chapman, J. & Cooper, J. Use of unphased multilocus genotype data in indirect association studies. Genet. Epidemiol. 27, 415-428 (2004).
57. Tzeng, J. Y., Zhang, D., Chang, S. M., Thomas, D. C. & Davidian, M. Gene-trait similarity regression for multimarker-based association analysis. Biometrics 65, 822-832 (2009).
58. Lin, W. Y & Schaid, D. J. Power comparisons between similarity-based multilocus association methods, logistic regression, and score tests for haplotypes. Genet. Epidemiol. 33, 183-197 (2009).
59. Ickstadt, K., Selinski, S. & Muller, T. D. in SFB 475 Komplexitatsreduktion in Multivariaten Datenstrukturen (Univ. Dortmund, Germany, 2005).
60. Templeton, A. R. et al. Tree scanning: a method for using haplotype trees in phenotype/genotype association studies. Genetics 169, 441-453 (2005).
61. Nair, R. P. et al. Localization of psoriasis-susceptibility locus PSORS1 to a 60-kb interval telomeric to HLA-C. Am. J. Hum. Genet. 66, 1833-1844 (2000).
62. Tachmazidou, I., Verzilli, C. J. & De Iorio, M. Genetic association mapping via evolution-based clustering of haplotypes. PLoS Genet. 3, e111 (2007).
63. Kowalski, J., Pagano, M. & DeGruttola, V. A nonparametric test of gene region heterogeneity associated with phenotype. J. Am. Stat Assoc. 97, 398-408 (2002).
64. Gilbert, P. B., Novitsky, V. A., Montano, M. A. & Essex, M. An efficient test for comparing sequence diversity between two populations. J. Comput. Biol. 8, 123-139 (2001).
65. Anderson, M. J. Distance-based tests for homogeneity of multivariate dispersions. Biometrics 62, 245-253 (2006).
66. Bhatia, G. et al. A covering method for detecting genetic associations between rare variants and common phenotypes. PLoS Genet. (in the press).
67. Kooperberg, C., Ruczinski, I., LeBlanc, M. L. & Hsu, L Sequence analysis using logic regression. Genet. Epidemiol. 21 (Suppl. 1), S626-S631 (2001).
68. Ott, J. Analysis of Human Genetic Linkage (Johns Hopkins Univ. Press, Baltimore, 1991).
69. Kruglyak, L., Daly, M. J., Reeve-Daly, M. P. & Lander, E. S. Parametric and nonparametric linkage analysis: a unified multipoint approach. Am. J. Hum. Genet. 58, 1347-1363 (1996).
70. Risch, N. & Merikangas, K. The future of genetic studies of complex human diseases. Science 273, 1516-1517 (1996).
71. Oexle, K. A remark on rare variants. J. Hum. Genet. 55, 219-226 (2010).
72. Haiman, C. A. et al. Multiple regions within 8q24 independently affect risk for prostate cancer. Nature Genet. 39, 638-644 (2007).
73. Clarke, R. et al. Genetic variants associated with Lp(a) lipoprotein level and coronary disease. N. Engl. J. Med. 361, 2518-2528 (2009).
74. Malo, N., Libiger, O. & Schork, N. J. Accommodating linkage disequilibrium in genetic-association analyses via ridge regression. Am. J. Hum. Genet. 82, 375-385 (2008).
75. Hoggart, C. J., Whittaker, J. C., De Iorio, M. & Balding, D. J. Simultaneous analysis of all SNPs in genome-wide and re-sequencing association studies. PLoS Genet. 4, e1000130 (2008)
76. Zhou, H., Sehl, M. E., Sinsheimer, J. S. & Lange, K. Association screening of common and rare genetic variants by penalized regression. Bioinformatics 6 Aug 2010 (doi:10.1093/bioinformatics/btq448).
77. Clark, T. G., De Iorio, M., Griffiths, R. C. & Farrall, M. Finding associations in dense genetic maps: a genetic algorithm approach. Hum. Hered. 60, 97-108 (2005).
78. Guo, W. & Li n, S. Generalized linear modeling with regularization for detecting common disease rare haplotype association. Genet. Epidemiol. 33, 308-316 (2009).
79. Luan, Y H. & Li, H. Z. Group additive regression models for genomic data analysis. Biostatistics 9, 100-113 (2008).
80. Kwee, L. C., Liu, D. W., Lin, X. H., Ghosh, D. & Epstein, M. P. A powerful and flexible multilocus association test for quantitative traits. Am. J. Hum. Genet. 82, 386-397 (2008).
81. Capanu, M. & Begg, C. B. Hierarchical modeling for estimating relative risks of rare genetic variants: properties of the pseudo-likelihood method. Biometrics 5 Aug 2010 (doi:10.1111/j.1541-0420.2010.01469.x).
82. Tibshirani, R. Regression shrinkage and selection via the Lasso. J. R. Stat. Soc. Series B Stat. Methodol. 58, 267-288 (1996).
83. Friedman, J. H. Fast sparse regression and classification. (Stanford Univ., California, 2008).
84. van der Laan, M. J., Polley, E. C. & Hubbard, A. E. Super learner. Stat Appl. Genet. Mol. Biol. 6, 2 5 (2007).
85. Dickson, S. P., Wang, K., Krantz, I., Hakonarson, H. & Goldstein, D. B. Rare variants create synthetic genome-wide associations. PLoS Biol. 8, e1000294 (2010).
86. Bansal, V., Libiger, O., Torkamani, A. & Schork, N. J. An application and empirical comparison of statistical analysis methods for associating rare variants to a complex phenotype. Pacific Symposium on Biocomputing Proceedings (in the press).
87. Wessel, J., Schork, A. J., Tiwari, H. K. & Schork, N. J. Powerful designs for genetic association studies that consider twins and sibling pairs with discordant genotypes. Genet. Epidemiol. 31, 789-796 (2007).
88. Nievergelt, C. M., Libiger, O. & Schork, N. J. Generalized analysis of molecular variance. PLoS Genet. 3, e51 (2007).
89. Moskvina, V., Craddock, N., Holmans, P., Owen, M. J. & O' Donovan, M. C. Effects of differential genotyping error rate on the type I error probability of case-control studies. Hum. Hered. 61, 55-64 (2006).
90. Zschocke, J. Dominant versus recessive: molecular mechanisms in metabolic disease. J. Inherit Metab. Dis. 31, 599-618 (2008).
91. Andres, A. M. et al. Understanding the accuracy of statistical haplotype inference with sequence data of known phase. Genet. Epidemiol. 31, 659-671 (2007).
92. Kim, J. H., Waterman, M. S. & Li, L. M. Accuracy assessment of diploid consensus sequences. IEEE/ACM Trans. Comput Biol. Bioinform. 4, 88-97 (2007).
93. Levy, S. et al. The diploid genome sequence of an individual human. PLoS Biol. 5, e254 (2007).
94. Price, A. L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nature Genet. 38, 904-909 (2006).
95. Kang, H. M. et al. Variance component model to account for sample structure in genome-wide association studies. Nature Genet. 42, 348-354 (2010).
96. Li, B. & Leal, S. M. Discovery of rare variants via sequencing: implications for the design of complex trait association studies. PLoS Genet. 5, e1000481 (2009).
97. Li, Y., Willer, C., Sanna, S. & Abecasis, G. Genotype imputation. Annu. Rev. Genomics Hum. Genet. 10, 387-406 (2009).
98. Wang, K. et al. Interpretation of association signals and identification of causal variants from genome-wide association studies. Am. J. Hum. Genet. 86, 730-742 (2010).
99. Efron, B. Correlation and large-sclae simultaneous significance testing J. Am. Stat Asso. 102, 92-103 (2007).
100. Sandelin, A., Wasserman, W. W. & Lenhard, B. ConSite: web-based prediction of regulatory elements using cross-species comparison. Nucleic Acids Res. 32, W249-W252 (2004).
101. Matys, V. et al. TRANSFAC® and its module TRANSCompel®: transcriptional gene regulation in eukaryotes. Nucleic Acids Res. 34, D108-D110 (2006).
102. Visel, A., Minovitsky, S., Dubchak, I. & Pennacchio, L. A VISTA Enhancer Browser\ a database of tissue-specific human enhancers. Nucleic Acids Res. 35, D88-D92 (2007).
103. Griffiths-Jones, S., Saini, H. K., van Dongen, S. & Enright, A. J. miRBase: tools for microRNA genomics. Nucleic Acids Res. 36, D154-D158 (2008).
104. Lewis, B. P., Burge, C. B. & Bartel, D. P. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120, 15-20 (2005).
105. Yeo, G. & Burge, C. B. Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals. J. Comput Biol. 11, 377-394 (2004).
106. Cartegni, L, Wang, J., Zhu, Z., Zhang, M. Q. & Krainer, A. R. ESEfinder: a web resource to identify exonic splicing enhancers. Nucleic Acids Res. 31, 3568-3571 (2003).
107. Fairbrother, W. G., Yeh, R. F., Sharp, P. A. & Burge, C. B. Predictive identification of exonic splicing enhancers in human genes. Science 297, 1007-1013 (2002).
108. Sironi, M. et al. Silencer elements as possible inhibitors of pseudoexon splicing. Nucleic Acids Res. 32, 1783-1791 (2004).
109. Wang, Z. et al. Systematic identification and analysis of exonic splicing silencers. Cell 119, 831-845 (2004).
110. Goren, A. et al. Comparative analysis identifies exonic splicing regulatory sequences-the complex definition of enhancers and silencers. Mol. Cell 22, 769-781 (2006).
111. Zhang, L. et al. Functional allelic heterogeneity and pleiotropy of a repeat polymorphism in tyrosine hydroxylase: prediction of catecholamines and response to stress in twins. Physiol. Genomics 19, 277-291 (2004).
112. Zhang, C., Li, W. H., Krainer, A. R. & Zhang, M. Q. RNA landscape of evolution for optimal exon and intron discrimination. Proc. Natl Acad. Sci. USA 105, 5797-5802 (2008).
113. Birney, E. et al. Identification and analysis of functional elements in 1 % of the human genome by the ENCODE pilot project. Nature 447, 799-816 (2007).
114. Kuhn, R. M. et al. The UCSC Genome Browser Database: update 2009. Nucleic Acids Res. 37, D755-D761 (2009).
115. Matthews, L. et al. Reactome knowledgebase of human biological pathways and processes. Nucleic Acids Res. 316, D16-D22 (2009).
116. Kanehisa, M., Goto, S., Furumichi, M., Tanabe, M. & Hirakawa, M. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res. 38, D35-D60 (2010).
117. Ashburner, M. et al. Gene ontology: tool for the unification of biology. Nature Genet. 25, 25-29 (2000).
118. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498-2504 (2003).
119. Dahlquist, K. D., Salomonis, N., Vranizan, K., Lawlor, S. C. & Conklin, B. R. GenMAPP, a new tool for viewing and analyzing microarray data on biological pathways. Nature Genet. 31, 19-20 (2002).
120. Dennis, G. Jr et al. DAVID: database for annotation, visualization, and integrated discovery. Genome Biol. 4, P3 (2003).
121. Suderman, M. & Hallett, M. Tools for visually exploring biological networks. Bioinformatics 23, 2651-2659 (2007).
122. Karchin, R. Next generation tools for the annotation of human SNPs. Brief. Bioinformatics 10, 35-52 (2009).
123. Plumpton, M. & Barnes, M. R. in Bioinformatics for Geneticists (ed. Barnes, M. R.) (John Wiley and Sons, New York, 2007).
124. Ng, P. C. & Henikoff, S. Predicting the effects of amino acid substitutions on protein function. Annu. Rev. Genomics Hum. Genet. 7, 61-80 (2006).
125. Andersen, M. C. et al. In silico detection of sequence variations modifying transcriptional regulation. PLoS Comput Biol. 4, e5 (2008).
126. Everitt, B. S. Cluster Analysis (John Wiley and Sons, New York, 2009).
127. Wong, K. M., Suchard, M. A. & Huelsenbeck, J. P. Alignment uncertainty and genomic analysis. Science 319, 473-476 (2008).
128. Libiger, O., Nievergelt, C. M. & Schork, N. J. Comparison of genetic distance measures using human SNP genotype data. Hum. Biol. 81, 389-406 (2009).
129. Hill, M. O. Diversity and evenness\ unifying notation and its consequences. Ecology 54, 427-432 (1973).
130. Keylock, C. J. Simpson diversity and the Shannon-Wiener index as special cases of a generalized entropy. Oikos 109, 203-207 (2005).
131. Lande, R. Statistics and partitioning of species diversity, and similarity among multiple communities. Oikos 76, 5-13 (1996).
132. Jost, L. et al. Partitioning diversity for conservation analyses. Divers. Distrib. 16, 65-76 (2010).
133. Johansen, C. T et al. Excess of rare variants in genes identified by genome-wide association study of hypertriglyceridemia. Nature Genet. 42, 684-687 (2010).
134. Romeo, S. et al. Rare loss-of-function mutations in ANGPTL family members contribute to plasma triglyceride levels in humans. J. Clin. Invest 119, 70-79 (2009).
135. Slatter, T L., Jones, G. T., Williams, M. J., van Rij, A. M. & McCormick, S. P. Novel rare mutations and promoter haplotypes in ABCA1 contribute to low-HDL-C levels. Clin. Genet. 73, 179-184 (2008).
136. Marini, N. J. et al. The prevalence of folate-remedial MTHFR enzyme variants in humans. Proc. Natl Acad. Sci. USA 105, 8055-8060 (2008).
137. Ji, W. et al. Rare independent mutations in renal salt handling genes contribute to blood pressure variation. Nature Genet. 40, 592-599 (2008).
138. Frikke-Schmidt, R., Sing, C. F., Nordestgaard, B. G., Steffensen, R. & Tybjaerg-Hansen, A. Subsets of SNPs define rare genotype classes that predict ischemic heart disease. Hum. Genet. 120, 865-877 (2007).
139. Azzopardi, D. et al. Multiple rare nonsynonymous variants in the adenomatous polyposis coli gene predispose to colorectal adenomas. Cancer Res. 68, 358-363 (2008).
140. Masson, E., Chen, J. M., Scotet, V., Le Marechal, C. & Ferec, C. Association of rare chymotrypsinogen C (CTRC) gene variations in patients with idiopathic chronic pancreatitis. Hum. Genet. 123, 83-91 (2008).
141. Ma, X. et al. Full-exon resequencing reveals Toll-like receptor variants contribute to human susceptibility to tuberculosis disease. PLoS ONE 2, e1318 (2007).
142. Ahituv, N. et al. Medical sequencing at the extremes of human body mass. Am. J. Hum. Genet. 80, 779-791 (2007).
143. Wang, J. et al. Resequencing genomic DNA of patients with severe hypertriglyceridemia (MIM 144650). Arterioscler. Thromb. Vasc. Biol. 27, 2450-2455 (2007).
144. Cohen, J. C., Boerwinkle, E., Mosley, T. H. Jr & Hobbs, H. H. Sequence variations in PCSK9, low LDL, and protection against coronary heart disease. N. Engl. J. Med. 354, 1264-1272 (2006).
145. Kotowski, I. K. et al. A spectrum of PCSK9 alleles contributes to plasma levels of low-density lipoprotein cholesterol. Am. J. Hum. Genet. 78, 410-422 (2006).
146. Cohen, J. C. et al. Multiple rare variants in NPC1L1 associated with reduced sterol absorption and plasma low-density lipoprotein levels. Proc. Natl Acad. Sci. USA 103, 1810-1815 (2006).
147. Cohen, J. et al. Low LDL cholesterol in individuals of African descent resulting from frequent nonsense mutations in PCSK9. Nature Genet. 37, 161-165 (2005).
148. Cohen, J. C. et al. Multiple rare alleles contribute to low plasma levels of HDL cholesterol. Science 305, 869-872 (2004).
149. Fearnhead, N. S. et al. Multiple rare variants in different genes account for multifactorial inherited susceptibility to colorectal adenomas. Proc. Natl Acad. Sci. USA 101, 15992-15997 (2004).
150. Calvo, S. E. et al. High-throughput, pooled sequencing identifies mutations in NUBPL and FOXRED1 in human complex I deficiency. Nature Genet. 5 Sept 2010 (doi:10.1038/ng.659).