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Finding the missing heritability of complex diseases

Abstract

Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, ‘missing’ heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.

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Figure 1: Feasibility of identifying genetic variants by risk allele frequency and strength of genetic effect (odds ratio).

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References

  1. Hardy, J. & Singleton, A. Genomewide association studies and human disease. N. Engl. J. Med. 360, 1759–1768 (2009)

    Article  CAS  Google Scholar 

  2. International HapMap Consortium. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861 (2007)

  3. Hindorff, L. A. et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl Acad. Sci. 106, 9362–9367 (2009)Comprehensive analysis of genomic annotations for disease-associated SNPs defined by GWAS, showing great majority of associated loci in intronic or intergenic regions of unknown function.

    Article  ADS  CAS  Google Scholar 

  4. Hindorff, L. A., Junkins, H. A., Mehta, J. P. & Manolio, T. A. A catalog of published genome-wide association studies. Available at 〈http://www.genome.gov/26525384〉 (accessed, 18 September 2009)

  5. Hirschhorn, J. N., Lohmueller, K., Byrne, E. & Hirschhorn, K. A comprehensive review of genetic association studies. Genet. Med. 4, 45–61 (2002)

    Article  CAS  Google Scholar 

  6. Todd, J. A. Statistical false positive or true disease pathway? Nature Genet. 38, 731–733 (2006)

    Article  CAS  Google Scholar 

  7. Corder, E. H. et al. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science 261, 921–923 (1993)

    Article  ADS  CAS  Google Scholar 

  8. Lifton, R. P. Genetic dissection of human blood pressure variation: common pathways from rare phenotypes. Harvey Lect. 100, 71–101 (2004)

    PubMed  Google Scholar 

  9. Altmüller, J., Palmer, L. J., Fischer, G., Scherb, H. & Wjst, M. Genome-wide scans of complex human diseases: true linkage is hard to find. Am. J. Hum. Genet. 69, 936–950 (2001)

    Article  Google Scholar 

  10. Risch, N. & Merikangas, K. The future of genetic studies of complex human diseases. Science 273, 1516–1517 (1996)

    Article  ADS  CAS  Google Scholar 

  11. Risch, N. J. Searching for genetic determinants in the new millennium. Nature 405, 847–856 (2000)

    Article  CAS  Google Scholar 

  12. Reich, D. E. & Lander, E. S. On the allelic spectrum of human disease. Trends Genet. 17, 502–510 (2001)

    Article  CAS  Google Scholar 

  13. Collins, F. S., Guyer, M. S. & Chakravarti, A. Variations on a theme: cataloging human DNA sequence variation. Science 278, 1580–1581 (1997)

    Article  ADS  CAS  Google Scholar 

  14. Pritchard, J. K. Are rare variants responsible for susceptibility to common diseases? Am. J. Hum. Genet. 69, 124–137 (2001)

    Article  CAS  Google Scholar 

  15. Visscher, P. M. Sizing up human height variation. Nature Genet. 40, 489–490 (2008)

    Article  CAS  Google Scholar 

  16. Collins, F. S. 2005 William Allan Award address. No longer just looking under the lamppost. Am. J. Hum. Genet. 79, 421–426 (2006)

    Article  CAS  Google Scholar 

  17. Pearson, T. A. & Manolio, T. A. How to interpret a genome-wide association study. J. Am. Med. Assoc. 299, 1335–1344 (2008)

    Article  CAS  Google Scholar 

  18. Maher, B. Personal genomes: The case of the missing heritability. Nature 456, 18–21 (2008)

    Article  CAS  Google Scholar 

  19. Pritchard, J. K. & Cox, N. J. The allelic architecture of human disease genes: common disease-common variant.or not? Hum. Mol. Genet. 11, 2417–2423 (2002)

    Article  CAS  Google Scholar 

  20. Jakobsdottir, J., Gorin, M. B., Conley, Y. P., Ferrell, R. E. & Weeks, D. E. Interpretation of genetic association studies: markers with replicated highly significant odds ratios may be poor classifiers. PLoS Genet. 5, e1000337 (2009)

    Article  Google Scholar 

  21. Barrett, J. C. et al. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn’s disease. Nature Genet. 40, 955–962 (2008)

    Article  CAS  Google Scholar 

  22. Kathiresan, S. et al. Common variants at 30 loci contribute to polygenic dyslipidemia. Nature Genet. 41, 56–65 (2009)

    Article  CAS  Google Scholar 

  23. Zeggini, E. et al. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nature Genet. 40, 638–645 (2008)

    Article  CAS  Google Scholar 

  24. Ahmed S. et al. Newly discovered breast cancer susceptibility loci on 3p24 and 17q23.2. Nature Genet. 41, 585–590 (2009)

    Article  ADS  Google Scholar 

  25. Lord, C., Cook, E. H., Leventhal, B. L. & Amaral, D. G. Autism spectrum disorders. Neuron 28, 355–363 (2000)

    Article  CAS  Google Scholar 

  26. Cooper, J. D. et al. Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci. Nature Genet. 40, 1399–1401 (2008)

    Article  CAS  Google Scholar 

  27. Barrett J. C. et al. Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nature Genet. 41, 703–707 (2009)

    Article  Google Scholar 

  28. Keller, M. C. & Miller, G. Resolving the paradox of common, harmful, heritable mental disorders: which evolutionary genetic models work best? Behav. Brain Sci. 29, 385–404 (2006)

    Article  Google Scholar 

  29. Gibson, G. & Wagner, G. Canalization in evolutionary genetics: a stabilizing theory? Bioessays 22, 372–380 (2000)

    Article  CAS  Google Scholar 

  30. Gibson, G. Decanalization and the origin of complex disease. Nature Rev. Genet. 10, 134–140 (2009)

    Article  CAS  Google Scholar 

  31. Campbell, M. C. & Tishkoff, S. A. African genetic diversity: implications for human demographic history, modern human origins, and complex disease mapping. Annu. Rev. Genomics Hum. Genet. 9, 403–433 (2008)

    Article  CAS  Google Scholar 

  32. Lusis, A. J. & Pajukanta, P. A treasure trove for lipoprotein biology. Nature Genet. 40, 129–130 (2008)

    Article  CAS  Google Scholar 

  33. Zheng, W. et al. Genome-wide association study identifies a new breast cancer susceptibility locus at 6q25.1. Nature Genet. 41, 324–328 (2009)

    Article  CAS  Google Scholar 

  34. Yasuda, K. et al. Variants in KCNQ1 are associated with susceptibility to type 2 diabetes mellitus. Nature Genet. 40, 1092–1097 (2008)

    Article  CAS  Google Scholar 

  35. Sabatti, C. et al. Genome-wide association analysis of metabolic traits in a birth cohort from a founder population. Nature Genet. 41, 35–46 (2009)

    Article  CAS  Google Scholar 

  36. Falconer, D. S. & Mackay, T. F. C. Introduction to Quantitative Genetics Addison 123 (Wesley Longman Ltd, 1996)

    Google Scholar 

  37. Visscher, P. M., Hill, W. G. & Wray, N. R. Heritability in the genomics era–concepts and misconceptions. Nature Rev. Genet. 9, 255–266 (2008)Detailed review of strengths, weaknesses and controversies in estimations of heritability from human, agricultural and experimental studies.

    Article  CAS  Google Scholar 

  38. Visscher, P. M. et al. Assumption-free estimation of heritability from genome-wide identity-by-descent sharing between full siblings. PLoS Genet. 2, e41 (2006)

    Article  Google Scholar 

  39. Meuwissen, T. H., Hayes, B. J. & Goddard, M. E. Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 1819–1829 (2001)

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Lee, S. H., van der Werf, J. H., Hayes, B. J., Goddard, M. E. & Visscher, P. M. Predicting unobserved phenotypes for complex traits from whole-genome SNP data. PLoS Genet. 4, e1000231 (2008)

    Article  Google Scholar 

  41. McCarthy, M. I. & Hirschhorn, J. N. Genome-wide association studies: potential next steps on a genetic journey. Hum. Mol. Genet. 17 (R2). R156–R165 (2008)Insightful review of initial findings from GWAS, the heritability that they do and do not explain, and potential for progress from other GWAS, identification of rare variants, and studies of epigenetics and gene expression and function.

    Article  CAS  Google Scholar 

  42. McCarthy, M. I. et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature Rev. Genet. 9, 356–369 (2008)

    Article  CAS  Google Scholar 

  43. Mardis, E. R. The impact of next-generation sequencing technology on genetics. Trends Genet. 24, 133–141 (2008)

    Article  CAS  Google Scholar 

  44. Abecasis, G. R. The 1000 Genomes Project: analysis of pilot datasets. Biology of Genomes page 246 (Cold Spring Harbor Laboratory, 5–9 May 2009)

  45. 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)

    Article  CAS  Google Scholar 

  46. 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)

    Article  ADS  CAS  Google Scholar 

  47. Romeo, S. et al. Population-based resequencing of ANGPTL4 uncovers variations that reduce triglycerides and increase HDL. Nature Genet. 39, 513–516 (2007)

    Article  CAS  Google Scholar 

  48. Haiman, C. A. et al. Multiple regions within 8q24 independently affect risk for prostate cancer. Nature Genet. 39, 638–644 (2007)

    Article  CAS  Google Scholar 

  49. 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)Four rare variants in IFIH1 independently lowering risk of type 1 diabetes were identified by sequencing exons and splice sites of 10 genes under GWA-defined peaks, demonstrating the power of intensive sequencing to identify potentially causative variants in follow-up of GWAS.

    Article  ADS  CAS  Google Scholar 

  50. 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)

    Article  CAS  Google Scholar 

  51. Crawford, M. H. Anthropological Genetics: Theory, Methods and Applications 341 (Cambridge Univ. Press, 2006)

    Book  Google Scholar 

  52. McCarroll, S. A. Extending genome-wide association studies to copy-number variation. Hum. Mol. Genet. 17 (R2). R135–R142 (2008)

    Article  CAS  Google Scholar 

  53. Scherer, S. W. et al. Challenges and standards in integrating surveys of structural variation. Nature Genet. 39 (suppl.). S7–S15 (2007)

    Article  CAS  Google Scholar 

  54. Kidd, J. M. et al. Mapping and sequencing of structural variation from eight human genomes. Nature 453, 56–64 (2008)

    Article  ADS  CAS  Google Scholar 

  55. McCarroll, S. A. et al. Integrated detection and population-genetic analysis of SNPs and copy number variation. Nature Genet. 40, 1166–1174 (2008)Initial map of CNVs demonstrating high proportion (>80%) of inter-individual differences in copy number differences due to common CNVs of MAF 5% or greater; >99% of CNVs probably derived from inheritance rather than de novo mutation; and most common diallelic CNVs in strong linkage disequilibrium with common SNPs.

    Article  CAS  Google Scholar 

  56. de Vries, B. B. et al. Diagnostic genome profiling in mental retardation. Am. J. Hum. Genet. 77, 606–616 (2005)

    Article  CAS  Google Scholar 

  57. Sebat, J. et al. Strong association of de novo copy number mutations with autism. Science 316, 445–449 (2007)

    Article  ADS  CAS  Google Scholar 

  58. Xu, B. et al. Strong association of de novo copy number mutations with sporadic schizophrenia. Nature Genet. 40, 880–885 (2008)

    Article  CAS  Google Scholar 

  59. Weiss, L. A. et al. Association between microdeletion and microduplication at 16p11.2 and autism. N. Engl. J. Med. 358, 667–675 (2008)

    Article  CAS  Google Scholar 

  60. Stefansson, H. et al. Large recurrent microdeletions associated with schizophrenia. Nature 455, 232–236 (2008)

    Article  ADS  CAS  Google Scholar 

  61. Willer, C. J. et al. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nature Genet. 41, 25–34 (2009)

    Article  CAS  Google Scholar 

  62. Abrahams, B. S. & Geschwind, D. H. Advances in autism genetics: on the threshold of a new neurobiology. Nature Rev. Genet. 9, 341–355 (2008)

    Article  CAS  Google Scholar 

  63. Kong, A. et al. Detection of sharing by descent, long-range phasing and haplotype imputation. Nature Genet. 40, 1068–1075 (2008)

    Article  CAS  Google Scholar 

  64. Thomas, A., Camp, N. J., Farnham, J. M., Allen-Brady, K. & Cannon-Albright, L. A. Shared genomic segment analysis. Mapping disease predisposition genes in extended pedigrees using SNP genotype assays. Ann. Hum. Genet. 72, 279–287 (2008)

    Article  CAS  Google Scholar 

  65. Roeder, K., Bacanu, S. A., Wasserman, L. & Devlin, B. Using linkage genome scans to improve power of association in genome scans. Am. J. Hum. Genet. 78, 243–252 (2006)

    Article  CAS  Google Scholar 

  66. MacLean, C. J., Sham, P. C. & Kendler, K. S. Joint linkage of multiple loci for a complex disorder. Am. J. Hum. Genet. 53, 353–366 (1993)

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Zhao, J., Jin, L. & Xiong, M. Test for interaction between two unlinked loci. Am. J. Hum. Genet. 79, 831–845 (2006)

    Article  CAS  Google Scholar 

  68. Waters, K. M. et al. Generalizability of associations from prostate cancer genome-wide association studies in multiple populations. Cancer Epidemiol. Biomarkers Prev. 18, 1285–1289 (2009)

    Article  CAS  Google Scholar 

  69. Clayton, D. G. Prediction and interaction in complex disease genetics: experience in type 1 diabetes. PLoS Genet. 5, e1000540 (2009)

    Article  Google Scholar 

  70. Khoury, M. J. et al. The scientific foundation for personal genomics: recommendations from a National Institutes of Health-Centers for Disease Control and Prevention multidisciplinary workshop. Genet. Med. 11, 559–567 (2009)

    Article  CAS  Google Scholar 

  71. Pharoah, P. D., Antoniou, A. C., Easton, D. F. & Ponder, B. A. Polygenes, risk prediction, and targeted prevention of breast cancer. N. Engl. J. Med. 358, 2796–2803 (2008)

    Article  CAS  Google Scholar 

  72. Maller, J. et al. Common variation in three genes, including a noncoding variant in CFH, strongly influences risk of age-related macular degeneration. Nature Genet. 38, 1055–1059 (2006)

    Article  CAS  Google Scholar 

  73. International Consortium for Systemic Lupus Erythematosus Genetics (SLEGEN). Genome-wide association scan in women with systemic lupus erythematosus identifies susceptibility variants in ITGAM, PXK, KIAA1542 and other loci. Nature Genet. 40, 204–210 (2008)

  74. Zeggini, E. et al. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nature Genet. 40, 638–645 (2008)

    Article  CAS  Google Scholar 

  75. Kathiresan, S. et al. Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans. Nature Genet. 40, 189–197 (2008)

    Article  CAS  Google Scholar 

  76. Myocardial Infarction Genetics Consortium. Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants. Nature Genet. 41, 334–341 (2009)

  77. Prokopenko, I. et al. Variants in MTNR1B influence fasting glucose levels. Nature Genet. 41, 77–81 (2009)

    Article  CAS  Google Scholar 

  78. International Schizophrenia Consortium. Rare chromosomal deletions and duplications increase risk of schizophrenia. Nature 455, 237–241 (2008)

  79. Mefford, H. C. et al. Recurrent rearrangements of chromosome 1q21.1 and variable pediatric phenotypes. N. Engl. J. Med. 359, 1685–1699 (2008)

    Article  CAS  Google Scholar 

  80. Helbig, I. et al. 15q13.3 microdeletions increase risk of idiopathic generalized epilepsy. Nature Genet. 41, 160–162 (2009)

    Article  CAS  Google Scholar 

  81. Sharp, A. J. et al. A recurrent 15q13.3 microdeletion syndrome associated with mental retardation and seizures. Nature Genet. 40, 322–328 (2008)

    Article  CAS  Google Scholar 

  82. Bassett, A. S., Marshall, C. R., Lionel, A. C., Chow, E. W. & Scherer, S. W. Copy number variations and risk for schizophrenia in 22q11.2 deletion syndrome. Hum. Mol. Genet. 17, 4045–4053 (2008)

    Article  CAS  Google Scholar 

  83. McCarroll, S. A. et al. Deletion polymorphism upstream of IRGM associated with altered IRGM expression and Crohn’s disease. Nature Genet. 40, 1107–1112 (2008)

    Article  CAS  Google Scholar 

  84. de Cid, R. et al. Deletion of the late cornified envelope LCE3B and LCE3C genes as a susceptibility factor for psoriasis. Nature Genet. 41, 211–215 (2009)

    Article  CAS  Google Scholar 

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Acknowledgements

This paper is inspired by the deliberations of an expert working group convened by the National Human Genome Research Institute (NHGRI) on 2–3 February 2009, to address the heritability unexplained in GWAS. The authors acknowledge the participation of J. C. Cohen, M. Daly and A. P. Feinberg in the workshop.

Author Contributions T.A.M., F.S.C., N.J.C., D.B.G., L.A.H., D.J.H., M.I.M. and E.M.R. planned and participated in the workshop; L.R.C., A.C., J.H.C., A.E.G., A.K., L.K., E.M., C.N.R., M.S., D.V., A.S.W., M.B., A.G.C., E.E.E., G.G., J.L.H., T.F.C.M., S.A.M. and P.M.V. participated in the workshop; T.A.M., P.M.V., G.G., M.I.M., E.E.E., T.F.C.M. and S.A.M. drafted the manuscript; F.S.C., N.J.C., D.B.G., L.A.H., D.J.H., E.M.R., L.R.C., A.C., J.H.C., A.P.R., A.E.G., A.K., L.K., E.M., C.N.R., M.S., D.V., A.S.W., M.B., A.G.C. and J.L.H. critically reviewed and revised the manuscript for content.

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Correspondence to Teri A. Manolio.

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[COMPETING INTERESTS: L.R.C. is employed by a pharmaceutical company; A.K. is an employee of decode Genetics, a commercial company that participates in gene discoveries and the development of diagnostic tests. He also owns stocks of the company. E.E.E. is a Pacific Biosciences SAB member. A.C. is a member of the Affymetrix SAB, a potential conflict of interest overseen by Johns Hopkins University policies.]

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Manolio, T., Collins, F., Cox, N. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009). https://doi.org/10.1038/nature08494

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