Rediscovering the value of families for psychiatric genetics research.
Journal
Molecular psychiatry
ISSN: 1476-5578
Titre abrégé: Mol Psychiatry
Pays: England
ID NLM: 9607835
Informations de publication
Date de publication:
04 2019
04 2019
Historique:
received:
21
11
2017
accepted:
26
03
2018
revised:
11
01
2018
pubmed:
30
6
2018
medline:
4
12
2019
entrez:
30
6
2018
Statut:
ppublish
Résumé
As it is likely that both common and rare genetic variation are important for complex disease risk, studies that examine the full range of the allelic frequency distribution should be utilized to dissect the genetic influences on mental illness. The rate limiting factor for inferring an association between a variant and a phenotype is inevitably the total number of copies of the minor allele captured in the studied sample. For rare variation, with minor allele frequencies of 0.5% or less, very large samples of unrelated individuals are necessary to unambiguously associate a locus with an illness. Unfortunately, such large samples are often cost prohibitive. However, by using alternative analytic strategies and studying related individuals, particularly those from large multiplex families, it is possible to reduce the required sample size while maintaining statistical power. We contend that using whole genome sequence (WGS) in extended pedigrees provides a cost-effective strategy for psychiatric gene mapping that complements common variant approaches and WGS in unrelated individuals. This was our impetus for forming the "Pedigree-Based Whole Genome Sequencing of Affective and Psychotic Disorders" consortium. In this review, we provide a rationale for the use of WGS with pedigrees in modern psychiatric genetics research. We begin with a focused review of the current literature, followed by a short history of family-based research in psychiatry. Next, we describe several advantages of pedigrees for WGS research, including power estimates, methods for studying the environment, and endophenotypes. We conclude with a brief description of our consortium and its goals.
Identifiants
pubmed: 29955165
doi: 10.1038/s41380-018-0073-x
pii: 10.1038/s41380-018-0073-x
pmc: PMC7028329
mid: NIHMS1558211
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
523-535Subventions
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : MH105632
Pays : International
Organisme : Medical Research Council
ID : G0700704
Pays : United Kingdom
Organisme : NIBIB NIH HHS
ID : R01 EB015611
Pays : United States
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : MH105630
Pays : International
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : MH105634
Pays : International
Organisme : NIMH NIH HHS
ID : U01 MH105632
Pays : United States
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : MH042191
Pays : International
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : MH083824
Pays : International
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : MH078143
Pays : International
Organisme : NIMH NIH HHS
ID : R01 MH061622
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH106324
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH083824
Pays : United States
Organisme : Medical Research Council
ID : MR/K026992/1
Pays : United Kingdom
Organisme : NIMH NIH HHS
ID : R01 MH078111
Pays : United States
Organisme : NIMH NIH HHS
ID : U01 MH105634
Pays : United States
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : MH061622
Pays : International
Organisme : NIMH NIH HHS
ID : R01 MH042191
Pays : United States
Organisme : NCRR NIH HHS
ID : C06 RR020547
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH063480
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH078143
Pays : United States
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : MH063480
Pays : International
Organisme : NIMH NIH HHS
ID : U01 MH105630
Pays : United States
Références
Sullivan PF, Agrawal A, Bulik CM, Andreassen OA, Borglum AD, Breen G, et al. Psychiatric genomics: an update and an agenda. Am J Psychiatry. 2017;175:15–27. appiajp201717030283
pubmed: 28969442
pmcid: 5756100
Hirschhorn JN, Daly MJ. Genome-wide association studies for common diseases and complex traits. Nat Rev Genet. 2005;6:95–108.
pubmed: 15716906
Cross-Disorder Group of the Psychiatric Genomics C. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet. 2013;381:1371–9.
Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Loh PR, et al. An atlas of genetic correlations across human diseases and traits. Nat Genet. 2015;47:1236–41.
pubmed: 4797329
pmcid: 4797329
Flint J, Mott R. Finding the molecular basis of quantitative traits: successes and pitfalls. Nat Rev Genet. 2001;2:437–45.
pubmed: 11389460
Pritchard JK, Cox NJ. The allelic architecture of human disease genes: common disease-common variant…or not? Hum Mol Genet. 2002;11:2417–23.
pubmed: 12351577
McClellan J, King MC. Genomic analysis of mental illness: a changing landscape. JAMA. 2010;303:2523–4.
pubmed: 20571020
Sanders SJ, Neale B, Huang H, Werling D, An J-Y, Dong S, et al. Whole genome sequencing in psychiatric disorders: the WGSPD consortium. Nat Neurosci. 2017;12:1661-1668.
pubmed: 29184211
Lander ES, Schork NJ. Genetic dissection of complex traits. Science. 1994;265:2037–48.
pubmed: 8091226
Boyle EA, Li YI, Pritchard JK. An expanded view of complex traits: from polygenic to omnigenic. Cell. 2017;169:1177–86.
pubmed: 5536862
pmcid: 5536862
Gibson G. Rare and common variants: twenty arguments. Nat Rev Genet. 2011;13:135–45.
Freimer N, Sabatti C. The use of pedigree, sib-pair and association studies of common diseases for genetic mapping and epidemiology. Nat Genet. 2004;36:1045–51.
pubmed: 15454942
Cirulli ET, Goldstein DB. Uncovering the roles of rare variants in common disease through whole-genome sequencing. Nat Rev Genet. 2010;11:415–25.
pubmed: 20479773
Marth GT, Yu F, Indap AR, Garimella K, Gravel S, Leong WF, et al. The functional spectrum of low-frequency coding variation. Genome Biol. 2011;12:R84.
pubmed: 21917140
pmcid: 3308047
McClellan J, King MC. Genetic heterogeneity in human disease. Cell. 2010;141:210–7.
pubmed: 20403315
Bodmer W, Bonilla C. Common and rare variants in multifactorial susceptibility to common diseases. Nat Genet. 2008;40:695–701.
pubmed: 18509313
pmcid: 18509313
Tennessen JA, Bigham AW, O’Connor TD, Fu W, Kenny EE, Gravel S, et al. Evolution and functional impact of rare coding variation from deep sequencing of human exomes. Science. 2012;337:64–69.
pubmed: 22604720
pmcid: 3708544
Veltman JA, Brunner HG. De novo mutations in human genetic disease. Nat Rev Genet. 2012;13:565–75.
pubmed: 22805709
MacArthur DG, Balasubramanian S, Frankish A, Huang N, Morris J, Walter K, et al. A systematic survey of loss-of-function variants in human protein-coding genes. Science. 2012;335:823–8.
pubmed: 22344438
pmcid: 3299548
Marouli E, Graff M, Medina-Gomez C, Lo KS, Wood AR, Kjaer TR, et al. Rare and low-frequency coding variants alter human adult height. Nature. 2017;542:186–90.
pubmed: 28146470
pmcid: 5302847
Pritchard JK. Are rare variants responsible for susceptibility to complex diseases? Am J Hum Genet. 2001;69:124–37.
pubmed: 11404818
pmcid: 11404818
Sveinbjornsson G, Albrechtsen A, Zink F, Gudjonsson SA, Oddson A, Masson G, et al. Weighting sequence variants based on their annotation increases power of whole-genome association studies. Nat Genet. 2016;48:314–7.
pubmed: 26854916
pmcid: 26854916
Chakravarti A, Clark AG, Mootha VK. Distilling pathophysiology from complex disease genetics. Cell. 2013;155:21–26.
pubmed: 24074858
pmcid: 4244836
Schork NJ, Murray SS, Frazer KA, Topol EJ. Common vs. rare allele hypotheses for complex diseases. Curr Opin Genet Dev. 2009;19:212–9.
pubmed: 19481926
pmcid: 19481926
Bansal V, Libiger O, Torkamani A, Schork NJ. Statistical analysis strategies for association studies involving rare variants. Nat Rev Genet. 2010;11:773–85.
pubmed: 20940738
pmcid: 3743540
Blangero J. Localization and identification of human quantitative trait loci: king harvest has surely come. Curr Opin Genet Dev. 2004;14:233–40.
pubmed: 15172664
Lee S, Abecasis GR, Boehnke M, Lin X. Rare-variant association analysis: study designs and statistical tests. Am J Hum Genet. 2014;95:5–23.
pubmed: 24995866
pmcid: 4085641
Bailey-Wilson JE, Wilson AF. Linkage analysis in the next-generation sequencing era. Hum Hered. 2011;72:228–36.
pubmed: 22189465
pmcid: 3267991
Wijsman EM. The role of large pedigrees in an era of high-throughput sequencing. Hum Genet. 2012;131:1555–63.
pubmed: 22714655
pmcid: 3638020
Epstein MP, Duncan R, Ware EB, Jhun MA, Bielak LF, Zhao W, et al. A statistical approach for rare-variant association testing in affected sibships. Am J Hum Genet. 2015;96:543–54.
pubmed: 25799106
pmcid: 4385187
Knight S, Abo RP, Abel HJ, Neklason DW, Tuohy TM, Burt RW, et al. Shared genomic segment analysis: the power to find rare disease variants. Ann Hum Genet. 2012;76:500–9.
pubmed: 22989048
Schizophrenia Working Group of the Psychiatric Genomics C. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421–7.
Charney AW, Ruderfer DM, Stahl EA, Moran JL, Chambert K, Belliveau RA, et al. Evidence for genetic heterogeneity between clinical subtypes of bipolar disorder. Transl Psychiatry. 2017;7:e993.
pubmed: 28072414
pmcid: 5545718
Hou L, Bergen SE, Akula N, Song J, Hultman CM, Landen M, et al. Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder. Hum Mol Genet. 2016;25:3383–94.
pubmed: 27329760
pmcid: 5179929
Wray NR, et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depressive disorder. Nat Genet. 2018;50:668-681.
Hall L, Adams M, Arnau-Soler A, Clarke T, Howard D, Zeng Y, et al. Genome-wide meta-analyses of stratified depression in generation Scotland and UK biobank. bioRxiv. 2017;8:9.
Hyde CL, Nagle MW, Tian C, Chen X, Paciga SA, Wendland JR, et al. Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nat Genet. 2016;48:1031–6.
pubmed: 27479909
pmcid: 27479909
Duncan LE, Ratanatharathorn A, Aiello AE, Almli LM, Amstadter AB, Ashley-Koch AE, et al. Largest GWAS of PTSD (N = 20,070) yields genetic overlap with schizophrenia and sex differences in heritability. Mol Psychiatry. 2018;23:666-673.
pubmed: 28439101
pmcid: 5696105
Demontis D, Walters R, Martin J, Mattheisen M, Als T, Agerbo E, et al. Discovery of the first genome-wide significant risk loci for ADHD. bioRxiv 2017.
Autism Spectrum Disorders Working Group of The Psychiatric Genomics C. Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia. Mol Autism. 2017;8:21.
Manolio TA. Genomewide association studies and assessment of the risk of disease. N Engl J Med. 2010;363:166–76.
pubmed: 20647212
Manolio T, Collins F, Cox N, Goldstein D, Hindorff L, Hunter D, et al. Finding the missing heritability of complex diseases. Nature. 2009;461:747–53.
pubmed: 2831613
pmcid: 2831613
Fisher RA. The correlation between relatives on the supposition of Mendelian inheritance. Trans R Soc Edinb. 1918;52:399–433.
Evans DM, Visscher PM, Wray NR. Harnessing the information contained within genome-wide association studies to improve individual prediction of complex disease risk. Hum Mol Genet. 2009;18:3525–31.
pubmed: 19553258
Purcell S, Wray N, Stone J, Visscher P, O’Donovan M, Sullivan P, et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature. 2009;460:748–52.
pubmed: 19571811
Wray NR, Yang J, Hayes BJ, Price AL, Goddard ME, Visscher PM. Pitfalls of predicting complex traits from SNPs. Nat Rev Genet. 2013;14:507–15.
pubmed: 23774735
pmcid: 4096801
Nelson MR, Tipney H, Painter JL, Shen J, Nicoletti P, Shen Y, et al. The support of human genetic evidence for approved drug indications. Nat Genet. 2015;47:856–60.
pubmed: 26121088
Breen G, Li Q, Roth BL, O’Donnell P, Didriksen M, Dolmetsch R, et al. Translating genome-wide association findings into new therapeutics for psychiatry. Nat Neurosci. 2016;19:1392–6.
pubmed: 27786187
pmcid: 5676453
Hyman SE. Revolution stalled. Sci Transl Med. 2012;4:155cm111.
Geschwind DH, State MW. Gene hunting in autism spectrum disorder: on the path to precision medicine. Lancet Neurol. 2015;14:1109–20.
pubmed: 25891009
pmcid: 4694565
Sanders SJ, Murtha MT, Gupta AR, Murdoch JD, Raubeson MJ, Willsey AJ, et al. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature. 2012;485:237–41.
pubmed: 22495306
pmcid: 22495306
Iossifov I, O’Roak BJ, Sanders SJ, Ronemus M, Krumm N, Levy D, et al. The contribution of de novo coding mutations to autism spectrum disorder. Nature. 2014;515:216–21.
pubmed: 4313871
pmcid: 4313871
De Rubeis S, He X, Goldberg AP, Poultney CS, Samocha K, Cicek AE, et al. Synaptic, transcriptional and chromatin genes disrupted in autism. Nature. 2014;515:209–15.
pubmed: 25363760
pmcid: 25363760
Sanders SJ. First glimpses of the neurobiology of autism spectrum disorder. Curr Opin Genet Dev. 2015;33:80–92.
pubmed: 26547130
Weiner DJ, Wigdor EM, Ripke S, Walters RK, Kosmicki JA, Grove J, et al. Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders. Nat Genet. 2017;49:978–85.
pubmed: 28504703
pmcid: 5552240
Shi H, Kichaev G, Pasaniuc B. Contrasting the genetic architecture of 30 complex traits from summary association data. Am J Hum Genet. 2016;99:139–53.
pubmed: 27346688
pmcid: 5005444
Singh T, Kurki MI, Curtis D, Purcell SM, Crooks L, McRae J, et al. Rare loss-of-function variants in SETD1A are associated with schizophrenia and developmental disorders. Nat Neurosci. 2016;19:571–7.
pubmed: 26974950
Genovese G, Fromer M, Stahl EA, Ruderfer DM, Chambert K, Landen M, et al. Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia. Nat Neurosci. 2016;19:1433–41.
pubmed: 27694994
pmcid: 5104192
Fromer M, Pocklington AJ, Kavanagh DH, Williams HJ, Dwyer S, Gormley P, et al. De novo mutations in schizophrenia implicate synaptic networks. Nature. 2014;506:179–84.
pubmed: 24463507
pmcid: 24463507
Malhotra D, Sebat J. CNVs: harbingers of a rare variant revolution in psychiatric genetics. Cell. 2012;148:1223–41.
pubmed: 22424231
pmcid: 3351385
Sebat J, Lakshmi B, Malhotra D, Troge J, Lese-Martin C, Walsh T, et al. Strong association of de novo copy number mutations with autism. Science. 2007;316:445–9.
pubmed: 17363630
pmcid: 2993504
Vissers LE, Gilissen C, Veltman JA. Genetic studies in intellectual disability and related disorders. Nat Rev Genet. 2016;17:9–18.
pubmed: 26503795
Marshall CR, Howrigan DP, Merico D, Thiruvahindrapuram B, Wu W, Greer DS, et al. Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects. Nat Genet. 2017;49:27–35.
Walsh T, McClellan JM, McCarthy SE, Addington AM, Pierce SB, Cooper GM, et al. Rare structural variants disrupt multiple genes in neurodevelopmental pathways in schizophrenia. Science. 2008;320:539–43.
pubmed: 18369103
Malhotra D, McCarthy S, Michaelson JJ, Vacic V, Burdick KE, Yoon S, et al. High frequencies of de novo CNVs in bipolar disorder and schizophrenia. Neuron. 2011;72:951–63.
pubmed: 22196331
pmcid: 3921625
Elia J, Gai X, Xie HM, Perin JC, Geiger E, Glessner JT, et al. Rare structural variants found in attention-deficit hyperactivity disorder are preferentially associated with neurodevelopmental genes. Mol Psychiatry. 2010;15:637–46.
Karayiorgou M, Morris MA, Morrow B, Shprintzen RJ, Goldberg R, Borrow J, et al. Schizophrenia susceptibility associated with interstitial deletions of chromosome 22q11. Proc Natl Acad Sci USA. 1995;92:7612–6.
pubmed: 7644464
Bassett AS, Lowther C, Merioo D, Costain G, Chow EWC, van Amelsvoort T, et al. Rare genome-wide copy number variation and expression of Schizophrenia in 22q11.2 deletion syndrome. Am J Psychiatry. 2017;174:1054-1063
pubmed: 28750581
Baron M, Risch N, Hamburger R, Mandel B, Kushner S, Newman M, et al. Genetic linkage between X-chromosome markers and bipolar affective illness. Nature. 1987;326:289–92.
pubmed: 3493438
Egeland JA, Gerhard DS, Pauls DL, Sussex JN, Kidd KK, Allen CR, et al. Bipolar affective disorders linked to DNA markers on chromosome 11. Nature. 1987;325:783–7.
pubmed: 2881209
Kelsoe JR, Ginns EI, Egeland JA, Gerhard DS, Goldstein AM, Bale SJ, et al. Re-evaluation of the linkage relationship between chromosome 11p loci and the gene for bipolar affective disorder in the Old Order Amish. Nature. 1989;342:238–43.
pubmed: 2682265
Gershon ES. Marker genotyping errors in old data on X-linkage in bipolar illness. Biol Psychiatry. 1991;29:721–9.
pubmed: 1888383
Burmeister M, McInnis MG, Zollner S. Psychiatric genetics: progress amid controversy. Nat Rev Genet. 2008;9:527–40.
pubmed: 18560438
Risch N. Genetic linkage and complex diseases, with special reference to psychiatric disorders. Genet Epidemiol. 1990;7:3–16. discussion 17-45
pubmed: 2184091
Risch N, Merikangas K. The future of genetic studies of complex human diseases. Science. 1996;273:1516–7.
pubmed: 8801636
Popejoy AB, Fullerton SM. Genomics is failing on diversity. Nature. 2016;538:161–4.
pubmed: 27734877
pmcid: 5089703
Olvera RL, Bearden CE, Velligan DI, Almasy L, Carless MA, Curran JE, et al. Common genetic influences on depression, alcohol, and substance use disorders in Mexican-American families. Am J Med Genet B Neuropsychiatr Genet. 2011;156B:561–8.
pubmed: 21557468
McKay DR, Knowles EE, Winkler AA, Sprooten E, Kochunov P, Olvera RL, et al. Influence of age, sex and genetic factors on the human brain. Brain Imaging Behav. 2014;8:143–52.
pubmed: 24297733
pmcid: 4011973
Hinrichs AL, Suarez BK. Incorporating linkage information into a common disease/rare variant framework. Genet Epidemiol. 2011;35(Suppl 1):S74–79.
pubmed: 22128063
pmcid: 4558895
Wilson AF, Ziegler A. Lessons learned from Genetic Analysis Workshop 17: transitioning from genome-wide association studies to whole-genome statistical genetic analysis. Genet Epidemiol. 2011;35(Suppl 1):S107–114.
pubmed: 22128050
pmcid: 3277851
Purcell SM, Moran JL, Fromer M, Ruderfer D, Solovieff N, Roussos P, et al. A polygenic burden of rare disruptive mutations in schizophrenia. Nature. 2014;506:185–90.
pubmed: 4136494
pmcid: 4136494
Blangero J, Diego VP, Dyer TD, Almeida M, Peralta J, Kent JW, et al. A kernel of truth: statistical advances in polygenic variance component models for complex human pedigrees. Adv Genet. 2013;81:1–31.
pubmed: 23419715
pmcid: 4019427
Teng J, Risch N. The relative power of family based and case-control designs for linkage disequilibrium studies of complex human diseases. II. Individual genotyping. Genome Res. 1999;9:234–41.
pubmed: 10077529
Zo¨llner S. Sampling strategies for rare variant tests in case-control studies. Eur J Hum Genet. 2012;20:1085–91.
Wijsman EM. Family-based approaches: design, imputation, analysis, and beyond. BMC Genet. 2016;17(Suppl 2):9.
pubmed: 26866700
pmcid: 4895701
Wijsman E, Amos C. Genetic analysis of simulated oligogenic traits in nuclear families and extended pedigrees: summary of GAW10 contributions. Genet Epidemiol. 1997;14:719–35.
pubmed: 9433569
Gagnon F, Roslin NM, Lemire M. Successful identification of rare variants using oligogenic segregation analysis as a prioritizing tool for whole-exome sequencing studies. BMC Proc. 2011;5(Suppl 9):S11.
pubmed: 22373114
pmcid: 3287833
Simpson CL, Justice CM, Krishnan M, Wojciechowski R, Sung H, Cai J, et al. Old lessons learned anew: family-based methods for detecting genes responsible for quantitative and qualitative traits in the Genetic Analysis Workshop 17 mini-exome sequence data. BMC Proc. 2011;5(Suppl 9):S83.
pubmed: 22373393
pmcid: 3287924
Li M, Boehnke M, Abecasis GR. Efficient study designs for test of genetic association using sibship data and unrelated cases and controls. Am J Hum Genet. 2006;78:778–92.
pubmed: 16642434
pmcid: 1474028
Saad M, Wijsman EM. Power of family-based association designs to detect rare variants in large pedigrees using imputed genotypes. Genet Epidemiol. 2014;38:1–9.
pubmed: 24243664
Laird NM, Lange C. Family-based designs in the age of large-scale gene-association studies. Nat Rev Genet. 2006;7:385–94.
pubmed: 16619052
Ionita-Laza I, Lee S, Makarov V, Buxbaum JD, Lin X. Family-based association tests for sequence data, and comparisons with population-based association tests. Eur J Hum Genet. 2013;21:1158–62.
pubmed: 23386037
pmcid: 3778346
Mathieson I, McVean G. Differential confounding of rare and common variants in spatially structured populations. Nat Genet. 2012;44:243–6.
pubmed: 22306651
pmcid: 3303124
Liu Q, Nicolae DL, Chen LS. Marbled inflation from population structure in gene-based association studies with rare variants. Genet Epidemiol. 2013;37:286–92.
pubmed: 23468125
Borecki IB, Province MA. Genetic and genomic discovery using family studies. Circulation. 2008;118:1057–63.
pubmed: 18765388
Haghighi F, Hodge SE. Likelihood formulation of parent-of-origin effects on segregation analysis, including ascertainment. Am J Hum Genet. 2002;70:142–56.
pubmed: 11741195
Spielman RS, McGinnis RE, Ewens WJ. Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). Am J Hum Genet. 1993;52:506–16.
pubmed: 8447318
pmcid: 1682161
Gao G, Allison DB, Hoeschele I. Haplotyping methods for pedigrees. Hum Hered. 2009;67:248–66.
pubmed: 19172084
pmcid: 2692835
Schouten MT, Williams CK, Haley CS. The impact of using related individuals for haplotype reconstruction in population studies. Genetics. 2005;171:1321–30.
pubmed: 15944347
pmcid: 1456835
Giudicessi JR, Ackerman MJ. Prevalence and potential genetic determinants of sensorineural deafness in KCNQ1 homozygosity and compound heterozygosity. Circ Cardiovasc Genet. 2013;6:193–200.
pubmed: 23392653
pmcid: 3683572
Zhong K, Zhu G, Jing X, Hendriks AEJ, Drop SLS, Ikram MA, et al. Genome-wide compound heterozygote analysis highlights alleles associated with adult height in Europeans. Hum Genet. 2017;136:1407–17.
pubmed: 28921393
pmcid: 5702380
Dudbridge F, Brown SJ, Ward L, Wilson SG, Walsh JP. How many cases of disease in a pedigree imply familial disease? Ann Hum Genet. 2017;82:109–13.
pubmed: 29058319
pmcid: 5813157
Chakravarti A, Turner TN. Revealing rate-limiting steps in complex disease biology: The crucial importance of studying rare, extreme-phenotype families. Bioessays. 2016;38:578–86.
pubmed: 27062178
Lescai F, Franceschi C. The impact of phenocopy on the genetic analysis of complex traits. PLoS ONE. 2010;5:e11876.
pubmed: 20686705
pmcid: 2912380
Steinberg S, Gudmundsdottir S, Sveinbjornsson G, Suvisaari J, Paunio T, Torniainen-Holm M, et al. Truncating mutations in RBM12 are associated with psychosis. Nat Genet. 2017;49:1251–4.
pubmed: 28628109
Homann OR, Misura K, Lamas E, Sandrock RW, Nelson P, McDonough SI, et al. Whole-genome sequencing in multiplex families with psychoses reveals mutations in the SHANK2 and SMARCA1 genes segregating with illness. Mol Psychiatry. 2016;21:1690–5.
pubmed: 27001614
pmcid: 5033653
Timms AE, Dorschner MO, Wechsler J, Choi KY, Kirkwood R, Girirajan S, et al. Support for the N-methyl-D-aspartate receptor hypofunction hypothesis of schizophrenia from exome sequencing in multiplex families. JAMA Psychiatry. 2013;70:582–90.
pubmed: 23553203
Peltonen L, Palotie A, Lange K. Use of population isolates for mapping complex traits. Nat Rev Genet. 2000;1:182–90.
pubmed: 11252747
Bouwkamp CG, Kievit AJ, Olgiati S, Breedveld GJ, Coesmans M, Bonifati V, et al. A balanced translocation disrupting BCL2L10 and PNLDC1 segregates with affective psychosis. Am J Med Genet B Neuropsychiatr Genet. 2017;174:214–9.
pubmed: 27260655
Tansey KE, Rees E, Linden DE, Ripke S, Chambert KD, Moran JL, et al. Common alleles contribute to schizophrenia in CNV carriers. Mol Psychiatry. 2016;21:1085–9.
pubmed: 26390827
Thomson PA, Duff B, Blackwood DH, Romaniuk L, Watson A, Whalley HC, et al. Balanced translocation linked to psychiatric disorder, glutamate, and cortical structure/function. NPJ Schizophr. 2016;2:16024.
pubmed: 27602385
pmcid: 4994153
Ryan NM, Lihm J, Kramer M, McCarthy S, Evans KL, Ghiban E, et al. Beyond the translocation: whole genome sequencing analysis of the Scottish t(1;11) family. Orlando, FL: World Congress of Psycahtric Genetics; 2017.
Burdick JT, Chen WM, Abecasis GR, Cheung VG. In silico method for inferring genotypes in pedigrees. Nat Genet. 2006;38:1002–4.
pubmed: 16921375
pmcid: 3005330
Livne OE, Han L, Alkorta-Aranburu G, Wentworth-Sheilds W, Abney M, Ober C, et al. PRIMAL: fast and accurate pedigree-based imputation from sequence data in a founder population. PLoS Comput Biol. 2015;11:e1004139.
pubmed: 25735005
pmcid: 4348507
Meuwissen T, Goddard M. The use of family relationships and linkage disequilibrium to impute phase and missing genotypes in up to whole-genome sequence density genotypic data. Genetics. 2010;185:1441–9.
pubmed: 20479147
pmcid: 2927768
Cheung CY, Thompson EA, Wijsman EM. GIGI: an approach to effective imputation of dense genotypes on large pedigrees. Am J Hum Genet. 2013;92:504–16.
pubmed: 23561844
pmcid: 3617386
Bonin A, Bellemain E, Bronken Eidesen P, Pompanon F, Brochmann C, Taberlet P. How to track and assess genotyping errors in population genetics studies. Mol Ecol. 2004;13:3261–73.
pubmed: 15487987
Taberlet P, Griffin S, Goossens B, Questiau S, Manceau V, Escaravage N, et al. Reliable genotyping of samples with very low DNA quantities using PCR. Nucleic Acids Res. 1996;24:3189–94.
pubmed: 8774899
pmcid: 146079
Xu J, Turner A, Little J, Bleecker ER, Meyers DA. Positive results in association studies are associated with departure from Hardy-Weinberg equilibrium: hint for genotyping error? Hum Genet. 2002;111:573–4.
pubmed: 12516594
Miller CR, Joyce P, Waits LP. Assessing allelic dropout and genotype reliability using maximum likelihood. Genetics. 2002;160:357–66.
pubmed: 11805071
pmcid: 1461941
Sobel E, Papp JC, Lange K. Detection and integration of genotyping errors in statistical genetics. Am J Hum Genet. 2002;70:496–508.
pubmed: 11791215
pmcid: 384922
Douglas JA, Skol AD, Boehnke M. Probability of detection of genotyping errors and mutations as inheritance inconsistencies in nuclear-family data. Am J Hum Genet. 2002;70:487–95.
pubmed: 11791214
pmcid: 419989
McGrath J, Saha S, Welham J, El Saadi O, MacCauley C, Chant D. A systematic review of the incidence of schizophrenia: the distribution of rates and the influence of sex, urbanicity, migrant status and methodology. BMC Med. 2004;2:13.
pubmed: 15115547
pmcid: 421751
Modabbernia A, Velthorst E, Reichenberg A. Environmental risk factors for autism: an evidence-based review of systematic reviews and meta-analyses. Mol Autism. 2017;8:13.
pubmed: 28331572
pmcid: 5356236
Malaspina D, Harlap S, Fennig S, Heiman D, Nahon D, Feldman D, et al. Advancing paternal age and the risk of schizophrenia. Arch Gen Psychiatry. 2001;58:361–7.
pubmed: 11296097
Vassos E, Pedersen CB, Murray RM, Collier DA, Lewis CM. Meta-analysis of the association of urbanicity with schizophrenia. Schizophr Bull. 2012;38:1118–23.
pubmed: 23015685
pmcid: 3494055
van Os J, Kenis G, Rutten BP. The environment and schizophrenia. Nature. 2010;468:203–12.
Krabbendam L, van Os J. Schizophrenia and urbanicity: a major environmental influence--conditional on genetic risk. Schizophr Bull. 2005;31:795–9.
pubmed: 16150958
Colodro-Conde L, Couvy-Duchesne B, Whitfield JB, Streit F, Gordon S, Rietschel M, et al. Higher genetic risk for schizophrenia is associated with living in urban and populated areas. bioRxiv 2017.
Quillen EE, Voruganti VS, Chittoor G, Rubicz R, Peralta JM, Almeida MA, et al. Evaluation of estimated genetic values and their application to genome-wide investigation of systolic blood pressure. BMC Proc. 2014;8:S66
pubmed: 25519398
pmcid: 4143678
Gottesman II, Gould TD. The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry. 2003;160:636–45.
pubmed: 12668349
Glahn DC, Knowles EE, McKay DR, Sprooten E, Raventós H, Blangero J, et al. Arguments for the sake of endophenotypes: examining common misconceptions about the use of endophenotypes in psychiatric genetics. Am J Med Genet B Neuropsychiatr Genet. 2014;165B:122–30.
pubmed: 24464604
Almasy L, Blangero J. Endophenotypes as quantitative risk factors for psychiatric disease: rationale and study design. Am J Med Genet. 2001;105:42–44.
pubmed: 11424994
Glahn DC, Curran JE, Winkler AM, Carless MA, Kent JW, Charlesworth JC, et al. High dimensional endophenotype ranking in the search for major depression risk genes. Biol Psychiatry. 2012;71:6–14.
pubmed: 21982424
Glahn DC, Williams JT, McKay DR, Knowles EE, Sprooten E, Mathias SR, et al. Discovering schizophrenia endophenotypes in randomly ascertained pedigrees. Biol Psychiatry. 2015;77:75–83.
pubmed: 25168609
Gur RC, Braff DL, Calkins ME, Dobie DJ, Freedman R, Green MF, et al. Neurocognitive performance in family-based and case-control studies of schizophrenia. Schizophr Res. 2015;163:17–23.
pubmed: 25432636
pmcid: 4441547
Leppa VM, Kravitz SN, Martin CL, Andrieux J, Le Caignec C, Martin-Coignard D, et al. Rare inherited and de novo CNVs reveal complex contributions to ASD risk in multiplex families. Am J Hum Genet. 2016;99:540–54.
pubmed: 27569545
pmcid: 5011063
Virkud YV, Todd RD, Abbacchi AM, Zhang Y, Constantino JN. Familial aggregation of quantitative autistic traits in multiplex versus simplex autism. Am J Med Genet B Neuropsychiatr Genet. 2009;150B:328–34.
pubmed: 18618672
pmcid: 2819431
Oerlemans AM, Hartman CA, de Bruijn YG, Franke B, Buitelaar JK, Rommelse NN. Cognitive impairments are different in single-incidence and multi-incidence ADHD families. J Child Psychol Psychiatry. 2015;56:782–91.
pubmed: 25346282
pmcid: 25346282
Donaldson CK, Stauder JEA, Donkers FCL. Increased sensory processing atypicalities in parents of multiplex ASD families versus typically developing and simplex ASD families. J Autism Dev Disord. 2017;47:535–48.
pubmed: 27538965
Bureau A, Parker MM, Ruczinski I, Taub MA, Marazita ML, Murray JC, et al. Whole exome sequencing of distant relatives in multiplex families implicates rare variants in candidate genes for oral clefts. Genetics. 2014;197:1039–44.
pubmed: 24793288
pmcid: 4096358
Georgi B, Craig D, Kember RL, Liu W, Lindquist I, Nasser S, et al. Genomic view of bipolar disorder revealed by whole genome sequencing in a genetic isolate. PLoS Genet. 2014;10:e1004229.
pubmed: 24625924
pmcid: 3953017
Hou L, Faraci G, Chen DT, Kassem L, Schulze TG, Shugart YY, et al. Amish revisited: next-generation sequencing studies of psychiatric disorders among the Plain people. Trends Genet. 2013;29:412–8.
pubmed: 23422049
pmcid: 3941079
McCarthy NS, Melton PE, Ward SV, Allan SM, Dragovic M, Clark ML, et al. Exome array analysis suggests an increased variant burden in families with schizophrenia. Schizophr Res. 2017;185:9–16.
pubmed: 27939555
Carmiol N, Peralta JM, Almasy L, Contreras J, Pacheco A, Escamilla MA, et al. Shared genetic factors influence risk for bipolar disorder and alcohol use disorders. Eur Psychiatry. 2014;29:282–7.
pubmed: 24321773
Gur R, Nimgaonkar V, Almasy L, Calkins M, Ragland J, Pogue-Geile M, et al. Neurocognitive endophenotypes in a multiplex multigenerational family study of schizophrenia. Am J Psychiatry. 2007;164:813–9.
pubmed: 17475741
Whalley HC, Sussmann JE, Chakirova G, Mukerjee P, Peel A, McKirdy J, et al. The neural basis of familial risk and temperamental variation in individuals at high risk of bipolar disorder. Biol Psychiatry. 2011;70:343–9.
pubmed: 21601834
Christoforou A, McGhee KA, Morris SW, Thomson PA, Anderson S, McLean A, et al. Convergence of linkage, association and GWAS findings for a candidate region for bipolar disorder and schizophrenia on chromosome 4p. Mol Psychiatry. 2011;16:240–2.
pubmed: 20351716
Auer PL, Reiner AP, Wang G, Kang HM, Abecasis GR, Altshuler D, et al. Guidelines for large-scale sequence-based complex trait association studies: lessons learned from the NHLBI exome sequencing project. Am J Hum Genet. 2016;99:791–801.
pubmed: 27666372
pmcid: 5065683
Makinen VP, Parkkonen M, Wessman M, Groop PH, Kanninen T, Kaski K. High-throughput pedigree drawing. Eur J Hum Genet. 2005;13:987–9.
pubmed: 15870825
Hornig T, Gruning B, Kundu K, Houwaart T, Backofen R, Biber K, et al. GRIN3B missense mutation as an inherited risk factor for schizophrenia: whole-exome sequencing in a family with a familiar history of psychotic disorders. Genet Res. 2017;99:e1.
John J, Kukshal P, Bhatia T, Chowdari KV, Nimgaonkar VL, Deshpande SN, et al. Possible role of rare variants in trace amine associated receptor 1 in schizophrenia. Schizophr Res. 2017;189:190–5.
pubmed: 28242106
pmcid: 5569002
Rao AR, Yourshaw M, Christensen B, Nelson SF, Kerner B. Rare deleterious mutations are associated with disease in bipolar disorder families. Mol Psychiatry. 2017;22:1009–14.
pubmed: 27725659
Zhang T, Hou L, Chen DT, McMahon FJ, Wang JC, Rice JP. Exome sequencing of a large family identifies potential candidate genes contributing risk to bipolar disorder. Gene. 2017;645:119–23.
pubmed: 29248581
pmcid: 6040674
Egawa J, Hoya S, Watanabe Y, Nunokawa A, Shibuya M, Ikeda M, et al. Rare UNC13B variations and risk of schizophrenia: whole-exome sequencing in a multiplex family and follow-up resequencing and a case-control study. Am J Med Genet B Neuropsychiatr Genet. 2016;171:797–805.
pubmed: 26990377
Goes FS, Pirooznia M, Parla JS, Kramer M, Ghiban E, Mavruk S, et al. Exome sequencing of familial bipolar disorder. JAMA Psychiatry. 2016;73:590–7.
pubmed: 27120077
pmcid: 5600716
Kos MZ, Carless MA, Peralta J, Blackburn A, Almeida M, Roalf D, et al. Exome sequence data from multigenerational families implicate AMPA receptor trafficking in neurocognitive impairment and schizophrenia risk. Schizophr Bull. 2016;42:288–300.
pubmed: 26405221
Subaran RL, Odgerel Z, Swaminathan R, Glatt CE, Weissman MM. Novel variants in ZNF34 and other brain-expressed transcription factors are shared among early-onset MDD relatives. Am J Med Genet B Neuropsychiatr Genet. 2016;171B:333–41.
pubmed: 26823146
pmcid: 5832964
Watanabe Y, Nunokawa A, Shibuya M, Ikeda M, Hishimoto A, Kondo K, et al. Rare truncating variations and risk of schizophrenia: whole-exome sequencing in three families with affected siblings and a three-stage follow-up study in a Japanese population. Psychiatry Res. 2016;235:13–18.
pubmed: 26706132
Zhou Z, Hu Z, Zhang L, Hu Z, Liu H, Liu Z, et al. Identification of RELN variation p.Thr3192Ser in a Chinese family with schizophrenia. Sci Rep. 2016;6:24327.
pubmed: 27071546
pmcid: 4829830
Ament SA, Szelinger S, Glusman G, Ashworth J, Hou L, Akula N, et al. Rare variants in neuronal excitability genes influence risk for bipolar disorder. Proc Natl Acad Sci USA. 2015;112:3576–81.
pubmed: 25730879
Kember RL, Georgi B, Bailey-Wilson JE, Stambolian D, Paul SM, Bucan M. Copy number variants encompassing Mendelian disease genes in a large multigenerational family segregating bipolar disorder. BMC Genet. 2015;16:27.
pubmed: 25887117
pmcid: 4382929
Thygesen JH, Zambach SK, Ingason A, Lundin P, Hansen T, Bertalan M, et al. Linkage and whole genome sequencing identify a locus on 6q25-26 for formal thought disorder and implicate MEF2A regulation. Schizophr Res. 2015;169:441–6.
pubmed: 26421691
Strauss KA, Markx S, Georgi B, Paul SM, Jinks RN, Hoshi T, et al. A population-based study of KCNH7 p.Arg394His and bipolar spectrum disorder. Hum Mol Genet. 2014;23:6395–406.
pubmed: 24986916
pmcid: 4222358