Abstract
Genome-wide association studies (GWAS) of mood disorders in large case-control cohorts have identified numerous risk loci, yet pathophysiological mechanisms remain elusive, primarily due to the very small effects of common variants. We sought to discover risk variants with larger effects by conducting a genome-wide association study of mood disorders in a founder population, the Old Order Amish (OOA, n = 1,672). Our analysis revealed four genome-wide significant risk loci, all of which were associated with >2-fold relative risk. Quantitative behavioral and neurocognitive assessments (n = 314) revealed effects of risk variants on sub-clinical depressive symptoms and information processing speed. Network analysis suggested that OOA-specific risk loci harbor novel risk-associated genes that interact with known neuropsychiatry-associated genes via gene interaction networks. Annotation of the variants at these risk loci revealed population-enriched, non-synonymous variants in two genes encoding neurodevelopmental transcription factors, CUX1 and CNOT1. Our findings provide insight into the genetic architecture of mood disorders and a substrate for mechanistic and clinical studies.
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References
GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392:1789–858.
Smoller JW, Finn CT. Family, twin, and adoption studies of bipolar disorder. Am J Med Genet C Semin Med Genet. 2003;123C:48–58.
Barnett JH, Smoller JW. The genetics of bipolar disorder. Neuroscience. 2009;164:331–43.
Sullivan PF, Neale MC, Kendler KS. Genetic epidemiology of major depression: review and meta-analysis. Am J Psychiatry. 2000;157:1552–62.
Kendler KS, Gatz M, Gardner CO, Pedersen NL. A Swedish national twin study of lifetime major depression. Am J Psychiatry. 2006;163:109–14.
Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet. 2018;50:668–81.
Howard DM, Adams MJ, Clarke T-K, Hafferty JD, Gibson J, Shirali M, et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci. 2019;22:343–52.
Stahl EA, Breen G, Forstner AJ, McQuillin A, Ripke S, Trubetskoy V, et al. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat Genet. 2019;51:793–803.
Mullins N, Forstner AJ, O’Connell KS, Coombes B, Coleman JRI, Qiao Z, et al. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology. Nat Genet. 2021;53:817–29.
Levey DF, Stein MB, Wendt FR, Pathak GA, Zhou H, Aslan M, et al. Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions. Nat Neurosci. 2021;24:954–63.
Cross-Disorder Group of the Psychiatric Genomics Consortium. Electronic address: plee0@mgh.harvard.edu, Cross-Disorder Group of the Psychiatric Genomics Consortium. Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders. Cell. 2019;179:1469–1482.e11.
Cross-Disorder Group of the Psychiatric Genomics Consortium, Lee SH, Ripke S, Neale BM, Faraone SV, Purcell SM, et al. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat Genet. 2013;45:984–94.
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.
Strauss KA, Puffenberger EG. Genetics, medicine, and the Plain people. Annu Rev Genomics Hum Genet. 2009;10:513–36.
Hou L, Faraci G, Chen DTW, 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.
Lopes FL, Hou L, Boldt ABW, Kassem L, Alves VM, Nardi AE, et al. Finding rare, disease-associated variants in isolated groups: potential advantages of mennonite populations. Hum Biol. 2016;88:109–20.
Hostetler JA. Amish society. 4th ed. Baltimore: Johns Hopkins University Press; 1993.
Smith C. The Mennonites: a brief history of their origins and later development in both Europe and America. Berne, Indiana: Mennonite Book Concern; 1920.
Krahn C, Bender H, Friesen J. Migrations. Glob Anabapt Mennon Encycl Online. 1989. http://gameo.org/index.php?title=Migrations.
Mckusick VA, Hostetler JA, Egeland JA. Genetic studies of the Amish, background and potentialities. Bull Johns Hopkins Hosp. 1964;115:203–22.
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.
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.
Pollin TI, Damcott CM, Shen H, Ott SH, Shelton J, Horenstein RB, et al. A null mutation in human APOC3 confers a favorable plasma lipid profile and apparent cardioprotection. Science. 2008;322:1702–5.
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.
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.
Kember RL, Hou L, Ji X, Andersen LH, Ghorai A, Estrella LN, et al. Genetic pleiotropy between mood disorders, metabolic, and endocrine traits in a multigenerational pedigree. Transl Psychiatry. 2018;8:218.
Kember RL, Georgi B, Bailey-Wilson JE, Stambolian D, Paul SM, Bućan M. Copy number variants encompassing Mendelian disease genes in a large multigenerational family segregating bipolar disorder. BMC Genet. 2015;16:27.
Kessler MD, Loesch DP, Perry JA, Heard-Costa NL, Taliun D, Cade BE, et al. De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population. Proc Natl Acad Sci USA. 2020;117:2560–9.
Taliun D, Harris DN, Kessler MD, Carlson J, Szpiech ZA, Torres R, et al. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature. 2021;590:290–9.
Purcell SM, Chang CC. PLINK v1.9. www.cog-genomics.org/plink/1.9/.
Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. GigaScience. 2015;4:7.
Mahajan A, Taliun D, Thurner M, Robertson NR, Torres JM, Rayner NW, et al. Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps. Nat Genet. 2018;50:1505–13.
Das S, Forer L, Schönherr S, Sidore C, Locke AE, Kwong A, et al. Next-generation genotype imputation service and methods. Nat Genet. 2016;48:1284–7.
Li H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics. 2011;27:2987–93.
Garrison E, Marth G. Haplotype-based variant detection from short-read sequencing. 2012. https://arxiv.org/abs/1207.3907.
Fernandez-Pujals AM, Adams MJ, Thomson P, McKechanie AG, Blackwood DHR, Smith BH, et al. Epidemiology and heritability of major depressive disorder, stratified by age of onset, sex, and illness course in generation Scotland: Scottish Family Health Study (GS:SFHS). PLoS ONE. 2015;10:e0142197.
Lichtenstein P, Yip BH, Björk C, Pawitan Y, Cannon TD, Sullivan PF, et al. Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study. Lancet. 2009;373:234–9.
Hulshoff Pol HE, van Baal GCM, Schnack HG, Brans RGH, van der Schot AC, Brouwer RM, et al. Overlapping and segregating structural brain abnormalities in twins with schizophrenia or bipolar disorder. Arch Gen Psychiatry. 2012;69:349–59.
Kang HM, Sul JH, Service SK, Zaitlen NA, Kong S-Y, Freimer NB, et al. Variance component model to account for sample structure in genome-wide association studies. Nat Genet. 2010;42:348–54.
Hellevik O. Linear versus logistic regression when the dependent variable is a dichotomy. Qual Quant. 2009;43:59–74.
Lloyd-Jones LR, Robinson MR, Yang J, Visscher PM. Transformation of summary statistics from linear mixed model association on all-or-none traits to odds ratio. Genetics. 2018;208:1397–408.
Quinlan AR. BEDTools: the Swiss-Army tool for genome feature analysis. Curr Protoc Bioinforma. 2014;47:1–34.
Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421–7.
Lee JJ, Wedow R, Okbay A, Kong E, Maghzian O, Zacher M, et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet. 2018;50:1112–21.
Gandal MJ, Zhang P, Hadjimichael E, Walker RL, Chen C, Liu S, et al. Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder. Science. 2018;362:eaat8127.
Singh T, Poterba T, Curtis D, Akil H, Al Eissa M, Barchas JD, et al. Rare coding variants in ten genes confer substantial risk for schizophrenia. Nature. 2022;604:509–16.
Satterstrom FK, Kosmicki JA, Wang J, Breen MS, De Rubeis S, An J-Y, et al. Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism. Cell. 2020;180:568–584.e23.
Abrahams BS, Arking DE, Campbell DB, Mefford HC, Morrow EM, Weiss LA, et al. SFARI Gene 2.0: a community-driven knowledgebase for the autism spectrum disorders (ASDs). Mol Autism. 2013;4:36.
Ge T, Chen CY, Ni Y, Feng YA, Smoller JW. Polygenic prediction via Bayesian regression and continuous shrinkage priors. Nat Commun. 2019;10:1776.
Ziyatdinov A, Vázquez-Santiago M, Brunel H, Martinez-Perez A, Aschard H, J Soria JM. lme4qtl: linear mixed models with flexible covariance structure for genetic studies of related individuals. BMC Bioinform. 2018;19:68.
Beck AT, Steer RA, Brown GK. BDI-II, Beck depression inventory: manual. 2nd ed. San Antonio, Tex.: Boston: Psychological Corp.; Harcourt Brace; 1996.
Chiappelli J, Nugent KL, Thangavelu K, Searcy K, Hong LE. Assessment of trait and state aspects of depression in schizophrenia. Schizophr Bull. 2014;40:132–42.
Bruce HA, Kochunov P, Mitchell B, Strauss KA, Ament SA, Rowland LM, et al. Clinical and genetic validity of quantitative bipolarity. Transl Psychiatry. 2019;9:228.
Wechsler D. Wechsler abbreviated scale of intelligence: WASI-II; Manual. 2nd ed. Bloomington, Minn: Pearson; 2011.
Ganjgahi H, Winkler AM, Glahn DC, Blangero J, Kochunov P, Nichols TE. Fast and powerful heritability inference for family-based neuroimaging studies. NeuroImage. 2015;115:256–68.
de Leeuw CA, Mooij JM, Heskes T, Posthuma D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput Biol. 2015;11:e1004219.
Hasin N, Riggs LM, Shekhtman T, Ashworth J, Lease R, Oshone RT, et al. Rare variants implicate NMDA receptor signaling and cerebellar gene networks in risk for bipolar disorder. Mol Psychiatry. 2022;27:3842–56.
Casella AM, Colantuoni C, Ament SA. Identifying enhancer properties associated with genetic risk for complex traits using regulome-wide association studies. PLoS Comput Biol. 2022;18:e1010430.
Wang D, Liu S, Warrell J, Won H, Shi X, Navarro FCP, et al. Comprehensive functional genomic resource and integrative model for the human brain. Science. 2018;362:eaat8464.
Luciano M, Hagenaars SP, Davies G, Hill WD, Clarke T-K, Shirali M, et al. Association analysis in over 329,000 individuals identifies 116 independent variants influencing neuroticism. Nat Genet. 2018;50:6–11.
Singh T, Neale BM, Daly MJ. Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia. Genet Genomic Med. 2020. https://doi.org/10.1101/2020.09.18.20192815.
Wright CF, Fitzgerald TW, Jones WD, Clayton S, McRae JF, van Kogelenberg M, et al. Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data. Lancet. 2015;385:1305–14.
Karczewski KJ, Francioli LC, Tiao G, Cummings BB, Alföldi J, Wang Q, et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature. 2020;581:434–43.
Genovese G, Fromer M, Stahl EA, Ruderfer DM, Chambert K, Landén M, et al. Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia. Nat Neurosci. 2016;19:1433–41.
Pirooznia M, Wang T, Avramopoulos D, Valle D, Thomas G, Huganir RL, et al. SynaptomeDB: an ontology-based knowledgebase for synaptic genes. Bioinformatics. 2012;28:897–9.
Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47:D607–D613.
Csardi G, Nepusz T. The igraph software package for complex network research. Complex Syst. 2006;1695:1–9.
Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4:44–57.
Li M, Santpere G, Imamura Kawasawa Y, Evgrafov OV, Gulden FO, Pochareddy S, et al. Integrative functional genomic analysis of human brain development and neuropsychiatric risks. Science. 2018;362:eaat7615.
Purcell S, Cherny SS, Sham PC. Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics. 2003;19:149–50.
Shen H, Damcott CM, Rampersaud E, Pollin TI, Horenstein RB, McArdle PF, et al. Familial defective apolipoprotein B-100 and increased low-density lipoprotein cholesterol and coronary artery calcification in the old order amish. Arch Intern Med. 2010;170:1850–5.
Clayton-Smith J, Giblin C, Smith RA, Dunn C, Willatt L. Familial 3q29 microdeletion syndrome providing further evidence of involvement of the 3q29 region in bipolar disorder. Clin Dysmorphol. 2010;19:128–32.
Mulle JG. The 3q29 deletion confers >40-fold increase in risk for schizophrenia. Mol Psychiatry. 2015;20:1028–9.
Guo X, Ge T, Xia S, Wu H, Colt M, Xie X, et al. Atp13a5 marker reveals pericytes of the central nervous system in mice. SSRN Electron J. 2021. https://doi.org/10.2139/ssrn.3881359.
Dunn AR, Stout KA, Ozawa M, Lohr KM, Hoffman CA, Bernstein AI, et al. Synaptic vesicle glycoprotein 2C (SV2C) modulates dopamine release and is disrupted in Parkinson disease. Proc Natl Acad Sci USA. 2017;114:E2253–E2262.
Larsen E, Menashe I, Ziats MN, Pereanu W, Packer A, Banerjee-Basu S. A systematic variant annotation approach for ranking genes associated with autism spectrum disorders. Mol Autism. 2016;7:44.
Doan RN, Bae B-I, Cubelos B, Chang C, Hossain AA, Al-Saad S, et al. Mutations in human accelerated regions disrupt cognition and social behavior. Cell. 2016;167:341–354.e12.
Cubelos B, Sebastián-Serrano A, Beccari L, Calcagnotto ME, Cisneros E, Kim S, et al. Cux1 and Cux2 regulate dendritic branching, spine morphology, and synapses of the upper layer neurons of the cortex. Neuron. 2010;66:523–35.
Li N, Zhao C-T, Wang Y, Yuan X-B. The transcription factor Cux1 regulates dendritic morphology of cortical pyramidal neurons. PLoS ONE. 2010;5:e10596.
Cubelos B, Briz CG, Esteban-Ortega GM, Nieto M. Cux1 and Cux2 selectively target basal and apical dendritic compartments of layer II-III cortical neurons. Dev Neurobiol. 2015;75:163–72.
Lievens PM, Tufarelli C, Donady JJ, Stagg A, Neufeld EJ. CASP, a novel, highly conserved alternative-splicing product of the CDP/cut/cux gene, lacks cut-repeat and homeo DNA-binding domains, and interacts with full-length CDP in vitro. Gene. 1997;197:73–81.
Ramdzan ZM, Nepveu A. CUX1, a haploinsufficient tumour suppressor gene overexpressed in advanced cancers. Nat Rev Cancer. 2014;14:673–82.
Gillingham AK, Pfeifer AC, Munro S. CASP, the alternatively spliced product of the gene encoding the CCAAT-displacement protein transcription factor, is a Golgi membrane protein related to giantin. Mol Biol Cell. 2002;13:3761–74.
Osterrieder A, Sparkes IA, Botchway SW, Ward A, Ketelaar T, de Ruijter N, et al. Stacks off tracks: a role for the golgin AtCASP in plant endoplasmic reticulum-Golgi apparatus tethering. J Exp Bot. 2017;68:3339–50.
Vissers LELM, Kalvakuri S, de Boer E, Geuer S, Oud M, van Outersterp I, et al. De novo variants in CNOT1, a central component of the CCR4-NOT complex involved in gene expression and RNA and protein stability, cause neurodevelopmental delay. Am J Hum Genet. 2020;107:164–72.
Bergen SE, Ploner A, Howrigan D, CNV Analysis Group and the Schizophrenia Working Group of the Psychiatric Genomics Consortium, O’Donovan MC, Smoller JW, et al. Joint contributions of rare copy number variants and common snps to risk for schizophrenia. Am J Psychiatry. 2019;176:29–35.
Glahn DC, Almasy L, Barguil M, Hare E, Peralta JM, Kent JW, et al. Neurocognitive endophenotypes for bipolar disorder identified in multiplex multigenerational families. Arch Gen Psychiatry. 2010;67:168.
Chaves OC, Lombardo LE, Bearden CE, Woolsey MD, Martinez DM, Barrett JA, et al. Association of clinical symptoms and neurocognitive performance in bipolar disorder: a longitudinal study: Symptoms and cognition in bipolar disorder. Bipolar Disord. 2011;13:118–23.
Austin M-P, Ross M, Murray C, O’Caŕroll RE, Ebmeier KP, Goodwin GM. Cognitive function in major depression. J Affect Disord. 1992;25:21–29.
Bora E, Harrison BJ, Yücel M, Pantelis C. Cognitive impairment in euthymic major depressive disorder: a meta-analysis. Psychol Med. 2013;43:2017–26.
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.
Palmer DS, Howrigan DP, Chapman SB, Adolfsson R, Bass N, Blackwood D, et al. Exome sequencing in bipolar disorder reveals shared risk gene AKAP11 with schizophrenia. Genet Genomic Med. 2022;54:541–7.
Lee J-A, Damianov A, Lin C-H, Fontes M, Parikshak NN, Anderson ES, et al. Cytoplasmic Rbfox1 regulates the expression of synaptic and autism-related genes. Neuron 2016;89:113–28.
Acknowledgements
This study was supported by grants and contracts from the National Institute of Mental Health (U01 MH108148 to LEH and PK, R01 MH110437 to PPZ, U01 MH105630 to DCG, U01 MH105632 to JB, R01 MH129343 to SAA, R01 MH093415 to M.B. and Steven. M. Paul), the Regeneron Genetics Center, the Intramural Research Program of the National Institute of Mental Health (ZIA MH002843 to FJM), and a NARSAD Young Investigator Award from the Brain and Behavior Research Foundation to SAA Most of all, we thank the Amish and Mennonite participants, without whose longstanding partnership this study would not have been possible.
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Conceptualization – EMH, MB, LEH, FJM, SAA. Formal analysis – EMH, KA, RLK, FLL, EM, JMP, SAA. Resources – JB, DCG, FSG, PPZ, PK, CVH, ARS, TIP, BDM, MB, LEH, FJM. Supervision – BDM, MB, LEH, FJM, SAA. Funding Acquisition – JB, DCG, PPZ, PK, ARS, TIP, BDM, MB, LEH, FJM, SAA. Writing (Original Draft) – EMH, SAA. Writing (review and editing) – All authors.
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ARS is an employee of Regeneron Pharmaceuticals. LEH has received or plans to receive research funding or consulting fees on research projects from Mitsubishi, Your Energy Systems LLC, Neuralstem, Taisho, Heptares, Pfizer, Sound Pharma, IGC Pharma, Regeneron, and Takeda. SAA has received research funding from Oryzon Genomics LLC. All other authors declare no biomedical financial interests or potential competing interests.
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Humphries, E.M., Ahn, K., Kember, R.L. et al. Genome-wide significant risk loci for mood disorders in the Old Order Amish founder population. Mol Psychiatry 28, 5262–5271 (2023). https://doi.org/10.1038/s41380-023-02014-1
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DOI: https://doi.org/10.1038/s41380-023-02014-1
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