Using Patterns of Genetic Association to Elucidate Shared Genetic Etiologies Across Psychiatric Disorders.

💬 Chat with this paper

paper Primary Public

Authors: Cho, Seung Bin; Aliev, Fazil; Clark, Shaunna L; Adkins, Amy E; Edenberg, Howard J; Bucholz, Kathleen K; Porjesz, Bernice; Dick, Danielle M
Year: 2017
Journal: Behavior genetics
PMID: 28343281
DOI: 10.1007/s10519-017-9844-4
PMCID: PMC5996973

#	Section	Preview
20	Discussion	This study examined the patterns of clustering of SNP association results by applying LPA to…
21	Discussion	The pattern of SNPs classified into varying numbers of classes further supported the existence of…
22	Discussion	LPA to SNP association results across multiple disorders may be a promising approach to identify…
23	Discussion — Limitations and future directions	An assumption of LPA, within-class normality, may not be met in our data. We examined the univariate…
24	Discussion — Limitations and future directions	assumption results in a different number of classes, we tried to fit LPA models with skewed…
25	Discussion — Limitations and future directions	The local independence assumption of LPA requires class indicators to be uncorrelated within each…
26	Discussion — Limitations and future directions	full set of SNPs. To incorporate common variance within classes, we fit the 3-class model with…
27	Discussion — Limitations and future directions	Further investigation on different indicators for LPA might be able to refine the classification of…
28	Discussion — Limitations and future directions	Expanding and refining phenotypes would further elaborate the results of current study.…
29	Discussion — Limitations and future directions	Although the results of our analysis are consistent with the conclusion from twin studies that SNPs…
30	Discussion — Limitations and future directions	phenotypes observed in our study. In addition, while previous studies on genetic architecture of…
31	Discussion — Limitations and future directions	Classifying SNPs based on their association patterns also lends itself to several additional…
32	Conclusion	This study presents a novel way to utilize GWAS results from multiple disorders to better understand…

Citation	PMID	DOI	Status
Akaike, H, Psychometrika, 1987, Factor anslysis and AIC	—	—	—
Bauer, DJ et al., Psychol Methods, 2003, Distributional assumptions of growth mixture models: implications for overextraction of latent trajectory classes	14596495	10.1037/1082-989X.8.3.338	Cited
Benke, KS et al., J Am Acad Child Adolesc Psychiatry, 2014, A genome-wide association meta-analysis of preschool internalizing problems	24839885	10.1016/j.jaac.2013.12.028	Cited
Bucholz, KK et al., J Stud Alcohol Drugs, 1994, A new, semi-structured psychiatric interview for use in genetic linkage studies: a report on the reliability of the SSAGA	8189735	10.15288/jsa.1994.55.149	Primary
Bulik-Sullivan, B et al., Nat Genet, An atlas of genetic correlations across human diseases and traits	26414676	10.1038/ng.3406	Cited
Bulik-Sullivan, BK et al., Nat Genet, LD Score regression distinguishes confounding from polygenicity in genome-wide association studies	25642630	10.1038/ng.3211	Cited
Celeux, G et al., J Classif, 1996, An entropy criterion for assessing the number of clusters in a mixture model	—	—	—
Derringer, J et al., Behav Genet, 2015, Genome-wide association study of behavioral disinhibition in a selected adolescent sample	25637581	10.1007/s10519-015-9705-y	Cited
Diagnostic and Statistical Manual of Mental Disorders, 1987	—	—	—
Diagnostic and Statistical Manual of Mental Disorders, 2000	—	—	—
Dick, DM et al., Arch Gen Psychiatry, 2008, Using dimensional models of externalizing psychopathology to aid in gene identification	18316677	10.1001/archpsyc.65.3.310	Primary
Edenberg, HJ et al., Alcohol Clin Exp Res, 2010, Genome-wide association study of alcohol dependence implicates a region on chromosome 11	20201924	10.1111/j.1530-0277.2010.01156.x	Primary
Edwards, AC et al., Alcohol Clin Exp Res, 2014, Childhood internalizing symptoms are negatively associated with early adolescent alcohol use	24848214	10.1111/acer.12402	Cited
Feighner, JP et al., Arch Gen Psychiatry, 1972, Diagnostic criteria for use in psychiatric research	5009428	10.1001/archpsyc.1972.01750190059011	Cited
Gibson, WA, Psychometrika, 1959, Three multivariate models: Factor analysis, latent structure analysis, and latent profile analysis	—	—	—
Gunderson, KL et al., Methods Enzymol, 2006, Whole-genome genotyping	16938560	10.1016/S0076-6879(06)10017-8	Cited
Hall, P et al., An overview of machine learning with SAS® enterprise miner™, 2014	—	—	—
Hesselbrock, M et al., Addiction, 1999, A validity study of the SSAGA-a comparison with the SCAN	10615721	10.1046/j.1360-0443.1999.94913618.x	Primary
Kendler, KS et al., Alcohol Clin Exp Res, Genomewide association analysis of symptoms of alcohol dependence in the molecular genetics of schizophrenia (MGS2) control sample	21314694	10.1111/j.1530-0277.2010.01427.x	Cited
Kendler, KS et al., Am J Psychiatry, The structure of genetic and environmental risk factors for syndromal and subsyndromal common DSM-IV axis I and all axis II disorders	20952461	10.1176/appi.ajp.2010.10030340	Cited
Kendler, KS et al., Arch Gen Psychiatry, 2003, The structure of genetic and environmental risk factors for common psychiatric and substance use disorders in men and women	12963675	10.1001/archpsyc.60.9.929	Cited
Krueger, RF et al., Curr Dir Psychol Sci, 2006, Understanding psychopathology: melding behavior genetics, personality, and quantitative psychology to develop an empirically based model	18392116	10.1111/j.0963-7214.2006.00418.x	Cited
Krueger, RF et al., J Abnorm Psychol, 2002, Etiologic connections among substance dependence, antisocial behavior and personality: Modeling the externalizing spectrum	12150417	—	Cited
Krueger, RF et al., Personal Individ Differ, 2001, The higher-order structure of common DSM mental disorders: internalization, externalization, and their connections to personality	—	—	—
Krueger, RF, Arch Gen Psychiatry, 1999, The structure of common mental disorders	10530634	10.1001/archpsyc.56.10.921	Cited
Lazarsfeld, PF et al., Latent structure analysis, 1968	—	—	—
Lo, Y et al., Biometrika, 2001, Testing the number of components in a normal mixture	—	—	—
Lubke, G et al., Multivar Behav Res, 2006, Distinguishing between latent classes and continuous factors: resolution by maximum likelihood?	26794916	10.1207/s15327906mbr4104_4	Cited
Lubke, GH et al., Psychol Med, 2015, Does nature have joints worth carving? A discussion of taxometrics, model-based clustering and latent variable mixture modeling	25137654	10.1017/S003329171400169X	Cited
Magidson, J et al., Canadian J Market Res, 2002, Latent class models for clustering: A comparison with K-means	—	—	—
McCarty, CA et al., J Stud Alcohol Drugs, 2012, Developmental consistency in associations between depressive symptoms and alcohol use in early adolescence	22456249	10.15288/jsad.2012.73.444	Cited
McGue, M et al., Behav Genet, 2013, A genome-wide association study of behavioral disinhibition	23942779	10.1007/s10519-013-9606-x	Cited
McLachlan, G et al., Finite mixture models, 2004	—	—	—
Muthén, B, Psychol Methods, 2003, Statistical and substantive checking in growth mixture modeling: comment on Bauer and Curran (2003)	14596497	10.1037/1082-989X.8.3.369	Cited
Muthén, LK et al., Mplus user’s guide	—	—	—
Needham, BL, Soc Sci Med, 2007, Gender differences in trajectories of depressive symptomatology and substance use during the transition from adolescence to young adulthood	17574316	10.1016/j.socscimed.2007.04.037	Cited
Purcell, S et al., Am J Hum Genet, 2007, PLINK: a tool set for whole-genome association and population-based linkage analyses	17701901	10.1086/519795	Cited
Purcell, SM et al., Nature, 2009, Common polygenic variation contributes to risk of schizophrenia and bipolar disorder	19571811	10.1038/nature08185	Cited
Salvatore, JE et al., Clin Psychol Sci, Polygenic risk for externalizing disorders gene-by-development and gene-by-environment effects in adolescents and young adults	25821660	10.1177/2167702614534211	Primary
Salvatore, JE et al., Genes, Polygenic scores predict alcohol problems in an independent sample and show moderation by the environment	24727307	10.3390/genes5020330	Cited
Schwarz, G, Ann Stat, 1978, Estimating the dimension of a model	—	—	—
Yang, J et al., Am J Hum Genet, 2011, GCTA: a tool for genome-wide complex trait analysis	21167468	10.1016/j.ajhg.2010.11.011	Cited
Yang, J et al., Nat Genet, 2010, Common SNPs explain a large proportion of the heritability for human height	20562875	10.1038/ng.608	Cited
Zhang, K et al., Nucleic Acids Res, 2010, i-GSEA4GWAS: a web server for identification of pathways/gene sets associated with traits by applying an improved gene set enrichment analysis to genome-wide association study	20435672	10.1093/nar/gkq324	Cited
Zhang, K et al., Protein Cell, 2014, I-GSEA4GWAS v2: a web server for functional analysis of SNPs in trait-associated pathways identified from genome-wide association study	25407412	10.1007/s13238-014-0114-4	Cited

Title	Authors	Journal	Year	Link
DNAJC13 influences responses of the extended reward system to conditioned stimuli: a genome-wide association study.	Treutlein J et al.	—	2025	→
Phenotypic and genetic markers of psychopathology in a population-based sample of older adults.	Gard AM et al.	—	2021	→
Updates on Genome-Wide Association Findings in Eating Disorders and Future Application to Precision Medicine.	Breithaupt L et al.	—	2018	→

Using Patterns of Genetic Association to Elucidate Shared Genetic Etiologies Across Psychiatric Disorders.

External