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Grillo AR. Polygene by environment interactions predicting depressive outcomes. Am J Med Genet B Neuropsychiatr Genet 2024:e33000. [PMID: 39012198 DOI: 10.1002/ajmg.b.33000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 06/13/2024] [Accepted: 06/17/2024] [Indexed: 07/17/2024]
Abstract
Depression is a major public health problem with a continued need to uncover its etiology. Current models of depression contend that gene-by-environment (G × E) interactions influence depression risk, and further, that depression is polygenic. Thus, recent models have emphasized two polygenic approaches: a hypothesis-driven multilocus genetic profile score (MGPS; "MGPS × E") and a polygenic risk score (PRS; "PRS × E") derived from genome-wide association studies (GWAS). This review for the first time synthesizes current knowledge on polygene by environment "P × E" interaction research predicting primarily depression-related outcomes, and in brief, neurobiological outcomes. The "environment" of focus in this project is stressful life events. It further discusses findings in the context of differential susceptibility and diathesis-stress theories-two major theories guiding G × E work. This synthesis indicates that, within the MGPS literature, polygenic scores based on the serotonin system, the HPA axis, or across multiple systems, interact with environmental stress exposure to predict outcomes at multiple levels of analyses and most consistently align with differential susceptibility theory. Depressive outcomes are the most studied, but neuroendocrine, and neuroimaging findings are observed as well. By contrast, vast methodological differences between GWAS-based PRS studies contribute to mixed findings that yield inconclusive results.
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Affiliation(s)
- Alessandra R Grillo
- Department of Psychology, University of North Carolina, Greensboro, North Carolina, USA
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2
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Dong Z, Zhao H, DeWan AT. A mediation analysis framework based on variance component to remove genetic confounding effect. J Hum Genet 2024; 69:301-309. [PMID: 38528049 DOI: 10.1038/s10038-024-01232-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 02/15/2024] [Accepted: 02/16/2024] [Indexed: 03/27/2024]
Abstract
Identification of pleiotropy at the single nucleotide polymorphism (SNP) level provides valuable insights into shared genetic signals among phenotypes. One approach to study these signals is through mediation analysis, which dissects the total effect of a SNP on the outcome into a direct effect and an indirect effect through a mediator. However, estimated effects from mediation analysis can be confounded by the genetic correlation between phenotypes, leading to inaccurate results. To address this confounding effect in the context of genetic mediation analysis, we propose a restricted-maximum-likelihood (REML)-based mediation analysis framework called REML-mediation, which can be applied to either individual-level or summary statistics data. Simulations demonstrated that REML-mediation provides unbiased estimates of the true cross-trait causal effect, assuming certain assumptions, albeit with a slightly inflated standard error compared to traditional linear regression. To validate the effectiveness of REML-mediation, we applied it to UK Biobank data and analyzed several mediator-outcome trait pairs along with their corresponding sets of pleiotropic SNPs. REML-mediation successfully identified and corrected for genetic confounding effects in these trait pairs, with correction magnitudes ranging from 7% to 39%. These findings highlight the presence of genetic confounding effects in cross-trait epidemiological studies and underscore the importance of accounting for them in data analysis.
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Affiliation(s)
- Zihan Dong
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, New Haven, CT, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
| | - Andrew T DeWan
- Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, New Haven, CT, USA.
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, USA.
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3
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Schwarzerova J, Hurta M, Barton V, Lexa M, Walther D, Provaznik V, Weckwerth W. A perspective on genetic and polygenic risk scores-advances and limitations and overview of associated tools. Brief Bioinform 2024; 25:bbae240. [PMID: 38770718 PMCID: PMC11106636 DOI: 10.1093/bib/bbae240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 04/14/2024] [Accepted: 05/03/2024] [Indexed: 05/22/2024] Open
Abstract
Polygenetic Risk Scores are used to evaluate an individual's vulnerability to developing specific diseases or conditions based on their genetic composition, by taking into account numerous genetic variations. This article provides an overview of the concept of Polygenic Risk Scores (PRS). We elucidate the historical advancements of PRS, their advantages and shortcomings in comparison with other predictive methods, and discuss their conceptual limitations in light of the complexity of biological systems. Furthermore, we provide a survey of published tools for computing PRS and associated resources. The various tools and software packages are categorized based on their technical utility for users or prospective developers. Understanding the array of available tools and their limitations is crucial for accurately assessing and predicting disease risks, facilitating early interventions, and guiding personalized healthcare decisions. Additionally, we also identify potential new avenues for future bioinformatic analyzes and advancements related to PRS.
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Affiliation(s)
- Jana Schwarzerova
- Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia
- Molecular Systems Biology (MOSYS), Department of Functional and Evolutionary Ecology, University of Vienna, Vienna 1010, Austria
| | - Martin Hurta
- Department of Computer Systems, Faculty of Information Technology, Brno University of Technology, Brno 612 00, Czechia
| | - Vojtech Barton
- Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, Brno 62500, Czech Republic
| | - Matej Lexa
- Faculty of Informatics, Masaryk University, Botanicka 68a, Brno 60200, Czech Republic
| | - Dirk Walther
- Max-Planck-Institute of Molecular Plant Physiology, Potsdam 14476, Germany
| | - Valentine Provaznik
- Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia
- Department of Physiology, Faculty of Medicine, Masaryk University, Brno 62500, Czech Republic
| | - Wolfram Weckwerth
- Molecular Systems Biology (MOSYS), Department of Functional and Evolutionary Ecology, University of Vienna, Vienna 1010, Austria
- Vienna Metabolomics Center (VIME), University of Vienna, Vienna 1010, Austria
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Hoy N, Lynch SJ, Waszczuk MA, Reppermund S, Mewton L. Transdiagnostic biomarkers of mental illness across the lifespan: A systematic review examining the genetic and neural correlates of latent transdiagnostic dimensions of psychopathology in the general population. Neurosci Biobehav Rev 2023; 155:105431. [PMID: 37898444 DOI: 10.1016/j.neubiorev.2023.105431] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/26/2023] [Accepted: 10/21/2023] [Indexed: 10/30/2023]
Abstract
This systematic review synthesizes evidence from research investigating the biological correlates of latent transdiagnostic dimensions of psychopathology (e.g., the p-factor, internalizing, externalizing) across the lifespan. Eligibility criteria captured genomic and neuroimaging studies investigating general and/or specific dimensions in general population samples across all age groups. MEDLINE, Embase, and PsycINFO were searched for relevant studies published up to March 2023 and 46 studies were selected for inclusion. The results revealed several biological correlates consistently associated with transdiagnostic dimensions of psychopathology, including polygenic scores for ADHD and neuroticism, global surface area and global gray matter volume. Shared and unique associations between symptom dimensions are highlighted, as are potential age-specific differences in biological associations. Findings are interpreted with reference to key methodological differences across studies. The included studies provide compelling evidence that the general dimension of psychopathology reflects common underlying genetic and neurobiological vulnerabilities that are shared across diverse manifestations of mental illness. Substantive interpretations of general psychopathology in the context of genetic and neurobiological evidence are discussed.
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Affiliation(s)
- Nicholas Hoy
- The Matilda Centre for Research in Mental Health and Substance Use, University of Sydney, Sydney, Australia; Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia.
| | - Samantha J Lynch
- The Matilda Centre for Research in Mental Health and Substance Use, University of Sydney, Sydney, Australia; Department of Psychiatry, Université de Montréal, Montreal, Canada; Research Centre, CHU Sainte-Justine, Montreal, Canada
| | - Monika A Waszczuk
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, United States
| | - Simone Reppermund
- Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia; Department of Developmental Disability Neuropsychiatry, University of New South Wales, Sydney, Australia
| | - Louise Mewton
- The Matilda Centre for Research in Mental Health and Substance Use, University of Sydney, Sydney, Australia
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5
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Su J, Kuo SIC, Aliev F, Rabinowitz JA, Jamil B, Chan G, Edenberg HJ, Francis M, Hesselbrock V, Kamarajan C, Kinreich S, Kramer J, Lai D, McCutcheon V, Meyers J, Pandey A, Pandey G, Plawecki MH, Schuckit M, Tischfield J, Dick DM. Alcohol use polygenic risk score, social support, and alcohol use among European American and African American adults. Dev Psychopathol 2023:1-13. [PMID: 37781861 PMCID: PMC10985050 DOI: 10.1017/s0954579423001141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
Alcohol use is influenced by genetic and environmental factors. We examined the interactive effects between genome-wide polygenic risk scores for alcohol use (alc-PRS) and social support in relation to alcohol use among European American (EA) and African American (AA) adults across sex and developmental stages (emerging adulthood, young adulthood, and middle adulthood). Data were drawn from 4,011 EA and 1,274 AA adults from the Collaborative Study on the Genetics of Alcoholism who were between ages 18-65 and had ever used alcohol. Participants completed the Semi-Structured Assessment for the Genetics of Alcoholism and provided saliva or blood samples for genotyping. Results indicated that social support from friends, but not family, moderated the association between alc-PRS and alcohol use among EAs and AAs (only in middle adulthood for AAs); alc-PRS was associated with higher levels of alcohol use when friend support was low, but not when friend support was high. Associations were similar across sex but differed across developmental stages. Findings support the important role of social support from friends in buffering genetic risk for alcohol use among EA and AA adults and highlight the need to consider developmental changes in the role of social support in relation to alcohol use.
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Affiliation(s)
- Jinni Su
- Department of Psychology, Arizona State University, Tempe, AZ, USA
| | - Sally I-Chun Kuo
- Department of Psychiatry, Rutgers University, New Brunswick, NJ, USA
| | - Fazil Aliev
- Department of Psychiatry, Rutgers University, New Brunswick, NJ, USA
| | - Jill A Rabinowitz
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Belal Jamil
- Department of Psychology, Arizona State University, Tempe, AZ, USA
| | - Grace Chan
- Department of Psychiatry, University of Connecticut, Farmington, CT, USA
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University, Indianapolis, IN, USA
| | - Meredith Francis
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Victor Hesselbrock
- Department of Psychiatry, University of Connecticut, Farmington, CT, USA
| | - Chella Kamarajan
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, USA
| | - Sivan Kinreich
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, USA
| | - John Kramer
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Donbing Lai
- Department of Biochemistry and Molecular Biology, Indiana University, Indianapolis, IN, USA
| | - Vivia McCutcheon
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Jacquelyn Meyers
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, USA
| | - Ashwini Pandey
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, USA
| | - Gayathri Pandey
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, USA
| | | | - Marc Schuckit
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Jay Tischfield
- Department of Genetics, Rutgers University, New Brunswick, NJ, USA
| | - Danielle M Dick
- Rutgers Addiction Research Center, Rutgers University, New Brunswick, NJ, USA
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Tiego J, Verdejo-Garcia A, Anderson A, Koutoulogenis J, Bellgrove MA. Mechanisms of cognitive disinhibition explain individual differences in adult attention deficit hyperactivity disorder traits. Cortex 2023; 167:178-196. [PMID: 37567053 DOI: 10.1016/j.cortex.2023.06.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 04/12/2023] [Accepted: 06/08/2023] [Indexed: 08/13/2023]
Abstract
BACKGROUND Attention deficit hyperactivity disorder (ADHD) in adults is strongly associated with psychiatric comorbidity and functional impairment. Here, we aimed to use a newly developed online cognitive battery with strong psychometric properties for measuring individual differences in three cognitive mechanisms proposed to underlie ADHD traits in adults: 1) attentional control - the ability to mobilize cognitive resources to stop a prepotent motor response; 2) information sampling/gathering - adequate sampling of information in a stimulus detection task prior to making a decision; and 3) shifting - the ability to adapt behavior in response to positive and negative contingencies. METHODS This cross-sectional and correlational study recruited 650 adults (330 males) aged 18-69 years (M = 33.06; MD = 31.00; SD = 10.50), with previously diagnosed ADHD (n = 329) and those from the general community without a history of ADHD (n = 321). Self-report measures of ADHD traits (i.e., inattention/disorganization, impulsivity, hyperactivity) and the cognitive battery were completed online. RESULTS Latent class analysis, exploratory structural equation modeling and factor mixture modeling revealed self-reported ADHD traits formed a unidimensional and approximately normally distributed phenotype. Bayesian structural equation modeling demonstrated that all three mechanisms measured by the cognitive battery, explained unique, incremental variance in ADHD traits, with a total of 15.9% explained in the ADHD trait factor. CONCLUSIONS Attentional control and shifting, as well as the less researched cognitive process of information gathering, explain individual difference variance in self-reported ADHD traits with potential to yield genetic and neurobiological insights into adult ADHD.
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Affiliation(s)
- Jeggan Tiego
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Level 5, 18 Innovation Walk, Monash University, Clayton, Victoria, Australia 3800.
| | - Antonio Verdejo-Garcia
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Level 5, 18 Innovation Walk, Monash University, Clayton, Victoria, Australia 3800.
| | - Alexandra Anderson
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Level 5, 18 Innovation Walk, Monash University, Clayton, Victoria, Australia 3800.
| | - Julia Koutoulogenis
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Level 5, 18 Innovation Walk, Monash University, Clayton, Victoria, Australia 3800.
| | - Mark A Bellgrove
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Level 5, 18 Innovation Walk, Monash University, Clayton, Victoria, Australia 3800.
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7
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Handley ED, Russotti J, Ross AJ, Toth SL, Cicchetti D. A person-centered data analytic approach to dopaminergic polygenic moderation of child maltreatment exposure. Dev Psychobiol 2023; 65:e22403. [PMID: 37338249 PMCID: PMC10287038 DOI: 10.1002/dev.22403] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 04/27/2023] [Accepted: 05/03/2023] [Indexed: 06/21/2023]
Abstract
The present study illustrates the utility of latent class analysis, a person-centered data analytic approach, as an innovative method for identifying naturally occurring patterns of polygenic risk, specifically within the dopaminergic system. Moreover, this study tests whether latent classes of polygenic variation moderate the effect of child maltreatment exposure on internalizing symptoms among African ancestry youth. African ancestry youth were selected for this study because youth of color are overrepresented in the child welfare system and because African ancestry individuals are significantly underrepresented in genomics research. Results identified three latent classes of dopaminergic gene variation. Class 1 was marked predominately by homozygous minor alleles, Class 2 was characterized by homozygous major and heterozygous presentations, and Class 3 was marked by heterozygous alleles on the DAT-1 single-nucleotide polymorphisms (SNPs) and a combination of homozygous major and minor alleles on the other SNPs. Results indicated that a greater number of maltreatment subtypes experienced were associated with higher internalizing symptoms only for children with the latent polygenic Class 2 pattern. This latent class was distinctly characterized by more homozygous major or heterozygous allelic presentations along all three DAT-1 SNPs. This significant latent polygenic class by environment interaction was replicated in an independent replication sample. Together, findings suggest that African ancestry children with a pattern of dopaminergic variation characterized by this specific combination of polygenic variation are more vulnerable to developing internalizing symptoms following maltreatment exposure, relative to their peers with other dopamine-related polygenic patterns.
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Affiliation(s)
| | | | | | | | - Dante Cicchetti
- Mt. Hope Family Center, University of Rochester
- University of Minnesota
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8
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Zhao B, Zou F, Zhu H. Cross-trait prediction accuracy of summary statistics in genome-wide association studies. Biometrics 2023; 79:841-853. [PMID: 35278218 PMCID: PMC9464799 DOI: 10.1111/biom.13661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 02/25/2022] [Indexed: 11/27/2022]
Abstract
In the era of big data, univariate models have widely been used as a workhorse tool for quickly producing marginal estimators; and this is true even when in a high-dimensional dense setting, in which many features are "true," but weak signals. Genome-wide association studies (GWAS) epitomize this type of setting. Although the GWAS marginal estimator is popular, it has long been criticized for ignoring the correlation structure of genetic variants (i.e., the linkage disequilibrium [LD] pattern). In this paper, we study the effects of LD pattern on the GWAS marginal estimator and investigate whether or not additionally accounting for the LD can improve the prediction accuracy of complex traits. We consider a general high-dimensional dense setting for GWAS and study a class of ridge-type estimators, including the popular marginal estimator and the best linear unbiased prediction (BLUP) estimator as two special cases. We show that the performance of GWAS marginal estimator depends on the LD pattern through the first three moments of its eigenvalue distribution. Furthermore, we uncover that the relative performance of GWAS marginal and BLUP estimators highly depends on the ratio of GWAS sample size over the number of genetic variants. Particularly, our finding reveals that the marginal estimator can easily become near-optimal within this class when the sample size is relatively small, even though it ignores the LD pattern. On the other hand, BLUP estimator has substantially better performance than the marginal estimator as the sample size increases toward the number of genetic variants, which is typically in millions. Therefore, adjusting for the LD (such as in the BLUP) is most needed when GWAS sample size is large. We illustrate the importance of our results by using the simulated data and real GWAS.
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Affiliation(s)
- Bingxin Zhao
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, U.S.A
| | - Fei Zou
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, U.S.A
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, U.S.A
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9
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McGeary JE, Benca-Bachman CE, Risner VA, Beevers CG, Gibb BE, Palmer RHC. Associating broad and clinically defined polygenic scores for depression with depression-related phenotypes. Sci Rep 2023; 13:6534. [PMID: 37085695 PMCID: PMC10121555 DOI: 10.1038/s41598-023-33645-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 04/16/2023] [Indexed: 04/23/2023] Open
Abstract
Twin studies indicate that 30-40% of the disease liability for depression can be attributed to genetic differences. Here, we assess the explanatory ability of polygenic scores (PGS) based on broad- (PGSBD) and clinical- (PGSMDD) depression summary statistics from the UK Biobank in an independent sample of adults (N = 210; 100% European Ancestry) who were extensively phenotyped for depression and related neurocognitive traits (e.g., rumination, emotion regulation, anhedonia, and resting frontal alpha asymmetry). The UK Biobank-derived PGSBD had small associations with MDD, depression severity, anhedonia, cognitive reappraisal, brooding, and suicidal ideation but only the association with suicidal ideation remained statistically significant after correcting for multiple comparisons. Similarly small associations were observed for the PGSMDD but none remained significant after correcting for multiple comparisons. These findings provide important initial guidance about the expected effect sizes between current UKB PGSs for depression and depression-related neurocognitive phenotypes.
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Affiliation(s)
- John E McGeary
- Providence Veterans Affairs Medical Center, Providence, RI, USA
| | - Chelsie E Benca-Bachman
- Providence Veterans Affairs Medical Center, Providence, RI, USA.
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA.
| | - Victoria A Risner
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA
| | | | - Brandon E Gibb
- Department of Psychology State, University of New York at Binghamton, Binghamton, NY, USA
| | - Rohan H C Palmer
- Providence Veterans Affairs Medical Center, Providence, RI, USA
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA
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Elam KK, Lemery-Chalfant K, Chassin L. A gene-environment cascade theoretical framework of developmental psychopathology. JOURNAL OF PSYCHOPATHOLOGY AND CLINICAL SCIENCE 2023; 132:287-296. [PMID: 36201798 PMCID: PMC10076453 DOI: 10.1037/abn0000546] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
Previous theories have emphasized genetic effects "inside the skin" via endophenotypes within the broader developmental psychopathology theory. Expanding on the mechanisms of gene-environment correlation, we propose a new integrative framework emphasizing how genetic effects "outside the skin" (Reiss & Leve, 2007) accumulate due to individual variation in social information processing in negative environments and sociocultural contexts as part of developmental cascades to psychopathology. In this gene-environment cascade theoretical framework, genetic predisposition for psychopathology, as well as stable traits and behaviors, can lead to negative environments via gene-environment correlations that can be exacerbated or buffered by an individual's social information processing. Moreover, these "environments" range from dyadic social relationships to broader sociocultural contexts. Over time, these processes exacerbate one another as part of developmental cascades, resulting in accumulating risk for psychopathology. By focusing on gene-environment correlations and integrating disparate social-emotional, cognitive, and sociocultural research domains, this framework delineates key processes by which early genetic predisposition can contribute to developmentally distinct and accumulating risk for psychopathology over the life course. Implications for intervention and methodological advances that facilitate testing models are presented. This new framework moves the field further away from genetic determinism by informing targets of early psychosocial prevention. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Affiliation(s)
- Kit K Elam
- Department of Applied Health Science, Indiana University Bloomington
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11
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Waszczuk MA, Miao J, Docherty AR, Shabalin AA, Jonas KG, Michelini G, Kotov R. General v. specific vulnerabilities: polygenic risk scores and higher-order psychopathology dimensions in the Adolescent Brain Cognitive Development (ABCD) Study. Psychol Med 2023; 53:1937-1946. [PMID: 37310323 PMCID: PMC10958676 DOI: 10.1017/s0033291721003639] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND Polygenic risk scores (PRSs) capture genetic vulnerability to psychiatric conditions. However, PRSs are often associated with multiple mental health problems in children, complicating their use in research and clinical practice. The current study is the first to systematically test which PRSs associate broadly with all forms of childhood psychopathology, and which PRSs are more specific to one or a handful of forms of psychopathology. METHODS The sample consisted of 4717 unrelated children (mean age = 9.92, s.d. = 0.62; 47.1% female; all European ancestry). Psychopathology was conceptualized hierarchically as empirically derived general factor (p-factor) and five specific factors: externalizing, internalizing, neurodevelopmental, somatoform, and detachment. Partial correlations explored associations between psychopathology factors and 22 psychopathology-related PRSs. Regressions tested which level of the psychopathology hierarchy was most strongly associated with each PRS. RESULTS Thirteen PRSs were significantly associated with the general factor, most prominently Chronic Multisite Pain-PRS (r = 0.098), ADHD-PRS (r = 0.079), and Depression-PRS (r = 0.078). After adjusting for the general factor, Depression-PRS, Neuroticism-PRS, PTSD-PRS, Insomnia-PRS, Chronic Back Pain-PRS, and Autism-PRS were not associated with lower order factors. Conversely, several externalizing PRSs, including Adventurousness-PRS and Disinhibition-PRS, remained associated with the externalizing factor (|r| = 0.040-0.058). The ADHD-PRS remained uniquely associated with the neurodevelopmental factor (r = 062). CONCLUSIONS PRSs developed to predict vulnerability to emotional difficulties and chronic pain generally captured genetic risk for all forms of childhood psychopathology. PRSs developed to predict vulnerability to externalizing difficulties, e.g. disinhibition, tended to be more specific in predicting behavioral problems. The results may inform translation of existing PRSs to pediatric research and future clinical practice.
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Affiliation(s)
- Monika A. Waszczuk
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, USA
| | - Jiaju Miao
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
| | - Anna R. Docherty
- Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Andrey A. Shabalin
- Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
| | | | - Giorgia Michelini
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Roman Kotov
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
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12
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Kuo SIC, Thomas NS, Aliev F, Bucholz KK, Dick DM, McCutcheon VV, Meyers JL, Chan G, Kamarajan C, Kramer JR, Hesselbrock V, Plawecki MH, Porjesz B, Tischfield J, Salvatore JE. Association of parental divorce, discord, and polygenic risk with children's alcohol initiation and lifetime risk for alcohol use disorder. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2023; 47:724-735. [PMID: 36807915 PMCID: PMC10149624 DOI: 10.1111/acer.15042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 01/25/2023] [Accepted: 02/14/2023] [Indexed: 02/21/2023]
Abstract
BACKGROUND Parental divorce and discord are associated with poorer alcohol-related outcomes for offspring. However, not all children exposed to these stressors develop alcohol problems. Our objective was to test gene-by-environment interaction effects whereby children's genetic risk for alcohol problems modifies the effects of parental divorce and discord to predict alcohol outcomes. METHODS The sample included European (EA; N = 5608, 47% male, Mage ~ 36 years) and African (AA; N = 1714, 46% female, Mage ~ 33 years) ancestry participants from the Collaborative Study on the Genetics of Alcoholism. Outcomes included age at initiation of regular drinking and lifetime DSM-5 alcohol use disorder (AUD). Predictors included parental divorce, parental relationship discord, and offspring alcohol problems polygenic risk scores (PRSALC ). Mixed effects Cox proportional hazard models were used to examine alcohol initiation and generalized linear mixed effects models were used to examine lifetime AUD. Tests of PRS moderation of the effects of parental divorce/relationship discord on alcohol outcomes were examined on multiplicative and additive scales. RESULTS Among EA participants, parental divorce, parental discord, and higher PRSALC were associated with earlier alcohol initiation and greater lifetime AUD risk. Among AA participants, parental divorce was associated with earlier alcohol initiation and discord was associated with earlier initiation and AUD. PRSALC was not associated with either. Parental divorce/discord and PRSALC interacted on an additive scale in the EA sample, but no interactions were found in AA participants. CONCLUSIONS Children's genetic risk for alcohol problems modifies the impact of parental divorce/discord, consistent with an additive model of diathesis-stress interaction, with some differences across ancestry.
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Affiliation(s)
- Sally I-Chun Kuo
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey, USA
| | - Nathaniel S. Thomas
- Department of Psychology, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Fazil Aliev
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey, USA
| | - Kathleen K. Bucholz
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Danielle M. Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey, USA
| | - Vivia V. McCutcheon
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Jacquelyn L. Meyers
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York, USA
| | - Grace Chan
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Connecticut, USA
| | - Chella Kamarajan
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York, USA
| | - John R. Kramer
- Department of Psychiatry, University of Iowa, Iowa City, Iowa, USA
| | - Victor Hesselbrock
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Connecticut, USA
| | - Martin H. Plawecki
- Department of Psychiatry, Indiana University, Indianapolis, Indiana, USA
| | - Bernice Porjesz
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York, USA
| | - Jay Tischfield
- Department of Genetics, Rutgers University, Piscataway, New Jersey, USA
| | - Jessica E. Salvatore
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey, USA
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13
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Pat N, Wang Y, Bartonicek A, Candia J, Stringaris A. Explainable machine learning approach to predict and explain the relationship between task-based fMRI and individual differences in cognition. Cereb Cortex 2023; 33:2682-2703. [PMID: 35697648 PMCID: PMC10016053 DOI: 10.1093/cercor/bhac235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 04/27/2022] [Accepted: 04/28/2022] [Indexed: 11/13/2022] Open
Abstract
Despite decades of costly research, we still cannot accurately predict individual differences in cognition from task-based functional magnetic resonance imaging (fMRI). Moreover, aiming for methods with higher prediction is not sufficient. To understand brain-cognition relationships, we need to explain how these methods draw brain information to make the prediction. Here we applied an explainable machine-learning (ML) framework to predict cognition from task-based fMRI during the n-back working-memory task, using data from the Adolescent Brain Cognitive Development (n = 3,989). We compared 9 predictive algorithms in their ability to predict 12 cognitive abilities. We found better out-of-sample prediction from ML algorithms over the mass-univariate and ordinary least squares (OLS) multiple regression. Among ML algorithms, Elastic Net, a linear and additive algorithm, performed either similar to or better than nonlinear and interactive algorithms. We explained how these algorithms drew information, using SHapley Additive explanation, eNetXplorer, Accumulated Local Effects, and Friedman's H-statistic. These explainers demonstrated benefits of ML over the OLS multiple regression. For example, ML provided some consistency in variable importance with a previous study and consistency with the mass-univariate approach in the directionality of brain-cognition relationships at different regions. Accordingly, our explainable-ML framework predicted cognition from task-based fMRI with boosted prediction and explainability over standard methodologies.
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Affiliation(s)
- Narun Pat
- Department of Psychology, University of Otago, William James Building, 275 Leith Walk, Dunedin 9016, New Zealand
| | - Yue Wang
- Department of Psychology, University of Otago, William James Building, 275 Leith Walk, Dunedin 9016, New Zealand
| | - Adam Bartonicek
- Department of Psychology, University of Otago, William James Building, 275 Leith Walk, Dunedin 9016, New Zealand
| | - Julián Candia
- Longitudinal Studies Section, Translational Gerontology National Institute on Aging, National Institute of Health, Branch, 251 Bayview Boulevard, Rm 05B113A, Biomedical Research Center, Baltimore, MD 21224, USA
| | - Argyris Stringaris
- Division of Psychiatry and Department of Clinical, Educational – Health Psychology, University College London, 1-19 Torrington Pl, London WC1E 7HB, United Kingdom
- Department of Psychiatry, National and Kapodistrian University of Athens, Medical School, Mikras Asias 75, Athina 115 27, Greece
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14
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Bogdan R, Hatoum AS, Johnson EC, Agrawal A. The Genetically Informed Neurobiology of Addiction (GINA) model. Nat Rev Neurosci 2023; 24:40-57. [PMID: 36446900 PMCID: PMC10041646 DOI: 10.1038/s41583-022-00656-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/19/2022] [Indexed: 11/30/2022]
Abstract
Addictions are heritable and unfold dynamically across the lifespan. One prominent neurobiological theory proposes that substance-induced changes in neural circuitry promote the progression of addiction. Genome-wide association studies have begun to characterize the polygenic architecture undergirding addiction liability and revealed that genetic loci associated with risk can be divided into those associated with a general broad-spectrum liability to addiction and those associated with drug-specific addiction risk. In this Perspective, we integrate these genomic findings with our current understanding of the neurobiology of addiction to propose a new Genetically Informed Neurobiology of Addiction (GINA) model.
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Affiliation(s)
- Ryan Bogdan
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA.
| | - Alexander S Hatoum
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.
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15
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Su J, Trevino A, Jamil B, Aliev F. Genetic risk of AUDs and childhood impulsivity: Examining the role of parenting and family environment. Dev Psychopathol 2022; 34:1-14. [PMID: 36523258 DOI: 10.1017/s095457942200092x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
This study examined the independent and interactive effects of genetic risk for alcohol use disorder (AUD), parenting behaviors, and family environment on childhood impulsivity. Data were drawn from White (n = 5,991), Black/African American (n = 1,693), and Hispanic/Latino (n = 2,118) youth who completed the baseline assessment (age 9-10) and had genotypic data available from the Adolescent Brain Cognitive Development Study. Participants completed questionnaires and provided saliva or blood samples for genotyping. Results indicated no significant main effects of AUD genome-wide polygenic scores (AUD-PRS) on childhood impulsivity as measured by the UPPS-P scale across racial/ethnic groups. In general, parental monitoring and parental acceptance were associated with lower impulsivity; family conflict was associated with higher impulsivity. There was an interaction effect between AUD-PRS and family conflict, such that family conflict exacerbated the association between AUD-PRS and positive urgency, only among Black/African American youth. This was the only significant interaction effect detected from a total of 45 tests (five impulsivity dimensions, three subsamples, and three family factors), and thus may be a false positive and needs to be replicated. These findings highlight the important role of parenting behaviors and family conflict in relation to impulsivity among children.
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Affiliation(s)
- Jinni Su
- Department of Psychology, Arizona State University, Tempe, AZ, USA
| | - Angel Trevino
- Department of Psychology, Arizona State University, Tempe, AZ, USA
| | - Belal Jamil
- Department of Psychology, Arizona State University, Tempe, AZ, USA
| | - Fazil Aliev
- Department of Psychiatry, Rutgers University, Newark, NJ, USA
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16
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Pat N, Wang Y, Anney R, Riglin L, Thapar A, Stringaris A. Longitudinally stable, brain-based predictive models mediate the relationships between childhood cognition and socio-demographic, psychological and genetic factors. Hum Brain Mapp 2022; 43:5520-5542. [PMID: 35903877 PMCID: PMC9704790 DOI: 10.1002/hbm.26027] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 06/22/2022] [Accepted: 07/07/2022] [Indexed: 01/15/2023] Open
Abstract
Cognitive abilities are one of the major transdiagnostic domains in the National Institute of Mental Health's Research Domain Criteria (RDoC). Following RDoC's integrative approach, we aimed to develop brain-based predictive models for cognitive abilities that (a) are developmentally stable over years during adolescence and (b) account for the relationships between cognitive abilities and socio-demographic, psychological and genetic factors. For this, we leveraged the unique power of the large-scale, longitudinal data from the Adolescent Brain Cognitive Development (ABCD) study (n ~ 11 k) and combined MRI data across modalities (task-fMRI from three tasks: resting-state fMRI, structural MRI and DTI) using machine-learning. Our brain-based, predictive models for cognitive abilities were stable across 2 years during young adolescence and generalisable to different sites, partially predicting childhood cognition at around 20% of the variance. Moreover, our use of 'opportunistic stacking' allowed the model to handle missing values, reducing the exclusion from around 80% to around 5% of the data. We found fronto-parietal networks during a working-memory task to drive childhood-cognition prediction. The brain-based, predictive models significantly, albeit partially, accounted for variance in childhood cognition due to (1) key socio-demographic and psychological factors (proportion mediated = 18.65% [17.29%-20.12%]) and (2) genetic variation, as reflected by the polygenic score of cognition (proportion mediated = 15.6% [11%-20.7%]). Thus, our brain-based predictive models for cognitive abilities facilitate the development of a robust, transdiagnostic research tool for cognition at the neural level in keeping with the RDoC's integrative framework.
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Affiliation(s)
- Narun Pat
- Department of PsychologyUniversity of OtagoDunedinNew Zealand
| | - Yue Wang
- Department of PsychologyUniversity of OtagoDunedinNew Zealand
| | - Richard Anney
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine and Wolfson Centre for Young People's Mental HealthCardiff UniversityCardiffUK
| | - Lucy Riglin
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine and Wolfson Centre for Young People's Mental HealthCardiff UniversityCardiffUK
| | - Anita Thapar
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine and Wolfson Centre for Young People's Mental HealthCardiff UniversityCardiffUK
| | - Argyris Stringaris
- Division of Psychiatry, Department of Clinical, Educational and Health PsychologyUniversity College LondonLondonUK
- Department of PsychiatryNational and Kapodistrian University of AthensAthensGreece
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17
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Su J, Kuo SIC, Trevino A, Barr PB, Aliev F, Bucholz K, Chan G, Edenberg HJ, Kuperman S, Lai D, Meyers JL, Pandey G, Porjesz B, Dick DM. Examining social genetic effects on educational attainment via parental educational attainment, income, and parenting. JOURNAL OF FAMILY PSYCHOLOGY : JFP : JOURNAL OF THE DIVISION OF FAMILY PSYCHOLOGY OF THE AMERICAN PSYCHOLOGICAL ASSOCIATION (DIVISION 43) 2022; 36:1340-1350. [PMID: 35666911 PMCID: PMC9733825 DOI: 10.1037/fam0001003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Higher parental educational attainment is associated with higher offspring educational attainment. In this study, we incorporated genotypic and phenotypic information from fathers, mothers, and offspring to disentangle the genetic and socioenvironmental pathways underlying this association. Data were drawn from a sample of individuals of European ancestry from the collaborative study on the genetics of alcoholism (n = 4,089; 51% female). Results from path analysis indicated that paternal and maternal educational attainment genome-wide polygenic scores were associated with offspring educational attainment, above and beyond the effect of offspring education polygenic score. Parental educational attainment, income, and parenting behaviors served as important socioenvironmental pathways that mediated the effect of parental education polygenic score on offspring educational attainment. Our study highlights the importance of using genetically informed family studies to disentangle the genetic and socioenvironmental pathways underlying parental influences on human development. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Affiliation(s)
- Jinni Su
- Department of Psychology, Arizona State University
| | - Sally I-Chun Kuo
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University
| | | | - Peter B. Barr
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University
| | - Fazil Aliev
- Rutgers Addiction Research Center, Rutgers University
| | | | - Grace Chan
- Department of Psychiatry, University of Connecticut School of Medicine
- Department of Psychiatry, University of Iowa
| | | | | | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University
| | - Jacquelyn L. Meyers
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University
| | - Gayathri Pandey
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University
| | - Bernice Porjesz
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University
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18
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Dick DM. The Promise and Peril of Genetics. CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE 2022; 31:480-485. [PMID: 36591341 PMCID: PMC9802013 DOI: 10.1177/09637214221112041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Human genetics is advancing at an unprecedented pace. Improvements in genotyping technology and rapidly falling costs have accelerated gene discovery. We can now comprehensively scan the genome, testing variation across millions of genetic markers, to identify specific variants associated with any outcome of interest. Large consortia consisting of hundreds of scientists are analyzing data from hundreds of thousands to millions of individuals. Multivariate methods now enable us to identify genes involved in underlying processes, to complement studies focused on specific disorders or traits. There has been an exponential increase in use of direct-to-consumer genetic feedback platforms. These advances are poised to have a widespread effect on medicine and society. However, with such rapid progress will come ethical, social, and legal challenges. Among those challenges is the need for increased efforts to enhance public understanding of the ways genes contribute to complex behavioral outcomes, and for increased diversity in the field of genetics to ensure that all people benefit from advances. Psychologists can play an important role in addressing the inevitable questions that will arise as genetics increasingly becomes mainstream.
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Affiliation(s)
- Danielle M. Dick
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Rutgers University
- Rutgers Addiction Research Center, Rutgers University
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19
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Uddin MJ, Hjorthøj C, Ahammed T, Nordentoft M, Ekstrøm CT. The use of polygenic risk scores as a covariate in psychological studies. METHODS IN PSYCHOLOGY 2022. [DOI: 10.1016/j.metip.2022.100099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022] Open
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20
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Sellers R, Riglin L, Harold GT, Thapar A. Using genetic designs to identify likely causal environmental contributions to psychopathology. Dev Psychopathol 2022; 34:1-13. [PMID: 36200346 DOI: 10.1017/s0954579422000906] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The multifactorial nature of psychopathology, whereby both genetic and environmental factors contribute risk, has long been established. In this paper, we provide an update on genetically informative designs that are utilized to disentangle genetic and environmental contributions to psychopathology. We provide a brief reminder of quantitative behavioral genetic research designs that have been used to identify potentially causal environmental processes, accounting for genetic contributions. We also provide an overview of recent molecular genetic approaches that utilize genome-wide association study data which are increasingly being applied to questions relevant to psychopathology research. While genetically informative designs typically have been applied to investigate the origins of psychopathology, we highlight how these approaches can also be used to elucidate potential causal environmental processes that contribute to developmental course and outcomes. We highlight the need to use genetically sensitive designs that align with intervention and prevention science efforts, by considering strengths-based environments to investigate how positive environments can mitigate risk and promote children's strengths.
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Affiliation(s)
- Ruth Sellers
- Brighton & Sussex Medical School, University of Sussex, Brighton, UK
| | - Lucy Riglin
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- Wolfson Centre for Young People's Mental Health, Cardiff University, Cardiff, UK
| | - Gordon T Harold
- Faculty of Education, University of Cambridge, Cambridge, UK
- School of Medicine, Child and Adolescent Psychiatry Unit, University College Dublin, Dublin, Ireland
| | - Anita Thapar
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- Wolfson Centre for Young People's Mental Health, Cardiff University, Cardiff, UK
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21
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Kuo SIC, Poore HE, Barr PB, Chirico IS, Aliev F, Bucholz KK, Chan G, Kamarajan C, Kramer JR, McCutcheon VV, Plawecki MH, Dick DM. The role of parental genotype in the intergenerational transmission of externalizing behavior: Evidence for genetic nurturance. Dev Psychopathol 2022; 34:1-11. [PMID: 36200344 PMCID: PMC10076450 DOI: 10.1017/s0954579422000700] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The purpose of this study was to examine possible pathways by which genetic risk associated with externalizing is transmitted in families. We used molecular data to disentangle the genetic and environmental pathways contributing to adolescent externalizing behavior in a sample of 1,111 adolescents (50% female; 719 European and 392 African ancestry) and their parents from the Collaborative Study on the Genetics of Alcoholism. We found evidence for genetic nurture such that parental externalizing polygenic scores were associated with adolescent externalizing behavior, over and above the effect of adolescents' own externalizing polygenic scores. Mediation analysis indicated that parental externalizing psychopathology partly explained the effect of parental genotype on children's externalizing behavior. We also found evidence for evocative gene-environment correlation, whereby adolescent externalizing polygenic scores were associated with lower parent-child communication, less parent-child closeness, and lower parental knowledge, controlling for parental genotype. These effects were observed among participants of European ancestry but not African ancestry, likely due to the limited predictive power of polygenic scores across ancestral background. These results demonstrate that in addition to genetic transmission, genes influence offspring behavior through the influence of parental genotypes on their children's environmental experiences, and the role of children's genotypes in shaping parent-child relationships.
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Affiliation(s)
- Sally I-Chun Kuo
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
| | - Holly E. Poore
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
| | - Peter B. Barr
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
- VA New York Harbor Healthcare System, Brooklyn, NY, USA
| | | | - Fazil Aliev
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
| | - Kathleen K. Bucholz
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Grace Chan
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Chella Kamarajan
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - John R. Kramer
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Vivia V. McCutcheon
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Danielle M. Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
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22
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Dai Y, Shi G, Chen M, Chen G, Wu Q. Using Polygenic Risk Scores Related to Complex Traits to Predict Production Performance in Cross-Breeding of Yeast. J Fungi (Basel) 2022; 8:jof8090914. [PMID: 36135639 PMCID: PMC9500933 DOI: 10.3390/jof8090914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 08/22/2022] [Accepted: 08/24/2022] [Indexed: 11/16/2022] Open
Abstract
The cultivation of hybrids with favorable complex traits is one of the important goals for animal, plant, and microbial breeding practices. A method that can closely predict the production performance of hybrids is of great significance for research and practice. In our study, polygenic risk scores (PRSs) were introduced to estimate the production performance of Saccharomyces cerevisiae. The genetic variation of 971 published isolates and their growth ratios under 35 medium conditions were analyzed by genome-wide association analysis, and the precise p-value threshold for each phenotype was calculated. Risk markers for the above 35 phenotypes were obtained. By estimating the genotype of F1 hybrids according to that of the parents, the PRS of 613 F1 hybrids was predicted. There was a significant linear correlation between the maximum growth rate at 40 °C and PRS in F1 hybrids and their parents (R2 = 0.2582, R2 = 0.2414, respectively), which indicates that PRS can be used to estimate the production performance of individuals and their hybrids. Our method can provide a reference for strain selection and F1 prediction in cross-breeding yeasts, reduce workload, and improve work efficiency.
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Affiliation(s)
- Yi Dai
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
- University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Guohui Shi
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Mengmeng Chen
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
- University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Guotao Chen
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
- University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Qi Wu
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
- Correspondence:
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23
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Hillary RF, McCartney DL, McRae AF, Campbell A, Walker RM, Hayward C, Horvath S, Porteous DJ, Evans KL, Marioni RE. Identification of influential probe types in epigenetic predictions of human traits: implications for microarray design. Clin Epigenetics 2022; 14:100. [PMID: 35948928 PMCID: PMC9367152 DOI: 10.1186/s13148-022-01320-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 07/29/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND CpG methylation levels can help to explain inter-individual differences in phenotypic traits. Few studies have explored whether identifying probe subsets based on their biological and statistical properties can maximise predictions whilst minimising array content. Variance component analyses and penalised regression (epigenetic predictors) were used to test the influence of (i) the number of probes considered, (ii) mean probe variability and (iii) methylation QTL status on the variance captured in eighteen traits by blood DNA methylation. Training and test samples comprised ≤ 4450 and ≤ 2578 unrelated individuals from Generation Scotland, respectively. RESULTS As the number of probes under consideration decreased, so too did the estimates from variance components and prediction analyses. Methylation QTL status and mean probe variability did not influence variance components. However, relative effect sizes were 15% larger for epigenetic predictors based on probes with known or reported methylation QTLs compared to probes without reported methylation QTLs. Relative effect sizes were 45% larger for predictors based on probes with mean Beta-values between 10 and 90% compared to those based on hypo- or hypermethylated probes (Beta-value ≤ 10% or ≥ 90%). CONCLUSIONS Arrays with fewer probes could reduce costs, leading to increased sample sizes for analyses. Our results show that reducing array content can restrict prediction metrics and careful attention must be given to the biological and distribution properties of CpG probes in array content selection.
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Affiliation(s)
- Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK.
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, 4072, Australia
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095-7088, USA.,Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095-1772, USA
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK
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Vrshek-Schallhorn S, Corneau GM, Grillo AR, Sapuram VR, Plieger T, Reuter M. Additive serotonergic genetic sensitivity and cortisol reactivity to lab-based social evaluative stress: Influence of severity across two samples. Psychoneuroendocrinology 2022; 142:105767. [PMID: 35525123 DOI: 10.1016/j.psyneuen.2022.105767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 02/28/2022] [Accepted: 04/10/2022] [Indexed: 11/29/2022]
Abstract
Prior work demonstrates that an additive serotonergic multilocus genetic profile score (MGPS) predicts amplified risk for depression following significant life stress, and that it interacts with elevations in the cortisol awakening response to predict depression. The serotonin system and HPA-axis have bidirectional influence, but whether this MGPS predicts acute cortisol reactivity, which might then serve as a mechanism for depression, is unknown. Our prior work suggests that depression risk factors predict blunted cortisol reactivity to explicit negative evaluative lab-based stress. Thus, we hypothesized that a 4-variant serotonergic MGPS (three SNPs from the original 5-variant version plus 5HTTLPR) would predict blunted cortisol reactivity to explicit negative evaluative stress versus a control. In Sample 1, growth curve modeling showed that the MGPS predicted heightened cortisol reactivity (p = 0.0001) in an explicitly negative evaluative Trier Social Stress Test variant (TSST) versus a control condition among non-depressed emerging adults (N = 152; 57% female). In Sample 2, 125 males completed the Socially Evaluative Cold Pressor Test (SECPT), an ambiguously negative evaluative manipulation; findings displayed a similar pattern but did not reach statistical significance (ps.075-.091). A participant-level meta-analysis of the two samples demonstrated a significant effect of negative evaluation severity, such that the MGPS effect size on reactivity increased linearly from control to SECPT to an explicitly negative evaluative TSST. Findings indicate that this MGPS contributes to sensitivity to social threat and that cortisol dysregulation in the context of social stress may be one mechanism by which this MGPS contributes to depression.
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Affiliation(s)
| | - Gail M Corneau
- Department of Psychology, University of North Carolina at Greensboro, USA
| | | | - Vaibhav R Sapuram
- Department of Psychology, University of North Carolina at Greensboro, USA
| | - Thomas Plieger
- Department of Psychology and Center for Economics & Neuroscience, Bonn University, Germany
| | - Martin Reuter
- Department of Psychology and Center for Economics & Neuroscience, Bonn University, Germany
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Pat N, Riglin L, Anney R, Wang Y, Barch DM, Thapar A, Stringaris A. Motivation and Cognitive Abilities as Mediators Between Polygenic Scores and Psychopathology in Children. J Am Acad Child Adolesc Psychiatry 2022; 61:782-795.e3. [PMID: 34506929 DOI: 10.1016/j.jaac.2021.08.019] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 07/23/2021] [Accepted: 08/31/2021] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Fundamental questions in biological psychiatry concern the mechanisms that mediate between genetic liability and psychiatric symptoms. Genetic liability for many common psychiatric disorders often confers transdiagnostic risk to develop a wide variety of psychopathological symptoms through yet unknown pathways. This study examined the psychological and cognitive pathways that might mediate the relationship between genetic liability (indexed by polygenic scores; PS) and broad psychopathology (indexed by p factor and its underlying dimensions). METHOD First, which of the common psychiatric PSs (major depressive disorder [MDD], attention-deficit/hyperactivity disorder [ADHD], anxiety, bipolar disorder, schizophrenia, autism) that were associated with p factor were identified. Then focused was shifted to 3 pathways: punishment sensitivity (reflected by behavioral inhibition system), reward sensitivity (reflected by behavioral activation system), and cognitive abilities (reflected by g factor based on 10 neurocognitive tasks). We applied structural equation modeling on the Adolescent Brain Cognitive Development (ABCD) Study dataset (n = 4,814; 2,263 girls; 9-10 years old). RESULTS MDD and ADHD PSs were associated with p factor. The association between MDD PS and psychopathology was partially mediated by punishment sensitivity and cognitive abilities (proportion mediated = 22.35%). Conversely, the influence of ADHD PS on psychopathology was partially mediated by reward sensitivity and cognitive abilities (proportion mediated = 30.04%). The mediating role of punishment sensitivity was specific to emotional/internalizing. The mediating role of both reward sensitivity and cognitive abilities was specific to behavioral/externalizing and neurodevelopmental dimensions of psychopathology. CONCLUSION This study provides a better understanding of how genetic risks for MDD and ADHD confer risks for psychopathology and suggests potential prevention/intervention targets for children at risk.
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Affiliation(s)
- Narun Pat
- University of Otago, Dunedin, New Zealand.
| | | | | | - Yue Wang
- University of Otago, Dunedin, New Zealand
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Thomas NS, Kuo SIC, Aliev F, McCutcheon VV, Meyers JM, Chan G, Hesselbrock V, Kamarajan C, Kinreich S, Kramer JR, Kuperman S, Lai D, Plawecki MH, Porjesz B, Schuckit MA, Dick DM, Bucholz KK, Salvatore JE. Alcohol use disorder, psychiatric comorbidities, marriage and divorce in a high-risk sample. PSYCHOLOGY OF ADDICTIVE BEHAVIORS 2022; 36:364-374. [PMID: 35617219 PMCID: PMC9247836 DOI: 10.1037/adb0000840] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
OBJECTIVE To examine associations between alcohol use disorder (AUD), its psychiatric comorbidities, and their interactions, with marital outcomes in a diverse high-risk, genetically informative sample. METHOD Participants included European ancestry (EA; n = 4,045) and African ancestry (AA; n = 1,550) individuals from the multigenerational Collaborative Study on the Genetics of Alcoholism (COGA) sample (56% female, Mage ∼ 41 years). Outcomes were lifetime marriage and divorce. Predictors included lifetime AUD, an alcohol problems polygenic score (PRS), and AUD comorbidities, including conduct or antisocial personality disorder (ASP), cannabis dependence/abuse (CAN), frequent tobacco use (TOB), and major depressive disorder (MDD). Mixed effect Cox models and generalized linear mixed effects models were fit. RESULTS Among EA participants, those with AUD and CAN were less likely to marry (hazard ratios [HRs] 0.70-0.83, ps < 0.01). Among AA participants, those with AUD and TOB were less likely to marry (HRs 0.66-0.82, ps < 0.05) and those with MDD were more likely to marry (HR = 1.34, ps < 0.01). Among EA participants, AUD, CAN, TOB, and MDD were associated with higher odds of divorce (odds ratios [ORs] 1.59-2.21, ps < 0.01). Among AA participants, no predictors were significantly associated with divorce. Significant random effects indicated genetic and environmental influences on marriage, but only environmental factors on divorce. CONCLUSIONS In a high-risk sample, AUD was associated with reduced likelihood of marriage in EA and AA individuals and increased risk of divorce in EA individuals. These associations were largely independent of comorbidities. Genetic and environmental background factors contributed to marriage, while only environmental background factors contributed to divorce. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Affiliation(s)
| | - Sally I-Chun Kuo
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University
| | - Fazil Aliev
- Department of Psychology, Virginia Commonwealth University
| | | | - Jacquelyn M. Meyers
- Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center
| | - Grace Chan
- Department of Psychiatry, University of Connecticut School of Medicine
| | | | - Chella Kamarajan
- Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center
| | - Sivan Kinreich
- Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center
| | | | | | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University
| | | | - Bernice Porjesz
- Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center
| | - Marc A. Schuckit
- Department of Psychiatry, University of California San Diego Medical School
| | - Danielle M. Dick
- Department of Psychology, Virginia Commonwealth University
- Department of Human & Molecular Genetics, Virginia Commonwealth University
| | | | - Jessica E. Salvatore
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University
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Su J, Trevino AD, Kuo SIC, Aliev F, Williams CD, Guy MC, Dick D, Amstadter A, Lilley E, Gelzinis R, Morris A, Bountress K, Adkins A, Thomas N, Neale Z, Pedersen K, Bannard T, Cho S, Barr P, Byers H, Berenz E, Caraway E, Clifford J, Cooke M, Do E, Edwards A, Goyal N, Hack L, Halberstadt L, Hawn S, Kuo S, Lasko E, Lent J, Lind M, Long E, Martelli A, Meyers J, Mitchell K, Moore A, Moscati A, Nasim A, Opalesky J, Overstreet C, Pais C, Raldiris T, Salvatore J, Savage J, Smith R, Sosnowski D, Su J, Walker C, Walsh M, Willoughby T, Woodroof M, Yan J, Sun C, Wormley B, Riley B, Aliev F, Peterson R, Webb B, Dick DM. Racial Discrimination and Alcohol Problems: Examining Interactions with Genetic Risk and Impulsivity among African American Young Adults. J Youth Adolesc 2022; 51:1552-1567. [DOI: 10.1007/s10964-022-01609-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 03/24/2022] [Indexed: 11/30/2022]
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Associations between cognition and polygenic liability to substance involvement in middle childhood: Results from the ABCD study. Drug Alcohol Depend 2022; 232:109277. [PMID: 35033950 PMCID: PMC9331817 DOI: 10.1016/j.drugalcdep.2022.109277] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 11/19/2021] [Accepted: 12/20/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Cognition is robustly associated with substance involvement. This relationship is attributable to multiple factors, including genetics, though such contributions show inconsistent patterns in the literature. For instance, genome-wide association studies point to potential positive relationships between educational achievement and common substance use but negative relationships with heavy and/or problematic substance use. METHODS We estimated associations between polygenic risk for substance involvement (i.e., alcohol, tobacco, and cannabis use and problematic use) and cognition subfacets (i.e., general ability, executive function, learning/memory) derived from confirmatory factor analysis among 3205 substance naïve children (ages 9-10) of European ancestry who completed the baseline session of the Adolescent Brain Cognitive Development (ABCD) Study. FINDINGS Polygenic risk for lifetime cannabis use was positively associated with all three facets of cognitive ability (Bs ≥ 0.045, qs ≤ 0.044). No other substance polygenic risk scores showed significant associations with cognition after adjustment for multiple testing (|Bs|≤0.033, qs ≥ 0.118). CONCLUSIONS Polygenic liability to lifetime cannabis use, but not use disorder, was positively associated with cognitive performance among substance-naïve children, possibly reflecting shared genetic overlap with openness to experience or the influence of genetic variance associated with socioeconomic status. Our lack of findings for the other polygenic scores may reflect ascertainment differences between the genome-wide association study (GWAS) samples and the current sample and/or the young age of the present sample. As longitudinal data in ABCD are collected, this sample may be useful for disentangling putatively causal or predispositional influences of substance use and misuse on cognition.
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Spychala KM, Gizer IR, Davis CN, Dash GF, Piasecki TM, Slutske WS. Predicting disordered gambling across adolescence and young adulthood from polygenic contributions to Big 5 personality traits in a UK birth cohort. Addiction 2022; 117:690-700. [PMID: 34342067 PMCID: PMC8810893 DOI: 10.1111/add.15648] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 07/14/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND AND AIMS Previous research has demonstrated phenotypical associations between disordered gambling (DG) and Big 5 personality traits, and a twin study suggested that shared genetic influences accounted for a substantial portion of this relation. The present study examined associations between DG and polygenic scores (PSs) for Big 5 traits to measure the shared genetic underpinnings of Big 5 personality traits and DG. DESIGN Zero-inflated negative binomial regression models estimated associations between Big 5 PSs and past-year and life-time assessments of DG in a longitudinally assessed population-based birth cohort. SETTING United Kingdom. PARTICIPANTS A total of 4729 unrelated children of European ancestry from the Avon Longitudinal Study of Parents and Children (ALSPAC) with both phenotypical and genetic data. MEASUREMENTS Phenotypical outcomes included past-year assessment of DG using the problem gambling severity index (PGSI) and life-time assessment of DSM-IV pathological gambling symptoms (DPG) across the ages of 17, 20 and 24 years. Polygenic scores were derived for the Big 5 personality traits of agreeableness, extraversion, conscientiousness, openness and neuroticism using summary statistics from genome-wide association studies (GWAS). FINDINGS PSs for agreeableness [β= - 0.25, standard error (SE) = 0.054, P = 3.031e-6, ΔR2 = 0.008] and neuroticism (β=0.14, SE = 0.046, P = 0.0017, ΔR2 = 0.002) significantly predicted PGSI scores over and above included covariates (i.e. sex and first five ancestral principal components). PSs for agreeableness (β= - 0.20, SE = 0.056, P = 0.00036, ΔR2 = 0.003) and neuroticism, when interactions with age were taken into account (β = 0.29, SE = 0.090, P = 0.002, ΔR2 = 0.004), also predicted DPG scores. CONCLUSIONS Polygenic contributions to low agreeableness and high neuroticism appear to predict two measures of disordered gambling (problem gambling severity index and life-time assessment of DSM-IV pathological gambling symptoms). Polygenic scores for neuroticism interact with age to suggest that the positive association becomes stronger from adolescence through young adulthood.
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Affiliation(s)
- Kellyn M Spychala
- Department of Psychological Sciences, University of Missouri, Columbia, MO, USA
| | - Ian R Gizer
- Department of Psychological Sciences, University of Missouri, Columbia, MO, USA
| | - Christal N Davis
- Department of Psychological Sciences, University of Missouri, Columbia, MO, USA
| | - Genevieve F Dash
- Department of Psychological Sciences, University of Missouri, Columbia, MO, USA
| | - Thomas M Piasecki
- Department of Psychological Sciences, University of Missouri, Columbia, MO, USA
| | - Wendy S Slutske
- Department of Psychological Sciences, University of Missouri, Columbia, MO, USA
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Karcher NR, Paul SE, Johnson EC, Hatoum AS, Baranger DAA, Agrawal A, Thompson WK, Barch DM, Bogdan R. Psychotic-like Experiences and Polygenic Liability in the Adolescent Brain Cognitive Development Study. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:45-55. [PMID: 34271214 PMCID: PMC8786267 DOI: 10.1016/j.bpsc.2021.06.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 06/01/2021] [Accepted: 06/28/2021] [Indexed: 01/26/2023]
Abstract
BACKGROUND Childhood psychotic-like experiences (PLEs) often precede the development of later severe psychopathology. This study examined whether childhood PLEs are associated with several psychopathology-related polygenic scores (PGSs) and additionally examined possible neural and behavioral mechanisms. METHODS Adolescent Brain Cognitive Development Study baseline data from children with European ancestry (n = 4650, ages 9-10 years, 46.8% female) were used to estimate associations between PLEs (i.e., both total and presence of significantly distressing) and PGSs for psychopathology (i.e., schizophrenia, psychiatric cross-disorder risk, PLEs) and related phenotypes (i.e., educational attainment [EDU], birth weight, inflammation). We also assessed whether variability in brain structure indices (i.e., volume, cortical thickness, surface area) and behaviors proximal to PGSs (e.g., cognition for EDU) indirectly linked PGSs to PLEs using mediational models. RESULTS Total and significantly distressing PLEs were associated with EDU and cross-disorder PGSs (all %ΔR2s = 0.202%-0.660%; false discovery rate-corrected ps < .006). Significantly distressing PLEs were also associated with higher schizophrenia and PLE PGSs (both %ΔR2 = 0.120%-0.216%; false discovery rate-corrected ps < .03). There was evidence that global brain volume metrics and cognitive performance indirectly linked EDU PGS to PLEs (estimated proportion mediated = 3.33%-32.22%). CONCLUSIONS Total and significantly distressing PLEs were associated with genomic risk indices of broad-spectrum psychopathology risk (i.e., EDU and cross-disorder PGSs). Significantly distressing PLEs were also associated with genomic risk for psychosis (i.e., schizophrenia, PLEs). Global brain volume metrics and PGS-proximal behaviors represent promising putative intermediary phenotypes that may indirectly link genomic risk to psychopathology. Broadly, polygenic scores derived from genome-wide association studies of adult samples generalize to indices of psychopathology risk among children.
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Affiliation(s)
- Nicole R Karcher
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri.
| | - Sarah E Paul
- Department of Psychological and Brain Sciences, Washington University, St. Louis, Missouri
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - Alexander S Hatoum
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - David A A Baranger
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - Wesley K Thompson
- Population Neuroscience and Genetics Laboratory, University of California San Diego, San Diego, California
| | - Deanna M Barch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri; Department of Psychological and Brain Sciences, Washington University, St. Louis, Missouri
| | - Ryan Bogdan
- Department of Psychological and Brain Sciences, Washington University, St. Louis, Missouri
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31
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Bondy E, Bogdan R. Understanding Anhedonia from a Genomic Perspective. Curr Top Behav Neurosci 2022; 58:61-79. [PMID: 35152374 PMCID: PMC9375777 DOI: 10.1007/7854_2021_293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Anhedonia, or the decreased ability to experience pleasure, is a cardinal symptom of major depression that commonly occurs within other forms of psychopathology. Supportive of long-held theory that anhedonia represents a genetically influenced vulnerability marker for depression, evidence from twin studies suggests that it is moderately-largely heritable. However, the genomic sources of this heritability are just beginning to be understood. In this review, we survey what is known about the genomic architecture underlying anhedonia and related constructs. We briefly review twin and initial candidate gene studies before focusing on genome-wide association study (GWAS) and polygenic efforts. As large samples are needed to reliably detect the small effects that typically characterize common genetic variants, the study of anhedonia and related phenotypes conflicts with current genomic research requirements and frameworks that prioritize sample size over precise phenotyping. This has resulted in few and underpowered studies of anhedonia-related constructs that have largely failed to reliably identify individual variants. Nonetheless, the polygenic architecture of anhedonia-related constructs identified in these studies has genetic overlap with depression and schizophrenia as well as related brain structure (e.g., striatal volume), providing important clues to etiology that may usefully guide refinement in nosology. As we await the accumulation of larger samples for more well-powered GWAS of reward-related constructs, novel analytic techniques that leverage GWAS summary statistics (e.g., genomic structural equation modeling) may currently be used to help characterize how the genomic architecture of anhedonia is shared and distinct from that underlying other constructs (e.g., depression, neuroticism, anxiety).
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Affiliation(s)
- Erin Bondy
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, St. Louis, MO, USA
| | - Ryan Bogdan
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, St. Louis, MO, USA.
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High Polygenic Risk Scores Are Associated With Early Age of Onset of Alcohol Use Disorder in Adolescents and Young Adults at Risk. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2021; 2:379-388. [DOI: 10.1016/j.bpsgos.2021.10.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 09/30/2021] [Accepted: 10/01/2021] [Indexed: 11/22/2022] Open
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Ma Y, Zhou X. Genetic prediction of complex traits with polygenic scores: a statistical review. Trends Genet 2021; 37:995-1011. [PMID: 34243982 PMCID: PMC8511058 DOI: 10.1016/j.tig.2021.06.004] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 05/31/2021] [Accepted: 06/03/2021] [Indexed: 01/03/2023]
Abstract
Accurate genetic prediction of complex traits can facilitate disease screening, improve early intervention, and aid in the development of personalized medicine. Genetic prediction of complex traits requires the development of statistical methods that can properly model polygenic architecture and construct a polygenic score (PGS). We present a comprehensive review of 46 methods for PGS construction. We connect the majority of these methods through a multiple linear regression framework which can be instrumental for understanding their prediction performance for traits with distinct genetic architectures. We discuss the practical considerations of PGS analysis as well as challenges and future directions of PGS method development. We hope our review serves as a useful reference both for statistical geneticists who develop PGS methods and for data analysts who perform PGS analysis.
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Affiliation(s)
- Ying Ma
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Xiang Zhou
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA.
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Ronald A, de Bode N, Polderman TJC. Systematic Review: How the Attention-Deficit/Hyperactivity Disorder Polygenic Risk Score Adds to Our Understanding of ADHD and Associated Traits. J Am Acad Child Adolesc Psychiatry 2021; 60:1234-1277. [PMID: 33548493 PMCID: PMC11164195 DOI: 10.1016/j.jaac.2021.01.019] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 01/04/2021] [Accepted: 01/28/2021] [Indexed: 12/21/2022]
Abstract
OBJECTIVE To investigate, by systematically reviewing the literature, whether the attention-deficit/hyperactivity disorder (ADHD) polygenic risk score (PRS) associates with ADHD and related traits in independent clinical and population samples. METHOD PubMed, Embase and PsychoInfo were systematically searched, alongside study bibliographies. Quality assessments were conducted, and a best-evidence synthesis was applied. Studies were excluded when the predictor was not based on the latest ADHD genome-wide association study, when PRS was not based on genome-wide results, or when the study was a review. Initially, 197 studies were retrieved (February 22, 2020), and a second search (June 3, 2020) yielded a further 49 studies. From both searches, 57 studies were eligible, and 44 studies met inclusion criteria. RESULTS Included studies were published in the last 3 years. Over 80% of the studies were rated excellent, based on a standardized quality assessment. Evidence of associations between ADHD PRS and the following categories was strong: ADHD, ADHD traits, brain structure, education, externalizing behaviors, neuropsychological constructs, physical health, and socioeconomic status. Evidence for associations with addiction, autism, and mental health were mixed and were, so far, inconclusive. Odds ratios for PRS associating with ADHD ranged from 1.22% to 1.76%; variance explained in dimensional assessments of ADHD traits was 0.7% to 3.3%. CONCLUSION A new wave of high-quality research using the ADHD PRS has emerged. Eventually, symptoms may be partly identified based on PRS, but the current ADHD PRS is useful for research purposes only. This review shows that the ADHD PRS is robust and reliable, associating not only with ADHD but many outcomes and challenges known to be linked to ADHD.
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Affiliation(s)
| | - Nora de Bode
- Vrije Universiteit Amsterdam, the Netherlands, and Amsterdam UMC, the Netherlands
| | - Tinca J C Polderman
- Vrije Universiteit Amsterdam, the Netherlands, and Amsterdam UMC, the Netherlands.
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Friedman NP, Banich MT, Keller MC. Twin studies to GWAS: there and back again. Trends Cogn Sci 2021; 25:855-869. [PMID: 34312064 PMCID: PMC8446317 DOI: 10.1016/j.tics.2021.06.007] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 06/25/2021] [Accepted: 06/28/2021] [Indexed: 01/01/2023]
Abstract
The field of human behavioral genetics has come full circle. It began by using twin/family studies to estimate the relative importance of genetic and environmental influences. As large-scale genotyping became cost-effective, genome-wide association studies (GWASs) yielded insights about the nature of genetic influences and new methods that use GWAS data to estimate heritability and genetic correlations invigorated the field. Yet these newer GWAS methods have not replaced twin/family studies. In this review, we discuss the strengths and weaknesses of the two approaches with respect to characterizing genetic and environmental influences, measurement of behavioral phenotypes, and evaluation of causal models, with a particular focus on cognitive neuroscience. This discussion highlights how twin/family studies and GWAS complement and mutually reinforce one another.
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Affiliation(s)
- Naomi P Friedman
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO 80309, USA; Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO 80309, USA.
| | - Marie T Banich
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO 80309, USA; Institute of Cognitive Science, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Matthew C Keller
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO 80309, USA; Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO 80309, USA
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Neale ZE, Kuo SIC, Dick DM. A systematic review of gene-by-intervention studies of alcohol and other substance use. Dev Psychopathol 2021; 33:1410-1427. [PMID: 32602428 PMCID: PMC7772257 DOI: 10.1017/s0954579420000590] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Alcohol and other substance use problems are common, and the efficacy of current prevention and intervention programs is limited. Genetics may contribute to differential effectiveness of psychosocial prevention and intervention programs. This paper reviews gene-by-intervention (G×I) studies of alcohol and other substance use, and implications for integrating genetics into prevention science. Systematic review yielded 17 studies for inclusion. Most studies focused on youth substance prevention, alcohol was the most common outcome, and measures of genotype were heterogeneous. All studies reported at least one significant G×I interaction. We discuss these findings in the context of the history and current state of genetics, and provide recommendations for future G×I research. These include the integration of genome-wide polygenic scores into prevention studies, broad outcome measurement, recruitment of underrepresented populations, testing mediators of G×I effects, and addressing ethical implications. Integrating genetic research into prevention science, and training researchers to work fluidly across these fields, will enhance our ability to determine the best intervention for each individual across development. With growing public interest in obtaining personalized genetic information, we anticipate that the integration of genetics and prevention science will become increasingly important as we move into the era of precision medicine.
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Affiliation(s)
- Zoe E. Neale
- Department of Psychology, Virginia Commonwealth University
| | | | - Danielle M. Dick
- Department of Psychology, Virginia Commonwealth University
- Department of Human and Molecular Genetics, Virginia Commonwealth University
- College Behavioral and Emotional Health Institute, Virginia Commonwealth University
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Byrd AL, Tung I, Manuck SD, Vine V, Horner M, Hipwell AE, Stepp SD. An interaction between early threat exposure and the oxytocin receptor in females: Disorder-specific versus general risk for psychopathology and social-emotional mediators. Dev Psychopathol 2021; 33:1248-1263. [PMID: 32693857 PMCID: PMC7934270 DOI: 10.1017/s0954579420000462] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Early threat exposure is a transdiagnostic risk factor for psychopathology, and evidence suggests that genetic variation in the oxytocin receptor (OXTR) moderates this association. However, it is unclear if this gene-by-environment (G×E) interaction is tied to unique risk for disorder-specific outcomes or instead increases shared risk for general psychopathology. Moreover, little is known about how this G×E interaction increases risk. The current study utilized a prospective, longitudinal sample of females (n = 2,020) to examine: (a) whether the interaction between early threat exposure and OXTR variation (rs53576, rs2254298) confers risk for disorder-specific outcomes (depression, anxiety, borderline and antisocial personality disorders) and/or general psychopathology in early adulthood; and (b) whether social-emotional deficits (emotion dysregulation, callousness, attachment quality) during adolescence constitute mediating mechanisms. Consistent with hypotheses, the interactive effects of early threat exposure and OXTR variation (rs53576) predicted general psychopathology, with threat-exposed women carrying at least one copy of the rs53576 A-allele at greatest risk. This interaction was mediated via emotional dysregulation in adolescence, with threat-exposed A-allele carriers demonstrating greater emotion dysregulation, and greater emotion dysregulation predicting general psychopathology in early adulthood. Findings suggest that this G×E places women at risk for a broad range of psychopathology via effects on emotion dysregulation.
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Affiliation(s)
- Amy L. Byrd
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Irene Tung
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Stephen D. Manuck
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Vera Vine
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Michelle Horner
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Alison E. Hipwell
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Stephanie D. Stepp
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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38
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Kuo SIC, Salvatore JE, Barr PB, Aliev F, Anokhin A, Bucholz KK, Chan G, Edenberg HJ, Hesselbrock V, Kamarajan C, Kramer JR, Lai D, Mallard TT, Nurnberger JI, Pandey G, Plawecki MH, Sanchez-Roige S, Waldman I, Palmer AA, Dick DM. Mapping Pathways by Which Genetic Risk Influences Adolescent Externalizing Behavior: The Interplay Between Externalizing Polygenic Risk Scores, Parental Knowledge, and Peer Substance Use. Behav Genet 2021; 51:543-558. [PMID: 34117972 PMCID: PMC8403154 DOI: 10.1007/s10519-021-10067-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 05/26/2021] [Indexed: 12/25/2022]
Abstract
Genetic predispositions and environmental influences both play an important role in adolescent externalizing behavior; however, they are not always independent. To elucidate gene-environment interplay, we examined the interrelationships between externalizing polygenic risk scores, parental knowledge, and peer substance use in impacting adolescent externalizing behavior across two time-points in a high-risk longitudinal sample of 1,200 adolescents (764 European and 436 African ancestry; Mage = 12.99) from the Collaborative Study on the Genetics of Alcoholism. Results from multivariate path analysis indicated that externalizing polygenic scores were directly associated with adolescent externalizing behavior but also indirectly via peer substance use, in the European ancestry sample. No significant polygenic association nor indirect effects of genetic risk were observed in the African ancestry group, likely due to more limited power. Our findings underscore the importance of gene-environment interplay and suggest peer substance use may be a mechanism through which genetic risk influences adolescent externalizing behavior.
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Affiliation(s)
- Sally I-Chun Kuo
- Department of Psychology, Virginia Commonwealth University, Box 842018, 806 W Franklin St, Richmond, VA, 23284, USA.
| | - Jessica E Salvatore
- Department of Psychology, Virginia Commonwealth University, Box 842018, 806 W Franklin St, Richmond, VA, 23284, USA
| | - Peter B Barr
- Department of Psychology, Virginia Commonwealth University, Box 842018, 806 W Franklin St, Richmond, VA, 23284, USA
| | - Fazil Aliev
- Department of Psychology, Virginia Commonwealth University, Box 842018, 806 W Franklin St, Richmond, VA, 23284, USA
| | - Andrey Anokhin
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Kathleen K Bucholz
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Grace Chan
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, USA
| | - Victor Hesselbrock
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Chella Kamarajan
- Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - John R Kramer
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, USA
| | - Travis T Mallard
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
| | - John I Nurnberger
- Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, USA
| | - Gayathri Pandey
- Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | | | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Irwin Waldman
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute of Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Danielle M Dick
- Department of Psychology, Virginia Commonwealth University, Box 842018, 806 W Franklin St, Richmond, VA, 23284, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
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39
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Quattrone D, Reininghaus U, Richards AL, Tripoli G, Ferraro L, Quattrone A, Marino P, Rodriguez V, Spinazzola E, Gayer-Anderson C, Jongsma HE, Jones PB, La Cascia C, La Barbera D, Tarricone I, Bonora E, Tosato S, Lasalvia A, Szöke A, Arango C, Bernardo M, Bobes J, Del Ben CM, Menezes PR, Llorca PM, Santos JL, Sanjuán J, Arrojo M, Tortelli A, Velthorst E, Berendsen S, de Haan L, Rutten BPF, Lynskey MT, Freeman TP, Kirkbride JB, Sham PC, O’Donovan MC, Cardno AG, Vassos E, van Os J, Morgan C, Murray RM, Lewis CM, Di Forti M. The continuity of effect of schizophrenia polygenic risk score and patterns of cannabis use on transdiagnostic symptom dimensions at first-episode psychosis: findings from the EU-GEI study. Transl Psychiatry 2021; 11:423. [PMID: 34376640 PMCID: PMC8355107 DOI: 10.1038/s41398-021-01526-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Revised: 06/16/2021] [Accepted: 06/30/2021] [Indexed: 12/22/2022] Open
Abstract
Diagnostic categories do not completely reflect the heterogeneous expression of psychosis. Using data from the EU-GEI study, we evaluated the impact of schizophrenia polygenic risk score (SZ-PRS) and patterns of cannabis use on the transdiagnostic expression of psychosis. We analysed first-episode psychosis patients (FEP) and controls, generating transdiagnostic dimensions of psychotic symptoms and experiences using item response bi-factor modelling. Linear regression was used to test the associations between these dimensions and SZ-PRS, as well as the combined effect of SZ-PRS and cannabis use on the dimensions of positive psychotic symptoms and experiences. We found associations between SZ-PRS and (1) both negative (B = 0.18; 95%CI 0.03-0.33) and positive (B = 0.19; 95%CI 0.03-0.35) symptom dimensions in 617 FEP patients, regardless of their categorical diagnosis; and (2) all the psychotic experience dimensions in 979 controls. We did not observe associations between SZ-PRS and the general and affective dimensions in FEP. Daily and current cannabis use were associated with the positive dimensions in FEP (B = 0.31; 95%CI 0.11-0.52) and in controls (B = 0.26; 95%CI 0.06-0.46), over and above SZ-PRS. We provide evidence that genetic liability to schizophrenia and cannabis use map onto transdiagnostic symptom dimensions, supporting the validity and utility of the dimensional representation of psychosis. In our sample, genetic liability to schizophrenia correlated with more severe psychosis presentation, and cannabis use conferred risk to positive symptomatology beyond the genetic risk. Our findings support the hypothesis that psychotic experiences in the general population have similar genetic substrates as clinical disorders.
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Affiliation(s)
- Diego Quattrone
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK. .,National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK. .,Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, 68159, Germany.
| | - Ulrich Reininghaus
- grid.7700.00000 0001 2190 4373Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, 68159 Germany ,grid.13097.3c0000 0001 2322 6764Department of Health Service and Population Research, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK ,grid.412966.e0000 0004 0480 1382Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, South Limburg Mental Health Research and Teaching Network, Maastricht University Medical Centre, P.O. Box 616, 6200 MD Maastricht, The Netherlands
| | - Alex L. Richards
- grid.5600.30000 0001 0807 5670Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, CF24 4HQ UK
| | - Giada Tripoli
- grid.10776.370000 0004 1762 5517Department of Experimental Biomedicine and Clinical Neuroscience, University of Palermo, Via G. La Loggia 1, 90129 Palermo, Italy
| | - Laura Ferraro
- grid.10776.370000 0004 1762 5517Department of Experimental Biomedicine and Clinical Neuroscience, University of Palermo, Via G. La Loggia 1, 90129 Palermo, Italy
| | - Andrea Quattrone
- National Health Care System, Villa Betania Psychological Institute, 89100 Reggio Calabria, Italy
| | - Paolo Marino
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Victoria Rodriguez
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Edoardo Spinazzola
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Charlotte Gayer-Anderson
- grid.13097.3c0000 0001 2322 6764Department of Health Service and Population Research, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Hannah E. Jongsma
- grid.83440.3b0000000121901201Psylife Group, Division of Psychiatry, University College London, 6th Floor, Maple House, 149 Tottenham Court Road, London, W1T 7NF UK ,grid.4494.d0000 0000 9558 4598Centre for Transcultural Psychiatry “Veldzicht” Balkbrug, the Netherlands, VR Mental Health Group, University Center for Psychiatry, Univerisity Medical Centre Groningen, Groningen, The Netherlands
| | - Peter B. Jones
- grid.5335.00000000121885934Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain & Mind Sciences, Forvie Site, Robinson Way, Cambridge, CB2 0SZ UK ,grid.450563.10000 0004 0412 9303CAMEO Early Intervention Service, Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, CB21 5EF UK
| | - Caterina La Cascia
- National Health Care System, Villa Betania Psychological Institute, 89100 Reggio Calabria, Italy
| | - Daniele La Barbera
- National Health Care System, Villa Betania Psychological Institute, 89100 Reggio Calabria, Italy
| | - Ilaria Tarricone
- grid.6292.f0000 0004 1757 1758Department of Medical and Surgical Science, Psychiatry Unit, Alma Mater Studiorum Università di Bologna, Viale Pepoli 5, 40126 Bologna, Italy
| | - Elena Bonora
- grid.6292.f0000 0004 1757 1758Department of Medical and Surgical Science, Psychiatry Unit, Alma Mater Studiorum Università di Bologna, Viale Pepoli 5, 40126 Bologna, Italy
| | - Sarah Tosato
- grid.5611.30000 0004 1763 1124Section of Psychiatry, Department of Neuroscience, Biomedicine and Movement, University of Verona, Piazzale L.A. Scuro 10, 37134 Verona, Italy
| | - Antonio Lasalvia
- grid.5611.30000 0004 1763 1124Section of Psychiatry, Department of Neuroscience, Biomedicine and Movement, University of Verona, Piazzale L.A. Scuro 10, 37134 Verona, Italy
| | - Andrei Szöke
- grid.7429.80000000121866389INSERM, U955, Equipe 15, 51 Avenue de Maréchal de Lattre de Tassigny, 94010 Créteil, France
| | - Celso Arango
- grid.4795.f0000 0001 2157 7667Child and Adolescent Psychiatry Department, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, School of Medicine, Universidad Complutense, IiSGM, CIBERSAM, C/Doctor Esquerdo 46, 28007 Madrid, Spain
| | - Miquel Bernardo
- grid.5841.80000 0004 1937 0247Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, Department of Medicine, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Spain
| | - Julio Bobes
- grid.10863.3c0000 0001 2164 6351Faculty of Medicine and Health Sciences - Psychiatry, Universidad de Oviedo, ISPA, INEUROPA. CIBERSAM, Oviedo, Spain
| | - Cristina Marta Del Ben
- grid.11899.380000 0004 1937 0722Neuroscience and Behavior Department, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
| | - Paulo Rossi Menezes
- grid.11899.380000 0004 1937 0722Department of Preventative Medicine, Faculdade de Medicina FMUSP, University of São Paulo, São Paulo, Brazil
| | - Pierre-Michel Llorca
- grid.494717.80000000115480420University Clermont Auvergne, CMP-B CHU, CNRS, Clermont Auvergne INP, Institut Pascal, F-63000 Clermont-Ferrand, France
| | - Jose Luis Santos
- grid.413507.40000 0004 1765 7383Department of Psychiatry, Servicio de Psiquiatría Hospital “Virgen de la Luz,”, Cuenca, Spain
| | - Julio Sanjuán
- grid.5338.d0000 0001 2173 938XDepartment of Psychiatry, School of Medicine, Universidad de Valencia, Centro de Investigación Biomédica en Red de Salud Mental, Valencia, Spain
| | - Manuel Arrojo
- grid.411048.80000 0000 8816 6945Department of Psychiatry, Psychiatric Genetic Group, Instituto de Investigación Sanitaria de Santiago de Compostela, Complejo Hospitalario Universitario de Santiago de Compostela, Santiago, Spain
| | | | - Eva Velthorst
- grid.7177.60000000084992262Department of Psychiatry, Early Psychosis Section, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands ,grid.59734.3c0000 0001 0670 2351Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Steven Berendsen
- grid.7177.60000000084992262Department of Psychiatry, Early Psychosis Section, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands
| | - Lieuwe de Haan
- grid.7177.60000000084992262Department of Psychiatry, Early Psychosis Section, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands
| | - Bart P. F. Rutten
- grid.412966.e0000 0004 0480 1382Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, South Limburg Mental Health Research and Teaching Network, Maastricht University Medical Centre, P.O. Box 616, 6200 MD Maastricht, The Netherlands
| | - Michael T. Lynskey
- grid.13097.3c0000 0001 2322 6764National Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 4 Windsor Walk, London, SE5 8BB UK
| | - Tom P. Freeman
- grid.13097.3c0000 0001 2322 6764National Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 4 Windsor Walk, London, SE5 8BB UK ,grid.7340.00000 0001 2162 1699Department of Psychology, University of Bath, 10 West, Bath, BA2 7AY UK
| | - James B. Kirkbride
- grid.83440.3b0000000121901201Psylife Group, Division of Psychiatry, University College London, 6th Floor, Maple House, 149 Tottenham Court Road, London, W1T 7NF UK
| | - Pak C. Sham
- grid.194645.b0000000121742757Department of Psychiatry, the University of Hong Kong, Pok Fu Lam, Hong Kong ,grid.194645.b0000000121742757Centre for Genomic Sciences, Li KaShing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Michael C. O’Donovan
- grid.5600.30000 0001 0807 5670Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, CF24 4HQ UK
| | - Alastair G. Cardno
- grid.9909.90000 0004 1936 8403Division of Psychological and Social Medicine, Leeds Institute of Health Sciences, Faculty of Medicine and Health, University of Leeds, Leeds, LS2 9NL UK
| | - Evangelos Vassos
- grid.13097.3c0000 0001 2322 6764Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, SE5 8AF, London, UK ,grid.13097.3c0000 0001 2322 6764National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, King’s College London, London, UK
| | - Jim van Os
- grid.412966.e0000 0004 0480 1382Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, South Limburg Mental Health Research and Teaching Network, Maastricht University Medical Centre, P.O. Box 616, 6200 MD Maastricht, The Netherlands ,grid.7692.a0000000090126352Brain Centre Rudolf Magnus, Utrecht University Medical Centre, Utrecht, The Netherlands
| | - Craig Morgan
- grid.13097.3c0000 0001 2322 6764Department of Health Service and Population Research, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Robin M. Murray
- grid.10776.370000 0004 1762 5517Department of Experimental Biomedicine and Clinical Neuroscience, University of Palermo, Via G. La Loggia 1, 90129 Palermo, Italy ,grid.13097.3c0000 0001 2322 6764National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, King’s College London, London, UK
| | - Cathryn M. Lewis
- grid.13097.3c0000 0001 2322 6764Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, SE5 8AF, London, UK ,grid.13097.3c0000 0001 2322 6764National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, King’s College London, London, UK
| | - Marta Di Forti
- grid.13097.3c0000 0001 2322 6764Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, SE5 8AF, London, UK ,grid.13097.3c0000 0001 2322 6764National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, King’s College London, London, UK
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40
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Cho SB, Smith RL, Bucholz K, Chan G, Edenberg HJ, Hesselbrock V, Kramer J, McCutcheon VV, Nurnberger J, Schuckit M, Zang Y, Dick DM, Salvatore JE. Using a developmental perspective to examine the moderating effects of marriage on heavy episodic drinking in a young adult sample enriched for risk. Dev Psychopathol 2021; 33:1097-1106. [PMID: 32611468 PMCID: PMC7775899 DOI: 10.1017/s0954579420000371] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Many studies demonstrate that marriage protects against risky alcohol use and moderates genetic influences on alcohol outcomes; however, previous work has not considered these effects from a developmental perspective or in high-risk individuals. These represent important gaps, as it cannot be assumed that marriage has uniform effects across development or in high-risk samples. We took a longitudinal developmental approach to examine whether marital status was associated with heavy episodic drinking (HED), and whether marital status moderated polygenic influences on HED. Our sample included 937 individuals (53.25% female) from the Collaborative Study on the Genetics of Alcoholism who reported their HED and marital status biennially between the ages of 21 and 25. Polygenic risk scores (PRS) were derived from a genome-wide association study of alcohol consumption. Marital status was not associated with HED; however, we observed pathogenic gene-by-environment effects that changed across young adulthood. Among those who married young (age 21), individuals with higher PRS reported more HED; however, these effects decayed over time. The same pattern was found in supplementary analyses using parental history of alcohol use disorder as the index of genetic liability. Our findings indicate that early marriage may exacerbate risk for those with higher polygenic load.
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Affiliation(s)
- Seung Bin Cho
- Department of Psychology, Pusan National University, Busan, South Korea
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - Rebecca L Smith
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - Kathleen Bucholz
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Grace Chan
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Victor Hesselbrock
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
| | - John Kramer
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Vivia V McCutcheon
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - John Nurnberger
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Marc Schuckit
- Department of Psychiatry, University of California-San Diego, La Jolla, CA, USA
| | - Yong Zang
- Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Danielle M Dick
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Jessica E Salvatore
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
- Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA
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41
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Hatoum AS, Johnson EC, Baranger DAA, Paul SE, Agrawal A, Bogdan R. Polygenic risk scores for alcohol involvement relate to brain structure in substance-naïve children: Results from the ABCD study. GENES, BRAIN, AND BEHAVIOR 2021; 20:e12756. [PMID: 34092032 PMCID: PMC8645657 DOI: 10.1111/gbb.12756] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 05/29/2021] [Accepted: 06/02/2021] [Indexed: 05/09/2023]
Abstract
Brain imaging-derived structural correlates of alcohol involvement have largely been speculated to arise as a consequence of alcohol exposure. However, they may also reflect predispositional risk. In substance naïve children of European ancestry who completed the baseline session of the Adolescent Brain Cognitive Development (ABCD) Study (n = 3013), mixed-effects models estimated whether polygenic risk scores (PRS) for problematic alcohol use (PAU-PRS) and drinks per week (DPW-PRS) are associated with magnetic resonance imaging-derived brain structure phenotypes (i.e., total and regional: cortical thickness, surface area and volume; subcortical volume; white matter volume, fractional anisotropy, mean diffusivity). Follow-up analyses evaluated whether any identified regions were also associated with polygenic risk among substance naïve children of African ancestry (n = 898). After adjustment for multiple testing correction, polygenic risk for PAU was associated with lower volume of the left frontal pole and greater cortical thickness of the right supramarginal gyrus (|βs| > 0.009; ps < 0.001; psfdr < 0.046; r2 s < 0.004). PAU PRS and DPW PRS showed nominally significant associations with a host of other regional brain structure phenotypes (e.g., insula surface area and volume). None of these regions showed any, even nominal association among children of African ancestry. Genomic liability to alcohol involvement may manifest as variability in brain structure during middle childhood prior to alcohol use initiation. Broadly, alcohol-related variability in brain morphometry may partially reflect predisposing genomic influence. Larger discovery genome-wide association studies and target samples of diverse ancestries are needed to determine whether observed associations may generalize across ancestral origins.
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Affiliation(s)
- Alexander S Hatoum
- Department of Psychiatry, Washington University St. Louis Medical School, St. Louis, Missouri, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University St. Louis Medical School, St. Louis, Missouri, USA
| | - David A A Baranger
- Department of Psychiatry, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Sarah E Paul
- Department of Psychology & Brain Sciences, Washington University St. Louis, St. Louis, Missouri, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University St. Louis Medical School, St. Louis, Missouri, USA
| | - Ryan Bogdan
- Department of Psychology & Brain Sciences, Washington University St. Louis, St. Louis, Missouri, USA
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42
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Downregulation by CNNM2 of ATP5MD expression in the 10q24.32 schizophrenia-associated locus involved in impaired ATP production and neurodevelopment. NPJ SCHIZOPHRENIA 2021; 7:27. [PMID: 34021155 PMCID: PMC8139961 DOI: 10.1038/s41537-021-00159-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 04/21/2021] [Indexed: 12/11/2022]
Abstract
Genome-wide association studies (GWAS) have accelerated the discovery of numerous genetic variants associated with schizophrenia. However, most risk variants show a small effect size (odds ratio (OR) <1.2), suggesting that more functional risk variants remain to be identified. Here, we employed region-based multi-marker analysis of genomic annotation (MAGMA) to identify additional risk loci containing variants with large OR value from Psychiatry Genomics Consortium (PGC2) schizophrenia GWAS data and then employed summary-data-based mendelian randomization (SMR) to prioritize schizophrenia susceptibility genes. The top-ranked susceptibility gene ATP5MD, encoding an ATP synthase membrane subunit, is observed to be downregulated in schizophrenia by the risk allele of CNNM2-rs1926032 in the schizophrenia-associated 10q24.32 locus. The Atp5md knockout (KO) in mice was associated with abnormal startle reflex and gait, and ATP5MD knockdown (KD) in human induced pluripotent stem cell-derived neurons disrupted the neural development and mitochondrial respiration and ATP production. Moreover, CNNM2-rs1926032 KO could induce downregulation of ATP5MD expression and disruptions of mitochondrial respiration and ATP production. This study constitutes an important mechanistic component that links schizophrenia-associated CNNM2 regions to disruption in energy adenosine system modulation and neuronal function by long-distance chromatin domain downregulation of ATP5MD. This pathogenic mechanism provides therapeutic implications for schizophrenia.
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Zhao B, Zhu H. On Genetic Correlation Estimation With Summary Statistics From Genome-Wide Association Studies. J Am Stat Assoc 2021; 117:1-11. [PMID: 35757777 PMCID: PMC9232179 DOI: 10.1080/01621459.2021.1906684] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Revised: 03/12/2021] [Accepted: 03/16/2021] [Indexed: 01/03/2023]
Abstract
Cross-trait polygenic risk score (PRS) method has gained popularity for assessing genetic correlation of complex traits using summary statistics from biobank-scale genome-wide association studies (GWAS). However, empirical evidence has shown a common bias phenomenon that highly significant cross-trait PRS can only account for a very small amount of genetic variance (R 2 can be < 1%) in independent testing GWAS. The aim of this paper is to investigate and address the bias phenomenon of cross-trait PRS in numerous GWAS applications. We show that the estimated genetic correlation can be asymptotically biased toward zero. A consistent cross-trait PRS estimator is then proposed to correct such asymptotic bias. In addition, we investigate whether or not SNP screening by GWAS p-values can lead to improved estimation and show the effect of overlapping samples among GWAS. We analyze GWAS summary statistics of reaction time and brain structural magnetic resonance imaging-based features measured in the Pediatric Imaging, Neurocognition, and Genetics study. We find that the raw cross-trait PRS estimators heavily underestimate the genetic similarity between cognitive function and human brain structures (mean R 2 = 1.32%), whereas the bias-corrected estimators uncover the moderate degree of genetic overlap between these closely related heritable traits (mean R 2 = 22.42%). Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
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Affiliation(s)
- Bingxin Zhao
- Department of Biostatistics, University of North Carolina at Chapel Hill, NC
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, NC
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Risner VA, Benca-Bachman CE, Bertin L, Smith AK, Kaprio J, McGeary JE, Chesler E, Knopik V, Friedman N, Palmer RHC. Multi-polygenic Analysis of Nicotine Dependence in Individuals of European Ancestry. Nicotine Tob Res 2021; 23:2102-2109. [PMID: 34008017 DOI: 10.1093/ntr/ntab105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 05/14/2021] [Indexed: 11/12/2022]
Abstract
INTRODUCTION Heritability estimates of nicotine dependence (ND) range from 40-70%, but discovery GWAS of ND are underpowered and have limited predictive utility. In this work, we leverage genetically correlated traits and diseases to increase the accuracy of polygenic risk prediction. METHODS We employed a multi-trait model using summary statistic-based best linear unbiased predictors (SBLUP) of genetic correlates of DSM-IV diagnosis of ND in 6,394 individuals of European Ancestry (prevalence = 45.3%, %female = 46.8%, µage = 40.08 [s.d. = 10.43]) and 3,061 individuals from a nationally-representative sample with Fagerström Test for Nicotine Dependence symptom count (FTND; 51.32% female, mean age = 28.9 [s.d. = 1.70]). Polygenic predictors were derived from GWASs known to be phenotypically and genetically correlated with ND (i.e., Cigarettes per Day (CPD), the Alcohol Use Disorders Identification Test (AUDIT-Consumption and AUDIT-Problems), Neuroticism, Depression, Schizophrenia, Educational Attainment, Body Mass Index (BMI), and Self-Perceived Risk-Taking); including Height as a negative control. Analyses controlled for age, gender, study site, and the first 10 ancestral principal components. RESULTS The multi-trait model accounted for 3.6% of the total trait variance in DSM-IV ND. Educational Attainment (β=-0.125; 95% confidence interval (CI): [-0.149,-0.101]), CPD (0.071 [0.047,0.095]), and Self-Perceived Risk-Taking (0.051 [0.026,0.075]) were the most robust predictors. PGS effects on FTND were limited. CONCLUSIONS Risk for ND is not only polygenic, but also pleiotropic. Polygenic effects on ND that are accessible by these traits are limited in size and act additively to explain risk.
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Affiliation(s)
- Victoria A Risner
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta GA
| | - Chelsie E Benca-Bachman
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta GA
| | - Lauren Bertin
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta GA
| | - Alicia K Smith
- Smith Lab, Department of Gynecology and Obstetrics, Emory University School of Medicine, Atlanta GA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki Finland.,Department of Public Health, University of Helsinki, Helsinki Finland
| | - John E McGeary
- Department of Psychiatry & Human Behavior, Brown University, Providence RI.,The Genomic Laboratory, Providence VA Medical Center, Providence RI
| | | | - Valerie Knopik
- Department of Human Development and Family Studies, College of Health and Human Sciences, Purdue University, West Lafayette IN
| | - Naomi Friedman
- Department of Psychology, University of Colorado at Boulder, Boulder, CO
| | - Rohan H C Palmer
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta GA
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Kibitov AO, Mazo GE. [Anhedonia in depression: neurobiological and genetic aspects]. Zh Nevrol Psikhiatr Im S S Korsakova 2021; 121:146-154. [PMID: 33834733 DOI: 10.17116/jnevro2021121031146] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Anhedonia is indeed a pathogenetically important clinical phenotype and a promising endophenotype for depressive symptoms with a very high contribution of biological and genetic factors. Neurobiological mechanisms of anhedonia are impaired functioning of the reward system of the brain, which is confirmed by many neuroimaging, genetic and experimental studies. Anhedonia has a trans-diagnoctic character and should be understood as a complex phenomenon, and it is important to correctly evaluate it within the framework of a particular research paradigm. It seems optimal to form several complementary research strategies that evaluate the most important «facets» of anhedonia, regardless of the nosological form of the disease, within the framework of one study using various methods to search for adequate biomarkers of anhedonia severity (genetic, neuroimaging, biochemical). Given the high-quality organization of such comprehensive studies based on the correct methodology of evidence-based medicine, it is likely that significant biomarker systems will be available in the near future, which, if replicated in independent samples, can be used to personalize the diagnosis and treatment of depression.
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Affiliation(s)
- A O Kibitov
- Bekhterev National Medical Research Center for Psychiatry and Neurology, St. Petersburg, Russia.,Serbsky National Medical Research Center on Psychiatry and Addictions, Moscow, Russia
| | - G E Mazo
- Bekhterev National Medical Research Center for Psychiatry and Neurology, St. Petersburg, Russia
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46
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Zhao B, Zou F. On polygenic risk scores for complex traits prediction. Biometrics 2021; 78:499-511. [PMID: 33786811 DOI: 10.1111/biom.13466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 03/10/2021] [Accepted: 03/15/2021] [Indexed: 12/01/2022]
Abstract
Polygenic risk scores (PRS) have gained substantial attention for complex traits prediction in genome-wide association studies (GWAS). Motivated by the polygenic model of complex traits, we study the statistical properties of PRS under the high-dimensional but sparsity free setting where the triplet ( n , p , m ) → ( ∞ , ∞ , ∞ ) with n , p , m being the sample size, the number of assayed single-nucleotide polymorphisms (SNPs), and the number of assayed causal SNPs, respectively. First, we derive asymptotic results on the out-of-sample (prediction) R-squared for PRS. These results help understand the widespread observed gap between the in-sample heritability (or partial R-squared due to the genetic features) estimate and the out-of-sample R-squared for most complex traits. Next, we investigate how features should be selected (e.g., by a p-value threshold) for constructing optimal PRS. We reveal that the optimal threshold depends largely on the genetic architecture underlying the complex trait and the sample size of the training GWAS, or the m / n ratio. For highly polygenic traits with a large m / n ratio, it is difficult to separate causal and null SNPs and stringent feature selection in principle often leads to poor PRS prediction. We numerically illustrate the theoretical results with intensive simulation studies and real data analysis on 33 complex traits with a wide range of genetic architectures in the UK Biobank database.
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Affiliation(s)
- Bingxin Zhao
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Fei Zou
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, USA
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Harper J, Liu M, Malone SM, McGue M, Iacono WG, Vrieze SI. Using multivariate endophenotypes to identify psychophysiological mechanisms associated with polygenic scores for substance use, schizophrenia, and education attainment. Psychol Med 2021; 52:1-11. [PMID: 33731234 PMCID: PMC8448784 DOI: 10.1017/s0033291721000763] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 02/16/2021] [Accepted: 02/17/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND To better characterize brain-based mechanisms of polygenic liability for psychopathology and psychological traits, we extended our previous report (Liu et al. Psychophysiological endophenotypes to characterize mechanisms of known schizophrenia genetic loci. Psychological Medicine, 2017), focused solely on schizophrenia, to test the association between multivariate psychophysiological candidate endophenotypes (including novel measures of θ/δ oscillatory activity) and a range of polygenic scores (PGSs), namely alcohol/cannabis/nicotine use, an updated schizophrenia PGS (containing 52 more genome-wide significant loci than the PGS used in our previous report) and educational attainment. METHOD A large community-based twin/family sample (N = 4893) was genome-wide genotyped and imputed. PGSs were constructed for alcohol use, regular smoking initiation, lifetime cannabis use, schizophrenia, and educational attainment. Eleven endophenotypes were assessed: visual oddball task event-related electroencephalogram (EEG) measures (target-related parietal P3 amplitude, frontal θ, and parietal δ energy/inter-trial phase clustering), band-limited resting-state EEG power, antisaccade error rate. Principal component analysis exploited covariation among endophenotypes to extract a smaller number of meaningful dimensions/components for statistical analysis. RESULTS Endophenotypes were heritable. PGSs showed expected intercorrelations (e.g. schizophrenia PGS correlated positively with alcohol/nicotine/cannabis PGSs). Schizophrenia PGS was negatively associated with an event-related P3/δ component [β = -0.032, nonparametric bootstrap 95% confidence interval (CI) -0.059 to -0.003]. A prefrontal control component (event-related θ/antisaccade errors) was negatively associated with alcohol (β = -0.034, 95% CI -0.063 to -0.006) and regular smoking PGSs (β = -0.032, 95% CI -0.061 to -0.005) and positively associated with educational attainment PGS (β = 0.031, 95% CI 0.003-0.058). CONCLUSIONS Evidence suggests that multivariate endophenotypes of decision-making (P3/δ) and cognitive/attentional control (θ/antisaccade error) relate to alcohol/nicotine, schizophrenia, and educational attainment PGSs and represent promising targets for future research.
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Affiliation(s)
- Jeremy Harper
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Twin Cities, MN, USA
| | - Mengzhen Liu
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
| | - Stephen M. Malone
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
| | - William G. Iacono
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
| | - Scott I. Vrieze
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
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Pathways to well-being: Untangling the causal relationships among biopsychosocial variables. Soc Sci Med 2021; 272:112846. [DOI: 10.1016/j.socscimed.2020.112846] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 12/30/2019] [Accepted: 02/08/2020] [Indexed: 02/07/2023]
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Mojarad BA, Yin Y, Manshaei R, Backstrom I, Costain G, Heung T, Merico D, Marshall CR, Bassett AS, Yuen RKC. Genome sequencing broadens the range of contributing variants with clinical implications in schizophrenia. Transl Psychiatry 2021; 11:84. [PMID: 33526774 PMCID: PMC7851385 DOI: 10.1038/s41398-021-01211-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Revised: 12/28/2020] [Accepted: 01/12/2021] [Indexed: 02/06/2023] Open
Abstract
The range of genetic variation with potential clinical implications in schizophrenia, beyond rare copy number variants (CNVs), remains uncertain. We therefore analyzed genome sequencing data for 259 unrelated adults with schizophrenia from a well-characterized community-based cohort previously examined with chromosomal microarray for CNVs (none with 22q11.2 deletions). We analyzed these genomes for rare high-impact variants considered causal for neurodevelopmental disorders, including single-nucleotide variants (SNVs) and small insertions/deletions (indels), for potential clinical relevance based on findings for neurodevelopmental disorders. Also, we investigated a novel variant type, tandem repeat expansions (TREs), in 45 loci known to be associated with monogenic neurological diseases. We found several of these variants in this schizophrenia population suggesting that these variants have a wider clinical spectrum than previously thought. In addition to known pathogenic CNVs, we identified 11 (4.3%) individuals with clinically relevant SNVs/indels in genes converging on schizophrenia-relevant pathways. Clinical yield was significantly enriched in females and in those with broadly defined learning/intellectual disabilities. Genome analyses also identified variants with potential clinical implications, including TREs (one in DMPK; two in ATXN8OS) and ultra-rare loss-of-function SNVs in ZMYM2 (a novel candidate gene for schizophrenia). Of the 233 individuals with no pathogenic CNVs, we identified rare high-impact variants (i.e., clinically relevant or with potential clinical implications) for 14 individuals (6.0%); some had multiple rare high-impact variants. Mean schizophrenia polygenic risk score was similar between individuals with and without clinically relevant rare genetic variation; common variants were not sufficient for clinical application. These findings broaden the individual and global picture of clinically relevant genetic risk in schizophrenia, and suggest the potential translational value of genome sequencing as a single genetic technology for schizophrenia.
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Affiliation(s)
- Bahareh A. Mojarad
- grid.42327.300000 0004 0473 9646Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON Canada
| | - Yue Yin
- grid.42327.300000 0004 0473 9646Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON Canada
| | - Roozbeh Manshaei
- grid.42327.300000 0004 0473 9646Ted Rogers Centre for Heart Research, Cardiac Genome Clinic, The Hospital for Sick Children, Toronto, ON Canada
| | - Ian Backstrom
- grid.42327.300000 0004 0473 9646Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON Canada
| | - Gregory Costain
- grid.42327.300000 0004 0473 9646Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON Canada ,grid.42327.300000 0004 0473 9646Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON Canada
| | - Tracy Heung
- grid.155956.b0000 0000 8793 5925Clinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.231844.80000 0004 0474 0428The Dalglish Family 22q Clinic for Adults with 22q11.2 Deletion Syndrome, Toronto General Hospital, University Health Network, Toronto, ON Canada
| | - Daniele Merico
- grid.42327.300000 0004 0473 9646Deep Genomics Inc., Toronto, Ontario and The Centre for Applied Genomics (TCAG), The Hospital for Sick Children, Toronto, ON Canada
| | - Christian R. Marshall
- grid.17063.330000 0001 2157 2938Paediatric Laboratory Medicine, Genome Diagnostics, The Hospital for Sick Children, Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON Canada
| | - Anne S. Bassett
- grid.155956.b0000 0000 8793 5925Clinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.231844.80000 0004 0474 0428The Dalglish Family 22q Clinic for Adults with 22q11.2 Deletion Syndrome, Toronto General Hospital, University Health Network, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto General Hospital Research Institute and Campbell Family Mental Health Research Institute, Toronto, ON Canada
| | - Ryan K. C. Yuen
- grid.42327.300000 0004 0473 9646Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Molecular Genetics, University of Toronto, Toronto, ON Canada
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Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder that is known to have a polygenic (i.e., many genes of individually small effects) architecture. Polygenic scores (PGS), which characterize this polygenicity as a single score for a given individual, are considered the state-of-the-art in psychiatric genetics research. Despite the proliferation of ADHD studies adopting this approach and its clinical implications, remarkably little is known about the predictive utility of PGS in ADHD research to date, given that there have not yet been any systematic or meta-analytic reviews of this rapidly developing literature. We meta-analyzed 12 unique effect sizes from ADHD PGS studies, yielding an N = 40,088. These studies, which included a mixture of large population-based cohorts and case-control samples of predominantly European ancestry, yielded a pooled ADHD PGS effect size of rrandom = 0.201 (95% CI = [0.144, 0.288]) and an rfixed = 0.190 (95% CI = [0.180, 0.199]) in predicting ADHD. In other words, ADHD PGS reliably account for between 3.6% (in the fixed effects model) to 4.0% (in the random effects model) of the variance in broadly defined phenotypic ADHD. Findings provide important insights into the genetics of psychiatric outcomes and raise several key questions about the impact of PGS on psychiatric research moving forward. Our review concludes by providing recommendations for future research directions in the use of PGS, including new methods to account for comorbidities, integrating bioinformatics to elucidate biological pathways, and leveraging PGS to test mechanistic models of ADHD.
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Affiliation(s)
- James J Li
- Department of Psychology, University of Wisconsin, Madison, WI, USA.
- Waisman Center, University of Wisconsin, WI, Madison, USA.
- Center for Demography of Health and Aging, University of Wisconsin, WI, Madison, USA.
| | - Quanfa He
- Department of Psychology, University of Wisconsin, Madison, WI, USA
- Waisman Center, University of Wisconsin, WI, Madison, USA
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