1
|
Lai D, Zhang M, Green N, Abreu M, Schwantes-An TH, Parker C, Zhang S, Jin F, Sun A, Zhang P, Edenberg H, Liu Y, Foroud T. Genome-wide meta-analyses of cross substance use disorders in European, African, and Latino ancestry populations. RESEARCH SQUARE 2024:rs.3.rs-3955955. [PMID: 39070649 PMCID: PMC11275984 DOI: 10.21203/rs.3.rs-3955955/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Genetic risks for substance use disorders (SUDs) are due to both SUD-specific and SUD-shared genes. We performed the largest multivariate analyses to date to search for SUD-shared genes using samples of European (EA), African (AA), and Latino (LA) ancestries. By focusing on variants having cross-SUD and cross-ancestry concordant effects, we identified 45 loci. Through gene-based analyses, gene mapping, and gene prioritization, we identified 250 SUD-shared genes. These genes are highly expressed in amygdala, cortex, hippocampus, hypothalamus, and thalamus, primarily in neuronal cells. Cross-SUD concordant variants explained ~ 50% of the heritability of each SUD in EA. The top 5% individuals having the highest polygenic scores were approximately twice as likely to have SUDs as others in EA and LA. Polygenic scores had higher predictability in females than in males in EA. Using real-world data, we identified five drugs targeting identified SUD-shared genes that may be repurposed to treat SUDs.
Collapse
Affiliation(s)
- Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine
| | | | | | | | - Tae-Hwi Schwantes-An
- Department of Medical and Molecular Genetics, Indiana University School of Medicine
| | | | | | | | - Anna Sun
- Indiana University School of Medicine
| | | | | | | | | |
Collapse
|
2
|
Ronald A, Gui A. The potential and translational application of infant genetic research. Nat Genet 2024; 56:1346-1354. [PMID: 38977854 DOI: 10.1038/s41588-024-01822-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 05/10/2024] [Indexed: 07/10/2024]
Abstract
In the current genomic revolution, the infancy life stage is the most neglected. Although clinical genetics recognizes the value of early identification in infancy of rare genetic causes of disorders and delay, common genetic variation is almost completely ignored in research on infant behavioral and neurodevelopmental traits. In this Perspective, we argue for a much-needed surge in research on common genetic variation influencing infant neurodevelopment and behavior, findings that would be relevant for all children. We now see convincing evidence from different research designs to suggest that developmental milestones, skills and behaviors of infants are heritable and thus are suitable candidates for gene-discovery research. We highlight the resources available to the field, including genotyped infant cohorts, and we outline, with recommendations, special considerations needed for infant data. Therefore, infant genetic research has the potential to impact basic science and to affect educational policy, public health and clinical practice.
Collapse
Affiliation(s)
- Angelica Ronald
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK.
| | - Anna Gui
- Department of Psychology, University of Essex, Essex, UK
| |
Collapse
|
3
|
Thorogood A. Population Neuroscience: Strategies to Promote Data Sharing While Protecting Privacy. Curr Top Behav Neurosci 2024. [PMID: 38509403 DOI: 10.1007/7854_2024_467] [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: 03/22/2024]
Abstract
Population neuroscience aims to advance our understanding of how genetic and environmental factors influence brain development and brain health over the life span, by integrating genomics, epidemiology, and neuroscience at population scale. This big data approach depends on data sharing strategies at both the micro- and macro-level, as well as attention to effective data management and protection of participant privacy. At the micro-level, researchers participate in international consortia that support collaboration, standards, and data sharing. They also seek to link together cohort studies, administrative health databases, and measures of the physical, built, and social environment in creative ways. Large-scale, longitudinal, and multi-modal cohorts are being designed to support explorations of genetic and environmental impacts on the brain. At a macro-level, funding agency policies now require data across health research domains to be managed according to the FAIR (findable, accessible, interoperable, and re-useable) Data principles and made available to the research community in a timely manner to support reproducibility and re-use. Data repositories provide technical infrastructure for storing, accessing, and increasingly also analyzing rich population-level data. Federated and cloud-based approaches are being leveraged to improve the security, remote accessibility, and performance of repositories. Finally, legal frameworks are being developed to facilitate secure health data access, integration, and analysis, providing new opportunities for the field.
Collapse
|
4
|
Lai D, Kuo SIC, Wetherill L, Aliev F, Zhang M, Abreu M, Schwantes-An TH, Dick D, Francis MW, Johnson EC, Kamarajan C, Kinreich S, Kuperman S, Meyers J, Nurnberger JI, Liu Y, Edenberg HJ, Porjesz B, Agrawal A, Foroud T, Schuckit M, Plawecki MH, Bucholz KK, McCutcheon VV. Associations between alcohol use disorder polygenic score and remission in participants from high-risk families and the Indiana Biobank. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2024; 48:283-294. [PMID: 38054532 PMCID: PMC10922306 DOI: 10.1111/acer.15239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 11/29/2023] [Accepted: 11/29/2023] [Indexed: 12/07/2023]
Abstract
BACKGROUND In the United States, ~50% of individuals who meet criteria for alcohol use disorder (AUD) during their lifetimes do not remit. We previously reported that a polygenic score for AUD (PGSAUD ) was positively associated with AUD severity as measured by DSM-5 lifetime criterion count, and AUD severity was negatively associated with remission. Thus, we hypothesized that PGSAUD would be negatively associated with remission. METHODS Individuals of European (EA) and African ancestry (AA) from the Collaborative Study on the Genetics of Alcoholism (COGA) who met lifetime criteria for AUD, and two EA cohorts ascertained for studies of liver diseases and substance use disorders from the Indiana Biobank were included. In COGA, 12-month remission was defined as any period of ≥12 consecutive months without meeting AUD criteria except craving and was further categorized as abstinent and non-abstinent. In the Indiana Biobank, remission was defined based on ICD codes and could not be further distinguished as abstinent or non-abstinent. Sex and age were included as covariates. COGA analyses included additional adjustment for AUD severity, family history of remission, and AUD treatment history. RESULTS In COGA EA, PGSAUD was negatively associated with 12-month and non-abstinent remission (p ≤ 0.013, βs between -0.15 and -0.10) after adjusting for all covariates. In contrast to the COGA findings, PGSAUD was positively associated with remission (p = 0.004, β = 0.28) in the Indiana Biobank liver diseases cohort but not in the Indiana Biobank substance use disorder cohort (p = 0.17, β = 0.15). CONCLUSIONS PGSAUD was negatively associated with 12-month and non-abstinent remission in COGA EA, independent of behavioral measures of AUD severity and family history of remission. The discrepant results in COGA and the Indiana Biobank could reflect different ascertainment strategies: the Indiana Biobank participants were older and had higher rates of liver disease, suggesting that these individuals remitted due to alcohol-related health conditions that manifested in later life.
Collapse
Affiliation(s)
- Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Sally I-Chun Kuo
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ
| | - Leah Wetherill
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Fazil Aliev
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ
| | - Michael Zhang
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Marco Abreu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Tae-Hwi Schwantes-An
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Danielle Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ
| | | | - Emma C. Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| | - Chella Kamarajan
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Science University, NY
| | - Sivan Kinreich
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Science University, NY
| | - Samuel Kuperman
- Department of Psychiatry, University of Iowa Roy J and Lucille A Carver College of Medicine, Iowa City, IA
| | - Jacquelyn Meyers
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Science University, NY
| | - John I Nurnberger
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Howard J Edenberg
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, SUNY Downstate Health Science University, NY
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Marc Schuckit
- Department of Psychiatry, University of California, San Diego Medical School, San Diego, CA
| | - Martin H. Plawecki
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN
| | - Kathleen K. Bucholz
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| | - Vivia V. McCutcheon
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| |
Collapse
|