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Hartwell EE, Jinwala Z, Milone J, Ramirez S, Gelernter J, Kranzler HR, Kember RL. Application of polygenic scores to a deeply phenotyped sample enriched for substance use disorders reveals extensive pleiotropy with psychiatric and somatic traits. Neuropsychopharmacology 2024:10.1038/s41386-024-01922-2. [PMID: 39043921 DOI: 10.1038/s41386-024-01922-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 06/07/2024] [Accepted: 06/28/2024] [Indexed: 07/25/2024]
Abstract
Co-occurring psychiatric, medical, and substance use disorders (SUDs) are common, but the complex pathways leading to such comorbidities are poorly understood. A greater understanding of genetic influences on this phenomenon could inform precision medicine efforts. We used the Yale-Penn dataset, a cross-sectional sample enriched for individuals with SUDs, to examine pleiotropic effects of genetic liability for psychiatric and somatic traits. Participants completed an in-depth interview that provides information on demographics, environment, medical illnesses, and psychiatric and SUDs. Polygenic scores (PGS) for psychiatric disorders and somatic traits were calculated in European-ancestry (EUR; n = 5691) participants and, when discovery datasets were available, for African-ancestry (AFR; n = 4918) participants. Phenome-wide association studies (PheWAS) were then conducted. In AFR participants, the only PGS with significant associations was bipolar disorder (BD), all of which were with substance use phenotypes. In EUR participants, PGS for major depressive disorder (MDD), generalized anxiety disorder (GAD), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), body mass index (BMI), coronary artery disease (CAD), and type 2 diabetes (T2D) all showed significant associations, the majority of which were with phenotypes in the substance use categories. For instance, PGSMDD was associated with over 200 phenotypes, 15 of which were depression-related (e.g., depression criterion count), 55 of which were other psychiatric phenotypes, and 126 of which were substance use phenotypes; and PGSBMI was associated with 138 phenotypes, 105 of which were substance related. Genetic liability for psychiatric and somatic traits is associated with numerous phenotypes across multiple categories, indicative of the broad genetic liability of these traits.
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Affiliation(s)
- Emily E Hartwell
- Crescenz VA Medical Center, Philadelphia, PA, USA
- University of Pennsylvania, Philadelphia, PA, USA
| | - Zeal Jinwala
- Crescenz VA Medical Center, Philadelphia, PA, USA
- University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Joel Gelernter
- West Haven VA Medical Center, West Haven, CT, USA
- Yale University, New Haven, CT, USA
| | - Henry R Kranzler
- Crescenz VA Medical Center, Philadelphia, PA, USA
- University of Pennsylvania, Philadelphia, PA, USA
| | - Rachel L Kember
- Crescenz VA Medical Center, Philadelphia, PA, USA.
- University of Pennsylvania, Philadelphia, PA, USA.
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2
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Gerring ZF, Thorp JG, Treur JL, Verweij KJH, Derks EM. The genetic landscape of substance use disorders. Mol Psychiatry 2024:10.1038/s41380-024-02547-z. [PMID: 38811691 DOI: 10.1038/s41380-024-02547-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 03/21/2024] [Accepted: 03/28/2024] [Indexed: 05/31/2024]
Abstract
Substance use disorders represent a significant public health concern with considerable socioeconomic implications worldwide. Twin and family-based studies have long established a heritable component underlying these disorders. In recent years, genome-wide association studies of large, broadly phenotyped samples have identified regions of the genome that harbour genetic risk variants associated with substance use disorders. These regions have enabled the discovery of putative causal genes and improved our understanding of genetic relationships among substance use disorders and other traits. Furthermore, the integration of these data with clinical information has yielded promising insights into how individuals respond to medications, allowing for the development of personalized treatment approaches based on an individual's genetic profile. This review article provides an overview of recent advances in the genetics of substance use disorders and demonstrates how genetic data may be used to reduce the burden of disease and improve public health outcomes.
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Affiliation(s)
- Zachary F Gerring
- Translational Neurogenomics Laboratory, Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jackson G Thorp
- Translational Neurogenomics Laboratory, Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jorien L Treur
- Department of Psychiatry, Amsterdam UMC, location University of Amsterdam, Amsterdam, the Netherlands
| | - Karin J H Verweij
- Department of Psychiatry, Amsterdam UMC, location University of Amsterdam, Amsterdam, the Netherlands
| | - Eske M Derks
- Translational Neurogenomics Laboratory, Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
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3
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Hartwell EE, Jinwala Z, Milone J, Ramirez S, Gelernter J, Kranzler HR, Kember RL. Application of polygenic scores to a deeply phenotyped sample enriched for substance use disorders reveals extensive pleiotropy with psychiatric and medical traits. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.22.24301615. [PMID: 38343859 PMCID: PMC10854354 DOI: 10.1101/2024.01.22.24301615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2024]
Abstract
Co-occurring psychiatric, medical, and substance use disorders (SUDs) are common, but the complex pathways leading to such comorbidities are poorly understood. A greater understanding of genetic influences on this phenomenon could inform precision medicine efforts. We used the Yale-Penn dataset, a cross-sectional sample enriched for individuals with SUDs, to examine pleiotropic effects of genetic liability for psychiatric and medical traits. Participants completed an in-depth interview that provides information on demographics, environment, medical illnesses, and psychiatric and SUDs. Polygenic scores (PGS) for psychiatric disorders and medical traits were calculated in European-ancestry (EUR; n=5,691) participants and, when discovery datasets were available, for African-ancestry (AFR; n=4,918) participants. Phenome-wide association studies (PheWAS) were then conducted. In AFR participants, the only PGS with significant associations was bipolar disorder (BD), all of which were with substance use phenotypes. In EUR participants, PGS for major depressive disorder (MDD), generalized anxiety disorder (GAD), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), body mass index (BMI), coronary artery disease (CAD), and type 2 diabetes (T2D) all showed significant associations, the majority of which were with phenotypes in the substance use categories. For instance, PGS MDD was associated with over 200 phenotypes, 15 of which were depression-related (e.g., depression criterion count), 55 of which were other psychiatric phenotypes, and 126 of which were substance use phenotypes; and PGS BMI was associated with 138 phenotypes, 105 of which were substance related. Genetic liability for psychiatric and medical traits is associated with numerous phenotypes across multiple categories, indicative of the broad genetic liability of these traits.
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Johnson EC, Salvatore JE, Lai D, Merikangas AK, Nurnberger JI, Tischfield JA, Xuei X, Kamarajan C, Wetherill L, Rice JP, Kramer JR, Kuperman S, Foroud T, Slesinger PA, Goate AM, Porjesz B, Dick DM, Edenberg HJ, Agrawal A. The collaborative study on the genetics of alcoholism: Genetics. GENES, BRAIN, AND BEHAVIOR 2023; 22:e12856. [PMID: 37387240 PMCID: PMC10550788 DOI: 10.1111/gbb.12856] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 06/02/2023] [Accepted: 06/17/2023] [Indexed: 07/01/2023]
Abstract
This review describes the genetic approaches and results from the family-based Collaborative Study on the Genetics of Alcoholism (COGA). COGA was designed during the linkage era to identify genes affecting the risk for alcohol use disorder (AUD) and related problems, and was among the first AUD-focused studies to subsequently adopt a genome-wide association (GWAS) approach. COGA's family-based structure, multimodal assessment with gold-standard clinical and neurophysiological data, and the availability of prospective longitudinal phenotyping continues to provide insights into the etiology of AUD and related disorders. These include investigations of genetic risk and trajectories of substance use and use disorders, phenome-wide association studies of loci of interest, and investigations of pleiotropy, social genomics, genetic nurture, and within-family comparisons. COGA is one of the few AUD genetics projects that includes a substantial number of participants of African ancestry. The sharing of data and biospecimens has been a cornerstone of the COGA project, and COGA is a key contributor to large-scale GWAS consortia. COGA's wealth of publicly available genetic and extensive phenotyping data continues to provide a unique and adaptable resource for our understanding of the genetic etiology of AUD and related traits.
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Affiliation(s)
- Emma C. Johnson
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
| | - Jessica E. Salvatore
- Department of Psychiatry, Robert Wood Johnson Medical SchoolRutgers UniversityPiscatawayNew JerseyUSA
| | - Dongbing Lai
- Department of Medical & Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Alison K. Merikangas
- Department of Biomedical and Health InformaticsChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
- Department of Genetics, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - John I. Nurnberger
- Department of Medical & Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
- Department of PsychiatryIndiana University School of MedicineIndianapolisIndianaUSA
| | | | - Xiaoling Xuei
- Department of Medical & Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Chella Kamarajan
- Department of Psychiatry and Behavioral SciencesState University of New York Health Sciences UniversityBrooklynNew YorkUSA
| | - Leah Wetherill
- Department of Medical & Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | | | - John P. Rice
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
| | - John R. Kramer
- Department of Psychiatry, Carver College of MedicineUniversity of IowaIowa CityIowaUSA
| | - Samuel Kuperman
- Department of Psychiatry, Carver College of MedicineUniversity of IowaIowa CityIowaUSA
| | - Tatiana Foroud
- Department of Medical & Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Paul A. Slesinger
- Departments of Neuroscience and Pharmacological SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Alison M. Goate
- Departments of Genetics and Genomic Sciences, Neuroscience, and NeurologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Bernice Porjesz
- Department of Psychiatry and Behavioral SciencesState University of New York Health Sciences UniversityBrooklynNew YorkUSA
| | - Danielle M. Dick
- Department of Psychiatry, Robert Wood Johnson Medical SchoolRutgers UniversityPiscatawayNew JerseyUSA
| | - Howard J. Edenberg
- Department of Medical & Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Biochemistry and Molecular BiologyIndiana UniversityIndianapolisIndianaUSA
| | - Arpana Agrawal
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
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Verma A, Damrauer SM, Naseer N, Weaver J, Kripke CM, Guare L, Sirugo G, Kember RL, Drivas TG, Dudek SM, Bradford Y, Lucas A, Judy R, Verma SS, Meagher E, Nathanson KL, Feldman M, Ritchie MD, Rader DJ, BioBank FTPM. The Penn Medicine BioBank: Towards a Genomics-Enabled Learning Healthcare System to Accelerate Precision Medicine in a Diverse Population. J Pers Med 2022; 12:jpm12121974. [PMID: 36556195 PMCID: PMC9785650 DOI: 10.3390/jpm12121974] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 11/17/2022] [Accepted: 11/19/2022] [Indexed: 12/02/2022] Open
Abstract
The Penn Medicine BioBank (PMBB) is an electronic health record (EHR)-linked biobank at the University of Pennsylvania (Penn Medicine). A large variety of health-related information, ranging from diagnosis codes to laboratory measurements, imaging data and lifestyle information, is integrated with genomic and biomarker data in the PMBB to facilitate discoveries and translational science. To date, 174,712 participants have been enrolled into the PMBB, including approximately 30% of participants of non-European ancestry, making it one of the most diverse medical biobanks. There is a median of seven years of longitudinal data in the EHR available on participants, who also consent to permission to recontact. Herein, we describe the operations and infrastructure of the PMBB, summarize the phenotypic architecture of the enrolled participants, and use body mass index (BMI) as a proof-of-concept quantitative phenotype for PheWAS, LabWAS, and GWAS. The major representation of African-American participants in the PMBB addresses the essential need to expand the diversity in genetic and translational research. There is a critical need for a "medical biobank consortium" to facilitate replication, increase power for rare phenotypes and variants, and promote harmonized collaboration to optimize the potential for biological discovery and precision medicine.
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Affiliation(s)
- Anurag Verma
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Correspondence: (A.V.); (D.J.R.)
| | - Scott M. Damrauer
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Surgery, Division of Vascular Surgery and Endovascular Therapy, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Nawar Naseer
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - JoEllen Weaver
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Colleen M. Kripke
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lindsay Guare
- Department of Pathology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Giorgio Sirugo
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Rachel L. Kember
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore G. Drivas
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Scott M. Dudek
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yuki Bradford
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Anastasia Lucas
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Renae Judy
- Department of Surgery, Division of Vascular Surgery and Endovascular Therapy, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shefali S. Verma
- Department of Pathology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Emma Meagher
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Katherine L. Nathanson
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael Feldman
- Department of Pathology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marylyn D. Ritchie
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel J. Rader
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Correspondence: (A.V.); (D.J.R.)
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Sanchez-Roige S, Kember RL, Agrawal A. Substance use and common contributors to morbidity: A genetics perspective. EBioMedicine 2022; 83:104212. [PMID: 35970022 PMCID: PMC9399262 DOI: 10.1016/j.ebiom.2022.104212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 07/27/2022] [Accepted: 07/28/2022] [Indexed: 11/23/2022] Open
Abstract
Excessive substance use and substance use disorders (SUDs) are common, serious and relapsing medical conditions. They frequently co-occur with other diseases that are leading contributors to disability worldwide. While heavy substance use may potentiate the course of some of these illnesses, there is accumulating evidence suggesting common genetic architectures. In this narrative review, we focus on four heritable medical conditions - cardiometabolic disease, chronic pain, depression and COVID-19, which are commonly overlapping with, but not necessarily a direct consequence of, SUDs. We find persuasive evidence of underlying genetic liability that predisposes to both SUDs and chronic pain, depression, and COVID-19. For cardiometabolic disease, there is greater support for a potential causal influence of problematic substance use. Our review encourages de-stigmatization of SUDs and the assessment of substance use in clinical settings. We assert that identifying shared pathways of risk has high translational potential, allowing tailoring of treatments for multiple medical conditions. FUNDING: SSR acknowledges T29KT0526, T32IR5226 and DP1DA054394; RLK acknowledges AA028292; AA acknowledges DA054869 & K02DA032573. The funders had no role in the conceptualization or writing of the paper.
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Affiliation(s)
- Sandra Sanchez-Roige
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Rachel L Kember
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA.
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Ritz BR, Kusters CDJ. The Promise of Mendelian Randomization in Parkinson's Disease: Has the Smoke Cleared Yet for Smoking and Parkinson's Disease Risk? JOURNAL OF PARKINSON'S DISEASE 2022; 12:807-812. [PMID: 35213390 PMCID: PMC10564582 DOI: 10.3233/jpd-223188] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
This commentary discusses the strengths and limitations of utilizing the Mendelian randomization (MR) approach in Parkinson's disease (PD) studies. Epidemiologists proposed to employ MR when genetic instruments are available that represent reliable proxies for modifiable lifelong exposures which elude easy measurement in studies of late onset diseases like PD. Here, we are using smoking as an example. The great promise of the MR approach is its resilience to confounding and reverse causation. Nevertheless, the approach has some drawbacks such as being liable to selection- and survival-bias, it makes some strong assumptions about the genetic instruments employed, and requires very large sample sizes. When interpreted carefully and put into the context of other studies that take both genetics and the environment into consideration, MR studies help us to not only ask interesting questions but also can support causal inference and provide novel insights.
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Affiliation(s)
- Beate R. Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA
- Department of Environmental Health, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Cynthia DJ Kusters
- Department of Human Genetics, David Geffen School of Medicine, Los Angeles, CA, USA
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