Application of polygenic scores to a deeply phenotyped sample enriched for substance use disorders reveals extensive pleiotropy with psychiatric and somatic traits.
Journal
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
ISSN: 1740-634X
Titre abrégé: Neuropsychopharmacology
Pays: England
ID NLM: 8904907
Informations de publication
Date de publication:
23 Jul 2024
23 Jul 2024
Historique:
received:
22
01
2024
accepted:
28
06
2024
revised:
07
06
2024
medline:
24
7
2024
pubmed:
24
7
2024
entrez:
23
7
2024
Statut:
aheadofprint
Résumé
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, PGS
Identifiants
pubmed: 39043921
doi: 10.1038/s41386-024-01922-2
pii: 10.1038/s41386-024-01922-2
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : CSRD VA
ID : IK2 CX002336
Pays : United States
Organisme : U.S. Department of Veterans Affairs (Department of Veterans Affairs)
ID : VISN4 MIRECC
Organisme : CSRD VA
ID : IK2 CX002336
Pays : United States
Organisme : U.S. Department of Veterans Affairs (Department of Veterans Affairs)
ID : VISN1 MIRECC
Organisme : BLRD VA
ID : I01 BX004820
Pays : United States
Organisme : U.S. Department of Veterans Affairs (Department of Veterans Affairs)
ID : VISN4 MIRECC
Organisme : U.S. Department of Veterans Affairs (Department of Veterans Affairs)
ID : VISN4 MIRECC
Organisme : U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (NIDA)
ID : R01DA037974
Organisme : U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (NIDA)
ID : R01DA058862
Organisme : U.S. Department of Health & Human Services | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA)
ID : K01AA028292
Informations de copyright
© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.
Références
Nakash O, Levav I, Aguilar-Gaxiola S, Alonso J, Andrade LH, Angermeyer MC, et al. Comorbidity of common mental disorders with cancer and their treatment gap: findings from the World Mental Health Surveys. Psychooncology. 2014;23:40–51.
pubmed: 23983079
doi: 10.1002/pon.3372
Wells KB, Golding JM, Burnam MA. Psychiatric disorder in a sample of the general population with and without chronic medical conditions. Am J Psychiatry. 1988;145:976–81.
pubmed: 2969199
doi: 10.1176/ajp.145.8.976
Danna SM, Graham E, Burns RJ, Deschênes SS, Schmitz N. Association between Depressive Symptoms and Cognitive Function in Persons with Diabetes Mellitus: A Systematic Review. PLOS One. 2016;11:e0160809.
pubmed: 27526176
pmcid: 4985066
doi: 10.1371/journal.pone.0160809
Zhang MWB, Ho RCM, Cheung MWL, Fu E, Mak A. Prevalence of depressive symptoms in patients with chronic obstructive pulmonary disease: a systematic review, meta-analysis and meta-regression. Gen Hosp Psychiatry. 2011;33:217–23.
pubmed: 21601717
doi: 10.1016/j.genhosppsych.2011.03.009
Esposito M, Gallai B, Roccella M, Marotta R, Lavano F, Lavano SM, et al. Anxiety and depression levels in prepubertal obese children: a case-control study. Neuropsychiatr Dis Treat. 2014;10:1897–902.
pubmed: 25336955
pmcid: 4200069
Substance Abuse and Mental Health Services Administration. Key substance use and mental health indicators in the United States: Results from the 2020 National Survey on Drug Use and Health (HHS Publication No. PEP21-07-01-003, NSDUH Series H-56), p.A-48. 2021.
Davis L, Uezato A, Newell JM, Frazier E. Major depression and comorbid substance use disorders. Curr Opin Psychiatry. 2008;21:14–18.
pubmed: 18281835
doi: 10.1097/YCO.0b013e3282f32408
Drake RE, Mueser KT. Co-Occurring Alcohol Use Disorder and Schizophrenia. Alcohol Res Health. 2002;26:99–102.
pmcid: 6683824
Momen NC, Plana-Ripoll O, Agerbo E, Christensen MK, Iburg KM, Laursen TM, et al. Mortality Associated With Mental Disorders and Comorbid General Medical Conditions. JAMA Psychiatry. 2022;79:444–53.
pubmed: 35353141
pmcid: 8968685
doi: 10.1001/jamapsychiatry.2022.0347
Solmi M, Soardo L, Kaur S, Azis M, Cabras A, Censori M, et al. Meta-analytic prevalence of comorbid mental disorders in individuals at clinical high risk of psychosis: the case for transdiagnostic assessment. Mol Psychiatry. 2023;28:2291–2300.
pubmed: 37296309
pmcid: 10611568
doi: 10.1038/s41380-023-02029-8
Lindsey WT, Stewart D, Childress D. Drug interactions between common illicit drugs and prescription therapies. Am J Drug Alcohol Abus. 2012;38:334–43.
doi: 10.3109/00952990.2011.643997
Dual Disorders: Counseling Clients with Chemical Dependency and Mental Illness, Daley DC, Moss HB - Google Books. 2024. https://books.google.com/books?hl=en&lr=&id=nzLXDQAAQBAJ&oi=fnd&pg=PT16&ots=3W00uBu13g&sig=TYg_nHqhlndV-4U8uT3xIHX36y4 . Accessed 9 January 2024.
Grella CE, Hser YI, Joshi V, Rounds-Bryant J. Drug treatment outcomes for adolescents with comorbid mental and substance use disorders. J Nerv Ment Dis. 2001;189:384–92.
pubmed: 11434639
doi: 10.1097/00005053-200106000-00006
Magura S, Rosenblum A, Fong C. Factors associated with medication adherence among psychiatric outpatients at substance abuse risk. Open Addict J. 2011;4:58–64.
pubmed: 23264842
pmcid: 3526017
doi: 10.2174/1874941001104010058
Greco LA, Reay WR, Dayas CV, Cairns MJ. Pairwise genetic meta-analyses between schizophrenia and substance dependence phenotypes reveals novel association signals with pharmacological significance. Transl Psychiatry. 2022;12:403.
pubmed: 36151087
pmcid: 9508072
doi: 10.1038/s41398-022-02186-4
Abdellaoui A, Smit DJA, van den Brink W, Denys D, Verweij KJH. Genomic relationships across psychiatric disorders including substance use disorders. Drug Alcohol Depend. 2021;220:108535.
pubmed: 33524898
doi: 10.1016/j.drugalcdep.2021.108535
Sanchez-Roige S, Kember RL, Agrawal A. Substance use and common contributors to morbidity: A genetics perspective. EBioMedicine. 2022;83:104212.
pubmed: 35970022
pmcid: 9399262
doi: 10.1016/j.ebiom.2022.104212
Vassy JL, Posner DC, Ho Y-L, Gagnon DR, Galloway A, Tanukonda V, et al. Cardiovascular Disease Risk Assessment Using Traditional Risk Factors and Polygenic Risk Scores in the Million Veteran Program. JAMA Cardiol. 2023;8:564–74.
pubmed: 37133828
pmcid: 10157509
doi: 10.1001/jamacardio.2023.0857
Khan A, Turchin MC, Patki A, Srinivasasainagendra V, Shang N, Nadukuru R, et al. Genome-wide polygenic score to predict chronic kidney disease across ancestries. Nat Med. 2022;28:1412–20.
pubmed: 35710995
pmcid: 9329233
doi: 10.1038/s41591-022-01869-1
Kember RL, Vickers-Smith R, Xu H, Toikumo S, Niarchou M, Zhou H, et al. Cross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects in brain regions associated with addiction. Nat Neurosci. 2022;25:1279–87.
pubmed: 36171425
pmcid: 9682545
doi: 10.1038/s41593-022-01160-z
Levey DF, Stein MB, Wendt FR, Pathak GA, Zhou H, Aslan M, et al. Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions. Nat Neurosci. 2021;24:954–63.
pubmed: 34045744
pmcid: 8404304
doi: 10.1038/s41593-021-00860-2
Toikumo S, Vickers-Smith R, Jinwala Z, Xu H, Saini D, Hartwell E, et al. The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans. Nat Med 2024;30:1075–84.
Denny JC, Ritchie MD, Basford MA, Pulley JM, Bastarache L, Brown-Gentry K, et al. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations. Bioinforma Oxf Engl. 2010;26:1205–10.
doi: 10.1093/bioinformatics/btq126
Hartwell EE, Merikangas AK, Verma SS, Ritchie MD, Regeneron Genetics Center, Kranzler HR, et al. Genetic liability for substance use associated with medical comorbidities in electronic health records of African- and European-ancestry individuals. Addict Biol. 2022;27:e13099.
pubmed: 34611967
doi: 10.1111/adb.13099
Kember RL, Verma SS, Verma A, Xiao B, Lucas A, Kripke CM, et al. Polygenic risk scores for cardiometabolic traits demonstrate importance of ancestry for predictive precision medicine. Pac Symp Biocomput Pac Symp Biocomput. 2024;29:611–26.
pubmed: 38160310
Pierucci-Lagha A, Gelernter J, Feinn R, Cubells JF, Pearson D, Pollastri A, et al. Diagnostic reliability of the Semi-structured Assessment for Drug Dependence and Alcoholism (SSADDA). Drug Alcohol Depend. 2005;80:303–12.
pubmed: 15896927
doi: 10.1016/j.drugalcdep.2005.04.005
Pierucci-Lagha A, Gelernter J, Chan G, Arias A, Cubells JF, Farrer L, et al. Reliability of DSM-IV diagnostic criteria using the semi-structured assessment for drug dependence and alcoholism (SSADDA). Drug Alcohol Depend. 2007;91:85–90.
pubmed: 17590536
pmcid: 2039919
doi: 10.1016/j.drugalcdep.2007.04.014
Sartor CE, Wang Z, Xu K, Kranzler HR, Gelernter J. The joint effects of ADH1B variants and childhood adversity on alcohol related phenotypes in African-American and European-American women and men. Alcohol Clin Exp Res. 2014;38:2907–14.
pubmed: 25410943
pmcid: 4445128
doi: 10.1111/acer.12572
Xu H, Toikumo S, Crist RC, Glogowska K, Jinwala Z, Deak JD, et al. Identifying genetic loci and phenomic associations of substance use traits: A multi-trait analysis of GWAS (MTAG) study. Addict Abingdon Engl. 2023;118:1942–52.
doi: 10.1111/add.16229
Zhou H, Cheng Z, Bass N, Krystal JH, Farrer LA, Kranzler HR, et al. Genome-wide association study identifies glutamate ionotropic receptor GRIA4 as a risk gene for comorbid nicotine dependence and major depression. Transl Psychiatry. 2018;8:208.
pubmed: 30287806
pmcid: 6172277
doi: 10.1038/s41398-018-0258-8
Gelernter J, Panhuysen C, Wilcox M, Hesselbrock V, Rounsaville B, Poling J, et al. Genomewide linkage scan for opioid dependence and related traits. Am J Hum Genet. 2006;78:759–69.
pubmed: 16642432
pmcid: 1474044
doi: 10.1086/503631
Gelernter J, Kranzler HR, Sherva R, Koesterer R, Almasy L, Zhao H, et al. Genome-wide association study of opioid dependence: multiple associations mapped to calcium and potassium pathways. Biol Psychiatry. 2014;76:66–74.
pubmed: 24143882
doi: 10.1016/j.biopsych.2013.08.034
Gelernter J, Sherva R, Koesterer R, Almasy L, Zhao H, Kranzler HR, et al. Genome-wide association study of cocaine dependence and related traits: FAM53B identified as a risk gene. Mol Psychiatry. 2014;19:717–23.
pubmed: 23958962
doi: 10.1038/mp.2013.99
Gelernter J, Panhuysen C, Weiss R, Brady K, Hesselbrock V, Rounsaville B, et al. Genomewide linkage scan for cocaine dependence and related traits: significant linkages for a cocaine-related trait and cocaine-induced paranoia. Am J Med Genet Part B Neuropsychiatr Genet Publ Int Soc Psychiatr Genet. 2005;136B:45–52.
doi: 10.1002/ajmg.b.30189
Gelernter J, Kranzler HR, Panhuysen C, Weiss RD, Brady K, Poling J, et al. Dense genomewide linkage scan for alcohol dependence in African Americans: significant linkage on chromosome 10. Biol Psychiatry. 2009;65:111–5.
pubmed: 18930185
doi: 10.1016/j.biopsych.2008.08.036
Gelernter J, Kranzler H, Sherva R, Almasy L, Koesterer R, Smith A, et al. Genome-wide association study of alcohol dependence: significant findings in African- and European-Americans including novel risk loci. Mol Psychiatry. 2014;19:41–49.
pubmed: 24166409
doi: 10.1038/mp.2013.145
Peer K, Rennert L, Lynch KG, Farrer L, Gelernter J, Kranzler HR. Prevalence of DSM-IV and DSM-5 alcohol, cocaine, opioid, and cannabis use disorders in a largely substance dependent sample. Drug Alcohol Depend. 2013;127:215–9.
pubmed: 22884164
doi: 10.1016/j.drugalcdep.2012.07.009
Kember RL, Hartwell EE, Xu H, Rotenberg J, Almasy L, Zhou H, et al. Phenome-wide Association Analysis of Substance Use Disorders in a Deeply Phenotyped Sample. Biol Psychiatry. 2023;93:536–45.
pubmed: 36273948
doi: 10.1016/j.biopsych.2022.08.010
Das S, Forer L, Schönherr S, Sidore C, Locke AE, Kwong A, et al. Next-generation genotype imputation service and methods. Nat Genet. 2016;48:1284–7.
pubmed: 27571263
pmcid: 5157836
doi: 10.1038/ng.3656
1000 Genomes Project Consortium, Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, et al. A global reference for human genetic variation. Nature. 2015;526:68–74.
doi: 10.1038/nature15393
Gelernter J, Kranzler HR, Sherva R, Almasy L, Herman AI, Koesterer R, et al. Genome-Wide Association Study of Nicotine Dependence in American Populations: Identification of Novel Risk Loci in Both African-Americans and European-Americans. Biol Psychiatry. 2015;77:493–503.
pubmed: 25555482
doi: 10.1016/j.biopsych.2014.08.025
Sherva R, Wang Q, Kranzler H, Zhao H, Koesterer R, Herman A, et al. Genome-wide Association Study of Cannabis Dependence Severity, Novel Risk Variants, and Shared Genetic Risks. JAMA Psychiatry. 2016;73:472–80.
pubmed: 27028160
pmcid: 4974817
doi: 10.1001/jamapsychiatry.2016.0036
Ge T, Chen C-Y, Ni Y, Feng Y-CA, Smoller JW. Polygenic prediction via Bayesian regression and continuous shrinkage priors. Nat Commun. 2019;10:1776.
pubmed: 30992449
pmcid: 6467998
doi: 10.1038/s41467-019-09718-5
Watson HJ, Yilmaz Z, Thornton LM, Hübel C, Coleman JRI, Gaspar HA, et al. Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa. Nat Genet. 2019;51:1207–14.
pubmed: 31308545
pmcid: 6779477
doi: 10.1038/s41588-019-0439-2
Grove J, Ripke S, Als TD, Mattheisen M, Walters RK, Won H, et al. Identification of common genetic risk variants for autism spectrum disorder. Nat Genet. 2019;51:431–44.
pubmed: 30804558
pmcid: 6454898
doi: 10.1038/s41588-019-0344-8
Mullins N, Forstner AJ, O’Connell KS, Coombes B, Coleman JRI, Qiao Z, et al. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology. Nat Genet. 2021;53:817–29.
pubmed: 34002096
pmcid: 8192451
doi: 10.1038/s41588-021-00857-4
Levey DF, Gelernter J, Polimanti R, Zhou H, Cheng Z, Aslan M, et al. Reproducible Genetic Risk Loci for Anxiety: Results From ∼200,000 Participants in the Million Veteran Program. Am J Psychiatry. 2020;177:223–32.
pubmed: 31906708
pmcid: 7869502
doi: 10.1176/appi.ajp.2019.19030256
Als TD, Kurki MI, Grove J, Voloudakis G, Therrien K, Tasanko E, et al. Depression pathophysiology, risk prediction of recurrence and comorbid psychiatric disorders using genome-wide analyses. Nat Med. 2023;29:1832–44.
pubmed: 37464041
pmcid: 10839245
doi: 10.1038/s41591-023-02352-1
International Obsessive Compulsive Disorder Foundation Genetics Collaborative (IOCDF-GC) and OCD Collaborative Genetics Association Studies (OCGAS). Revealing the complex genetic architecture of obsessive-compulsive disorder using meta-analysis. Mol Psychiatry. 2018;23:1181–8.
doi: 10.1038/mp.2017.154
Forstner AJ, Awasthi S, Wolf C, Maron E, Erhardt A, Czamara D, et al. Genome-wide association study of panic disorder reveals genetic overlap with neuroticism and depression. Mol Psychiatry. 2021;26:4179–90.
pubmed: 31712720
doi: 10.1038/s41380-019-0590-2
Stein MB, Levey DF, Cheng Z, Wendt FR, Harrington K, Pathak GA, et al. Genome-wide association analyses of post-traumatic stress disorder and its symptom subdomains in the Million Veteran Program. Nat Genet. 2021;53:174–84.
pubmed: 33510476
pmcid: 7972521
doi: 10.1038/s41588-020-00767-x
Trubetskoy V, Pardiñas AF, Qi T, Panagiotaropoulou G, Awasthi S, Bigdeli TB, et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature. 2022;604:502–8.
pubmed: 35396580
pmcid: 9392466
doi: 10.1038/s41586-022-04434-5
Yu D, Sul JH, Tsetsos F, Nawaz MS, Huang AY, Zelaya I, et al. Interrogating the Genetic Determinants of Tourette’s Syndrome and Other Tic Disorders Through Genome-Wide Association Studies. Am J Psychiatry. 2019;176:217–27.
pubmed: 30818990
pmcid: 6677250
doi: 10.1176/appi.ajp.2018.18070857
Yengo L, Sidorenko J, Kemper KE, Zheng Z, Wood AR, Weedon MN, et al. Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry. Hum Mol Genet. 2018;27:3641–9.
pubmed: 30124842
pmcid: 6488973
doi: 10.1093/hmg/ddy271
Schunkert H, König IR, Kathiresan S, Reilly MP, Assimes TL, Holm H, et al. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat Genet. 2011;43:333–8.
pubmed: 21378990
pmcid: 3119261
doi: 10.1038/ng.784
Mahajan A, Spracklen CN, Zhang W, Ng MCY, Petty LE, Kitajima H, et al. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. Nat Genet. 2022;54:560–72.
pubmed: 35551307
pmcid: 9179018
doi: 10.1038/s41588-022-01058-3
Bigdeli TB, Fanous AH, Li Y, Rajeevan N, Sayward F, Genovese G, et al. Genome-Wide Association Studies of Schizophrenia and Bipolar Disorder in a Diverse Cohort of US Veterans. Schizophr Bull. 2021;47:517–29.
pubmed: 33169155
doi: 10.1093/schbul/sbaa133
Lee SH, Wray NR, Goddard ME, Visscher PM. Estimating Missing Heritability for Disease from Genome-wide Association Studies. Am J Hum Genet. 2011;88:294–305.
pubmed: 21376301
pmcid: 3059431
doi: 10.1016/j.ajhg.2011.02.002
Fang Y, Fritsche LG, Mukherjee B, Sen S, Richmond-Rakerd LS. Polygenic Liability to Depression Is Associated With Multiple Medical Conditions in the Electronic Health Record: Phenome-wide Association Study of 46,782 Individuals. Biol Psychiatry. 2022;92:923–31.
pubmed: 35965108
pmcid: 10712651
doi: 10.1016/j.biopsych.2022.06.004
Mulugeta A, Zhou A, King C, Hyppönen E. Association between major depressive disorder and multiple disease outcomes: a phenome-wide Mendelian randomisation study in the UK Biobank. Mol Psychiatry. 2020;25:1469–76.
pubmed: 31427754
doi: 10.1038/s41380-019-0486-1
Pathak GA, Singh K, Choi KW, Fang Y, Kouakou MR, Lee YH, et al. Genetic Liability to Posttraumatic Stress Disorder Symptoms and Its Association With Cardiometabolic and Respiratory Outcomes. JAMA Psychiatry. 2024;81:34–44.
pubmed: 37910111
doi: 10.1001/jamapsychiatry.2023.4127
Zheutlin AB, Dennis J, Karlsson Linnér R, Moscati A, Restrepo N, Straub P, et al. Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia in 106,160 Patients Across Four Health Care Systems. Am J Psychiatry. 2019;176:846–55.
pubmed: 31416338
pmcid: 6961974
doi: 10.1176/appi.ajp.2019.18091085
Hyppönen E, Mulugeta A, Zhou A, Santhanakrishnan VK. A data-driven approach for studying the role of body mass in multiple diseases: a phenome-wide registry-based case-control study in the UK Biobank. Lancet Digit Health. 2019;1:e116–e126.
pubmed: 33323262
doi: 10.1016/S2589-7500(19)30028-7
Fogelman N, Magin Z, Hart R, Sinha R. A Longitudinal Study of Life Trauma, Chronic Stress and Body Mass Index on Weight Gain over a 2-Year Period. Behav Med Wash DC. 2022;48:162–70.
doi: 10.1080/08964289.2020.1780192
Wu L-T, Ghitza UE, Batch BC, Pencina MJ, Rojas LF, Goldstein BA, et al. Substance use and mental diagnoses among adults with and without type 2 diabetes: Results from electronic health records data. Drug Alcohol Depend. 2015;156:162–9.
pubmed: 26392231
pmcid: 4633379
doi: 10.1016/j.drugalcdep.2015.09.003
Winhusen T, Theobald J, Kaelber DC, Lewis D. Medical complications associated with substance use disorders in patients with type 2 diabetes and hypertension: electronic health record findings. Addict Abingdon Engl. 2019;114:1462–70.
doi: 10.1111/add.14607
Tcheandjieu C, Zhu X, Hilliard AT, Clarke SL, Napolioni V, Ma S, et al. Large-scale genome-wide association study of coronary artery disease in genetically diverse populations. Nat Med. 2022;28:1679–92.
pubmed: 35915156
pmcid: 9419655
doi: 10.1038/s41591-022-01891-3
Major Depression - National Institute of Mental Health (NIMH). https://www.nimh.nih.gov/health/statistics/major-depression . Accessed 6 June 2024.
Howard DM, Adams MJ, Clarke T-K, Hafferty JD, Gibson J, Shirali M, et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci. 2019;22:343–52.
pubmed: 30718901
pmcid: 6522363
doi: 10.1038/s41593-018-0326-7
Panic Disorder - National Institute of Mental Health (NIMH). https://www.nimh.nih.gov/health/statistics/panic-disorder . Accessed 6 June 2024.
Post-Traumatic Stress Disorder (PTSD) - National Institute of Mental Health (NIMH). https://www.nimh.nih.gov/health/statistics/post-traumatic-stress-disorder-ptsd . Accessed 6 June 2024.
Huang J, Huffman JE, Huang Y, Do Valle Í, Assimes TL, Raghavan S, et al. Genomics and phenomics of body mass index reveals a complex disease network. Nat Commun. 2022;13:7973.
pubmed: 36581621
pmcid: 9798356
doi: 10.1038/s41467-022-35553-2
The National Academies, Committee on a National Surveillance System for Cardiovascular and Select Chronic Diseases. Cardiovascular Disease. In: A Nationwide Framework for Surveillance of Cardiovascular and Chronic Lung Diseases. Washington, DC: National Academies Press (US); 2011.
Patel AP, Wang M, Ruan Y, Koyama S, Clarke SL, Yang X, et al. A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease. Nat Med. 2023;29:1793–803.
pubmed: 37414900
pmcid: 10353935
doi: 10.1038/s41591-023-02429-x
CDC. National Diabetes Statistics Report. Diabetes. 2024. https://www.cdc.gov/diabetes/php/data-research/index.html . Accessed 6 June 2024.