Browsing by Author "Neale, Michael C."

Now showing 1 - 6 of 6
  • Thumbnail Image
    Item
    Assessment and ascertainment in psychiatric molecular genetics: challenges and opportunities for cross-disorder research
    (Springer Nature, 2025) Cai, Na; Verhulst, Brad; Andreassen, Ole A.; Buitelaar, Jan; Edenberg, Howard J.; Hettema, John M.; Gandal, Michael; Grotzinger, Andrew; Jonas, Katherine; Lee, Phil; Mallard, Travis T.; Mattheisen, Manuel; Neale, Michael C.; Nurnberger, John I., Jr.; Peyrot, Wouter J.; Tucker-Drob, Elliot M.; Smoller, Jordan W.; Kendler, Kenneth S.; Biochemistry and Molecular Biology, School of Medicine
    Psychiatric disorders are highly comorbid, heritable, and genetically correlated [1-4]. The primary objective of cross-disorder psychiatric genetics research is to identify and characterize both the shared genetic factors that contribute to convergent disease etiologies and the unique genetic factors that distinguish between disorders [4, 5]. This information can illuminate the biological mechanisms underlying comorbid presentations of psychopathology, improve nosology and prediction of illness risk and trajectories, and aid the development of more effective and targeted interventions. In this review we discuss how estimates of comorbidity and identification of shared genetic loci between disorders can be influenced by how disorders are measured (phenotypic assessment) and the inclusion or exclusion criteria in individual genetic studies (sample ascertainment). Specifically, the depth of measurement, source of diagnosis, and time frame of disease trajectory have major implications for the clinical validity of the assessed phenotypes. Further, biases introduced in the ascertainment of both cases and controls can inflate or reduce estimates of genetic correlations. The impact of these design choices may have important implications for large meta-analyses of cohorts from diverse populations that use different forms of assessment and inclusion criteria, and subsequent cross-disorder analyses thereof. We review how assessment and ascertainment affect genetic findings in both univariate and multivariate analyses and conclude with recommendations for addressing them in future research.
  • Thumbnail Image
    Item
    Association of the OPRM1 Variant rs1799971 (A118G) with Non-Specific Liability to Substance Dependence in a Collaborative de novo Meta-Analysis of European-Ancestry Cohorts
    (Springer, 2016-03) Schwantes-An, Tae-Hwi; Zhang, Juan; Chen, Li-Shiun; Hartz, Sarah M.; Culverhouse, Robert C.; Chen, Xiangning; Coon, Hilary; Frank, Josef; Kamens, Helen M.; Konte, Bettina; Kovanen, Leena; Latvala, Antti; Legrand, Lisa N.; Maher, Brion S.; Melroy, Whitney E.; Nelson, Elliot C.; Reid, Mark W.; Robinson, Jason D.; Shen, Pei-Hong; Yang, Bao-Zhu; Andrews, Judy A.; Aveyard, Paul; Beltcheva, Olga; Brown, Sandra A.; Cannon, Dale S.; Cichon, Sven; Corley, Robin P.; Dahmen, Norbert; Degenhardt, Louisa; Foroud, Tatiana; Gaebel, Wolfgang; Giegling, Ina; Glatt, Stephen J.; Grucza, Richard A.; Hardin, Jill; Hartmann, Annette M.; Heath, Andrew C.; Herms, Stefan; Hodgkinson, Colin A.; Hoffmann, Per; Hops, Hyman; Huizinga, David; Ising, Marcus; Johnson, Eric O.; Johnstone, Elaine; Kaneva, Radka P.; Kendler, Kenneth S.; Kiefer, Falk; Kranzler, Henry R.; Krauter, Ken S.; Levran, Orna; Lucae, Susanne; Lynskey, Michael T.; Maier, Wolfgang; Mann, Karl; Martin, Nicholas G.; Mattheisen, Manuel; Montgomery, Grant W.; Müller-Myhsok, Bertram; Murphy, Michael F.; Neale, Michael C.; Nikolov, Momchil A.; Nishita, Denise; Nöthen, Markus M.; Nurnberger, John; Partonen, Timo; Pergadia, Michele L.; Reynolds, Maureen; Ridinger, Monika; Rose, Richard J.; Rouvinen-Lagerström, Noora; Scherbaum, Norbert; Schmäl, Christine; Soyka, Michael; Stallings, Michael C.; Steffens, Michael; Treutlein, Jens; Tsuang, Ming; Wallace, Tamara L.; Wodarz, Norbert; Yuferov, Vadim; Zill, Peter; Bergen, Andrew W.; Chen, Jingchun; Cinciripini, Paul M.; Edenberg, Howard J.; Ehringer, Marissa A.; Ferrell, Robert E.; Gelernter, Joel; Goldman, David; Hewitt, John K.; Hopfer, Christian J.; Iacono, William G.; Kaprio, Jaakko; Kreek, Mary Jeanne; Kremensky, Ivo M.; Madden, Pamela A.F.; McGue, Matt; Munafò, Marcus R.; Philibert, Robert A.; Rietschel, Marcella; Roy, Alec; Rujescu, Dan; Saarikoski, Sirkku T.; Swan, Gary E.; Todorov, Alexandre A.; Vanyukov, Michael M.; Weiss, Robert B.; Bierut, Laura J.; Saccone, Nancy L.; Department of Medical & Molecular Genetics, IU School of Medicine
    The mu1 opioid receptor gene, OPRM1, has long been a high-priority candidate for human genetic studies of addiction. Because of its potential functional significance, the non-synonymous variant rs1799971 (A118G, Asn40Asp) in OPRM1 has been extensively studied, yet its role in addiction has remained unclear, with conflicting association findings. To resolve the question of what effect, if any, rs1799971 has on substance dependence risk, we conducted collaborative meta-analyses of 25 datasets with over 28,000 European-ancestry subjects. We investigated non-specific risk for "general" substance dependence, comparing cases dependent on any substance to controls who were non-dependent on all assessed substances. We also examined five specific substance dependence diagnoses: DSM-IV alcohol, opioid, cannabis, and cocaine dependence, and nicotine dependence defined by the proxy of heavy/light smoking (cigarettes-per-day >20 vs. ≤ 10). The G allele showed a modest protective effect on general substance dependence (OR = 0.90, 95% C.I. [0.83-0.97], p value = 0.0095, N = 16,908). We observed similar effects for each individual substance, although these were not statistically significant, likely because of reduced sample sizes. We conclude that rs1799971 contributes to mechanisms of addiction liability that are shared across different addictive substances. This project highlights the benefits of examining addictive behaviors collectively and the power of collaborative data sharing and meta-analyses.
  • Thumbnail Image
    Item
    Correction: Assessment and ascertainment in psychiatric molecular genetics: challenges and opportunities for cross-disorder research
    (Springer Nature, 2025) Cai, Na; Verhulst, Brad; Andreassen, Ole A.; Buitelaar, Jan; Edenberg, Howard J.; Hettema, John M.; Gandal, Michael; Grotzinger, Andrew; Jonas, Katherine; Lee, Phil; Mallard, Travis T.; Mattheisen, Manuel; Neale, Michael C.; Nurnberger, John I., Jr.; Peyrot, Wouter J.; Tucker-Drob, Elliot M.; Smoller, Jordan W.; Kendler, Kenneth S.; Biochemistry and Molecular Biology, School of Medicine
    Correction to: Molecular Psychiatry 10.1038/s41380-024-02878-x, published online 27 December 2024 In this article the author’s name Wouter J. Peyrot was incorrectly written as Wouter Peyrout. The original article has been corrected.
  • Thumbnail Image
    Item
    Genetic and Environmental Influences on the Prospective Correlation Between Systemic Inflammation and Coronary Heart Disease Death in Male Twins
    (American Heart Association, 2014) Wu, Sheng-Hui; Neale, Michael C.; Acton, Anthony J., Jr.; Considine, Robert V.; Krasnow, Ruth E.; Reed, Terry; Dai, Jun; Medical and Molecular Genetics, School of Medicine
    Objective: Because of lack of evidence, we aimed to examine to what degree low-grade systemic inflammation and coronary heart disease (CHD) death shared common genetic and environmental substrates. Approach and results: From the 41-year prospective National Heart, Lung, and Blood Institute Twin Study, we included 950 middle-aged male twins at baseline (1969-1973). Low-grade systemic inflammation was measured with plasma levels of interleukin-6 (IL-6) and C-reactive protein. Univariate and bivariate structural equation models were used, adjusted for a risk score for CHD death. The score-adjusted heritability was 19% for IL-6, 27% for C-reactive protein, and 22% for CHD death. The positive phenotypic correlation of IL-6 with CHD death (radjusted=0.27; 95% confidence interval [CI], 0.08-0.43) was driven by additive genetic factors (contribution [relative contribution], 0.30 [111%]) but attenuated by unique environment (-0.03 [-11%]). The genetic correlation between IL-6 and CHD death was 0.74 (95% CI, 0.21-1.00), whereas the unique environmental correlation was -0.05 (95% CI, -0.35 to 0.25). The proportion of genetic variance for CHD death shared with that for IL-6 was 74%. The phenotypic correlation of C-reactive protein with CHD death (radjusted=0.10; 95% CI, -0.02 to 0.22) was explained by additive genetic factors (0.20 [149%]) but was attenuated by the unique environment (-0.09 [-49%]). The genetic correlation of C-reactive protein with CHD death was 0.63 (95% CI, -0.07 to 1.00), whereas the unique environmental correlation was -0.07 (95% CI, -0.29 to 0.17). Conclusions: Low-grade systemic inflammation, measured by IL-6, and long-term CHD death share moderate genetic substrates that augment both traits.
  • Thumbnail Image
    Item
    Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept
    (SpringerNature, 2016-03) Franke, Barbara; Stein, Jason L.; Ripke, Stephan; Anttila, Verneri; Hibar, Derrek P.; van Hulzen, Kimm J.; Arias-Vasquez, Alejandro; Smoller, Jordan W.; Nichols, Thomas E.; Neale, Michael C.; McIntosh, Andrew M.; Lee, Phil; McMahon, Francis J.; Meyer-Lindenberg, Andreas; Mattheisen, Manuel; Andreassen, Ole A.; Gruber, Oliver; Sachdev, Perminder S.; Roiz-Santiañez, Roberto; Saykin, Andrew J.; Ehrlich, Stefan; Mather, Karen A.; Turner, Jessica A.; Schwarz, Emanuel; Thalamuthu, Anbupalam; Shugart, Yin Yao; Ho, Yvonne Y.W.; Martin, Nicholas G.; Wright, Margaret J.; O'Donovan, Michael C.; Thompson, Paul M.; Neale, Benjamin M.; Medland, Sarah E.; Sullivan, Patrick F.; Department of Medical and Molecular Genetics, IU School of Medicine
    Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders.
  • Thumbnail Image
    Item
    Researching COVID to enhance recovery (RECOVER) pediatric study protocol: Rationale, objectives and design
    (Public Library of Science, 2023-06-23) Gross, Rachel; Thaweethai, Tanayott; Rosenzweig, Erika B.; Chan, James; Chibnik, Lori B.; Cicek, Mine S.; Elliott, Amy J.; Flaherman, Valerie J.; Foulkes, Andrea S.; Witvliet, Margot Gage; Gallagher, Richard; Gennaro, Maria Laura; Jernigan, Terry L.; Karlson, Elizabeth W.; Katz, Stuart D.; Kinser, Patricia A.; Kleinman, Lawrence C.; Lamendola-Essel, Michelle F.; Milner, Joshua D.; Mohandas, Sindhu; Mudumbi, Praveen C.; Newburger, Jane W.; Rhee, Kyung E.; Salisbury, Amy L.; Snowden, Jessica N.; Stein, Cheryl R.; Stockwell, Melissa S.; Tantisira, Kelan G.; Thomason, Moriah E.; Truong, Dongngan T.; Warburton, David; Wood, John C.; Ahmed, Shifa; Akerlundh, Almary; Alshawabkeh, Akram N.; Anderson, Brett R.; Aschner, Judy L.; Atz, Andrew M.; Aupperle, Robin L.; Baker, Fiona C.; Balaraman, Venkataraman; Banerjee, Dithi; Barch, Deanna M.; Baskin-Sommers, Arielle; Bhuiyan, Sultana; Bind, Marie-Abele C.; Bogie, Amanda L.; Buchbinder, Natalie C.; Bueler, Elliott; Bükülmez, Hülya; Casey, B. J.; Chang, Linda; Clark, Duncan B.; Clifton, Rebecca G.; Clouser, Katharine N.; Cottrell, Lesley; Cowan, Kelly; D'Sa, Viren; Dapretto, Mirella; Dasgupta, Soham; Dehority, Walter; Dummer, Kirsten B.; Elias, Matthew D.; Esquenazi-Karonika, Shari; Evans, Danielle N.; Faustino, E. Vincent S.; Fiks, Alexander G.; Forsha, Daniel; Foxe, John J.; Friedman, Naomi P.; Fry, Greta; Gaur, Sunanda; Gee, Dylan G.; Gray, Kevin M.; Harahsheh, Ashraf S.; Heath, Andrew C.; Heitzeg, Mary M.; Hester, Christina M.; Hill, Sophia; Hobart-Porter, Laura; Hong, Travis K. F.; Horowitz, Carol R.; Hsia, Daniel S.; Huentelman, Matthew; Hummel, Kathy D.; Iacono, William G.; Irby, Katherine; Jacobus, Joanna; Jacoby, Vanessa L.; Jone, Pei-Ni; Kaelber, David C.; Kasmarcak, Tyler J.; Kluko, Matthew J.; Kosut, Jessica S.; Laird, Angela R.; Landeo-Gutierrez, Jeremy; Lang, Sean M.; Larson, Christine L.; Lim, Peter Paul C.; Lisdahl, Krista M.; McCrindle, Brian W.; McCulloh, Russell J.; Mendelsohn, Alan L.; Metz, Torri D.; Morgan, Lerraughn M.; Müller-Oehring, Eva M.; Nahin, Erica R.; Neale, Michael C.; Ness-Cochinwala, Manette; Nolan, Sheila M.; Oliveira, Carlos R.; Oster, Matthew E.; Payne, R. Mark; Raissy, Hengameh; Randall, Isabelle G.; Rao, Suchitra; Reeder, Harrison T.; Rosas, Johana M.; Russell, Mark W.; Sabati, Arash A.; Sanil, Yamuna; Sato, Alice I.; Schechter, Michael S.; Selvarangan, Rangaraj; Shakti, Divya; Sharma, Kavita; Squeglia, Lindsay M.; Stevenson, Michelle D.; Szmuszkovicz, Jacqueline; Talavera-Barber, Maria M.; Teufel, Ronald J., II; Thacker, Deepika; Udosen, Mmekom M.; Warner, Megan R.; Watson, Sara E.; Werzberger, Alan; Weyer, Jordan C.; Wood, Marion J.; Yin, H. Shonna; Zempsky, William T.; Zimmerman, Emily; Dreyer, Benard P.; Pediatrics, School of Medicine
    Importance: SARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or other health effects after the acute phase of infection; termed post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are ill-defined. The objectives of the Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC in Adults (RECOVER-Adult) are to: (1) characterize PASC prevalence; (2) characterize the symptoms, organ dysfunction, natural history, and distinct phenotypes of PASC; (3) identify demographic, social and clinical risk factors for PASC onset and recovery; and (4) define the biological mechanisms underlying PASC pathogenesis. Methods: RECOVER-Adult is a combined prospective/retrospective cohort currently planned to enroll 14,880 adults aged ≥18 years. Eligible participants either must meet WHO criteria for suspected, probable, or confirmed infection; or must have evidence of no prior infection. Recruitment occurs at 86 sites in 33 U.S. states, Washington, DC and Puerto Rico, via facility- and community-based outreach. Participants complete quarterly questionnaires about symptoms, social determinants, vaccination status, and interim SARS-CoV-2 infections. In addition, participants contribute biospecimens and undergo physical and laboratory examinations at approximately 0, 90 and 180 days from infection or negative test date, and yearly thereafter. Some participants undergo additional testing based on specific criteria or random sampling. Patient representatives provide input on all study processes. The primary study outcome is onset of PASC, measured by signs and symptoms. A paradigm for identifying PASC cases will be defined and updated using supervised and unsupervised learning approaches with cross-validation. Logistic regression and proportional hazards regression will be conducted to investigate associations between risk factors, onset, and resolution of PASC symptoms. Discussion: RECOVER-Adult is the first national, prospective, longitudinal cohort of PASC among US adults. Results of this study are intended to inform public health, spur clinical trials, and expand treatment options.