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Wang X, Walker A, Revez JA, Ni G, Adams MJ, McIntosh AM, Visscher PM, Wray NR. Polygenic risk prediction: why and when out-of-sample prediction R 2 can exceed SNP-based heritability. Am J Hum Genet 2023; 110:1207-1215. [PMID: 37379836 PMCID: PMC10357496 DOI: 10.1016/j.ajhg.2023.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 06/05/2023] [Accepted: 06/12/2023] [Indexed: 06/30/2023] Open
Abstract
In polygenic score (PGS) analysis, the coefficient of determination (R2) is a key statistic to evaluate efficacy. R2 is the proportion of phenotypic variance explained by the PGS, calculated in a cohort that is independent of the genome-wide association study (GWAS) that provided estimates of allelic effect sizes. The SNP-based heritability (hSNP2, the proportion of total phenotypic variances attributable to all common SNPs) is the theoretical upper limit of the out-of-sample prediction R2. However, in real data analyses R2 has been reported to exceed hSNP2, which occurs in parallel with the observation that hSNP2 estimates tend to decline as the number of cohorts being meta-analyzed increases. Here, we quantify why and when these observations are expected. Using theory and simulation, we show that if heterogeneities in cohort-specific hSNP2 exist, or if genetic correlations between cohorts are less than one, hSNP2 estimates can decrease as the number of cohorts being meta-analyzed increases. We derive conditions when the out-of-sample prediction R2 will be greater than hSNP2 and show the validity of our derivations with real data from a binary trait (major depression) and a continuous trait (educational attainment). Our research calls for a better approach to integrating information from multiple cohorts to address issues of between-cohort heterogeneity.
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Affiliation(s)
- Xiaotong Wang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Alicia Walker
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Joana A Revez
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Guiyan Ni
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia.
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia; Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia.
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Tsuo K, Zhou W, Wang Y, Kanai M, Namba S, Gupta R, Majara L, Nkambule LL, Morisaki T, Okada Y, Neale BM, Daly MJ, Martin AR. Multi-ancestry meta-analysis of asthma identifies novel associations and highlights the value of increased power and diversity. Cell Genom 2022; 2:100212. [PMID: 36778051 PMCID: PMC9903683 DOI: 10.1016/j.xgen.2022.100212] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 09/01/2022] [Accepted: 10/12/2022] [Indexed: 11/09/2022]
Abstract
Asthma is a complex disease that varies widely in prevalence across populations. The extent to which genetic variation contributes to these disparities is unclear, as the genetics underlying asthma have been investigated primarily in populations of European descent. As part of the Global Biobank Meta-analysis Initiative, we conducted a large-scale genome-wide association study of asthma (153,763 cases and 1,647,022 controls) via meta-analysis across 22 biobanks spanning multiple ancestries. We discovered 179 asthma-associated loci, 49 of which were not previously reported. Despite the wide range in asthma prevalence among biobanks, we found largely consistent genetic effects across biobanks and ancestries. The meta-analysis also improved polygenic risk prediction in non-European populations compared with previous studies. Additionally, we found considerable genetic overlap between age-of-onset subtypes and between asthma and comorbid diseases. Our work underscores the multi-factorial nature of asthma development and offers insight into its shared genetic architecture.
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Affiliation(s)
- Kristin Tsuo
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ying Wang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Rahul Gupta
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Howard Hughes Medical Institute and Department of Molecular Biology, Massachusetts General Hospital, Boston, MA, USA
| | - Lerato Majara
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Lethukuthula L. Nkambule
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Takayuki Morisaki
- Division of Molecular Pathology, The Institute of Medical Science, The University of Tokyo, Minatu-ku, Tokyo, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita 565-0871, Japan
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
- Center for Infectious Disease Education and Research (CiDER), Osaka University, Suita 565-0871, Japan
| | - Benjamin M. Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Global Biobank Meta-analysis Initiative
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Howard Hughes Medical Institute and Department of Molecular Biology, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Division of Molecular Pathology, The Institute of Medical Science, The University of Tokyo, Minatu-ku, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita 565-0871, Japan
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
- Center for Infectious Disease Education and Research (CiDER), Osaka University, Suita 565-0871, Japan
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Mark J. Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Alicia R. Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Barzilay R, Visoki E, Schultz LM, Warrier V, Daskalakis NP, Almasy L. Genetic risk, parental history, and suicide attempts in a diverse sample of US adolescents. Front Psychiatry 2022; 13:941772. [PMID: 36186872 PMCID: PMC9515424 DOI: 10.3389/fpsyt.2022.941772] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 08/17/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Adolescent suicide is a major health problem in the US marked by a recent increase in risk of suicidal behavior among Black/African American youth. While genetic factors partly account for familial transmission of suicidal behavior, it is not clear whether polygenic risk scores of suicide attempt can contribute to suicide risk classification. OBJECTIVES To evaluate the contribution of a polygenic risk score for suicide attempt (PRS-SA) in explaining variance in suicide attempt by early adolescence. METHODS We studied N = 5,214 non-related youth of African and European genetic ancestry from the Adolescent Brain Cognitive Development (ABCD) Study (ages 8.9-13.8 years) who were evaluated between 2016 and 2021. Regression models tested associations between PRS-SA and parental history of suicide attempt/death with youth-reported suicide attempt. Covariates included age and sex. RESULTS Over three waves of assessments, 182 youth (3.5%) reported a past suicide attempt, with Black youth reporting significantly more suicide attempts than their White counterparts (6.1 vs. 2.8%, p < 0.001). PRS-SA was associated with suicide attempt [odds ratio (OR) = 1.3, 95% confidence interval (CI) 1.1-1.5, p = 0.001]. Parental history of suicide attempt/death was also associated with youth suicide attempt (OR = 3.1, 95% CI, 2.0-4.7, p < 0.001). PRS-SA remained significantly associated with suicide attempt even when accounting for parental history (OR = 1.29, 95% CI = 1.1-1.5, p = 0.002). In European ancestry youth (n = 4,128), inclusion of PRS-SA in models containing parental history explained more variance in suicide attempt compared to models that included only parental history (ΔR 2 = 0.7%, p = 0.009). CONCLUSIONS Findings suggest that PRS-SA may be useful for youth suicide risk classification in addition to established risk factors.
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Affiliation(s)
- Ran Barzilay
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia (CHOP), Philadelphia, PA, United States.,Lifespan Brain Institute of CHOP and Penn Medicine, Philadelphia, PA, United States.,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Elina Visoki
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia (CHOP), Philadelphia, PA, United States.,Lifespan Brain Institute of CHOP and Penn Medicine, Philadelphia, PA, United States
| | - Laura M Schultz
- Lifespan Brain Institute of CHOP and Penn Medicine, Philadelphia, PA, United States.,Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia (CHOP), Philadelphia, PA, United States
| | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Nikolaos P Daskalakis
- Department of Psychiatry, McLean Hospital and Harvard Medical School, Belmont, MA, United States.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, United States
| | - Laura Almasy
- Lifespan Brain Institute of CHOP and Penn Medicine, Philadelphia, PA, United States.,Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia (CHOP), Philadelphia, PA, United States.,Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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