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Comajoan Cara M, Mas Montserrat D, Ioannidis AG. PopGenAdapt: Semi-Supervised Domain Adaptation for Genotype-to-Phenotype Prediction in Underrepresented Populations. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2024; 29:327-340. [PMID: 38160290 PMCID: PMC10906137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
The lack of diversity in genomic datasets, currently skewed towards individuals of European ancestry, presents a challenge in developing inclusive biomedical models. The scarcity of such data is particularly evident in labeled datasets that include genomic data linked to electronic health records. To address this gap, this paper presents PopGenAdapt, a genotype-to-phenotype prediction model which adopts semi-supervised domain adaptation (SSDA) techniques originally proposed for computer vision. PopGenAdapt is designed to leverage the substantial labeled data available from individuals of European ancestry, as well as the limited labeled and the larger amount of unlabeled data from currently underrepresented populations. The method is evaluated in underrepresented populations from Nigeria, Sri Lanka, and Hawaii for the prediction of several disease outcomes. The results suggest a significant improvement in the performance of genotype-to-phenotype models for these populations over state-of-the-art supervised learning methods, setting SSDA as a promising strategy for creating more inclusive machine learning models in biomedical research.Our code is available at https://github.com/AI-sandbox/PopGenAdapt.
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Affiliation(s)
- Marçal Comajoan Cara
- Dept. of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA2Dept. of Signal Theory & Communications, Universitat Politècnica de Catalunya, Barcelona, Spain
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Elam KK, Su J, Kutzner J, Trevino A. Individual Trajectories of Depressive Symptoms Within Racially-Ethnically Diverse Youth: Associations with Polygenic Risk for Depression and Substance Use Intent and Perceived Harm. Behav Genet 2024; 54:86-100. [PMID: 38097814 DOI: 10.1007/s10519-023-10167-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 11/10/2023] [Indexed: 01/30/2024]
Abstract
There are distinct individual trajectories of depressive symptoms across adolescence which are most often differentiated into low, moderate/stable, and high/increasing groups. Research has found genetic predisposition for depression associated with trajectories characterized by greater depressive symptoms. However, the majority of this research has been conducted in White youth. Moreover, a separate literature indicates that trajectories with elevated depressive symptoms can result in substance use. It is critical to identify depressive symptom trajectories, genetic predictors, and substance use outcomes in diverse samples in early adolescence to understand distinct processes and convey equitable benefits from research. Using data from the Adolescent Cognitive Brain Development Study (ABCD), we examined parent-reported depressive symptom trajectories within Black/African American (AA, n = 1783), White/European American (EA, n = 6179), and Hispanic/Latinx (LX, n = 2410) youth across four annual assessments in early adolescence (age 9-10 to 12-13). We examined racially/ethnically aligned polygenic scores (Dep-PGS) as predictors of trajectories as well as substance use intent and perceived substance use harm as outcomes at age 12-13. Differential trajectories were found in AA, EA, and LX youth but low and high trajectories were represented within each group. In EA youth, greater Dep-PGS were broadly associated with membership in trajectories with greater depressive symptoms. Genetic effects were not significant in AA and LX youth. In AA youth, membership in the low trajectory was associated with greater substance use intent. In EA youth, membership in trajectories with higher depressive symptoms was associated with greater substance use intent and less perceived harm. There were no associations between trajectories and substance use intent and perceived harm in LX youth. These findings indicate that there are distinct depressive symptom trajectories in AA, EA, and LX youth, accompanied by unique associations with genetic predisposition for depressive symptoms and substance use outcomes.
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Affiliation(s)
- Kit K Elam
- Department of Applied Health Science, Indiana University, 1025 E. 7th St., Suite 116, Bloomington, IN, 47405, USA.
| | - Jinni Su
- Department of Psychology, Arizona State University, Phoenix, USA
| | - Jodi Kutzner
- Department of Applied Health Science, Indiana University, 1025 E. 7th St., Suite 116, Bloomington, IN, 47405, USA
| | - Angel Trevino
- Department of Psychology, Arizona State University, Phoenix, USA
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203
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Lebenbaum M, Gagnon F, de Oliveira C, Laporte A. Genetic endowments for social capital: An investigation accounting for genetic nurturing effects. ECONOMICS AND HUMAN BIOLOGY 2024; 52:101316. [PMID: 38056316 DOI: 10.1016/j.ehb.2023.101316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 11/02/2023] [Accepted: 11/11/2023] [Indexed: 12/08/2023]
Abstract
Despite social capital having been shown to be important for health and well-being, relatively little research has examined genetic determinants. Genetic endowments for education have been shown to influence human, financial, and health capital, but few studies have examined social capital, and those conducted have yet to account for genetic nurturing. We used the Add-Health data to study the effect of genetic endowments on individual social capital using the education polygenic score (PGS). We used sibling fixed effects models and controlled for the family environment to account for genetic nurturing. After accounting for the family environment, we found moderately large significant associations between the education PGS and volunteering, but associations with religious service attendance and number of friends were completely attenuated in sibling fixed effects models. These findings highlight that genetic endowments play an important role in influencing volunteering and the importance of accounting for genetic nurturing.
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Affiliation(s)
- Michael Lebenbaum
- Institute of Health Policy, Management and Evaluation (IHPME), University of Toronto, 155 College St 4th Floor, Toronto, ON M5T 3M6, Canada; Canadian Centre for Health Economics, 155 College St 4th Floor, Toronto, ON M5T 3M6, Canada.
| | - France Gagnon
- The Dalla Lana School of Public Health (DLSPH), University of Toronto, 155 College St Room 500, Toronto, ON M5T 3M7, Canada
| | - Claire de Oliveira
- Institute of Health Policy, Management and Evaluation (IHPME), University of Toronto, 155 College St 4th Floor, Toronto, ON M5T 3M6, Canada; Canadian Centre for Health Economics, 155 College St 4th Floor, Toronto, ON M5T 3M6, Canada; Centre for Health Economics and the Hull York Medical School, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Audrey Laporte
- Institute of Health Policy, Management and Evaluation (IHPME), University of Toronto, 155 College St 4th Floor, Toronto, ON M5T 3M6, Canada; Canadian Centre for Health Economics, 155 College St 4th Floor, Toronto, ON M5T 3M6, Canada
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Kachuri L, Chatterjee N, Hirbo J, Schaid DJ, Martin I, Kullo IJ, Kenny EE, Pasaniuc B, Witte JS, Ge T. Principles and methods for transferring polygenic risk scores across global populations. Nat Rev Genet 2024; 25:8-25. [PMID: 37620596 PMCID: PMC10961971 DOI: 10.1038/s41576-023-00637-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/11/2023] [Indexed: 08/26/2023]
Abstract
Polygenic risk scores (PRSs) summarize the genetic predisposition of a complex human trait or disease and may become a valuable tool for advancing precision medicine. However, PRSs that are developed in populations of predominantly European genetic ancestries can increase health disparities due to poor predictive performance in individuals of diverse and complex genetic ancestries. We describe genetic and modifiable risk factors that limit the transferability of PRSs across populations and review the strengths and weaknesses of existing PRS construction methods for diverse ancestries. Developing PRSs that benefit global populations in research and clinical settings provides an opportunity for innovation and is essential for health equity.
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Affiliation(s)
- Linda Kachuri
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jibril Hirbo
- Department of Medicine Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Daniel J Schaid
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Iman Martin
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, MD, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bogdan Pasaniuc
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - John S Witte
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
- Department of Genetics, Stanford University, Stanford, CA, USA.
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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205
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Cornelissen A, Gadhoke NV, Ryan K, Hodonsky CJ, Mitchell R, Bihlmeyer NA, Duong T, Chen Z, Dikongue A, Sakamoto A, Sato Y, Kawakami R, Mori M, Kawai K, Fernandez R, Ghosh SKB, Braumann R, Abebe B, Kutys R, Kutyna M, Romero ME, Kolodgie FD, Miller CL, Hong CC, Grove ML, Brody JA, Sotoodehnia N, Arking DE, Schunkert H, Mitchell BD, Guo L, Virmani R, Finn AV. Polygenic Risk Score Associates With Atherosclerotic Plaque Characteristics at Autopsy. Arterioscler Thromb Vasc Biol 2024; 44:300-313. [PMID: 37916415 DOI: 10.1161/atvbaha.123.319818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 10/19/2023] [Indexed: 11/03/2023]
Abstract
BACKGROUND Polygenic risk scores (PRSs) for coronary artery disease (CAD) potentially improve cardiovascular risk prediction. However, their relationship with histopathologic features of CAD has never been examined systematically. METHODS From 4327 subjects referred to CVPath by the State of Maryland Office Chief Medical Examiner for sudden death between 1994 and 2015, 2455 cases were randomly selected for genotyping. We generated PRS from 291 known CAD risk loci. Detailed histopathologic examination of the coronary arteries was performed in all subjects. The primary study outcome measurements were histopathologic plaque features determining severity of atherosclerosis, including %stenosis, calcification, thin-cap fibroatheromas, and thrombotic CAD. RESULTS After exclusion of cases with insufficient DNA sample quality or with missing data, 954 cases (mean age, 48.8±14.7 years; 75.7% men) remained in the final study cohort. Subjects in the highest PRS quintile exhibited more severe atherosclerosis compared with subjects in the lowest quintile, with greater %stenosis (80.3%±27.0% versus 50.4%±38.7%; adjusted P<0.001) and a higher frequency of calcification (69.6% versus 35.8%; adjusted P=0.004) and thin-cap fibroatheroma (26.7% versus 9.5%; adjusted P=0.007). Even after adjustment for traditional CAD risk factors, subjects within the highest PRS quintile had higher odds of severe atherosclerosis (ie, ≥75% stenosis; adjusted odds ratio, 3.77 [95% CI, 2.10-6.78]; P<0.001) and plaque rupture (adjusted odds ratio, 4.05 [95% CI, 2.26-7.24]; P<0.001). Moreover, subjects within the highest quintile had higher odds of CAD-associated cause of death, especially among those aged ≤50 years (adjusted odds ratio, 4.08 [95% CI, 2.01-8.30]; P<0.001). No statistically significant associations were observed with plaque erosion after adjusting for covariates. CONCLUSIONS This is the first autopsy study investigating associations between PRS and atherosclerosis severity at the histopathologic level in subjects with sudden death. Our pathological analysis suggests PRS correlates with plaque burden and features of advanced atherosclerosis and may be useful as a method for CAD risk stratification, especially in younger subjects.
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Affiliation(s)
- Anne Cornelissen
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
- Department of Cardiology, University Hospital RWTH Aachen, Germany (A.C.)
| | - Neel V Gadhoke
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Kathleen Ryan
- Department of Medicine, University of Maryland School of Medicine, Baltimore (K.R., C.C.H., B.D.M., A.V.F.)
| | - Chani J Hodonsky
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville (C.J.H., C.L.M.)
| | - Rebecca Mitchell
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Nathan A Bihlmeyer
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - ThuyVy Duong
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Zhifen Chen
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Munich, Germany (Z.C., H.S.)
- Deutsches Zentrum für Herz-und Kreislauferkrankungen (DZHK), Partner Site Munich Heart Alliance, Germany (Z.C., H.S.)
| | - Armelle Dikongue
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Atsushi Sakamoto
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Yu Sato
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Rika Kawakami
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Masayuki Mori
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Kenji Kawai
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Raquel Fernandez
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Saikat Kumar B Ghosh
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Ryan Braumann
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Biniyam Abebe
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Robert Kutys
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Matthew Kutyna
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Maria E Romero
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Frank D Kolodgie
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Clint L Miller
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville (C.J.H., C.L.M.)
| | - Charles C Hong
- Department of Medicine, University of Maryland School of Medicine, Baltimore (K.R., C.C.H., B.D.M., A.V.F.)
| | - Megan L Grove
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.A.B.)
| | - Nona Sotoodehnia
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Dan E Arking
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Heribert Schunkert
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Munich, Germany (Z.C., H.S.)
- Deutsches Zentrum für Herz-und Kreislauferkrankungen (DZHK), Partner Site Munich Heart Alliance, Germany (Z.C., H.S.)
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore (K.R., C.C.H., B.D.M., A.V.F.)
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, MD (B.D.M.)
| | - Liang Guo
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Renu Virmani
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Aloke V Finn
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
- Department of Medicine, University of Maryland School of Medicine, Baltimore (K.R., C.C.H., B.D.M., A.V.F.)
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Sohail M, Moreno-Estrada A. The Mexican Biobank Project promotes genetic discovery, inclusive science and local capacity building. Dis Model Mech 2024; 17:dmm050522. [PMID: 38299665 PMCID: PMC10855211 DOI: 10.1242/dmm.050522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024] Open
Abstract
Diversifying genotype-phenotype databases is essential to understanding complex trait and disease etiology across different environments and genetic ancestries. The rise of biobanks across the world is helping reveal the genetic and environmental architecture of multiple disease traits but the diversity they capture remains limited. To help close this gap, the Mexican Biobank (MXB) Project was recently generated, and has already revealed fine-scale genetic ancestries and demographic histories across the country, and their impact on trait-relevant genetic variation. This will help guide future genetic epidemiology and public health efforts, and has also improved polygenic prediction for several traits in Mexican populations compared with using data from other genome-wide association studies, such as the UK Biobank. The MXB illustrates the importance of transnational initiatives and funding calls that prioritize local leadership and capacity building to move towards inclusive genomic science.
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Affiliation(s)
- Mashaal Sohail
- Genómica Computacional, Centro de Ciencias Genómicas (CCG), Universidad Nacional Autónoma de México (UNAM), 62209 Cuernavaca, Morelos, México
| | - Andrés Moreno-Estrada
- Unidad de Genómica Avanzada (UGA-LANGEBIO), Centro de Investigación y Estudios Avanzados del IPN (Cinvestav), 36821 Irapuato, Guanajuato, México
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Kępińska AP, Johnson JS, Huckins LM. Open Science Practices in Psychiatric Genetics: A Primer. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:110-119. [PMID: 38298792 PMCID: PMC10829621 DOI: 10.1016/j.bpsgos.2023.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 08/04/2023] [Accepted: 08/11/2023] [Indexed: 02/02/2024] Open
Abstract
Open science ensures that research is transparently reported and freely accessible for all to assess and collaboratively build on. Psychiatric genetics has led among the health sciences in implementing some open science practices in common study designs, such as replication as part of genome-wide association studies. However, thorough open science implementation guidelines are limited and largely not specific to data, privacy, and research conduct challenges in psychiatric genetics. Here, we present a primer of open science practices, including selection of a research topic with patients/nonacademic collaborators, equitable authorship and citation practices, design of replicable, reproducible studies, preregistrations, open data, and privacy issues. We provide tips for informative figures and inclusive, precise reporting. We discuss considerations in working with nonacademic collaborators and distributing research through preprints, blogs, social media, and accessible lecture materials. Finally, we provide extra resources to support every step of the research process.
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Affiliation(s)
- Adrianna P. Kępińska
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Jessica S. Johnson
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, New York
- Psychiatry Department, The University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina
| | - Laura M. Huckins
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Psychiatry, Yale University, New Haven, Connecticut
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Qian W, Zhang C, Piersiak HA, Humphreys KL, Mitchell C. Biomarker adoption in developmental science: A data-driven modelling of trends from 90 biomarkers across 20 years. INFANT AND CHILD DEVELOPMENT 2024; 33:e2366. [PMID: 38389732 PMCID: PMC10882483 DOI: 10.1002/icd.2366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 07/26/2022] [Indexed: 11/11/2022]
Abstract
Developmental scientists have adopted numerous biomarkers in their research to better understand the biological underpinnings of development, environmental exposures, and variation in long-term health. Yet, adoption patterns merit investigation given the substantial resources used to collect, analyse, and train to use biomarkers in research with infants and children. We document trends in use of 90 biomarkers between 2000 and 2020 from approximately 430,000 publications indexed by the Web of Science. We provide a tool for researchers to examine each of these biomarkers individually using a data-driven approach to estimate the biomarker growth trajectory based on yearly publication number, publication growth rate, number of author affiliations, National Institutes of Health dedicated funding resources, journal impact factor, and years since the first publication. Results indicate that most biomarkers fit a "learning curve" trajectory (i.e., experience rapid growth followed by a plateau), though a small subset decline in use over time.
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Affiliation(s)
| | - Chao Zhang
- Vanderbilt University, Nashville, Tennessee, USA
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209
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Alimohamed MZ, Mnika K, Adadey SM, Barbosa-Matos R, Avram E, Nevondwe P, Akurugu WA, Mupfururirwa W, de Miranda Cerqueira JX, Dore R, Săbău ID, Kalantari S, da Silva ARGF, Anzaku AA, Matimba A, Chauke PA, Johari M, Nembaware V, Mroczek M. Advancing intercontinental collaboration in human genetics: success story of the African and European Young Investigator Forum. Eur J Hum Genet 2024; 32:3-5. [PMID: 37880422 PMCID: PMC10772082 DOI: 10.1038/s41431-023-01487-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Accepted: 10/10/2023] [Indexed: 10/27/2023] Open
Affiliation(s)
- Mohamed Zahir Alimohamed
- Department of Biochemistry and Molecular Biology, School of Biomedical Sciences, Muhimbili University of Health and Allied Sciences, Dar es salaam, Tanzania
- Tanzania Human Genetics Organization, Dar es salaam, Tanzania
- Department of Genetics, University Medical Center Groningen, Groningen, the Netherlands
| | - Khuthala Mnika
- Division of Human Genetics, National Health Laboratory Services, and School of Pathology, Faculty of Health Sciences, The University of the Witwatersrand, Johannesburg, South Africa
- Division of Human Genetics, Department of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Samuel Mawuli Adadey
- Division of Human Genetics, Department of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), University of Ghana, P.O. Box LG 54, Legon GA184, Accra, Greater Accra Region, Ghana
| | - Rita Barbosa-Matos
- European Society of Human Genetics-Young Committee, Vienna, Austria
- Institute for Research and Innovation in Health, University of Porto, Porto, Portugal
- International Doctoral Programme in Molecular and Cellular Biotechnology Applied to Health Sciences (BiotechHealth), School of Medicine and Biomedical Sciences (ICBAS), University of Porto, Porto, Portugal
| | - Elena Avram
- Medicover Ophthalmology and Ophthalmogenetics Department, Bucharest, Romania
- Medlife Ophthalmology Department, Bucharest, Romania
- Public and Professional Policy Committee, European Society of Human Genetics, Vienna, Austria
| | - Patracia Nevondwe
- Division of Human Genetics, National Health Laboratory Services, and School of Pathology, Faculty of Health Sciences, The University of the Witwatersrand, Johannesburg, South Africa
| | - Wisdom A Akurugu
- Computational Biology Group, Department of Integrative Biomedical Science, University of Cape Town, Cape Town, South Africa
| | - Wilson Mupfururirwa
- Division of Human Genetics, Department of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Juliana Xavier de Miranda Cerqueira
- European Society of Human Genetics-Young Committee, Vienna, Austria
- Coeliac Disease Research Center, Faculty of Medicine and Health Technology, University of Tampere, Tampere, Finland
- Faculty of Nutrition and Food Sciences, University of Porto, Porto, Portugal
| | - Rhys Dore
- European Society of Human Genetics-Young Committee, Vienna, Austria
- Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Ileana-Delia Săbău
- European Society of Human Genetics-Young Committee, Vienna, Austria
- Synevo-Department of Medical Genetics, Bucharest, Romania
| | - Silvia Kalantari
- European Society of Human Genetics-Young Committee, Vienna, Austria
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Ana Raquel Gouveia Freitas da Silva
- European Society of Human Genetics-Young Committee, Vienna, Austria
- Serviço de Genética Médica, Departamento de Pediatria, Hospital de Santa Maria, Centro Hospitalar Universitário Lisboa Norte, Lisboa, Portugal
| | - Abbas Abel Anzaku
- Department of Clinical Laboratory Services, Institute of Human Virology, Abuja, Nigeria
| | - Alice Matimba
- Wellcome Connecting Science, Wellcome Genome Campus, Hinxton, UK
| | - Paballo Abel Chauke
- Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, CIDRI Africa Wellcome Trust Centre, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Mridul Johari
- European Society of Human Genetics-Young Committee, Vienna, Austria
- Harry Perkins Institute of Medical Research, Centre for Medical Research, University of Western Australia, Nedlands, WA, Australia
- Folkhälsan Research Center, Department of Medical and Clinical Genetics, Medicum, University of Helsinki, Helsinki, Finland
| | - Victoria Nembaware
- Division of Human Genetics, Department of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Magdalena Mroczek
- European Society of Human Genetics-Young Committee, Vienna, Austria.
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210
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Dennison CA, Martin J, Shakeshaft A, Riglin L, Rice F, Lewis CM, O'Donovan MC, Thapar A. Stratifying early-onset emotional disorders: using genetics to assess persistence in young people of European and South Asian ancestry. J Child Psychol Psychiatry 2024; 65:42-51. [PMID: 37469035 PMCID: PMC10807819 DOI: 10.1111/jcpp.13862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/26/2023] [Indexed: 07/21/2023]
Abstract
BACKGROUND Depression and anxiety are the most common mental health problems in young people. Currently, clinicians are advised to wait before initiating treatment for young people with these disorders as many spontaneously remit. However, others develop recurrent disorder but this subgroup cannot be identified at the outset. We examined whether psychiatric polygenic scores (PGS) could help inform stratification efforts to predict those at higher risk of recurrence. METHODS Probable emotional disorder was examined in two UK population cohorts using the emotional symptoms subscale of the Strengths and Difficulties Questionnaire (SDQ). Those with emotional disorder at two or more time points between ages 5 and 25 years were classed as 'recurrent emotional disorder' (n = 1,643) and those with emotional disorder at one time point as having 'single episode emotional disorder' (n = 1,435, controls n = 8,715). We first examined the relationship between psychiatric PGS and emotional disorders in childhood and adolescence. Second, we tested whether psychiatric PGS added to predictor variables of known association with emotional disorder (neurodevelopmental comorbidity, special educational needs, family history of depression and socioeconomic status) when discriminating between single-episode and recurrent emotional disorder. Analyses were conducted separately in individuals of European and South Asian ancestry. RESULTS Probable emotional disorder was associated with higher PGS for major depressive disorder (MDD), anxiety, broad depression, ADHD and autism spectrum disorder (ASD) in those of European ancestry. Higher MDD and broad depression PGS were associated with emotional disorder in people of South Asian ancestry. Recurrent, compared to single-episode, emotional disorder was associated with ASD and parental psychiatric history. PGS were not associated with episode recurrence, and PGS did not improve discrimination of recurrence when combined with clinical predictors. CONCLUSIONS Our findings do not support the use of PGS as a tool to assess the likelihood of recurrence in young people experiencing their first episode of emotional disorder.
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Affiliation(s)
- Charlotte A. Dennison
- Wolfson Centre for Young People's Mental HealthCardiff UniversityCardiffUK
- Centre for Neuropsychiatric Genetics and Genomics, School of MedicineCardiff UniversityCardiffUK
| | - Joanna Martin
- Wolfson Centre for Young People's Mental HealthCardiff UniversityCardiffUK
- Centre for Neuropsychiatric Genetics and Genomics, School of MedicineCardiff UniversityCardiffUK
| | - Amy Shakeshaft
- Wolfson Centre for Young People's Mental HealthCardiff UniversityCardiffUK
- Centre for Neuropsychiatric Genetics and Genomics, School of MedicineCardiff UniversityCardiffUK
| | - Lucy Riglin
- Wolfson Centre for Young People's Mental HealthCardiff UniversityCardiffUK
- Centre for Neuropsychiatric Genetics and Genomics, School of MedicineCardiff UniversityCardiffUK
| | - Frances Rice
- Wolfson Centre for Young People's Mental HealthCardiff UniversityCardiffUK
- Centre for Neuropsychiatric Genetics and Genomics, School of MedicineCardiff UniversityCardiffUK
| | - Cathryn M. Lewis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | - Michael C. O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, School of MedicineCardiff UniversityCardiffUK
| | - Anita Thapar
- Wolfson Centre for Young People's Mental HealthCardiff UniversityCardiffUK
- Centre for Neuropsychiatric Genetics and Genomics, School of MedicineCardiff UniversityCardiffUK
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211
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Chotiprasidhi P, Sato-Espinoza AK, Wangensteen KJ. Germline Genetic Associations for Hepatobiliary Cancers. Cell Mol Gastroenterol Hepatol 2023; 17:623-638. [PMID: 38163482 PMCID: PMC10899027 DOI: 10.1016/j.jcmgh.2023.12.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Revised: 12/19/2023] [Accepted: 12/20/2023] [Indexed: 01/03/2024]
Abstract
Hepatobiliary cancers (HBCs) include hepatocellular carcinoma, cholangiocarcinoma, and gallbladder carcinoma, which originate from the liver, bile ducts, and gallbladder, respectively. They are responsible for a substantial burden of cancer-related deaths worldwide. Despite knowledge of risk factors and advancements in therapeutics and surgical interventions, the prognosis for most patients with HBC remains bleak. There is evidence from familial aggregation and case-control studies to suggest a familial risk component in HBC susceptibility. Recent progress in genomics research has led to the identification of germline variants including single nucleotide polymorphisms (SNPs) and pathogenic or likely pathogenic (P/LP) variants in cancer-associated genes associated with HBC risk. These findings emerged from genome-wide association studies and next-generation sequencing techniques such as whole-exome sequencing. Patients with other cancer types, including breast, colon, ovarian, prostate, and pancreatic cancer, are recommended by guidelines to undergo germline genetic testing, but similar recommendations are lagging in HBC. This prompts the question of whether multi-gene panel testing should be integrated into clinical guidelines for HBC management. Here, we review the hereditary genetics of HBC, explore studies investigating SNPs and P/LP variants in HBC patients, discuss the clinical implications and potential for personalized treatments and impact on patient's family members, and conclude that additional studies are needed to examine how genetic testing can be applied clinically.
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Affiliation(s)
- Perapa Chotiprasidhi
- Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, Minnesota
| | | | - Kirk J Wangensteen
- Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, Minnesota.
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212
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Lo YC, Chan TF, Jeon S, Maskarinec G, Taparra K, Nakatsuka N, Yu M, Chen CY, Lin YF, Wilkens LR, Le Marchand L, Haiman CA, Chiang CWK. The accuracy of polygenic score models for anthropometric traits and Type II Diabetes in the Native Hawaiian Population. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.25.23300499. [PMID: 38234828 PMCID: PMC10793530 DOI: 10.1101/2023.12.25.23300499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Polygenic scores (PGS) are promising in stratifying individuals based on the genetic susceptibility to complex diseases or traits. However, the accuracy of PGS models, typically trained in European- or East Asian-ancestry populations, tend to perform poorly in other ethnic minority populations, and their accuracies have not been evaluated for Native Hawaiians. Using body mass index, height, and type-2 diabetes as examples of highly polygenic traits, we evaluated the prediction accuracies of PGS models in a large Native Hawaiian sample from the Multiethnic Cohort with up to 5,300 individuals. We evaluated both publicly available PGS models or genome-wide PGS models trained in this study using the largest available GWAS. We found evidence of lowered prediction accuracies for the PGS models in some cases, particularly for height. We also found that using the Native Hawaiian samples as an optimization cohort during training did not consistently improve PGS performance. Moreover, even the best performing PGS models among Native Hawaiians would have lowered prediction accuracy among the subset of individuals most enriched with Polynesian ancestry. Our findings indicate that factors such as admixture histories, sample size and diversity in GWAS can influence PGS performance for complex traits among Native Hawaiian samples. This study provides an initial survey of PGS performance among Native Hawaiians and exposes the current gaps and challenges associated with improving polygenic prediction models for underrepresented minority populations.
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Affiliation(s)
- Ying-Chu Lo
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Tsz Fung Chan
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Soyoung Jeon
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Gertraud Maskarinec
- Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i, Manoa, Honolulu, HI, USA
| | - Kekoa Taparra
- Standard Health Care, Department of Radiation Oncology, Palo Alto, CA, USA
| | | | - Mingrui Yu
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
| | - Chia-Yen Chen
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
- Biogen, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Yen-Feng Lin
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
- Department of Public Health & Medical Humanities, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Lynne R Wilkens
- Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i, Manoa, Honolulu, HI, USA
| | - Loic Le Marchand
- Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i, Manoa, Honolulu, HI, USA
| | - Christopher A Haiman
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Cancer Epidemiology Program, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Charleston W K Chiang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Cancer Epidemiology Program, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
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213
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Kanjira SC, Adams MJ, Yunxuan J, Chao T, Lewis CM, Kuchenbaecker K, McIntosh AM. Polygenic prediction of major depressive disorder and related traits in African ancestries UK Biobank participants. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.24.23300412. [PMID: 38234770 PMCID: PMC10793522 DOI: 10.1101/2023.12.24.23300412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Introduction Genome-Wide Association Studies (GWAS) over-represent European ancestries compared to the global population, neglecting all other ancestry groups and low-income nations. Consequently, polygenic risk scores (PRS) more accurately predict complex traits in Europeans than African Ancestries groups. Very few studies have looked at the transferability of European-derived PRS for behavioural and mental health phenotypes to non-Europeans. We assessed the comparative accuracy of PRS for Major Depressive Disorder (MDD) trained on European and African Ancestries GWAS studies to predict MDD and related traits in African Ancestries participants from the UK Biobank. Methods UK Biobank participants were selected based on Principal component analysis (PCA) clustering with an African genetic similarity reference population and MDD was assessed with the Composite International Diagnostic Interview (CIDI). Polygenic Risk Scores (PRS) were computed using PRSice2 using either European or African Ancestries GWAS summary statistics. Results PRS trained on European ancestry samples (246,363 cases) predicted case control status in Africans of the UK Biobank with similar accuracies (190 cases, R2=2%) to PRS trained on far much smaller samples of African Ancestries participants from 23andMe, Inc. (5045 cases, R2=1.8%). This suggests that prediction of MDD status from Africans to Africans had greater efficiency per unit increase in the discovery sample size than prediction of MDD from Europeans to Africans. Prediction of MDD status in African UK Biobank participants using GWAS findings of causal risk factors from European ancestries was non-significant. Conclusion GWAS studies of MDD in European ancestries are an inefficient means of improving polygenic prediction accuracy in African samples.
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Affiliation(s)
- S C Kanjira
- Centre for Clinical Brain Sciences, University of Edinburgh, UK
- Malawi Epidemiology and Intervention Research Unit, Lilongwe, Malawi
| | - M J Adams
- Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | | | | | | | | | - A M McIntosh
- Centre for Clinical Brain Sciences, University of Edinburgh, UK
- Centre for Genomic and Experimental Medicine, University of Edinburgh, UK
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Rout M, Wander GS, Ralhan S, Singh JR, Aston CE, Blackett PR, Chernausek S, Sanghera DK. Assessing the prediction of type 2 diabetes risk using polygenic and clinical risk scores in South Asian study populations. Ther Adv Endocrinol Metab 2023; 14:20420188231220120. [PMID: 38152657 PMCID: PMC10752110 DOI: 10.1177/20420188231220120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 11/11/2023] [Indexed: 12/29/2023] Open
Abstract
Background Genome-wide polygenic risk scores (PRS) have shown high specificity and sensitivity in predicting type 2 diabetes (T2D) risk in Europeans. However, the PRS-driven information and its clinical significance in non-Europeans are underrepresented. We examined the predictive efficacy and transferability of PRS models using variant information derived from genome-wide studies of Asian Indians (AIs) (PRSAI) and Europeans (PRSEU) using 13,974 AI individuals. Methods Weighted PRS models were constructed and analyzed on 4602 individuals from the Asian Indian Diabetes Heart Study/Sikh Diabetes Study (AIDHS/SDS) as discovery/training and test/validation datasets. The results were further replicated in 9372 South Asian individuals from UK Biobank (UKBB). We also assessed the performance of each PRS model by combining data of the clinical risk score (CRS). Results Both genetic models (PRSAI and PRSEU) successfully predicted the T2D risk. However, the PRSAI revealed 13.2% odds ratio (OR) 1.80 [95% confidence interval (CI) 1.63-1.97; p = 1.6 × 10-152] and 12.2% OR 1.38 (95% CI 1.30-1.46; p = 7.1 × 10-237) superior performance in AIDHS/SDS and UKBB validation sets, respectively. Comparing individuals of extreme PRS (ninth decile) with the average PRS (fifth decile), PRSAI showed about two-fold OR 20.73 (95% CI 10.27-41.83; p = 2.7 × 10-17) and 1.4-fold OR 3.19 (95% CI 2.51-4.06; p = 4.8 × 10-21) higher predictability to identify subgroups with higher genetic risk than the PRSEU. Combining PRS and CRS improved the area under the curve from 0.74 to 0.79 in PRSAI and 0.72 to 0.75 in PRSEU. Conclusion Our data suggest the need for extending genetic and clinical studies in varied ethnic groups to exploit the full clinical potential of PRS as a risk prediction tool in diverse study populations.
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Affiliation(s)
- Madhusmita Rout
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | | | - Sarju Ralhan
- Hero DMC Heart Institute, Ludhiana, Punjab, India
| | - Jai Rup Singh
- Central University of Punjab, Bathinda, Punjab, India
| | - Christopher E. Aston
- Section of Developmental and Behavioral Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Piers R. Blackett
- Department of Pediatrics, Section of Endocrinology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Steven Chernausek
- Department of Pediatrics, Section of Endocrinology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Dharambir K. Sanghera
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK 73104, USA
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Physiology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Neuroscience, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
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Torkamani A, Chen SF, Lee SE, Sadaei H, Park JB, Khattab A, Henegar C, Wineinger N, Muse E. Meta-Prediction of Coronary Artery Disease Risk. RESEARCH SQUARE 2023:rs.3.rs-3694374. [PMID: 38196609 PMCID: PMC10775391 DOI: 10.21203/rs.3.rs-3694374/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Coronary artery disease (CAD) remains the leading cause of mortality and morbidity worldwide. Recent advances in large-scale genome-wide association studies have highlighted the potential of genetic risk, captured as polygenic risk scores (PRS), in clinical prevention. However, the current clinical utility of PRS models is limited to identifying high-risk populations based on the top percentiles of genetic susceptibility. While some studies have attempted integrative prediction using genetic and non-genetic factors, many of these studies have been cross-sectional and focused solely on risk stratification. Our primary objective in this study was to integrate unmodifiable (age / genetics) and modifiable (clinical / biometric) risk factors into a prospective prediction framework which also produces actionable and personalized risk estimates for the purpose of CAD prevention in a heterogenous adult population. Thus, we present an integrative, omnigenic, meta-prediction framework that effectively captures CAD risk subgroups, primarily distinguished by degree and nature of genetic risk, with distinct risk reduction profiles predicted from standard clinical interventions. Initial model development considered ~ 2,000 predictive features, including demographic data, lifestyle factors, physical measurements, laboratory tests, medication usage, diagnoses, and genetics. To power our meta-prediction approach, we stratified the UK Biobank into two primary cohorts: 1) a prevalent CAD cohort used to train baseline and prospective predictive models for contributing risk factors and diagnoses, and 2) an incident CAD cohort used to train the final CAD incident risk prediction model. The resultant 10-year incident CAD risk model is composed of 35 derived meta-features from models trained on the prevalent risk cohort, most of which are predicted baseline diagnoses with multiple embedded PRSs. This model achieved an AUC of 0.81 and macro-averaged F1-score of 0.65, outperforming standard clinical scores and prior integrative models. We further demonstrate that individualized risk reduction profiles can be derived from this model, with genetic risk mediating the degree of risk reduction achieved by standard clinical interventions.
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Affiliation(s)
- Ali Torkamani
- Scripps Research & Scripps Research Translational Institute
| | - Shang-Fu Chen
- Scripps Research & Scripps Research Translational Institute
| | - Sang Eun Lee
- Asan Medical Center, University of Ulsan College of Medicine
| | - Hossein Sadaei
- Scripps Research & Scripps Research Translational Institute
| | | | - Ahmed Khattab
- Scripps Research & Scripps Research Translational Institute
| | | | | | - Evan Muse
- Scripps Translational Science Institute, The Scripps Research Institute, Scripps Health
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216
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Singh S, Choudhury A, Hazelhurst S, Crowther NJ, Boua PR, Sorgho H, Agongo G, Nonterah EA, Micklesfield LK, Norris SA, Kisiangani I, Mohamed S, Gómez-Olivé FX, Tollman SM, Choma S, Brandenburg JT, Ramsay M. Genome-wide association study meta-analysis of blood pressure traits and hypertension in sub-Saharan African populations: an AWI-Gen study. Nat Commun 2023; 14:8376. [PMID: 38104120 PMCID: PMC10725455 DOI: 10.1038/s41467-023-44079-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 11/29/2023] [Indexed: 12/19/2023] Open
Abstract
Most hypertension-related genome-wide association studies (GWASs) focus on non-African populations, despite hypertension (a major risk factor for cardiovascular disease) being highly prevalent in Africa. The AWI-Gen study GWAS meta-analysis for blood pressure (BP)-related traits (systolic and diastolic BP, pulse pressure, mean-arterial pressure and hypertension) from three sub-Saharan African geographic regions (N = 10,775), identifies two novel genome-wide significant signals (p < 5E-08): systolic BP near P2RY1 (rs77846204; intergenic variant, p = 4.95E-08) and pulse pressure near LINC01256 (rs80141533; intergenic variant, p = 1.76E-08). No genome-wide signals are detected for the AWI-Gen GWAS meta-analysis with previous African-ancestry GWASs (UK Biobank (African), Uganda Genome Resource). Suggestive signals (p < 5E-06) are observed for all traits, with 29 SNPs associating with more than one trait and several replicating known associations. Polygenic risk scores (PRSs) developed from studies on different ancestries have limited transferability, with multi-ancestry PRS providing better prediction. This study provides insights into the genetics of BP variation in African populations.
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Affiliation(s)
- Surina Singh
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - Ananyo Choudhury
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| | - Nigel J Crowther
- Department of Chemical Pathology, National Health Laboratory Service, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Palwendé R Boua
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Sante, Ouagadougou, Burkina Faso
| | - Hermann Sorgho
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Sante, Ouagadougou, Burkina Faso
| | - Godfred Agongo
- Department of Biochemistry and Forensic Sciences, School of Chemical and Biochemical Sciences, C.K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana
- Navrongo Health Research Centre, Ghana Health Service, Navrongo, Ghana
| | - Engelbert A Nonterah
- Navrongo Health Research Centre, Ghana Health Service, Navrongo, Ghana
- Julius Global Health, Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Lisa K Micklesfield
- SAMRC Developmental Pathways for Health Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Shane A Norris
- SAMRC Developmental Pathways for Health Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Health and Human Development, University of Southampton, Southampton, UK
| | | | - Shukri Mohamed
- African Population and Health Research Center, Nairobi, Kenya
| | - Francesc X Gómez-Olivé
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Stephen M Tollman
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Solomon Choma
- Department of Medical Science, Public Health and Health Promotion, School of Health Care Sciences, Faculty of Health Sciences, University of Limpopo, Polokwane, South Africa
| | - J-T Brandenburg
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Strengthening Oncology Services, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
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217
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Baron C, Cherkaoui S, Therrien-Laperriere S, Ilboudo Y, Poujol R, Mehanna P, Garrett ME, Telen MJ, Ashley-Koch AE, Bartolucci P, Rioux JD, Lettre G, Rosiers CD, Ruiz M, Hussin JG. Gene-metabolite annotation with shortest reactional distance enhances metabolite genome-wide association studies results. iScience 2023; 26:108473. [PMID: 38077122 PMCID: PMC10709128 DOI: 10.1016/j.isci.2023.108473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 08/24/2023] [Accepted: 11/13/2023] [Indexed: 12/20/2023] Open
Abstract
Metabolite genome-wide association studies (mGWAS) have advanced our understanding of the genetic control of metabolite levels. However, interpreting these associations remains challenging due to a lack of tools to annotate gene-metabolite pairs beyond the use of conservative statistical significance threshold. Here, we introduce the shortest reactional distance (SRD) metric, drawing from the comprehensive KEGG database, to enhance the biological interpretation of mGWAS results. We applied this approach to three independent mGWAS, including a case study on sickle cell disease patients. Our analysis reveals an enrichment of small SRD values in reported mGWAS pairs, with SRD values significantly correlating with mGWAS p values, even beyond the standard conservative thresholds. We demonstrate the utility of SRD annotation in identifying potential false negatives and inaccuracies within current metabolic pathway databases. Our findings highlight the SRD metric as an objective, quantitative and easy-to-compute annotation for gene-metabolite pairs, suitable to integrate statistical evidence to biological networks.
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Affiliation(s)
- Cantin Baron
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Montréal, QC, Canada
- Montreal Heart Institute, Montréal, QC, Canada
| | - Sarah Cherkaoui
- Montreal Heart Institute, Montréal, QC, Canada
- Division of Oncology and Children’s Research Center, University Children’s Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Center, Université Paris-Saclay, Villejuif, France
| | | | - Yann Ilboudo
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Montréal, QC, Canada
- Montreal Heart Institute, Montréal, QC, Canada
| | | | | | - Melanie E. Garrett
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
| | - Marilyn J. Telen
- Division of Hematology, Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | | | - Pablo Bartolucci
- Université Paris Est Créteil, Hôpitaux Universitaires Henri Mondor, APHP, Sickle cell referral center – UMGGR, Créteil, France
- Université Paris Est Créteil, IMRB, Laboratory of excellence LABEX, Créteil, France
| | - John D. Rioux
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Montréal, QC, Canada
- Montreal Heart Institute, Montréal, QC, Canada
- Département de Médecine, Université de Montréal, Montréal, QC, Canada
| | - Guillaume Lettre
- Montreal Heart Institute, Montréal, QC, Canada
- Département de Médecine, Université de Montréal, Montréal, QC, Canada
| | - Christine Des Rosiers
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Montréal, QC, Canada
- Montreal Heart Institute, Montréal, QC, Canada
- Département de Nutrition, Université de Montréal, Montréal, QC, Canada
| | - Matthieu Ruiz
- Montreal Heart Institute, Montréal, QC, Canada
- Département de Nutrition, Université de Montréal, Montréal, QC, Canada
| | - Julie G. Hussin
- Montreal Heart Institute, Montréal, QC, Canada
- Département de Médecine, Université de Montréal, Montréal, QC, Canada
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218
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Zhang MJ, Durvasula A, Chiang C, Koch EM, Strober BJ, Shi H, Barton AR, Kim SS, Weissbrod O, Loh PR, Gazal S, Sunyaev S, Price AL. Pervasive correlations between causal disease effects of proximal SNPs vary with functional annotations and implicate stabilizing selection. RESEARCH SQUARE 2023:rs.3.rs-3707248. [PMID: 38168385 PMCID: PMC10760228 DOI: 10.21203/rs.3.rs-3707248/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
The genetic architecture of human diseases and complex traits has been extensively studied, but little is known about the relationship of causal disease effect sizes between proximal SNPs, which have largely been assumed to be independent. We introduce a new method, LD SNP-pair effect correlation regression (LDSPEC), to estimate the correlation of causal disease effect sizes of derived alleles between proximal SNPs, depending on their allele frequencies, LD, and functional annotations; LDSPEC produced robust estimates in simulations across various genetic architectures. We applied LDSPEC to 70 diseases and complex traits from the UK Biobank (average N=306K), meta-analyzing results across diseases/traits. We detected significantly nonzero effect correlations for proximal SNP pairs (e.g., -0.37±0.09 for low-frequency positive-LD 0-100bp SNP pairs) that decayed with distance (e.g., -0.07±0.01 for low-frequency positive-LD 1-10kb), varied with allele frequency (e.g., -0.15±0.04 for common positive-LD 0-100bp), and varied with LD between SNPs (e.g., +0.12±0.05 for common negative-LD 0-100bp) (because we consider derived alleles, positive-LD and negative-LD SNP pairs may yield very different results). We further determined that SNP pairs with shared functions had stronger effect correlations that spanned longer genomic distances, e.g., -0.37±0.08 for low-frequency positive-LD same-gene promoter SNP pairs (average genomic distance of 47kb (due to alternative splicing)) and -0.32±0.04 for low-frequency positive-LD H3K27ac 0-1kb SNP pairs. Consequently, SNP-heritability estimates were substantially smaller than estimates of the sum of causal effect size variances across all SNPs (ratio of 0.87±0.02 across diseases/traits), particularly for certain functional annotations (e.g., 0.78±0.01 for common Super enhancer SNPs)-even though these quantities are widely assumed to be equal. We recapitulated our findings via forward simulations with an evolutionary model involving stabilizing selection, implicating the action of linkage masking, whereby haplotypes containing linked SNPs with opposite effects on disease have reduced effects on fitness and escape negative selection.
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Affiliation(s)
- Martin Jinye Zhang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Arun Durvasula
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - Colby Chiang
- Department of Pediatrics, Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA
| | - Evan M. Koch
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Benjamin J. Strober
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Huwenbo Shi
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Alison R. Barton
- Department of Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Samuel S. Kim
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Omer Weissbrod
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Po-Ru Loh
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Steven Gazal
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
- Department of Quantitative and Computational Biology, University of Southern California
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California
| | - Shamil Sunyaev
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Alkes L. Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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219
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He Y, Qian DC, Diao JA, Cho MH, Silverman EK, Gusev A, Manrai AK, Martin AR, Patel CJ. Prediction and stratification of longitudinal risk for chronic obstructive pulmonary disease across smoking behaviors. Nat Commun 2023; 14:8297. [PMID: 38097585 PMCID: PMC10721891 DOI: 10.1038/s41467-023-44047-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 11/28/2023] [Indexed: 12/17/2023] Open
Abstract
Smoking is the leading risk factor for chronic obstructive pulmonary disease (COPD) worldwide, yet many people who never smoke develop COPD. We perform a longitudinal analysis of COPD in the UK Biobank to derive and validate the Socioeconomic and Environmental Risk Score which captures additive and cumulative environmental, behavioral, and socioeconomic exposure risks beyond tobacco smoking. The Socioeconomic and Environmental Risk Score is more predictive of COPD than smoking status and pack-years. Individuals in the highest decile of the risk score have a greater risk for incident COPD compared to the remaining population. Never smokers in the highest decile of exposure risk are more likely to develop COPD than previous and current smokers in the lowest decile. In general, the prediction accuracy of the Social and Environmental Risk Score is lower in non-European populations. While smoking status is often considered in screening COPD, our finding highlights the importance of other non-smoking environmental and socioeconomic variables.
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Affiliation(s)
- Yixuan He
- 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
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - David C Qian
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA, USA
| | - James A Diao
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Edwin K Silverman
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Alexander Gusev
- Department of Medicine, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Arjun K Manrai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - 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.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
| | - Chirag J Patel
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
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220
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Hernandez LM. Mapping the genetic and phenotypic landscape of neonatal C3 and C4 protein concentrations. CELL GENOMICS 2023; 3:100456. [PMID: 38116124 PMCID: PMC10726484 DOI: 10.1016/j.xgen.2023.100456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
The complement system is crucial for innate immunity and has been linked to autoimmune and psychiatric disorders. Borbye-Lorenzen et al.1 perform GWASs and PheWASs of neonatal C3/C4 protein concentrations, finding multiple genome-wide significant loci, and identify sex-specific associations between C3 protein concentration and C4 copy number with risk for schizophrenia.
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Affiliation(s)
- Leanna M. Hernandez
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
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221
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Chen CY, Chen TT, Feng YCA, Yu M, Lin SC, Longchamps RJ, Wang SH, Hsu YH, Yang HI, Kuo PH, Daly MJ, Chen WJ, Huang H, Ge T, Lin YF. Analysis across Taiwan Biobank, Biobank Japan, and UK Biobank identifies hundreds of novel loci for 36 quantitative traits. CELL GENOMICS 2023; 3:100436. [PMID: 38116116 PMCID: PMC10726425 DOI: 10.1016/j.xgen.2023.100436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 11/21/2021] [Accepted: 10/09/2023] [Indexed: 12/21/2023]
Abstract
Genome-wide association studies (GWASs) have identified tens of thousands of genetic loci associated with human complex traits. However, the majority of GWASs were conducted in individuals of European ancestries. Failure to capture global genetic diversity has limited genomic discovery and has impeded equitable delivery of genomic knowledge to diverse populations. Here we report findings from 102,900 individuals across 36 human quantitative traits in the Taiwan Biobank (TWB), a major biobank effort that broadens the population diversity of genetic studies in East Asia. We identified 968 novel genetic loci, pinpointed novel causal variants through statistical fine-mapping, compared the genetic architecture across TWB, Biobank Japan, and UK Biobank, and evaluated the utility of cross-phenotype, cross-population polygenic risk scores in disease risk prediction. These results demonstrated the potential to advance discovery through diversifying GWAS populations and provided insights into the common genetic basis of human complex traits in East Asia.
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Affiliation(s)
- Chia-Yen Chen
- Biogen, Cambridge, MA 02142, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Tzu-Ting Chen
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli 35053, Taiwan
| | - Yen-Chen Anne Feng
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 100025, Taiwan
- Institute of Health Data Analytics and Statistics, College of Public Health, National Taiwan University, Taipei 100025, Taiwan
| | - Mingrui Yu
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shu-Chin Lin
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli 35053, Taiwan
| | - Ryan J. Longchamps
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shi-Heng Wang
- National Center for Geriatrics and Welfare Research, National Health Research Institutes, Miaoli 35053, Taiwan
- Department of Public Health, College of Public Health, China Medical University, Taichung 40678, Taiwan
| | - Yi-Hsiang Hsu
- Marcus Institute for Aging Research and Harvard Medical School, Boston, MA 02131, USA
- Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
- Harvard School of Public Health, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Hwai-I. Yang
- Genomics Research Center, Academia Sinica, Taipei 115201, Taiwan
- Institute of Clinical Medicine, National Yang-Ming University, Taipei 112304, Taiwan
- Doctoral Program of Clinical and Experimental Medicine, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan
- Biomedical Translation Research Center, Academia Sinica, Taipei 115021, Taiwan
| | - Po-Hsiu Kuo
- Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 100025, Taiwan
- Department of Psychiatry, College of Medicine and National Taiwan University Hospital, Taipei 106319, Taiwan
| | - Mark J. Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, Finland
| | - Wei J. Chen
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli 35053, Taiwan
- Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 100025, Taiwan
- Department of Psychiatry, College of Medicine and National Taiwan University Hospital, Taipei 106319, Taiwan
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02114, USA
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Yen-Feng Lin
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli 35053, Taiwan
- Department of Public Health & Medical Humanities, School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
- Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan
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222
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Xu L, Zhou G, Jiang W, Guan L, Zhao H. Leveraging genetic correlations and multiple populations to improve genetic risk prediction for non-European populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.29.564615. [PMID: 37961111 PMCID: PMC10634936 DOI: 10.1101/2023.10.29.564615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The disparity in genetic risk prediction accuracy between European and non-European individuals highlights a critical challenge in health inequality. To bridge this gap, we introduce JointPRS, a novel method that models multiple populations jointly to improve genetic risk predictions for non-European individuals. JointPRS has three key features. First, it encompasses all diverse populations to improve prediction accuracy, rather than relying solely on the target population with a singular auxiliary European group. Second, it autonomously estimates and leverages chromosome-wise cross-population genetic correlations to infer the effect sizes of genetic variants. Lastly, it provides an auto version that has comparable performance to the tuning version to accommodate the situation with no validation dataset. Through extensive simulations and real data applications to 22 quantitative traits and four binary traits in East Asian populations, nine quantitative traits and one binary trait in African populations, and four quantitative traits in South Asian populations, we demonstrate that JointPRS outperforms state-of-art methods, improving the prediction accuracy for both quantitative and binary traits in non-European populations.
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Affiliation(s)
- Leqi Xu
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Geyu Zhou
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Wei Jiang
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Leying Guan
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
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223
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Zhang MJ, Durvasula A, Chiang C, Koch EM, Strober BJ, Shi H, Barton AR, Kim SS, Weissbrod O, Loh PR, Gazal S, Sunyaev S, Price AL. Pervasive correlations between causal disease effects of proximal SNPs vary with functional annotations and implicate stabilizing selection. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.04.23299391. [PMID: 38106023 PMCID: PMC10723494 DOI: 10.1101/2023.12.04.23299391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
The genetic architecture of human diseases and complex traits has been extensively studied, but little is known about the relationship of causal disease effect sizes between proximal SNPs, which have largely been assumed to be independent. We introduce a new method, LD SNP-pair effect correlation regression (LDSPEC), to estimate the correlation of causal disease effect sizes of derived alleles between proximal SNPs, depending on their allele frequencies, LD, and functional annotations; LDSPEC produced robust estimates in simulations across various genetic architectures. We applied LDSPEC to 70 diseases and complex traits from the UK Biobank (average N=306K), meta-analyzing results across diseases/traits. We detected significantly nonzero effect correlations for proximal SNP pairs (e.g., -0.37±0.09 for low-frequency positive-LD 0-100bp SNP pairs) that decayed with distance (e.g., -0.07±0.01 for low-frequency positive-LD 1-10kb), varied with allele frequency (e.g., -0.15±0.04 for common positive-LD 0-100bp), and varied with LD between SNPs (e.g., +0.12±0.05 for common negative-LD 0-100bp) (because we consider derived alleles, positive-LD and negative-LD SNP pairs may yield very different results). We further determined that SNP pairs with shared functions had stronger effect correlations that spanned longer genomic distances, e.g., -0.37±0.08 for low-frequency positive-LD same-gene promoter SNP pairs (average genomic distance of 47kb (due to alternative splicing)) and -0.32±0.04 for low-frequency positive-LD H3K27ac 0-1kb SNP pairs. Consequently, SNP-heritability estimates were substantially smaller than estimates of the sum of causal effect size variances across all SNPs (ratio of 0.87±0.02 across diseases/traits), particularly for certain functional annotations (e.g., 0.78±0.01 for common Super enhancer SNPs)-even though these quantities are widely assumed to be equal. We recapitulated our findings via forward simulations with an evolutionary model involving stabilizing selection, implicating the action of linkage masking, whereby haplotypes containing linked SNPs with opposite effects on disease have reduced effects on fitness and escape negative selection.
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Affiliation(s)
- Martin Jinye Zhang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Arun Durvasula
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - Colby Chiang
- Department of Pediatrics, Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA
| | - Evan M Koch
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Benjamin J Strober
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Huwenbo Shi
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Alison R Barton
- Department of Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Samuel S Kim
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Omer Weissbrod
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Po-Ru Loh
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Steven Gazal
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
- Department of Quantitative and Computational Biology, University of Southern California
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California
| | - Shamil Sunyaev
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alkes L Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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224
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Furuya S, Liu J, Sun Z, Lu Q, Fletcher JM. The Big (Genetic) Sort? A Research Note on Migration Patterns and Their Genetic Imprint in the United Kingdom. Demography 2023; 60:1649-1664. [PMID: 37942709 DOI: 10.1215/00703370-11054960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
This research note reinvestigates Abdellaoui et al.'s (2019) findings that genetically selective migration may lead to persistent and accumulating socioeconomic and health inequalities between types (coal mining or non-coal mining) of places in the United Kingdom. Their migration measure classified migrants who moved to the same type of place (coal mining to coal mining or non-coal mining to non-coal mining) into "stay" categories, preventing them from distinguishing migrants from nonmigrants. We reinvestigate the question of genetically selective migration by examining migration patterns between places rather than place types and find genetic selectivity in whether people migrate and where. For example, we find evidence of positive selection: people with genetic variants correlated with better education moved from non-coal mining to coal mining places with our measure of migration. Such findings were obscured in earlier work that could not distinguish nonmigrants from migrants.
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Affiliation(s)
- Shiro Furuya
- Department of Sociology, Center for Demography of Health and Aging, and Center for Demography and Ecology, University of Wisconsin-Madison, Madison, WI, USA
| | - Jihua Liu
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Zhongxuan Sun
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
| | - Qiongshi Lu
- Center for Demography of Health and Aging, Department of Biostatistics and Medical Informatics, and Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA
| | - Jason M Fletcher
- Center for Demography of Health and Aging, Center for Demography and Ecology, La Follette School of Public Affairs, Department of Population Health Science, and Department of Agricultural and Applied Economics, University of Wisconsin-Madison, Madison, WI, USA
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225
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Ginod P, Dahan MH. Polygenic embryo screening: are there potential maternal and fetal harms? Reprod Biomed Online 2023; 47:103327. [PMID: 37820464 DOI: 10.1016/j.rbmo.2023.103327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 07/28/2023] [Accepted: 07/31/2023] [Indexed: 10/13/2023]
Abstract
Polygenic embryo screening (PES) and its derivate the Embryo Health Score (EHS) have generated interest in both infertile and fertile populations due to their potential ability to select embryos with a reduced risk of disease and improved long-term health outcomes. Concerns have been raised regarding the potential harms of IVF itself, including possible epigenetic changes that may affect the health of the offspring in late adulthood, which are not fully captured in the EHS calculation. Knowledge of the potential impacts of the trophectoderm biopsy, which is a key component of the PES procedure, on the offsprings' health is limited by the heterogeneity of the population characteristics used in the published studies. Nonetheless, the literature suggests a possible increased risk of preterm delivery, birth defects and pre-eclampsia after trophectoderm biopsy. Overall, the risks of PES for prenatal and postnatal health remain uncertain, and further research is needed. Counselling patients regarding these risks before considering PES is important, to provide an understanding of the risks and benefits. This review aims to highlight some of these issues, the need for continued investigation in this area, and the importance of informed decision-making in the context of PES.
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Affiliation(s)
- Perrine Ginod
- MUHC Reproductive Centre, McGill University, Montréal, Quebec, Canada; CHU Dijon Bourgogne, Service de Gynécologie-Obstétrique et Assistance Médicale à la Procréation, Dijon, France
| | - Michael H Dahan
- MUHC Reproductive Centre, McGill University, Montréal, Quebec, Canada; Department of Obstetrics and Gynecology, Division of Reproductive Endocrinology and Infertility, McGill University, Montréal, Quebec, Canada.
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226
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Dahl A, Thompson M, An U, Krebs M, Appadurai V, Border R, Bacanu SA, Werge T, Flint J, Schork AJ, Sankararaman S, Kendler KS, Cai N. Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder. Nat Genet 2023; 55:2082-2093. [PMID: 37985818 PMCID: PMC10703686 DOI: 10.1038/s41588-023-01559-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 09/18/2023] [Indexed: 11/22/2023]
Abstract
Biobanks often contain several phenotypes relevant to diseases such as major depressive disorder (MDD), with partly distinct genetic architectures. Researchers face complex tradeoffs between shallow (large sample size, low specificity/sensitivity) and deep (small sample size, high specificity/sensitivity) phenotypes, and the optimal choices are often unclear. Here we propose to integrate these phenotypes to combine the benefits of each. We use phenotype imputation to integrate information across hundreds of MDD-relevant phenotypes, which significantly increases genome-wide association study (GWAS) power and polygenic risk score (PRS) prediction accuracy of the deepest available MDD phenotype in UK Biobank, LifetimeMDD. We demonstrate that imputation preserves specificity in its genetic architecture using a novel PRS-based pleiotropy metric. We further find that integration via summary statistics also enhances GWAS power and PRS predictions, but can introduce nonspecific genetic effects depending on input. Our work provides a simple and scalable approach to improve genetic studies in large biobanks by integrating shallow and deep phenotypes.
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Affiliation(s)
- Andrew Dahl
- Section of Genetic Medicine, University of Chicago, Chicago, IL, USA.
| | - Michael Thompson
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Ulzee An
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Morten Krebs
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
| | - Vivek Appadurai
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
| | - Richard Border
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Silviu-Alin Bacanu
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
- Lundbeck Foundation GeoGenetics Centre, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jonathan Flint
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
- Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA
- Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark
| | - Sriram Sankararaman
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Na Cai
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany.
- Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany.
- School of Medicine, Technical University of Munich, Munich, Germany.
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227
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Hoy N, Lynch SJ, Waszczuk MA, Reppermund S, Mewton L. Transdiagnostic biomarkers of mental illness across the lifespan: A systematic review examining the genetic and neural correlates of latent transdiagnostic dimensions of psychopathology in the general population. Neurosci Biobehav Rev 2023; 155:105431. [PMID: 37898444 DOI: 10.1016/j.neubiorev.2023.105431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/26/2023] [Accepted: 10/21/2023] [Indexed: 10/30/2023]
Abstract
This systematic review synthesizes evidence from research investigating the biological correlates of latent transdiagnostic dimensions of psychopathology (e.g., the p-factor, internalizing, externalizing) across the lifespan. Eligibility criteria captured genomic and neuroimaging studies investigating general and/or specific dimensions in general population samples across all age groups. MEDLINE, Embase, and PsycINFO were searched for relevant studies published up to March 2023 and 46 studies were selected for inclusion. The results revealed several biological correlates consistently associated with transdiagnostic dimensions of psychopathology, including polygenic scores for ADHD and neuroticism, global surface area and global gray matter volume. Shared and unique associations between symptom dimensions are highlighted, as are potential age-specific differences in biological associations. Findings are interpreted with reference to key methodological differences across studies. The included studies provide compelling evidence that the general dimension of psychopathology reflects common underlying genetic and neurobiological vulnerabilities that are shared across diverse manifestations of mental illness. Substantive interpretations of general psychopathology in the context of genetic and neurobiological evidence are discussed.
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Affiliation(s)
- Nicholas Hoy
- The Matilda Centre for Research in Mental Health and Substance Use, University of Sydney, Sydney, Australia; Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia.
| | - Samantha J Lynch
- The Matilda Centre for Research in Mental Health and Substance Use, University of Sydney, Sydney, Australia; Department of Psychiatry, Université de Montréal, Montreal, Canada; Research Centre, CHU Sainte-Justine, Montreal, Canada
| | - Monika A Waszczuk
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, United States
| | - Simone Reppermund
- Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia; Department of Developmental Disability Neuropsychiatry, University of New South Wales, Sydney, Australia
| | - Louise Mewton
- The Matilda Centre for Research in Mental Health and Substance Use, University of Sydney, Sydney, Australia
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228
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Katz AE, Ganesh SK. Advancements in the Genetics of Spontaneous Coronary Artery Dissection. Curr Cardiol Rep 2023; 25:1735-1743. [PMID: 37979122 PMCID: PMC10810930 DOI: 10.1007/s11886-023-01989-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/24/2023] [Indexed: 11/19/2023]
Abstract
PURPOSE OF REVIEW Spontaneous coronary artery dissection (SCAD) is a significant cause of acute myocardial infarction that is increasingly recognized in young and middle-aged women. The etiology of SCAD is likely multifactorial and may include the interaction of environmental and individual factors. Here, we summarize the current understanding of the genetic factors contributing to the development of SCAD. RECENT FINDINGS The molecular findings underlying SCAD have been demonstrated to include a combination of rare DNA sequence variants with large effects, common variants contributing to a complex genetic architecture, and variants with intermediate impact. The genes associated with SCAD highlight the role of arterial cells and their extracellular matrix in the pathogenesis of the disease and shed light on the relationship between SCAD and other disorders, including fibromuscular dysplasia and connective tissue diseases. While up to 10% of affected individuals may harbor a rare variant with large effect, SCAD most often presents as a complex genetic condition. Analyses of larger and more diverse cohorts will continue to improve our understanding of risk susceptibility loci and will also enable consideration of the clinical utility of genetic testing strategies in the management of SCAD.
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Affiliation(s)
- Alexander E Katz
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, USA
- Department of Human Genetics, University of Michigan, 7220, MSRB III, 1150 West Medical Center Drive, Ann Arbor, MI, 48109-0644, USA
| | - Santhi K Ganesh
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, USA.
- Department of Human Genetics, University of Michigan, 7220, MSRB III, 1150 West Medical Center Drive, Ann Arbor, MI, 48109-0644, USA.
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229
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Serpico D. A Wolf in Sheep's Clothing: Idealisations and the aims of polygenic scores. STUDIES IN HISTORY AND PHILOSOPHY OF SCIENCE 2023; 102:72-83. [PMID: 37907020 DOI: 10.1016/j.shpsa.2023.10.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 07/13/2023] [Accepted: 10/07/2023] [Indexed: 11/02/2023]
Abstract
Research in pharmacogenomics and precision medicine has recently introduced the concept of Polygenic Scores (PGSs), namely, indexes that aggregate the effects that many genetic variants are predicted to have on individual disease risk. The popularity of PGSs is increasing rapidly, but surprisingly little attention has been paid to the idealisations they make about phenotypic development. Indeed, PGSs rely on quantitative genetics models and methods, which involve considerable theoretical assumptions that have been questioned on various grounds. This comes with epistemological and ethical concerns about the use of PGSs in clinical decision-making. In this paper, I investigate to what extent idealisations in genetics models can impact the data gathering and clinical interpretation of genomics findings, particularly the calculation and predictive accuracy of PGSs. Although idealisations are considered ineliminable components of scientific models, they may be legitimate or not depending on the epistemic aims of a model. I thus analyse how various idealisations have been introduced in classical models and progressively readapted throughout the history of genetic theorising. Notably, this process involved important changes in the epistemic purpose of such idealisations, which raises the question of whether they are legitimate in the context of contemporary genomics.
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Affiliation(s)
- Davide Serpico
- Department of Economics and Management, University of Trento, Via Vigilio Inama 5, 38122, Trento, Italy; Interdisciplinary Centre for Ethics & Institute of Philosophy, Jagiellonian University, Grodzka 52, 31-044 Kraków, Poland.
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230
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Lu T, Forgetta V, Zhou S, Richards JB, Greenwood CM. Identifying Rare Genetic Determinants for Improved Polygenic Risk Prediction of Bone Mineral Density and Fracture Risk. J Bone Miner Res 2023; 38:1771-1781. [PMID: 37830501 DOI: 10.1002/jbmr.4920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 09/13/2023] [Accepted: 10/06/2023] [Indexed: 10/14/2023]
Abstract
Osteoporosis and fractures severely impact the elderly population. Polygenic risk scores for bone mineral density have demonstrated potential clinical utility. However, the value of rare genetic determinants in risk prediction has not been assessed. With whole-exome sequencing data from 436,824 UK Biobank participants, we assigned White British ancestry individuals into a training data set (n = 317,434) and a test data set (n = 74,825). In the training data set, we developed a common variant-based polygenic risk score for heel ultrasound speed of sound (SOS). Next, we performed burden testing to identify genes harboring rare determinants of bone mineral density, targeting influential rare variants with predicted high deleteriousness. We constructed a genetic risk score, called ggSOS, to incorporate influential rare variants in significant gene burden masks into the common variant-based polygenic risk score. We assessed the predictive performance of ggSOS in the White British test data set, as well as in populations of non-White British European (n = 18,885), African (n = 7165), East Asian (n = 2236), South Asian (n = 9829), and other admixed (n = 1481) ancestries. Twelve genes in pivotal regulatory pathways of bone homeostasis harbored influential rare variants associated with SOS (p < 5.5 × 10-7 ), including AHNAK, BMP5, CYP19A1, FAM20A, FBXW5, KDM5B, KREMEN1, LGR4, LRP5, SMAD6, SOST, and WNT1. Among 4013 (5.4%) individuals in the test data set carrying these variants, a one standard deviation decrease in ggSOS was associated with 1.35-fold (95% confidence interval [CI] 1.16-1.57) increased hazard of major osteoporotic fracture. However, compared with a common variant-based polygenic risk score (C-index = 0.641), ggSOS had only marginally improved prediction accuracy in identifying at-risk individuals (C-index = 0.644), with overlapping confidence intervals. Similarly, ggSOS did not demonstrate substantially improved predictive performance in non-European ancestry populations. In summary, modeling the effects of rare genetic determinants may assist polygenic prediction of fracture risk among carriers of influential rare variants. Nonetheless, improved clinical utility is not guaranteed for population-level risk screening. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Tianyuan Lu
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
| | | | - Sirui Zhou
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - J Brent Richards
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
- 5 Prime Sciences Inc., Montreal, QC, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Celia Mt Greenwood
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- Gerald Bronfman Department of Oncology, McGill University, Montreal, QC, Canada
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231
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Long L, He H, Shen Q, Peng H, Zhou X, Wang H, Zhang S, Qin S, Lu Z, Zhu Y, Tian J, Chang J, Miao X, Shen N, Zhong R. Birthweight, genetic risk, and gastrointestinal cancer incidence: a prospective cohort study. Ann Med 2023; 55:62-71. [PMID: 36503347 PMCID: PMC9754019 DOI: 10.1080/07853890.2022.2146743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND The epidemiologic studies investigating the association of birthweight and genetic factors with gastrointestinal cancer remain scarce. The study aimed to prospectively assess the interactions and joint effects of birthweight and genetic risk levels on gastrointestinal cancer incidence in adulthood. METHODS A total of 254,997 participants were included in the UK Biobank study. We used multivariate restricted cubic splines and Cox regression models to estimate the hazard ratios (HRs) and 95% confidential intervals (CI) for the association between birthweight and gastrointestinal cancer risk, then constructed a polygenic risk score (PRS) to assess its interaction and joint effect with birthweight on the development of gastrointestinal cancer. RESULTS We documented 2512 incident cases during a median follow-up of 8.88 years. Compare with participants reporting a normal birthweight (2.5-4.5 kg), multivariable-adjusted HR of gastrointestinal cancer incidence for participants with high birthweight (≥4.5 kg) was 1.17 (95%CI: 1.01-1.36). Such association was remarkably observed in pancreatic cancer, with an HR of 1.82 (95%CI: 1.26-2.64). No statistically significant association was observed between low birth weight and gastrointestinal cancers. Participants with high birthweight and high PRS had the highest risk of gastrointestinal cancer (HR: 2.95, 95%CI: 2.19-3.96). CONCLUSION Our findings highlight that high birthweight is associated with a higher incidence of gastrointestinal cancer, especially for pancreatic cancer. Benefits would be obtained from birthweight control, particularly for individuals with a high genetic risk.KEY MESSAGESThe epidemiologic studies investigating the association of birthweight and genetic factors with gastrointestinal cancer remain scarce.This cohort study of 254,997 adults in the United Kingdom found an association of high birthweight with the incidence of gastrointestinal cancer, especially for pancreatic cancer, and also found that participants with high birthweight and high polygenic risk score had the highest risk of gastrointestinal cancer.Our data suggests a possible effect of in utero or early life exposures on adulthood gastrointestinal cancer, especially for those with a high genetic risk.
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Affiliation(s)
- Lu Long
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Heng He
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Qian Shen
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongxia Peng
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xiaorui Zhou
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Haoxue Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shanshan Zhang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shifan Qin
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- School of Public Health, Wuhan University, Wuhan, China
| | - Jianbo Tian
- School of Public Health, Wuhan University, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Miao
- School of Public Health, Wuhan University, Wuhan, China
| | - Na Shen
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, HUST, Wuhan, China
- Na Shen Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, HUST, Wuhan, 430030, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- CONTACT Rong Zhong Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
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232
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Smith WR, Appelbaum PS, Lebowitz MS, Gülöksüz S, Calkins ME, Kohler CG, Gur RE, Barzilay R. The Ethics of Risk Prediction for Psychosis and Suicide Attempt in Youth Mental Health. J Pediatr 2023; 263:113583. [PMID: 37353146 PMCID: PMC10828819 DOI: 10.1016/j.jpeds.2023.113583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 06/01/2023] [Accepted: 06/16/2023] [Indexed: 06/25/2023]
Abstract
OBJECTIVE To identify potential clinical utility of polygenic risk scores (PRS) and exposomic risk scores (ERS) for psychosis and suicide attempt in youth and assess the ethical implications of these tools. STUDY DESIGN We conducted a narrative literature review of emerging findings on PRS and ERS for suicide and psychosis as well as a literature review on the ethics of PRS. We discuss the ethical implications of the emerging findings for the clinical potential of PRS and ERS. RESULTS Emerging evidence suggests that PRS and ERS may offer clinical utility in the relatively near future but that this utility will be limited to specific, narrow clinical questions, in contrast to the suggestion that population-level screening will have sweeping impact. Combining PRS and ERS might optimize prediction. This clinical utility would change the risk-benefit balance of PRS, and further empirical assessment of proposed risks would be necessary. Some concerns for PRS, such as those about counseling, privacy, and inequities, apply to ERS. ERS raise distinct ethical challenges as well, including some that involve informed consent and direct-to-consumer advertising. Both raise questions about the ethics of machine-learning/artificial intelligence approaches. CONCLUSIONS Predictive analytics using PRS and ERS may soon play a role in youth mental health settings. Our findings help educate clinicians about potential capabilities, limitations, and ethical implications of these tools. We suggest that a broader discussion with the public is needed to avoid overenthusiasm and determine regulations and guidelines for use of predictive scores.
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Affiliation(s)
- William R Smith
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA.
| | - Paul S Appelbaum
- Department of Psychiatry, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY; New York State Psychiatric Institute, New York, NY
| | - Matthew S Lebowitz
- Department of Psychiatry, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
| | - Sinan Gülöksüz
- Department of Psychiatry, Yale School of Medicine, New Haven, CT; Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Monica E Calkins
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Christian G Kohler
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Lifespan Brain Institute, Children's Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia, PA; Department of Child and Adolescent Psychiatry, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA
| | - Ran Barzilay
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Department of Child and Adolescent Psychiatry, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA; Department of Child and Adolescent Psychiatry, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA
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233
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Kim JS, Montesi SB, Adegunsoye A, Humphries SM, Salisbury ML, Hariri LP, Kropski JA, Richeldi L, Wells AU, Walsh S, Jenkins RG, Rosas I, Noth I, Hunninghake GM, Martinez FJ, Podolanczuk AJ. Approach to Clinical Trials for the Prevention of Pulmonary Fibrosis. Ann Am Thorac Soc 2023; 20:1683-1693. [PMID: 37703509 PMCID: PMC10704236 DOI: 10.1513/annalsats.202303-188ps] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 09/13/2023] [Indexed: 09/15/2023] Open
Affiliation(s)
- John S. Kim
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Virginia, Charlottesville, Virginia
- Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | | | - Ayodeji Adegunsoye
- Department of Medicine, The University of Chicago Medicine, Chicago, Illinois
| | | | - Margaret L. Salisbury
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Lida P. Hariri
- Division of Pulmonary and Critical Care Medicine, and
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Jonathan A. Kropski
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Luca Richeldi
- Fondazione Policlinico Universitario Agostino Gemelli Istituto di Ricovero e Cura a Carattere Scientifico, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Athol U. Wells
- Department of Radiology, and
- Interstitial Lung Disease Service, Royal Brompton Hospital, London, United Kingdom
| | - Simon Walsh
- National Heart and Lung Institute, Imperial College, London, United Kingdom
| | - R. Gisli Jenkins
- National Heart and Lung Institute, Imperial College, London, United Kingdom
| | - Ivan Rosas
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Imre Noth
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Virginia, Charlottesville, Virginia
| | - Gary M. Hunninghake
- Pulmonary and Critical Care Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts; and
| | - Fernando J. Martinez
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, New York
| | - Anna J. Podolanczuk
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, New York
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Lin J, Mars N, Fu Y, Ripatti P, Kiiskinen T, Tukiainen T, Ripatti S, Pirinen M. Integration of Biomarker Polygenic Risk Score Improves Prediction of Coronary Heart Disease. JACC Basic Transl Sci 2023; 8:1489-1499. [PMID: 38205343 PMCID: PMC10774750 DOI: 10.1016/j.jacbts.2023.07.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 07/06/2023] [Accepted: 07/10/2023] [Indexed: 01/12/2024]
Abstract
There are several established biomarkers for coronary heart disease (CHD), including blood pressure, cholesterol, and lipoproteins. It is of high interest to determine how a combined polygenic risk score (PRS) of CHD-associated biomarkers (BioPRS) can further improve genetic prediction of CHD. We developed CHDBioPRS, combining BioPRS with PRS of CHD in the UK Biobank and tested it on FinnGen. We found that BioPRS was clearly predictive of CHD and that CHDBioPRS improved the standard CHD PRS. The largest effect was observed with early onset cases in FinnGen, with HRs above 2 per standard deviation of CHDBioPRS.
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Affiliation(s)
- Jake Lin
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Health Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland
| | - Nina Mars
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Yu Fu
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Pietari Ripatti
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Tuomo Kiiskinen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - FinnGen study
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Health Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Broad Institute of Massachusetts Institute of Technology, Harvard University, Cambridge, Massachusetts, USA
- Massachusetts General Hospital, Cambridge, Massachusetts, USA
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Taru Tukiainen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Broad Institute of Massachusetts Institute of Technology, Harvard University, Cambridge, Massachusetts, USA
- Massachusetts General Hospital, Cambridge, Massachusetts, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
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Takase M, Nakaya N, Nakamura T, Kogure M, Hatanaka R, Nakaya K, Chiba I, Kanno I, Nochioka K, Tsuchiya N, Hirata T, Narita A, Obara T, Ishikuro M, Uruno A, Kobayashi T, N Kodama E, Hamanaka Y, Orui M, Ogishima S, Nagaie S, Fuse N, Sugawara J, Kuriyama S, Tsuji I, Tamiya G, Hozawa A, Yamamoto M. Influence of Diabetes Family History on the Associations of Combined Genetic and Lifestyle Risks with Diabetes in the Tohoku Medical Megabank Community-Based Cohort Study. J Atheroscler Thromb 2023; 30:1950-1965. [PMID: 37813642 DOI: 10.5551/jat.64425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/11/2023] Open
Abstract
AIM The influence of family history of diabetes, probably reflecting genetic and lifestyle factors, on the association of combined genetic and lifestyle risks with diabetes is unknown. We examined these associations. METHODS This cross-sectional study included 9,681 participants in the Tohoku Medical Megabank Community-based Cohort Study. A lifestyle score, which was categorized into ideal, intermediate, and poor lifestyles, was given. Family history was obtained through a self-reported questionnaire. A polygenic risk score (PRS) was constructed in the target data (n=1,936) using publicly available genome-wide association study summary statistics from BioBank Japan. For test data (n=7,745), we evaluated PRS performance and examined the associations of combined family history and genetic and lifestyle risks with diabetes. Diabetes was defined as non-fasting blood glucose ≥ 200 mmHg, HbA1c ≥ 6.5%, and/or self-reported diabetes treatment. RESULTS In test data, 467 (6.0%) participants had diabetes. Compared with a low genetic risk and an ideal lifestyle without a family history, the odds ratio (OR) was 3.73 (95% confidence interval [CI], 1.92-7.00) for a lower genetic risk and a poor lifestyle without a family history. Family history was significantly associated with diabetes (OR, 3.58 [95% CI, 1.73-6.98]), even in those with a low genetic risk and an ideal lifestyle. Even among participants who had an ideal lifestyle without a family history, a high genetic risk was associated with diabetes (OR, 2.49 [95% CI, 1.65-3.85]). Adding PRS to family history and conventional lifestyle risk factors improved the prediction ability for diabetes. CONCLUSIONS Our findings support the notion that a healthy lifestyle is important to prevent diabetes regardless of genetic risk.
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Affiliation(s)
| | - Naoki Nakaya
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Tomohiro Nakamura
- Tohoku Medical Megabank Organization, Tohoku University
- Kyoto Women fs University
| | - Mana Kogure
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Rieko Hatanaka
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Kumi Nakaya
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Ippei Chiba
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Ikumi Kanno
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Kotaro Nochioka
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
- Tohoku University Hospital, Tohoku University
| | - Naho Tsuchiya
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Takumi Hirata
- Tohoku Medical Megabank Organization, Tohoku University
- Institute for Clinical and Translational Science, Nara Medical University
| | - Akira Narita
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Taku Obara
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Mami Ishikuro
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Akira Uruno
- Tohoku Medical Megabank Organization, Tohoku University
| | - Tomoko Kobayashi
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
- Tohoku University Hospital, Tohoku University
| | - Eiichi N Kodama
- Graduate School of Medicine, Tohoku University
- International Research Institute of Disaster Science, Tohoku University
| | | | - Masatsugu Orui
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Soichi Ogishima
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Satoshi Nagaie
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Nobuo Fuse
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Junichi Sugawara
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
- Tohoku University Hospital, Tohoku University
- Suzuki Memorial Hospital
| | - Shinichi Kuriyama
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
- International Research Institute of Disaster Science, Tohoku University
| | - Ichiro Tsuji
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Gen Tamiya
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
- RIKEN Center for Advanced Intelligence Project
| | - Atsushi Hozawa
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
| | - Masayuki Yamamoto
- Graduate School of Medicine, Tohoku University
- Tohoku Medical Megabank Organization, Tohoku University
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Sleiman PM, Qu HQ, Connolly JJ, Mentch F, Pereira A, Lotufo PA, Tollman S, Choudhury A, Ramsay M, Kato N, Ozaki K, Mitsumori R, Jeon JP, Hong CH, Son SJ, Roh HW, Lee DG, Mukadam N, Foote IF, Marshall CR, Butterworth A, Prins BP, Glessner JT, Hakonarson H. Trans-ethnic genomic informed risk assessment for Alzheimer's disease: An International Hundred K+ Cohorts Consortium study. Alzheimers Dement 2023; 19:5765-5772. [PMID: 37450379 PMCID: PMC10854406 DOI: 10.1002/alz.13378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 04/26/2023] [Accepted: 05/05/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND As a collaboration model between the International HundredK+ Cohorts Consortium (IHCC) and the Davos Alzheimer's Collaborative (DAC), our aim was to develop a trans-ethnic genomic informed risk assessment (GIRA) algorithm for Alzheimer's disease (AD). METHODS The GIRA model was created to include polygenic risk score calculated from the AD genome-wide association study loci, the apolipoprotein E haplotypes, and non-genetic covariates including age, sex, and the first three principal components of population substructure. RESULTS We validated the performance of the GIRA model in different populations. The proteomic study in the participant sites identified proteins related to female infertility and autoimmune thyroiditis and associated with the risk scores of AD. CONCLUSIONS As the initial effort by the IHCC to leverage existing large-scale datasets in a collaborative setting with DAC, we developed a trans-ethnic GIRA for AD with the potential of identifying individuals at high risk of developing AD for future clinical applications.
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Affiliation(s)
- Patrick M. Sleiman
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
| | - Hui-Qi Qu
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
| | - John J Connolly
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
| | - Frank Mentch
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
| | - Alexandre Pereira
- Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Centro de Pesquisas Clínicas e Epidemiológicas, Hospital Universitário, Universidade de São Paulo, São Paulo, Brazil
| | - Paulo A Lotufo
- Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Centro de Pesquisas Clínicas e Epidemiológicas, Hospital Universitário, Universidade de São Paulo, São Paulo, Brazil
| | - Stephen Tollman
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Ananyo Choudhury
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Michele Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Norihiro Kato
- National Center for Global Health and Medicine, Tokyo, 1628655, Japan
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology (NCGG), Obu City, Aichi Prefecture, Japan
| | - Risa Mitsumori
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology (NCGG), Obu City, Aichi Prefecture, Japan
| | - Jae-Pil Jeon
- Korea Biobank Project, Korea National Institute of Health, Osong, Korea
| | - Chang Hyung Hong
- Department of Psychiatry, Ajou University School of Medicine, Suwon, Korea
| | - Sang Joon Son
- Department of Psychiatry, Ajou University School of Medicine, Suwon, Korea
| | - Hyun Woong Roh
- Department of Psychiatry, Ajou University School of Medicine, Suwon, Korea
| | - Dong-gi Lee
- Department of Psychiatry, Ajou University School of Medicine, Suwon, Korea
- Department of Biostatistics, Epidemiology and Informatics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
| | - Naaheed Mukadam
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, UK
| | - Isabelle F Foote
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, UK
- Genes & Health, Blizard Institute, Queen Mary University of London, UK
| | - Charles R Marshall
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, UK
- Genes & Health, Blizard Institute, Queen Mary University of London, UK
| | - Adam Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Bram P Prins
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Joseph T Glessner
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
| | - Hakon Hakonarson
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
- Division of Pulmonary Medicine, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
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Chen J, Gatev E, Everson T, Conneely KN, Koen N, Epstein MP, Kobor MS, Zar HJ, Stein DJ, Hüls A. Pruning and thresholding approach for methylation risk scores in multi-ancestry populations. Epigenetics 2023; 18:2187172. [PMID: 36908043 PMCID: PMC10026878 DOI: 10.1080/15592294.2023.2187172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2023] Open
Abstract
Recent efforts have focused on developing methylation risk scores (MRS), a weighted sum of the individual's DNA methylation (DNAm) values of pre-selected CpG sites. Most of the current MRS approaches that utilize Epigenome-wide association studies (EWAS) summary statistics only include genome-wide significant CpG sites and do not consider co-methylation. New methods that relax the p-value threshold to include more CpG sites and account for the inter-correlation of DNAm might improve the predictive performance of MRS. We paired informed co-methylation pruning with P-value thresholding to generate pruning and thresholding (P+T) MRS and evaluated its performance among multi-ancestry populations. Through simulation studies and real data analyses, we demonstrated that pruning provides an improvement over simple thresholding methods for prediction of phenotypes. We demonstrated that European-derived summary statistics can be used to develop P+T MRS among other populations such as African populations. However, the prediction accuracy of P+T MRS may differ across multi-ancestry population due to environmental/cultural/social differences.
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Affiliation(s)
- Junyu Chen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA USA
| | - Evan Gatev
- Institute of Molecular Biology "Acad. Roumen Tsanev", Sofia, Bulgaria
- Department of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Todd Everson
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA USA
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Karen N Conneely
- Department of Human Genetics, School of Medicine, Emory University, Atlanta, GA USA
| | - Nastassja Koen
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, University of Cape Town, Cape Town, South Africa
| | - Michael P Epstein
- Department of Human Genetics, School of Medicine, Emory University, Atlanta, GA USA
| | - Michael S Kobor
- Department of Medical Genetics, University of British Columbia, Vancouver, Canada
- BC Children's Hospital Research Institute, Vancouver, Canada
- Centre for Molecular Medicine and Therapeutics, Vancouver, Canada
| | - Heather J Zar
- Department of Pediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council (SAMRC) Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - Dan J Stein
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, University of Cape Town, Cape Town, South Africa
| | - Anke Hüls
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA USA
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia
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238
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Chen JJ, Chen IC, Wei CY, Lin SY, Chen YM. Utilize polygenic risk score to enhance fracture risk estimation and improve the performance of FRAX in patients with osteoporosis. Arch Osteoporos 2023; 18:147. [PMID: 38036866 DOI: 10.1007/s11657-023-01357-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 11/20/2023] [Indexed: 12/02/2023]
Abstract
This study examined the use of polygenic risk scores (PGS) in combination with the Fracture Risk Assessment Tool (FRAX) to enhance fragility fractures risk estimation in osteoporosis patients. Analyzing data from over 57,000 participants, PGS improved fracture risk estimation, especially for individuals with intermediate to low risks, allowing personalized preventive strategies. INTRODUCTION Osteoporosis and fragility fractures are multifactorial, with contributions from both clinical and genetic determinants. However, whether using polygenic risk scores (PGS) may enhance the risk estimation of osteoporotic fracture in addition to Fracture Risk Assessment Tool (FRAX) remains unknown. This study investigated the collective association of PGS and FRAX with fragility fracture. METHODS We conducted a cohort study from the Taiwan Precision Medicine Initiative (TPMI) at Taichung Veterans General Hospital, Taiwan. Genotyping was performed to compute PGS associated with bone mineral density (BMD). Phenome-wide association studies were executed to pinpoint phenotypes correlated with the PGS. Logistic regression analysis was conducted to ascertain factors associated with osteoporotic fractures. RESULTS Among all 57,257 TPMI participants, 3744 (904 men and 2840 women, with a mean age of 66.7) individuals had BMD testing, with 540 (14.42%) presenting with fractures. The 3744 individuals who underwent BMD testing were categorized into four quartiles (Q1-Q4) based on PGS; 540 (14.42%) presented with fractures. Individuals with PGS-Q1 exhibited lower BMD, a higher prevalence of major fractures, and elevated FRAX-major and FRAX-hip than those with PGS-Q4. PGS was associated with major fractures after adjusting age, sex, and FRAX scores. Notably, the risk of major fractures (PGS-Q1 vs. Q4) was significantly higher in the subgroups of FRAX-major scores < 10% and 10-20%, but not in participants with a FRAX-major score ≧ 20%. CONCLUSIONS Our study highlights the potential of PGS to augment fracture risk estimation in conjunction with FRAX, particularly in individuals with middle to low risks. Incorporating genetic testing could empower physicians to tailor personalized preventive strategies for osteoporosis.
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Affiliation(s)
- Jian-Jiun Chen
- Department of Orthopedics, Taipei Veterans General Hospital, Taipei, Taiwan
| | - I-Chieh Chen
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Chia-Yi Wei
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Shih-Yi Lin
- Center for Geriatrics and Gerontology, Taichung Veterans General Hospital, Taichung, Taiwan.
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung-Hsing University, Taichung, Taiwan.
- School of Medicine, National Yang-Ming Chiao Tung University, Taipei, Taiwan.
| | - Yi-Ming Chen
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan.
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung-Hsing University, Taichung, Taiwan.
- School of Medicine, National Yang-Ming Chiao Tung University, Taipei, Taiwan.
- Division of Allergy, Immunology and Rheumatology, Taichung Veterans General Hospital, Taichung, Taiwan.
- Institute of Biomedical Science and Rong-Hsing Research Center for Translational Medicine, Chung-Hsing University, Taichung, Taiwan.
- Precision Medicine Research Center, College of Medicine, National Chung Hsing University, Taichung, Taiwan.
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Maldonado BL, Piqué DG, Kaplan RC, Claw KG, Gignoux CR. Genetic risk prediction in Hispanics/Latinos: milestones, challenges, and social-ethical considerations. J Community Genet 2023; 14:543-553. [PMID: 37962783 PMCID: PMC10725387 DOI: 10.1007/s12687-023-00686-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 10/18/2023] [Indexed: 11/15/2023] Open
Abstract
Genome-wide association studies (GWAS) have allowed the identification of disease-associated variants, which can be leveraged to build polygenic scores (PGSs). Even though PGSs can be a valuable tool in personalized medicine, their predictive power is limited in populations of non-European ancestry, particularly in admixed populations. Recent efforts have focused on increasing racial and ethnic diversity in GWAS, thus, addressing some of the limitations of genetic risk prediction in these populations. Even with these efforts, few studies focus exclusively on Hispanics/Latinos. Additionally, Hispanic/Latino populations are often considered a single population despite varying admixture proportions between and within ethnic groups, diverse genetic heterogeneity, and demographic history. Combined with highly heterogeneous environmental and socioeconomic exposures, this diversity can reduce the transferability of genetic risk prediction models. Given the recent increase of genomic studies that include Hispanics/Latinos, we review the milestones and efforts that focus on genetic risk prediction, summarize the potential for improving PGS transferability, and highlight the challenges yet to be addressed. Additionally, we summarize social-ethical considerations and provide ideas to promote genetic risk prediction models that can be implemented equitably.
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Affiliation(s)
- Betzaida L Maldonado
- Human Medical Genetics & Genomics Graduate Program, University of Colorado-Anschutz Medical Campus, Aurora, CO, USA.
- Colorado Center for Personalized Medicine, University of Colorado-Anschutz Medical Campus, Aurora, CO, USA.
- Department of Biomedical Informatics, University of Colorado-Anschutz Medical Campus, Aurora, CO, USA.
| | - Daniel G Piqué
- Colorado Center for Personalized Medicine, University of Colorado-Anschutz Medical Campus, Aurora, CO, USA
- Section of Genetics and Metabolism, Department of Pediatrics, Children's Hospital Colorado, Aurora, CO, USA
| | - Robert C Kaplan
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Katrina G Claw
- Human Medical Genetics & Genomics Graduate Program, University of Colorado-Anschutz Medical Campus, Aurora, CO, USA
- Colorado Center for Personalized Medicine, University of Colorado-Anschutz Medical Campus, Aurora, CO, USA
- Department of Biomedical Informatics, University of Colorado-Anschutz Medical Campus, Aurora, CO, USA
| | - Christopher R Gignoux
- Human Medical Genetics & Genomics Graduate Program, University of Colorado-Anschutz Medical Campus, Aurora, CO, USA
- Colorado Center for Personalized Medicine, University of Colorado-Anschutz Medical Campus, Aurora, CO, USA
- Department of Biomedical Informatics, University of Colorado-Anschutz Medical Campus, Aurora, CO, USA
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Gharahkhani P, He W, Han X, Ong JS, Rentería ME, Wiggs JL, Khawaja AP, Trzaskowski M, Mackey DA, Craig JE, Hewitt AW, MacGregor S, Wu Y. WITHDRAWN: Genome-wide risk prediction of primary open-angle glaucoma across multiple ancestries. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.08.23298255. [PMID: 37986775 PMCID: PMC10659472 DOI: 10.1101/2023.11.08.23298255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
This manuscript has been withdrawn by medRxiv following a formal request by the QIMR Berghofer Medical Research Institute Research Integrity Office owing to lack of author consent.
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Levi H, Carmi S, Rosset S, Yerushalmi R, Zick A, Yablonski-Peretz T, Wang Q, Bolla MK, Dennis J, Michailidou K, Lush M, Ahearn T, Andrulis IL, Anton-Culver H, Antoniou AC, Arndt V, Augustinsson A, Auvinen P, Beane Freeman L, Beckmann M, Behrens S, Bermisheva M, Bodelon C, Bogdanova NV, Bojesen SE, Brenner H, Byers H, Camp N, Castelao J, Chang-Claude J, Chirlaque MD, Chung W, Clarke C, Collee MJ, Colonna S, Couch F, Cox A, Cross SS, Czene K, Daly M, Devilee P, Dork T, Dossus L, Eccles DM, Eliassen AH, Eriksson M, Evans G, Fasching P, Fletcher O, Flyger H, Fritschi L, Gabrielson M, Gago-Dominguez M, García-Closas M, Garcia-Saenz JA, Genkinger J, Giles GG, Goldberg M, Guénel P, Hall P, Hamann U, He W, Hillemanns P, Hollestelle A, Hoppe R, Hopper J, Jakovchevska S, Jakubowska A, Jernström H, John E, Johnson N, Jones M, Vijai J, Kaaks R, Khusnutdinova E, Kitahara C, Koutros S, Kristensen V, Kurian AW, Lacey J, Lambrechts D, Le Marchand L, Lejbkowicz F, Lindblom A, Loibl S, Lori A, Lubinski J, Mannermaa A, Manoochehri M, Mavroudis D, Menon U, Mulligan A, Murphy R, Nevelsteen I, Newman WG, Obi N, O'Brien K, Offit K, Olshan A, Plaseska-Karanfilska D, Olson J, Panico S, Park-Simon TW, Patel A, Peterlongo P, Rack B, Radice P, Rennert G, Rhenius V, Romero A, Saloustros E, Sandler D, Schmidt MK, Schwentner L, Shah M, Sharma P, Simard J, Southey M, Stone J, Tapper WJ, Taylor J, Teras L, Toland AE, Troester M, Truong T, van der Kolk LE, Weinberg C, Wendt C, Yang XR, Zheng W, Ziogas A, Dunning AM, Pharoah P, Easton DF, Ben-Sachar S, Elefant N, Shamir R, Elkon R. Evaluation of European-based polygenic risk score for breast cancer in Ashkenazi Jewish women in Israel. J Med Genet 2023; 60:1186-1197. [PMID: 37451831 PMCID: PMC10715538 DOI: 10.1136/jmg-2023-109185] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 05/28/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND Polygenic risk score (PRS), calculated based on genome-wide association studies (GWASs), can improve breast cancer (BC) risk assessment. To date, most BC GWASs have been performed in individuals of European (EUR) ancestry, and the generalisation of EUR-based PRS to other populations is a major challenge. In this study, we examined the performance of EUR-based BC PRS models in Ashkenazi Jewish (AJ) women. METHODS We generated PRSs based on data on EUR women from the Breast Cancer Association Consortium (BCAC). We tested the performance of the PRSs in a cohort of 2161 AJ women from Israel (1437 cases and 724 controls) from BCAC (BCAC cohort from Israel (BCAC-IL)). In addition, we tested the performance of these EUR-based BC PRSs, as well as the established 313-SNP EUR BC PRS, in an independent cohort of 181 AJ women from Hadassah Medical Center (HMC) in Israel. RESULTS In the BCAC-IL cohort, the highest OR per 1 SD was 1.56 (±0.09). The OR for AJ women at the top 10% of the PRS distribution compared with the middle quintile was 2.10 (±0.24). In the HMC cohort, the OR per 1 SD of the EUR-based PRS that performed best in the BCAC-IL cohort was 1.58±0.27. The OR per 1 SD of the commonly used 313-SNP BC PRS was 1.64 (±0.28). CONCLUSIONS Extant EUR GWAS data can be used for generating PRSs that identify AJ women with markedly elevated risk of BC and therefore hold promise for improving BC risk assessment in AJ women.
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Grants
- R01 CA176785 NCI NIH HHS
- NU58DP006344 NCCDPHP CDC HHS
- R37 CA070867 NCI NIH HHS
- HHSN261201800015I NCI NIH HHS
- R01 CA064277 NCI NIH HHS
- P50 CA116201 NCI NIH HHS
- G1000143 Medical Research Council
- P30 CA062203 NCI NIH HHS
- HHSN261201800015C NCI NIH HHS
- R01 CA047305 NCI NIH HHS
- HHSN261201800009I NCI NIH HHS
- R01 CA163353 NCI NIH HHS
- UM1 CA164917 NCI NIH HHS
- U01 CA199277 NCI NIH HHS
- U01 CA179715 NCI NIH HHS
- HHSN261201800032C NCI NIH HHS
- U54 CA156733 NCI NIH HHS
- HHSN261201800009C NCI NIH HHS
- Z01 CP010119 Intramural NIH HHS
- UM1 CA164973 NCI NIH HHS
- P01 CA087969 NCI NIH HHS
- UM1 CA164920 NCI NIH HHS
- NU58DP006320 CDC HHS
- UM1 CA176726 NCI NIH HHS
- R01 CA092447 NCI NIH HHS
- Z01 ES049030 Intramural NIH HHS
- R01 CA058860 NCI NIH HHS
- K07 CA092044 NCI NIH HHS
- HHSN261201800016C NCI NIH HHS
- P50 CA058223 NCI NIH HHS
- R01 CA100374 NCI NIH HHS
- P30 CA008748 NCI NIH HHS
- R01 CA128978 NCI NIH HHS
- R01 CA047147 NCI NIH HHS
- U19 CA148537 NCI NIH HHS
- R01 CA116167 NCI NIH HHS
- R01 CA148667 NCI NIH HHS
- R01 CA063464 NCI NIH HHS
- HHSN261201800016I NCI NIH HHS
- UM1 CA186107 NCI NIH HHS
- P30 CA023100 NCI NIH HHS
- U01 CA063464 NCI NIH HHS
- R01 CA077398 NCI NIH HHS
- R01 CA054281 NCI NIH HHS
- R01 CA132839 NCI NIH HHS
- P30 CA068485 NCI NIH HHS
- U01 CA058860 NCI NIH HHS
- U01 CA164920 NCI NIH HHS
- R35 CA253187 NCI NIH HHS
- 14136 Cancer Research UK
- U19 CA148112 NCI NIH HHS
- HHSN261201800032I NCI NIH HHS
- U01 CA098758 NCI NIH HHS
- Z01 ES044005 Intramural NIH HHS
- U19 CA148065 NCI NIH HHS
- P30 CA033572 NCI NIH HHS
- R01 CA069664 NCI NIH HHS
- Wellcome Trust
- 001 World Health Organization
- Z01 ES049033 Intramural NIH HHS
- R01 CA192393 NCI NIH HHS
- U01 CA164973 NCI NIH HHS
- R37 CA054281 NCI NIH HHS
- Consellería de Industria Programa Sectorial de Investigación Aplicada
- Statistics Netherlands
- South Eastern Norway Health Authority
- Lower Saxonian Cancer Society
- Lise Boserup Fund
- Heidelberger Zentrum für Personalisierte Onkologie Deutsches Krebsforschungszentrum In Der Helmholtz-Gemeinschaft
- Lon V. Smith Foundation
- Scottish Funding Council
- Komen Foundation
- Claudia von Schilling Foundation for Breast Cancer Research
- Russian Foundation for Basic Research
- Ligue Contre le Cancer
- Sigrid Juselius Foundation
- Kuopion Yliopistollinen Sairaala
- Sheffield Experimental Cancer Medicine Centre
- Stockholm läns landsting
- Department of Health and Human Services (USA)
- Department of Defence (USA)
- Stichting Tegen Kanker
- David F. and Margaret T. Grohne Family Foundation
- Sundhed og Sygdom, Det Frie Forskningsråd
- Stavros Niarchos Foundation
- Post-Cancer GWAS initiative
- Institute of the Ruhr University Bochum
- Instituto de Salud Carlos III
- Institute of Cancer Research
- Public Health Institute
- Fondation du cancer du sein du Québec
- Institut National de la Santé et de la Recherche Médicale
- Pink Ribbon
- Institute for Prevention and Occupational Medicine
- K.G. Jebsen Centre for Breast Cancer Research
- Research Centre for Genetic Engineering and Biotechnology
- Center of Excellence (Finland)
- Robert and Kate Niehaus Clinical Cancer Genetics Initiative
- Rudolf Bartling Foundation
- Center for Disease Control and Prevention (USA)
- Karolinska Institutet
- Norges Forskningsråd
- Robert Bosch Stiftung
- Intramural Research Funds of the National Cancer Institute (USA)
- Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC
- Intramural Research Program of the Division of Cancer Epidemiology and Genetics
- Centre International de Recherche sur le Cancer
- Queensland Cancer Fund
- Red Temática de Investigación Cooperativa en Cáncer
- Intramural Research Program of the National Institutes of Health
- National Health Service (UK)
- Ministerie van Volksgezondheid, Welzijn en Sport
- National cancer institute (USA)
- KWF Kankerbestrijding
- Märit and Hans Rausings Initiative Against Breast Cancer
- Associazione Italiana per la Ricerca sul Cancro
- Fundación Científica Asociación Española Contra el Cáncer
- ERC advanced grant
- Australian National Health and Medical Research Council
- Agence Nationale de la Recherche
- Dutch Prevention Funds,
- Agence Nationale de Sécurité Sanitaire de l'Alimentation, de l'Environnement et du Travail
- American Cancer Society
- Dutch Zorg Onderzoek
- Alexander von Humboldt-Stiftung
- Ministerio de Economia y Competitividad (Spain)
- Ministère du Développement Économique, de l’Innovation et de l’Exportation
- Susan G. Komen for the Cure
- Minister of Science and Higher Education
- Medical Research Council UK
- Ministry of Science and Higher Education of the Russian Federation
- Ministry of Science and Higher Education (Sweden)
- Against Breast Cancer
- Mutuelle Générale de l’Education Nationale
- Academy of Finland
- Deutsche Krebshilfe e.V.
- Dietmar-Hopp Foundation,
- Division of Cancer Prevention, National Cancer Institute
- Deutsche Krebshilfe
- World Cancer Research Fund
- Genome Québec
- National Cancer Institute’s Surveillance, Epidemiology and End Results Program
- Breast Cancer Campaign
- National Cancer Research Network
- Berta Kamprad Foundation FBKS
- Bert von Kantzows foundation
- Biomedical Research Centre at Guy’s and St Thomas
- Genome Canada
- Freistaat Sachsen
- Biobanking and Biomolecular Resources Research Infrastructure
- Friends of Hannover Medical School
- Breast Cancer Research Foundation
- California Department of Public Health
- Government of Russian Federation
- Deutsche Forschungsgemeinschaft
- National Institute for Health and Care Research
- National Health and Medical Research Council (Australia)
- German Federal Ministry of Research and Education
- National Institute of Environmental Health Sciences
- Breast Cancer Now
- Seventh Framework Programme
- Transcan
- Centrum för idrottsforskning
- UK National Institute for Health Research Biomedical Research Centre
- University of Crete
- National Breast Cancer Foundation (Finland)
- European Regional Development Fund
- National Breast Cancer Foundation (Australia)
- United States Army Medical Research and Materiel Command
- EU Horizon 2020 Research and Innovation Programme
- Directorate-General XII, Science, Research, and Development
- Baden Württemberg Ministry of Science, Research and Arts
- VicHealth
- Fondo de Investigación Sanitario
- Victorian Breast Cancer Research Consortium.
- Finnish Cancer Foundation
- University of Southern California San Francisco
- Fomento de la Investigación Clínica Independiente
- the Cancer Biology Research Center (CBRC), Djerassi Oncology Center
- Bundesministerium für Bildung und Forschung
- Cancerfonden
- Tel Aviv University Center for AI and Data Science
- University of Oulu
- National Breast Cancer Foundation (JS)
- Safra Center for Bioinformatics
- Fondation de France, Institut National du Cancer
- Israeli Science Foundation
- University of Utah
- National Cancer Center Research and Development Fund (Japan)
- Chief Scientist Office, Scottish Government Health and Social Care Directorate
- Oak Foundation
- Health Research Fund (FIS)
- Ontario Familial Breast Cancer Registry
- New South Wales Cancer Council
- North Carolina University Cancer Research Fund
- Kreftforeningen
- Northern California Breast Cancer Family Registry
- Institut Gustave Roussy
- Huntsman Cancer Institute, University of Utah
- Ovarian Cancer Research Fund
- NIHR Oxford Biomedical Research Centre
- Hellenic Health Foundation
- Oulun Yliopistollinen Sairaala
- Helmholtz Society
- Herlev and Gentofte Hospital
- PSRSIIRI-701
- Helsinki University Hospital Research Fund
- Cancer Council Victoria
- National Research Council (Italy)
- Cancer Council Tasmania
- Cancer Council Western Australia
- Hamburger Krebsgesellschaft
- Gustav V Jubilee foundation
- National Program of Cancer Registries
- Canadian Cancer Society
- Cancer Council South Australia
- Canadian Institutes of Health Research
- Cancer Council NSW
- Guy's & St. Thomas' NHS Foundation Trust
- Netherlands Organisation of Scientific Research
- Cancer Institute NSW
- National Institutes of Health (USA)
- National Research Foundation of Korea
- Syöpäsäätiö
- Cancer Foundation of Western Australia
- Netherlands Cancer Registry (NKR),
- Cancer Fund of North Savo
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Affiliation(s)
- Hagai Levi
- The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
- Department of Human Molecular Genetics and Biochemistry, Tel Aviv University, Tel Aviv, Israel
| | - Shai Carmi
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Saharon Rosset
- Department of Statistics and Operations Research, Tel Aviv University, Tel Aviv, Israel
| | - Rinat Yerushalmi
- Institute of Oncology, Davidoff Cancer Center, Rabin Medical Center, Beilinson Hospital, Petah Tikva, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Aviad Zick
- Department of oncology, Hadassah Medical Center, Jerusalem, Israel
- Hebrew University of Jerusalem, Jerusalem, Israel
| | - Tamar Yablonski-Peretz
- Department of oncology, Hadassah Medical Center, Jerusalem, Israel
- Hebrew University of Jerusalem, Jerusalem, Israel
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Biostatistics Unit, The Cyprus Institute of Neurology & Genetics, Nicosia, Cyprus
| | - Michael Lush
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Thomas Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Irene L Andrulis
- Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Hoda Anton-Culver
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Annelie Augustinsson
- Oncology, Department of Clinical Sciences in Lund, Lund University, Lund, Sweden
| | - Päivi Auvinen
- Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland
- Institute of Clinical Medicine, Oncology, University of Eastern Finland, Kuopio, Finland
- Department of Oncology, Cancer Center, Kuopio University Hospital, Kuopio, Finland
| | - Laura Beane Freeman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Matthias Beckmann
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Sabine Behrens
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Marina Bermisheva
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia
| | - Clara Bodelon
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Natalia V Bogdanova
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany
- Gynaecology Research Unit, Hannover Medical School, Hamburg, Germany
- N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus
| | - Stig E Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, Copenhagen, Denmark
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Helen Byers
- North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Nicola Camp
- Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt lake city, UT, USA
| | - Jose Castelao
- Oncology and Genetics Unit, Instituto de Investigación Sanitaria Galicia Sur (IISGS), Xerencia de Xestion Integrada de Vigo-SERGAS, Vigo, Spain
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | | | - Wendy Chung
- Departments of Pediatrics and Medicine, Columbia University, New York, NY, USA
| | - Christine Clarke
- Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia
| | - Margriet J Collee
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, Netherlands
| | - Sarah Colonna
- Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt lake city, UT, USA
| | - Fergus Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Angela Cox
- Department of Oncology and Metabolism, Sheffield Institute for Nucleic Acids (SInFoNiA), University of Sheffield, Sheffield, UK
| | - Simon S Cross
- Academic Unit of Pathology, Department of Neuroscience, University of Sheffield, Sheffield, UK
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mary Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Peter Devilee
- Department of Pathology, Leiden University Medical Center, Leiden, Netherlands
- Department of Human Genetics, Leiden University Medical, Leiden, Netherlands
| | - Thilo Dork
- Gynaecology Research Unit, Hannover Medical School, Hamburg, Germany
| | - Laure Dossus
- Nutrition and Metabolism Section, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Diana M Eccles
- Cancer Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - A Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Gareth Evans
- North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Peter Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Olivia Fletcher
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - Henrik Flyger
- Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Lin Fritschi
- School of Population Health, Curtin University, Perth, Western Australia, Australia
| | - Marike Gabrielson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Manuela Gago-Dominguez
- Genomic Medicine Group, International Cancer Genetics and Epidemiology Group, Fundación Pública Galega de Medicina Xenómica, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela, Spain
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Jeanine Genkinger
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, New York, New York, USA
| | - Graham G Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Mark Goldberg
- Department of Medicine, McGill University, Montreal, Quebec, Canada
- Division of Clinical Epidemiology, Royal Victoria Hospital, McGill University, Montreal, QU, Canada
| | - Pascal Guénel
- Team 'Exposome and Heredity', CESP, Gustave Roussy, INSERM, University Paris-Saclay, UVSQ, Villejuif, France
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Wei He
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Peter Hillemanns
- Gynaecology Research Unit, Hannover Medical School, Hamburg, Germany
| | | | - Reiner Hoppe
- Dr Margarete Fischer Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tubingen, Germany
| | - John Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Simona Jakovchevska
- Research Centre for Genetic Engineering and Biotechnology 'Georgi D. Efremov', Skopje, North Macedonia
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
- Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University, Szczecin, Poland
| | - Helena Jernström
- Oncology, Department of Clinical Sciences in Lund, Lund University, Lund, Sweden
| | - Esther John
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine, Division of Oncology, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Nichola Johnson
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - Michael Jones
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, UK
| | - Joseph Vijai
- Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Clinical Genetics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Elza Khusnutdinova
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia
- Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa, Russia
| | - Cari Kitahara
- Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Stella Koutros
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Vessela Kristensen
- Institute of Clinical Medicine, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Allison W Kurian
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine, Division of Oncology, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - James Lacey
- Department of Computational and Quantitative Medicine, City of Hope, Duarte, CA, USA
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, USA
| | - Diether Lambrechts
- Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium
- VIB Center for Cancer Biology, VIB, Leuven, Belgium
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Flavio Lejbkowicz
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Haifa, Israel
| | - Annika Lindblom
- Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | | | - Adriana Lori
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Jan Lubinski
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Arto Mannermaa
- Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
- Biobank of Eastern Finland, Kuopio University Hospital, Kuopio, Finland
| | - Mehdi Manoochehri
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Dimitrios Mavroudis
- Department of Medical Oncology, University Hospital of Heraklion, Heraklion, Greece
| | - Usha Menon
- MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College, London, UK
| | - AnnaMarie Mulligan
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
- Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada
| | - Rachel Murphy
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
- Cancer Control Research, BC Cancer Agency, Vancouver, BC, Canada
| | - Ines Nevelsteen
- Leuven Multidisciplinary Breast Center, Department of Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium
| | - William G Newman
- North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Nadia Obi
- Institute for Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Katie O'Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Ken Offit
- Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Clinical Genetics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Andrew Olshan
- Department of Epidemiology, Gillings School of Global Public Health and UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Janet Olson
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN, USA
| | - Salvatore Panico
- Dipertimento Di Medicina Clinca e Chirurgia, Federico II University, Naples, Italy
| | | | - Alpa Patel
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Paolo Peterlongo
- Genome Diagnostics Program, IFOM ETS - the AIRC Institute of Molecular Oncology, Milan, Italy
| | - Brigitte Rack
- Department of Gynaecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Milan, Italy
| | - Gad Rennert
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Haifa, Israel
| | - Valerie Rhenius
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Atocha Romero
- Laboratorio de Oncología Molecular, Hospital Clínico San Carlos, Madrid, Spain
| | | | - Dale Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Marjanka K Schmidt
- Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, Netherlands
- Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, Netherlands
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Lukas Schwentner
- Department of Gynaecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Priyanka Sharma
- Department of Internal Medicine, Division of Medical Oncology, University of Kansas Medical Center, Westwood, KS, USA
| | - Jacques Simard
- Genomics Center, Molecular Medicine, Université Laval, Quebec, Quebec, Canada
| | - Melissa Southey
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jennifer Stone
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Genetic Epidemiology Group, School of Population and Global Health, University of Western Australia, Perth, Western Australia, Australia
| | - William J Tapper
- Cancer Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Jack Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
- Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Lauren Teras
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Amanda E Toland
- Department of Cancer Biology and Genetics, The Ohio State University, Columbus, OH, USA
| | - Melissa Troester
- Department of Epidemiology, Gillings School of Global Public Health and UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Thérèse Truong
- Team 'Exposome and Heredity', CESP, Gustave Roussy, INSERM, University Paris-Saclay, UVSQ, Villejuif, France
| | | | - Clarice Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Camilla Wendt
- Department of Clinical Science and Education, Karolinska Institutet, Stockholm, Sweden
| | - Xiaohong Rose Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Argyrios Ziogas
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Paul Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, West Hollywood, CA, USA
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Shay Ben-Sachar
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Clalit Research Institute, Clalit Health Services, Ramat Gan, Israel
| | - Naama Elefant
- Clalit Research Institute, Clalit Health Services, Ramat Gan, Israel
- Department of Genetics, Hadassah Medical Center, Jerusalem, Israel
| | - Ron Shamir
- The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
| | - Ran Elkon
- Department of Human Molecular Genetics and Biochemistry, Tel Aviv University, Tel Aviv, Israel
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242
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Heyne HO, Pajuste FD, Wanner J, Onwuchekwa JID, Mägi R, Palotie A, Kälviainen R, Daly MJ. Polygenic risk scores as a marker for epilepsy risk across lifetime and after unspecified seizure events. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.27.23297542. [PMID: 38076931 PMCID: PMC10705659 DOI: 10.1101/2023.11.27.23297542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
A diagnosis of epilepsy has significant consequences for an individual but is often challenging in clinical practice. Novel biomarkers are thus greatly needed. Here, we investigated how common genetic factors (epilepsy polygenic risk scores, [PRSs]) influence epilepsy risk in detailed longitudinal electronic health records (EHRs) of > 360k Finns spanning up to 50 years of individuals' lifetimes. Individuals with a high genetic generalized epilepsy PRS (PRSGGE) in FinnGen had an increased risk for genetic generalized epilepsy (GGE) (hazard ratio [HR] 1.55 per PRSGGE standard deviation [SD]) across their lifetime and after unspecified seizure events. Effect sizes of epilepsy PRSs were comparable to effect sizes in clinically curated data supporting our EHR-derived epilepsy diagnoses. Within 10 years after an unspecified seizure, the GGE rate was 37% when PRSGGE > 2 SD compared to 5.6% when PRSGGE < -2 SD. The effect of PRSGGE was even larger on GGE subtypes of idiopathic generalized epilepsy (IGE) (HR 2.1 per SD PRSGGE). We further report significantly larger effects of PRSGGE on epilepsy in females and in younger age groups. Analogously, we found significant but more modest focal epilepsy PRS burden associated with non-acquired focal epilepsy (NAFE). We found PRSGGE specifically associated with GGE in comparison with >2000 independent diseases while PRSNAFE was also associated with other diseases than NAFE such as back pain. Here, we show that epilepsy specific PRSs have good discriminative ability after a first seizure event i.e. in circumstances where the prior probability of epilepsy is high outlining a potential to serve as biomarkers for an epilepsy diagnosis.
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Affiliation(s)
- Henrike O Heyne
- Hasso Plattner Institute for Digital Engineering, University of Potsdam, Germany
- Hasso Plattner Institute, Mount Sinai School of Medicine, NY, US
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
- Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Fanny-Dhelia Pajuste
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Julian Wanner
- Hasso Plattner Institute for Digital Engineering, University of Potsdam, Germany
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
| | - Jennifer I Daniel Onwuchekwa
- Hasso Plattner Institute for Digital Engineering, University of Potsdam, Germany
- Faculty of Life Sciences, University of Siegen, Germany
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Aarno Palotie
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
- Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Reetta Kälviainen
- Kuopio Epilepsy Center, Neurocenter, Kuopio University Hospital, Member of ERN EpiCARE, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Mark J Daly
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
- Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
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243
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Khanna NN, Singh M, Maindarkar M, Kumar A, Johri AM, Mentella L, Laird JR, Paraskevas KI, Ruzsa Z, Singh N, Kalra MK, Fernandes JFE, Chaturvedi S, Nicolaides A, Rathore V, Singh I, Teji JS, Al-Maini M, Isenovic ER, Viswanathan V, Khanna P, Fouda MM, Saba L, Suri JS. Polygenic Risk Score for Cardiovascular Diseases in Artificial Intelligence Paradigm: A Review. J Korean Med Sci 2023; 38:e395. [PMID: 38013648 PMCID: PMC10681845 DOI: 10.3346/jkms.2023.38.e395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 10/15/2023] [Indexed: 11/29/2023] Open
Abstract
Cardiovascular disease (CVD) related mortality and morbidity heavily strain society. The relationship between external risk factors and our genetics have not been well established. It is widely acknowledged that environmental influence and individual behaviours play a significant role in CVD vulnerability, leading to the development of polygenic risk scores (PRS). We employed the PRISMA search method to locate pertinent research and literature to extensively review artificial intelligence (AI)-based PRS models for CVD risk prediction. Furthermore, we analyzed and compared conventional vs. AI-based solutions for PRS. We summarized the recent advances in our understanding of the use of AI-based PRS for risk prediction of CVD. Our study proposes three hypotheses: i) Multiple genetic variations and risk factors can be incorporated into AI-based PRS to improve the accuracy of CVD risk predicting. ii) AI-based PRS for CVD circumvents the drawbacks of conventional PRS calculators by incorporating a larger variety of genetic and non-genetic components, allowing for more precise and individualised risk estimations. iii) Using AI approaches, it is possible to significantly reduce the dimensionality of huge genomic datasets, resulting in more accurate and effective disease risk prediction models. Our study highlighted that the AI-PRS model outperformed traditional PRS calculators in predicting CVD risk. Furthermore, using AI-based methods to calculate PRS may increase the precision of risk predictions for CVD and have significant ramifications for individualized prevention and treatment plans.
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Affiliation(s)
- Narendra N Khanna
- Department of Cardiology, Indraprastha APOLLO Hospitals, New Delhi, India
- Asia Pacific Vascular Society, New Delhi, India
| | - Manasvi Singh
- Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA
- Bennett University, Greater Noida, India
| | - Mahesh Maindarkar
- Asia Pacific Vascular Society, New Delhi, India
- Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA
- School of Bioengineering Sciences and Research, Maharashtra Institute of Technology's Art, Design and Technology University, Pune, India
| | | | - Amer M Johri
- Department of Medicine, Division of Cardiology, Queen's University, Kingston, Canada
| | - Laura Mentella
- Department of Medicine, Division of Cardiology, University of Toronto, Toronto, Canada
| | - John R Laird
- Heart and Vascular Institute, Adventist Health St. Helena, St. Helena, CA, USA
| | | | - Zoltan Ruzsa
- Invasive Cardiology Division, University of Szeged, Szeged, Hungary
| | - Narpinder Singh
- Department of Food Science and Technology, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India
| | | | | | - Seemant Chaturvedi
- Department of Neurology & Stroke Program, University of Maryland, Baltimore, MD, USA
| | - Andrew Nicolaides
- Vascular Screening and Diagnostic Centre and University of Nicosia Medical School, Cyprus
| | - Vijay Rathore
- Nephrology Department, Kaiser Permanente, Sacramento, CA, USA
| | - Inder Singh
- Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA
| | - Jagjit S Teji
- Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - Mostafa Al-Maini
- Allergy, Clinical Immunology and Rheumatology Institute, Toronto, ON, Canada
| | - Esma R Isenovic
- Department of Radiobiology and Molecular Genetics, National Institute of The Republic of Serbia, University of Belgrade, Beograd, Serbia
| | | | - Puneet Khanna
- Department of Anaesthesiology, AIIMS, New Delhi, India
| | - Mostafa M Fouda
- Department of Electrical and Computer Engineering, Idaho State University, Pocatello, ID, USA
| | - Luca Saba
- Department of Radiology, Azienda Ospedaliero Universitaria, Cagliari, Italy
| | - Jasjit S Suri
- Asia Pacific Vascular Society, New Delhi, India
- Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA
- Department of Computer Engineering, Graphic Era Deemed to be University, Dehradun, India.
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244
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Bhattacharya R, Chen N, Shim I, Kuwahara H, Gao X, Alkuraya FS, Fahed AC. Massive underrepresentation of Arabs in genomic studies of common disease. Genome Med 2023; 15:99. [PMID: 37993966 PMCID: PMC10664351 DOI: 10.1186/s13073-023-01254-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 11/08/2023] [Indexed: 11/24/2023] Open
Abstract
Arabs represent 5% of the world population and have a high prevalence of common disease, yet remain greatly underrepresented in genome-wide association studies, where only 1 in 600 individuals are Arab. We highlight the persistent and unaddressed underrepresentation of Arabs in genomic databases and discuss its impact on public health genomics and missed opportunities for biological discovery.
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Affiliation(s)
- Romit Bhattacharya
- Department of Medicine, Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street | CPZN 3.128, Boston, MA, 02114, USA
- Department of Medicine, Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - NingNing Chen
- Computational Biosciences Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia
| | - Injeong Shim
- Department of Medicine, Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Digital Health, Samsung Medical Center, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of South Korea
| | - Hiroyuki Kuwahara
- Computational Biosciences Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia
| | - Xin Gao
- Computational Biosciences Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia
| | - Fowzan S Alkuraya
- Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Kingdom of Saudi Arabia.
| | - Akl C Fahed
- Department of Medicine, Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street | CPZN 3.128, Boston, MA, 02114, USA.
- Department of Medicine, Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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245
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Jain PR, Burch M, Martinez M, Mir P, Fichna JP, Zekanowski C, Rizzo R, Tümer Z, Barta C, Yannaki E, Stamatoyannopoulos J, Drineas P, Paschou P. Can polygenic risk scores help explain disease prevalence differences around the world? A worldwide investigation. BMC Genom Data 2023; 24:70. [PMID: 37986041 PMCID: PMC10662565 DOI: 10.1186/s12863-023-01168-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 10/20/2023] [Indexed: 11/22/2023] Open
Abstract
Complex disorders are caused by a combination of genetic, environmental and lifestyle factors, and their prevalence can vary greatly across different populations. The extent to which genetic risk, as identified by Genome Wide Association Study (GWAS), correlates to disease prevalence in different populations has not been investigated systematically. Here, we studied 14 different complex disorders and explored whether polygenic risk scores (PRS) based on current GWAS correlate to disease prevalence within Europe and around the world. A clear variation in GWAS-based genetic risk was observed based on ancestry and we identified populations that have a higher genetic liability for developing certain disorders. We found that for four out of the 14 studied disorders, PRS significantly correlates to disease prevalence within Europe. We also found significant correlations between worldwide disease prevalence and PRS for eight of the studied disorders with Multiple Sclerosis genetic risk having the highest correlation to disease prevalence. Based on current GWAS results, the across population differences in genetic risk for certain disorders can potentially be used to understand differences in disease prevalence and identify populations with the highest genetic liability. The study highlights both the limitations of PRS based on current GWAS but also the fact that in some cases, PRS may already have high predictive power. This could be due to the genetic architecture of specific disorders or increased GWAS power in some cases.
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Affiliation(s)
- Pritesh R Jain
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Myson Burch
- Department of Computer Sciences, Purdue University, West Lafayette, IN, USA
| | - Melanie Martinez
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Pablo Mir
- Unidad de Trastornos del Movimiento, Instituto de Biomedicina de Sevilla (IBiS). Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Jakub P Fichna
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
- Department of Neurogenetics and Functional Genomics, Mossakowski Medical Research Institute, Polish Academy of Sciences, Warsaw, Poland
| | - Cezary Zekanowski
- Department of Neurogenetics and Functional Genomics, Mossakowski Medical Research Institute, Polish Academy of Sciences, Warsaw, Poland
| | - Renata Rizzo
- Child and Adolescent Neurology and Psychiatry, Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy
| | - Zeynep Tümer
- Department of Clinical Genetics, Kennedy Center, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Csaba Barta
- Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, Budapest, Hungary
| | - Evangelia Yannaki
- Hematology Department- Hematopoietic Cell Transplantation Unit, Gene and Cell Therapy Center, George Papanikolaou Hospital, Thessaloniki, Greece
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Stamatoyannopoulos
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Department of Medicine, Division of Oncology, University of Washington, Seattle, WA, USA
| | - Petros Drineas
- Department of Computer Sciences, Purdue University, West Lafayette, IN, USA
| | - Peristera Paschou
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA.
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246
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Mbuya-Bienge C, Pashayan N, Kazemali CD, Lapointe J, Simard J, Nabi H. A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population. Cancers (Basel) 2023; 15:5380. [PMID: 38001640 PMCID: PMC10670420 DOI: 10.3390/cancers15225380] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/26/2023] [Accepted: 11/03/2023] [Indexed: 11/26/2023] Open
Abstract
Single nucleotide polymorphisms (SNPs) in the form of a polygenic risk score (PRS) have emerged as a promising factor that could improve the predictive performance of breast cancer (BC) risk prediction tools. This study aims to appraise and critically assess the current evidence on these tools. Studies were identified using Medline, EMBASE and the Cochrane Library up to November 2022 and were included if they described the development and/ or validation of a BC risk prediction model using a PRS for women of the general population and if they reported a measure of predictive performance. We identified 37 articles, of which 29 combined genetic and non-genetic risk factors using seven different risk prediction tools. Most models (55.0%) were developed on populations from European ancestry and performed better than those developed on populations from other ancestry groups. Regardless of the number of SNPs in each PRS, models combining a PRS with genetic and non-genetic risk factors generally had better discriminatory accuracy (AUC from 0.52 to 0.77) than those using a PRS alone (AUC from 0.48 to 0.68). The overall risk of bias was considered low in most studies. BC risk prediction tools combining a PRS with genetic and non-genetic risk factors provided better discriminative accuracy than either used alone. Further studies are needed to cross-compare their clinical utility and readiness for implementation in public health practices.
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Affiliation(s)
- Cynthia Mbuya-Bienge
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Nora Pashayan
- Department of Applied Health Research, University College London, London WC1E 6BT, UK;
| | - Cornelia D. Kazemali
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Julie Lapointe
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Jacques Simard
- Endocrinology and Nephology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1V 4G2, Canada;
- Department of Molecular Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada
| | - Hermann Nabi
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
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247
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Liu T, Li C, Zhang R, Millender EF, Miao H, Ormsbee M, Guo J, Westbrook A, Pan Y, Wang J, Kelly TN. A longitudinal study of polygenic score and cognitive function decline considering baseline cognitive function, lifestyle behaviors, and diabetes among middle-aged and older US adults. Alzheimers Res Ther 2023; 15:196. [PMID: 37950263 PMCID: PMC10636974 DOI: 10.1186/s13195-023-01343-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 10/25/2023] [Indexed: 11/12/2023]
Abstract
BACKGROUND Genomic study of cognition decline while considering baseline cognition and lifestyle behaviors is scarce. We aimed to evaluate the impact of a polygenic score for general cognition on cognition decline rate, while considering baseline cognition and lifestyle behaviors, among the general population and people with diabetes, a patient group commonly affected by cognition impairment. METHODS We tested associations of the polygenic score for general cognition with annual changing rates of cognition measures in 8 years of follow-up among 12,090 White and 3100 Black participants of the Health and Retirement Study (HRS), a nationally representative sample of adults aged 50 years and older in the USA. Cognition measures including word recall, mental status, and total cognitive score were measured biannually. To maximize sample size and length of follow-up, we treated the 2010 wave of survey as baseline, and follow-up data until 2018 were analyzed. Baseline lifestyle behaviors, APOE status, and measured cognition were sequentially adjusted. Given racial differences in polygenic score, all analyses were conducted by race. RESULTS The polygenic score was significantly associated with annual changing rates of all cognition measures independent of lifestyle behaviors and APOE status. Together with age and sex, the polygenic score explained 29.9%, 15.9%, and 26.5% variances of annual changing rates of word recall, mental status, and total cognitive scores among Whites and explained 17.2%, 13.9%, and 18.7% variance of the three traits among Blacks. Among both White and Black participants, those in the top quartile of polygenic score had the three cognition measures increased annually, while those in the bottom quartile had the three cognition measures decreased annually. After further adjusting for the average cognition assessed in 3 visits around baseline, the polygenic score was still positively associated with annual changing rates of all cognition measures for White (P ≤ 2.89E - 19) but not for Black (P ≥ 0.07) participants. In addition, among participants with diabetes, physical activity offset the genetic susceptibility to decline of mental status (interaction P ≤ 0.01) and total cognitive scores (interaction P = 0.03). CONCLUSIONS Polygenic score predicted cognition changes in addition to measured cognition. Physical activity offset genetic risk for cognition decline among diabetes patients.
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Affiliation(s)
- Tingting Liu
- College of Nursing, Florida State University, Tallahassee, FL, 32306, USA
| | - Changwei Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street Suite 2000, New Orleans, LA, 70112, USA.
| | - Ruiyuan Zhang
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street Suite 2000, New Orleans, LA, 70112, USA
| | - Eugenia Flores Millender
- College of Nursing, Florida State University, Tallahassee, FL, 32306, USA
- Center of Population Sciences for Health Equity, Florida State University College of Nursing, Tallahassee, FL, 32306, USA
| | - Hongyu Miao
- College of Nursing, Florida State University, Tallahassee, FL, 32306, USA
| | - Michael Ormsbee
- Institute of Sports Sciences and Medicine, Florida State University, Tallahassee, FL, 32306, USA
| | - Jinzhen Guo
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Adrianna Westbrook
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Yang Pan
- Division of Nephrology, Department of Medicine, University of Illinois at Chicago, Chicago, IL, 60612, USA
| | - Jing Wang
- College of Nursing, Florida State University, Tallahassee, FL, 32306, USA
| | - Tanika N Kelly
- Division of Nephrology, Department of Medicine, University of Illinois at Chicago, Chicago, IL, 60612, USA
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248
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Kim DJ, Kang JH, Kim JW, Cheon MJ, Kim SB, Lee YK, Lee BC. Evaluation of optimal methods and ancestries for calculating polygenic risk scores in East Asian population. Sci Rep 2023; 13:19195. [PMID: 37932343 PMCID: PMC10628155 DOI: 10.1038/s41598-023-45859-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 10/25/2023] [Indexed: 11/08/2023] Open
Abstract
Polygenic risk scores (PRSs) have been studied for predicting human diseases, and various methods for PRS calculation have been developed. Most PRS studies to date have focused on European ancestry, and the performance of PRS has not been sufficiently assessed in East Asia. Herein, we evaluated the predictive performance of PRSs for East Asian populations under various conditions. Simulation studies using data from the Korean cohort, Health Examinees (HEXA), demonstrated that SBayesRC and PRS-CS outperformed other PRS methods (lassosum, LDpred-funct, and PRSice) in high fixed heritability (0.3 and 0.7). In addition, we generated PRSs using real-world data from HEXA for ten diseases: asthma, breast cancer, cataract, coronary artery disease, gastric cancer, glaucoma, hyperthyroidism, hypothyroidism, osteoporosis, and type 2 diabetes (T2D). We utilized the five previous PRS methods and genome-wide association study (GWAS) data from two biobank-scale datasets [European (UK Biobank) and East Asian (BioBank Japan) ancestry]. Additionally, we employed PRS-CSx, a PRS method that combines GWAS data from both ancestries, to generate a total of 110 PRS for ten diseases. Similar to the simulation results, SBayesRC showed better predictive performance for disease risk than the other methods. Furthermore, the East Asian GWAS data outperformed those from European ancestry for breast cancer, cataract, gastric cancer, and T2D, but neither of the two GWAS ancestries showed a significant advantage on PRS performance for the remaining six diseases. Based on simulation data and real data studies, it is expected that SBayesRC will offer superior performance for East Asian populations, and PRS generated using GWAS from non-East Asian may also yield good results.
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Palmer JR, Cozier YC, Rosenberg L. Research on Health Disparities: Strategies and Findings From the Black Women's Health Study. Am J Epidemiol 2023; 192:1806-1810. [PMID: 35136921 PMCID: PMC11004793 DOI: 10.1093/aje/kwac022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 01/24/2022] [Accepted: 02/01/2022] [Indexed: 01/10/2023] Open
Abstract
The American Journal of Epidemiology has been a platform for findings from the Black Women's Health Study (BWHS) that are relevant to health disparities. Topics addressed have included methods of follow-up of a large cohort of Black women, disparities in health-care delivery, modifiable risk factors for health conditions that disproportionately affect Black women, associations with exposures that are highly prevalent in Black women, and methods for genetic research. BWHS papers have also highlighted the importance of considering social context, including perceived experiences of racism, in understanding health disparities. In the future, BWHS investigators will contribute to documentation of the role that structural racism plays in health disparities.
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Affiliation(s)
| | | | - Lynn Rosenberg
- Correspondence to Dr. Lynn Rosenberg, Slone Epidemiology Center at Boston University, 72 East Concord Street L7, Boston, MA 02118 (e-mail: )
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250
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Tanigawa Y, Kellis M. Power of inclusion: Enhancing polygenic prediction with admixed individuals. Am J Hum Genet 2023; 110:1888-1902. [PMID: 37890495 PMCID: PMC10645553 DOI: 10.1016/j.ajhg.2023.09.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 09/22/2023] [Accepted: 09/22/2023] [Indexed: 10/29/2023] Open
Abstract
Admixed individuals offer unique opportunities for addressing limited transferability in polygenic scores (PGSs), given the substantial trans-ancestry genetic correlation in many complex traits. However, they are rarely considered in PGS training, given the challenges in representing ancestry-matched linkage-disequilibrium reference panels for admixed individuals. Here we present inclusive PGS (iPGS), which captures ancestry-shared genetic effects by finding the exact solution for penalized regression on individual-level data and is thus naturally applicable to admixed individuals. We validate our approach in a simulation study across 33 configurations with varying heritability, polygenicity, and ancestry composition in the training set. When iPGS is applied to n = 237,055 ancestry-diverse individuals in the UK Biobank, it shows the greatest improvements in Africans by 48.9% on average across 60 quantitative traits and up to 50-fold improvements for some traits (neutrophil count, R2 = 0.058) over the baseline model trained on the same number of European individuals. When we allowed iPGS to use n = 284,661 individuals, we observed an average improvement of 60.8% for African, 11.6% for South Asian, 7.3% for non-British White, 4.8% for White British, and 17.8% for the other individuals. We further developed iPGS+refit to jointly model the ancestry-shared and -dependent genetic effects when heterogeneous genetic associations were present. For neutrophil count, for example, iPGS+refit showed the highest predictive performance in the African group (R2 = 0.115), which exceeds the best predictive performance for the White British group (R2 = 0.090 in the iPGS model), even though only 1.49% of individuals used in the iPGS training are of African ancestry. Our results indicate the power of including diverse individuals for developing more equitable PGS models.
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Affiliation(s)
- Yosuke Tanigawa
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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