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Bragazzi NL, Zhang L, Omarov M, Georgakis MK. Genetic Risk Scores in Stroke Research and Care. Stroke 2025. [PMID: 40396275 DOI: 10.1161/strokeaha.125.050961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2025]
Abstract
Stroke remains a leading cause of death and disability worldwide. While well-established risk factors play a major role, genetic predisposition is a crucial determinant of stroke susceptibility, with heritability estimates up to 39% for ischemic stroke and 29% for intracerebral hemorrhage. Advances in next-generation sequencing and genome-wide association studies have identified numerous genetic loci associated with stroke risk, paving the way for the development of genetic risk scores. These scores aggregate information from multiple genetic variants to estimate an individual's stroke risk, offering a promising tool for personalized risk stratification that complements traditional clinical models. While GRSs have demonstrated strong predictive potential for primary stroke events in population-based settings, their integration into clinical practice remains limited. Emerging evidence suggests that GRSs could add value in clinical decision-making, for instance, for stratifying ischemic stroke risk in patients with atrial fibrillation, assessing intracerebral hemorrhage risk in anticoagulant users, and predicting vascular risk factor control in stroke survivors. The incorporation of GRSs with multiomics data and machine learning may further refine risk assessment, driving personalized prevention strategies for both primary and secondary stroke preventions. A major challenge is the limited applicability of GRS across diverse populations, as most genome-wide association studies have been conducted in individuals of European ancestry. Addressing this limitation is critical for ensuring equitable and effective implementation of GRSs in clinical settings. As methodologies continue to evolve, integrating GRS into stroke research could significantly enhance risk assessment and support precision medicine approaches tailored to individual patients.
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Affiliation(s)
- Nicola Luigi Bragazzi
- Institute for Stroke and Dementia Research, LMU University Hospital, LMU Munich, Germany (N.L.B., L.Z., M.O., M.K.G.)
| | - Lanyue Zhang
- Institute for Stroke and Dementia Research, LMU University Hospital, LMU Munich, Germany (N.L.B., L.Z., M.O., M.K.G.)
| | - Murad Omarov
- Institute for Stroke and Dementia Research, LMU University Hospital, LMU Munich, Germany (N.L.B., L.Z., M.O., M.K.G.)
| | - Marios K Georgakis
- Institute for Stroke and Dementia Research, LMU University Hospital, LMU Munich, Germany (N.L.B., L.Z., M.O., M.K.G.)
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (M.K.G.)
- Munich Cluster for Systems Neurology, Germany (M.K.G.)
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2
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Riglea T, Dessy T, Kalubi J, Goulet D, Ikwa Ndol Mbutiwi F, Williams SM, Engert JC, Chen HY, O'Loughlin J, Sylvestre MP. Body mass index modifies genetic susceptibility to high systolic blood pressure in adolescents and young adults: results from an 18-year longitudinal study. J Hum Hypertens 2025; 39:334-342. [PMID: 40089570 DOI: 10.1038/s41371-025-01003-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2024] [Revised: 02/07/2025] [Accepted: 02/27/2025] [Indexed: 03/17/2025]
Abstract
Genome-wide association studies (GWAS) in adults have identified single nucleotide polymorphisms (SNPs) associated with systolic blood pressure (SBP), but it is unclear whether the findings apply in youth. Further, the role of body mass index (BMI) in these associations is understudied. Our objective was to determine whether BMI modifies genetic susceptibility to high SBP in young people. The sample comprised 714 participants of European ancestry recruited in 1999-2000 from 10 Montreal-area high schools for a longitudinal study. SBP was measured at ages 12, 15, 17, 24, and 30. Blood and saliva samples were collected at ages 14, 20, and 25. Two evidence-based genetic risk scores (GRS) were constructed based on GWAS results in adults: GRS22 used 22 SNPs and GRS182 added 160 additional SNPs to GRS22. Sex-specific associations between each GRS and repeated measures of SBP were estimated using linear mixed models including BMI and a GRS*BMI product term. GRS182 explained a greater proportion of SBP variance than GRS22, and a greater proportion in females than males. The associations increased monotonically with BMI values between 22 kg/m2 and 35 kg/m2. Results indicate that BMI modifies the association between a GRS and SBP levels from adolescence to adulthood.
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Affiliation(s)
- Teodora Riglea
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CrCHUM), Montréal, QC, Canada
- Department of Social and Preventive Medicine, Université de Montréal, Montréal, QC, Canada
| | - Tatiana Dessy
- Department of Social and Preventive Medicine, Université de Montréal, Montréal, QC, Canada
- Montreal Heart Institute, Montréal, QC, Canada
- Centre de Pharmacogénomique Beaulieu-Saucier de l'Université de Montréal, Montréal, QC, Canada
| | - Jodi Kalubi
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CrCHUM), Montréal, QC, Canada
- Department of Social and Preventive Medicine, Université de Montréal, Montréal, QC, Canada
- Centre de recherche en santé publique (CReSP), Université de Montréal & CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montreal, QC, Canada
| | - Danick Goulet
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
| | - Fiston Ikwa Ndol Mbutiwi
- Department of Social and Preventive Medicine, Université de Montréal, Montréal, QC, Canada
- Faculty of Medicine, University of Kikwit, Kikwit, Democratic Republic of the Congo
| | - Scott M Williams
- Case Western Reserve University School of Medicine Department of Population and Quantitative Health Sciences, Cleveland, OH, USA
- Cleveland Institute for Computational Biology, Cleveland, OH, USA
| | - James C Engert
- McGill University Department of Medicine, Montréal, QC, Canada
- McGill University Department of Human Genetics, Montréal, QC, Canada
| | - Hao Yu Chen
- McGill University Department of Medicine, Montréal, QC, Canada
| | - Jennifer O'Loughlin
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CrCHUM), Montréal, QC, Canada
- Department of Social and Preventive Medicine, Université de Montréal, Montréal, QC, Canada
| | - Marie-Pierre Sylvestre
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CrCHUM), Montréal, QC, Canada.
- Department of Social and Preventive Medicine, Université de Montréal, Montréal, QC, Canada.
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3
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Lo YC, Tian H, Chan TF, Jeon S, Alatorre K, Dinh BL, 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 BMI and Type II diabetes in the Native Hawaiian population. Commun Biol 2025; 8:651. [PMID: 40269120 PMCID: PMC12018950 DOI: 10.1038/s42003-025-08050-7] [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: 08/23/2024] [Accepted: 04/07/2025] [Indexed: 04/25/2025] Open
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. In particular, for body mass index (BMI) and type-2 diabetes (T2D), Polynesian-ancestry individuals such as Native Hawaiians or Samoans exhibit varied distribution from other continental populations, but are understudied, particularly in the context of PGS. Using BMI and T2D as examples of metabolic traits of importance to Polynesian populations (along with height as a comparison of a similarly highly polygenic trait), here we examine the prediction accuracies of PGS models in a large Native Hawaiian sample from the Multiethnic Cohort with up to 5300 individuals. We find evidence of lowered prediction accuracies for the PGS models in some cases, particularly for height. We also find that using the Native Hawaiian samples as an optimization cohort during training does not consistently improve PGS performance. Moreover, even the best-performing PGS models among Native Hawaiians 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
| | - He Tian
- 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
| | - Kimberli Alatorre
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Bryan L Dinh
- 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
| | | | - 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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Zhu X, Ventura EF, Bansal S, Wijeyesekera A, Vimaleswaran KS. Integrating genetics, metabolites, and clinical characteristics in predicting cardiometabolic health outcomes using machine learning algorithms - A systematic review. Comput Biol Med 2025; 186:109661. [PMID: 39799831 DOI: 10.1016/j.compbiomed.2025.109661] [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: 04/14/2024] [Revised: 01/02/2025] [Accepted: 01/06/2025] [Indexed: 01/15/2025]
Abstract
BACKGROUND Machine learning (ML) integration of clinical, metabolite, and genetic data reveals variable results in predicting cardiometabolic health (CMH) outcomes. Therefore, we aim to (1) evaluate whether a multi-modal approach incorporating all three data types using ML algorithms can improve CMH outcome prediction compared to single-modal or paired-modal models, and (2) compare the methodologies used in existing prediction models. METHODS We systematically searched five databases from 1998 to 2024 for ML predictive modelling studies using the multi-modal approach for CMH outcomes. Risk-of-bias assessment tools were used to assess methodological quality. Study characteristics, ML algorithms, data preprocessing, evaluation methods and metrics, feature selections, and feature importance parameters were synthesized narratively to show methodological heterogeneity. RESULTS Of the four included studies (3 ML algorithms), three were at low risk of bias, and one was at high risk. The multi-modal approach consistently improved T2D and BP prediction compared to single-modal or paired-modal models. Genetics showed the lowest predictive performance in three studies. Logistic regression (n = 2 studies) and random forest (n = 1) were used in T2D studies, while XGBoost was used in one BP study. One study with missing data and variations in feature selection across all studies hindered a comprehensive comparison of feature importance. CONCLUSIONS Our review emphasizes the potential improvement in T2D and BP prediction using ML algorithms with the multi-modal approach. However, further studies using diverse ML algorithms with optimized methodologies on single-modal, paired-modal, and multi-modal models are needed to gain insights into biomarker selection for predicting CMH outcomes.
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Affiliation(s)
- Xianyu Zhu
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, RG6 6DZ, UK
| | - Eduard F Ventura
- Institute of Agrochemistry and Food Technology-National Research Council (IATA-CSIC), Department of Biotechnology, Av. Agustin Escardino 7, 46980, Valencia, Spain
| | - Sakshi Bansal
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, RG6 6DZ, UK
| | - Anisha Wijeyesekera
- Food Microbial Sciences Unit, Department of Food and Nutritional Sciences, School of Chemistry, Food and Pharmacy, University of Reading, Reading, RG6 6DZ, UK
| | - Karani S Vimaleswaran
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, RG6 6DZ, UK; Institute for Food, Nutrition and Health (IFNH), University of Reading, Reading, RG6 6AH, UK.
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Drzymalla E, Raffield L, Kolor K, Koyama A, Moonesinghe R, Pavkov ME, Spracklen CN, Khoury MJ. Additive Value of Polygenic Risk Score to Family History for Type 2 Diabetes Prediction: Results From the All of Us Research Database. Diabetes Care 2025; 48:212-219. [PMID: 39841967 PMCID: PMC11770167 DOI: 10.2337/dc24-1537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2024] [Accepted: 10/28/2024] [Indexed: 01/24/2025]
Abstract
OBJECTIVE The goal of this study was to assess the additive value of considering type 2 diabetes (T2D) polygenic risk score (PRS) in addition to family history for T2D prediction. RESEARCH DESIGN AND METHODS Data were obtained from the All of Us (AoU) research database. First-degree T2D family history was self-reported on the personal family history health questionnaire. A PRS was constructed from 1,289 variants identified from a large multiancestry genome-wide association study meta-analysis for T2D. Logistic regression models were run to generate odds ratios (ORs) and 95% CIs for T2D. All models were adjusted for age, sex, and BMI. RESULTS A total of 109,958 AoU research participants were included in the analysis. The odds of T2D increased with 1 SD PRS (OR 1.75; 95% CI 1.71-1.79) and positive T2D family history (OR 2.32; 95% CI 2.20-2.43). In the joint model, both 1 SD PRS (OR 1.69; 95% CI 1.65-1.72) and family history (OR 2.06; 95% CI 1.98-2.15) were significantly associated with T2D, although the ORs were slightly attenuated. Predictive models that included both the PRS and family history (area under the curve [AUC] 0.794) performed better than models including only family history (AUC 0.763) or the PRS (AUC 0.785). CONCLUSIONS In predicting T2D, inclusion of a T2D PRS in addition to family history of T2D (first-degree relatives) added statistical value. Further study is needed to determine whether consideration of both family history and a PRS would be useful for clinical T2D prediction.
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Affiliation(s)
- Emily Drzymalla
- Division of Blood Disorders and Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA
- Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Laura Raffield
- Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Katherine Kolor
- Division of Blood Disorders and Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA
| | - Alain Koyama
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Ramal Moonesinghe
- Division of Blood Disorders and Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA
| | - Meda E. Pavkov
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Cassandra N. Spracklen
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA
| | - Muin J. Khoury
- Division of Blood Disorders and Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA
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Chase BA, Frigerio R, Rubin S, Semenov I, Meyers S, Mark A, Freedom T, Marcus R, Dafer R, Wei J, Zheng SL, Xu J, Mulford AJ, Sanders AR, Pham A, Epshteyn A, Maraganore D, Markopoulou K. Migraine Genetic Susceptibility Does Not Strongly Influence Migraine Characteristics and Outcomes in a Treated, Real-World, Community Cohort. J Clin Med 2025; 14:536. [PMID: 39860542 PMCID: PMC11765864 DOI: 10.3390/jcm14020536] [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: 10/31/2024] [Revised: 12/30/2024] [Accepted: 01/04/2025] [Indexed: 01/27/2025] Open
Abstract
Background/Objectives: Migraine is a common neurological disorder with highly variable characteristics. While genome-wide association studies have identified genetic risk factors that implicate underlying pathways, the influence of genetic susceptibility on disease characteristics or treatment response is incompletely understood. We examined the relationships between a previously developed standardized integrative migraine polygenic genetic risk score (PRS) and migraine characteristics in a real-world, treated patient cohort. Methods: This retrospective cohort study used covariate-adjusted regression to comprehensively evaluate associations between the PRS and clinical characteristics in 1653 treated migraine cases with European ancestry at baseline and, in 800 cases, after one year. Cases were deeply phenotyped by neurologists during extensive interviews, using structured clinical documentation tools to record ~200 discrete data elements. Results: In treated patients, higher standardized PRS showed associations with two common migraine symptoms: photophobia (odds ratio [confidence interval]: 1.33 [1.13-1.56], p = 0.001) and stabbing pain (1.21 [1.08-1.36], p = 0.001]; both retained significance at Q = 0.05. Associations with phonophobia, nausea, emesis, and unilateral headache had similar effect sizes but did not survive correction for multiple tests. In this population, the PRS was not associated with other symptoms of migraine attacks, objective measures of migraine disability, frequency, severity, average duration, time-to-peak intensity of migraine attacks, chronification, emergency department visits, triptan responsiveness, or changes at follow-up. Conclusions: In treated patients, genetic risk was associated with common migraine symptoms but not with the severity of migraine characteristics or treatment outcomes. This suggests that in treated patients, other genetic and non-genetic factors influence migraine symptom severity and disease course more strongly than genetic susceptibility.
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Affiliation(s)
- Bruce A. Chase
- Department of Information Technology, Endeavor Health, Skokie, IL 60077, USA
- Pritzker School of Medicine, Chicago, IL 60637, USA
| | - Roberta Frigerio
- Pritzker School of Medicine, Chicago, IL 60637, USA
- Research Institute, Endeavor Health, Evanston, IL 60201, USA
| | - Susan Rubin
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
- University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA
| | - Irene Semenov
- Pritzker School of Medicine, Chicago, IL 60637, USA
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
| | - Steven Meyers
- Pritzker School of Medicine, Chicago, IL 60637, USA
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
| | - Angela Mark
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
- University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA
| | - Thomas Freedom
- Pritzker School of Medicine, Chicago, IL 60637, USA
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
| | - Revital Marcus
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
| | - Rima Dafer
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Jun Wei
- Center for Individualized Medicine, Endeavor Health, Evanston, IL 60201, USA
| | - Siqun L. Zheng
- Center for Individualized Medicine, Endeavor Health, Evanston, IL 60201, USA
| | - Jianfeng Xu
- Center for Individualized Medicine, Endeavor Health, Evanston, IL 60201, USA
| | | | - Alan R. Sanders
- Genomic Health Initiative, Endeavor Health, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637, USA
| | - Anna Pham
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
| | - Alexander Epshteyn
- Department of Information Technology, Endeavor Health, Skokie, IL 60077, USA
| | - Demetrius Maraganore
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
- Department of Neurology, Tulane University, New Orleans, LA 70118, USA
| | - Katerina Markopoulou
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
- University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA
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Bui TH, Kaga H, Kakehi S, Someya Y, Tabata H, Yoshizawa Y, Naito H, Tajima T, Ito N, Kadowaki S, Nishida Y, Kawamori R, Watada H, Tamura Y. Factors Associated With Type 2 Diabetes in Older Japanese With Similar Genetic Risk Scores: The Bunkyo Health Study. J Endocr Soc 2025; 9:bvaf019. [PMID: 39902403 PMCID: PMC11788508 DOI: 10.1210/jendso/bvaf019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2024] [Indexed: 02/05/2025] Open
Abstract
Context Genome-wide association studies have identified numerous single-nucleotide variations (SNVs, formerly single-nucleotide polymorphisms) linked to type 2 diabetes (T2D), thus improving the accuracy of genetic risk scores (GRS) in predicting T2D. Objective This study aimed to investigate the association between the novel GRS and the prevalence of T2D and clarify the characteristics that differentiate individuals with and without T2D with similar genetic risk. Methods This cross-sectional study analyzed 1610 Japanese individuals aged 65 to 84 years. GRS were calculated using 110 SNVs associated with T2D in Japanese, and GRS classified individuals as having low, average, or high risk for T2D. The characteristics of participants with or without diabetes were compared by sex at each risk level. Results The prevalences of T2D were 7.8%, 14.7%, and 16.7% at low-, average-, and high-risk levels, respectively. The odds ratios at the high- and average-risk levels were significantly higher than those at the low-risk level, even after adjusting for confounding factors. The diabetes group had a higher visceral fat area (VFA) and Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) value, but a lower insulinogenic index, than the nondiabetes group across all risk levels. In the nondiabetes group, the II decreased significantly as GRS increased, but the HOMA-IR and Matsuda index values showed no association. In men with diabetes, VFA tended to decrease with higher GRS. Conclusion A higher GRS was significantly associated with increased T2D prevalence in older Japanese individuals. Our data demonstrated that the contribution of VFA to the development of diabetes varies with genetic risk.
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Affiliation(s)
- Thu Hien Bui
- Department of Metabolism and Endocrinology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
| | - Hideyoshi Kaga
- Department of Metabolism and Endocrinology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
| | - Saori Kakehi
- Sports Medicine and Sportology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
- Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
| | - Yuki Someya
- Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
| | - Hiroki Tabata
- Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
- Juntendo Advanced Research Institute for Health Science, Tokyo 113-8421, Japan
| | - Yasuyo Yoshizawa
- Juntendo Advanced Research Institute for Health Science, Tokyo 113-8421, Japan
- Faculty of International Liberal Arts, Juntendo University, Tokyo 113-8421, Japan
| | - Hitoshi Naito
- Department of Metabolism and Endocrinology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
| | - Tsubasa Tajima
- Department of Metabolism and Endocrinology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
| | - Naoaki Ito
- Department of Metabolism and Endocrinology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
| | - Satoshi Kadowaki
- Department of Metabolism and Endocrinology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
| | - Yuya Nishida
- Department of Metabolism and Endocrinology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
| | - Ryuzo Kawamori
- Department of Metabolism and Endocrinology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
- Sports Medicine and Sportology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
- Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
| | - Hirotaka Watada
- Department of Metabolism and Endocrinology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
- Sports Medicine and Sportology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
- Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
| | - Yoshifumi Tamura
- Department of Metabolism and Endocrinology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
- Sports Medicine and Sportology, Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
- Sportology Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
- Juntendo Advanced Research Institute for Health Science, Tokyo 113-8421, Japan
- Faculty of International Liberal Arts, Juntendo University, Tokyo 113-8421, Japan
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8
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Wheeler AM, Riley TR, Merriman TR. Genetic Risk Scores for the Clinical Rheumatologist. J Clin Rheumatol 2025; 31:26-32. [PMID: 39454094 PMCID: PMC11888151 DOI: 10.1097/rhu.0000000000002152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2024]
Abstract
BACKGROUND/HISTORICAL PERSPECTIVE The advent of genome-wide sequencing and large-scale genetic epidemiological studies has led to numerous opportunities for the application of genetics in clinical medicine. Leveraging this information toward the formation of clinically useful tools has been an ongoing research goal in this area. A genetic risk score (GRS) is a measure that attempts to estimate the cumulative contribution of established genetic risk factors toward an outcome of interest, taking into account the cumulative risk that each of these individual genetic risk factors conveys. The purpose of this perspective is to provide a systematic framework to evaluate a GRS for clinical application. SUMMARY OF CURRENT LITERATURE Since the initial polygenic risk score methodology in 2007, there has been increasing GRS application across the medical literature. In rheumatology, this has included application to rheumatoid arthritis, gout, spondyloarthritis, lupus, and inflammatory arthritis. MAJOR CONCLUSIONS GRSs are particularly relevant to rheumatology, where common diseases have many complex genetic factors contributing to risk. Despite this, there is no widely accepted method for the critical application of a GRS, which can be a particular challenge for the clinical rheumatologist seeking to clinically apply GRSs. This review provides a framework by which the clinician may systematically evaluate a GRS. FUTURE RESEARCH DIRECTIONS As genotyping becomes more accessible and cost-effective, it will become increasingly important to recognize the clinical applicability of GRSs and identify those of the highest utility for patient care. This framework for the evaluation of a GRS will also help ensure reliability among GRS research in rheumatology, thereby helping to advance the field.
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Affiliation(s)
- Austin M. Wheeler
- University of Nebraska Medical Center & VA Nebraska-Western Iowa Health Care System, Omaha, NE, USA
| | - Thomas R. Riley
- University of Pennsylvania & Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
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Hesketh KD, Zheng M, Campbell KJ. Early life factors that affect obesity and the need for complex solutions. Nat Rev Endocrinol 2025; 21:31-44. [PMID: 39313572 DOI: 10.1038/s41574-024-01035-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/27/2024] [Indexed: 09/25/2024]
Abstract
The prevalence of obesity increases with age but is apparent even in early life. Early childhood is a critical period for development that is known to influence future health. Even so, the focus on obesity in this phase, and the factors that affect the development of obesity, has only emerged over the past two decades. Furthermore, there is a paucity of iterative work in this area that would move the field forward. Obesity is a complex condition involving the interplay of multiple influences at different levels: the individual and biological level, the sociocultural level, and the environmental and system levels. This Review provides a brief overview of the evidence for these factors with a focus on aspects specific to early life. By spotlighting the complex web of interactions between the broad range of influences, both causal and risk markers, we highlight the complex nature of the condition. Much work in the early life field remains observational and many of the intervention studies are limited by a focus on single influences and a disjointed approach to solutions. Yet the complexity of obesity necessitates coordinated multi-focused solutions and joined-up action across the first 2,000 days from conception, and beyond.
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Affiliation(s)
- Kylie D Hesketh
- Institute for Physical Activity and Nutrition, Faculty of Health, Deakin University, Geelong, Victoria, Australia.
| | - Miaobing Zheng
- Institute for Physical Activity and Nutrition, Faculty of Health, Deakin University, Geelong, Victoria, Australia
| | - Karen J Campbell
- Institute for Physical Activity and Nutrition, Faculty of Health, Deakin University, Geelong, Victoria, Australia
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Bhowmik N, Cook SR, Croney C, Barnard S, Romaniuk AC, Ekenstedt KJ. Heritability and Genome-Wide Association Study of Dog Behavioral Phenotypes in a Commercial Breeding Cohort. Genes (Basel) 2024; 15:1611. [PMID: 39766878 PMCID: PMC11675989 DOI: 10.3390/genes15121611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2024] [Revised: 12/12/2024] [Accepted: 12/13/2024] [Indexed: 01/11/2025] Open
Abstract
Background: Canine behavior plays an important role in the success of the human-dog relationship and the dog's overall welfare, making selection for behavior a vital part of any breeding program. While behaviors are complex traits determined by gene × environment interactions, genetic selection for desirable behavioral phenotypes remains possible. Methods: No genomic association studies of dog behavior to date have been reported on a commercial breeding (CB) cohort; therefore, we utilized dogs from these facilities (n = 615 dogs). Behavioral testing followed previously validated protocols, resulting in three phenotypes/variables [social fear (SF), non-social fear (NSF), and startle response (SR)]. Dogs were genotyped on the 710 K Affymetrix Axiom CanineHD SNP array. Results: Inbreeding coefficients indicated that dogs from CB facilities are statistically less inbred than dogs originating from other breeding sources. Heritability estimates for behavioral phenotypes ranged from 0.042 ± 0.045 to 0.354 ± 0.111. A genome-wide association analysis identified genetic loci associated with SF, NSF, and SR; genes near many of these loci have been previously associated with behavioral phenotypes in other populations of dogs. Finally, genetic risk scores demonstrated differences between dogs that were more or less fearful in response to test stimuli, suggesting that these behaviors could be subjected to genetic improvement. Conclusions: This study confirms several canine genetic behavioral loci identified in previous studies. It also demonstrates that inbreeding coefficients of dogs in CB facilities are typically lower than those in dogs originating from other breeding sources. SF and NSF were more heritable than SR. Risk allele and weighted risk scores suggest that fearful behaviors could be subjected to genetic improvement.
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Affiliation(s)
- Nayan Bhowmik
- Department of Basic Medical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA or (N.B.); (S.R.C.)
| | - Shawna R. Cook
- Department of Basic Medical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA or (N.B.); (S.R.C.)
| | - Candace Croney
- Department of Comparative Pathobiology, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA; (C.C.); (S.B.); (A.C.R.)
| | - Shanis Barnard
- Department of Comparative Pathobiology, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA; (C.C.); (S.B.); (A.C.R.)
| | - Aynsley C. Romaniuk
- Department of Comparative Pathobiology, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA; (C.C.); (S.B.); (A.C.R.)
| | - Kari J. Ekenstedt
- Department of Basic Medical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA or (N.B.); (S.R.C.)
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Fan J, Hao J, Fu Y, Liu X, Qu HQ, Glessner JT, Ji D, Liu W, Zheng G, Ding Z, Cui S, Xia Q, Hakonarson H, Wei W, Li J. Genetic Association of Juvenile Idiopathic Arthritis With Adult Rheumatic Disease. JAMA Netw Open 2024; 7:e2451341. [PMID: 39729320 DOI: 10.1001/jamanetworkopen.2024.51341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2024] Open
Abstract
Importance Patients with juvenile idiopathic arthritis (JIA) may develop adult rheumatic diseases later in life, and prolonged or recurrent disease activity is often associated with substantial disability; therefore, it is important to identify patients with JIA at high risk of developing adult rheumatic diseases and provide specialized attention and preventive care to them. Objective To elucidate the full extent of the genetic association of JIA with adult rheumatic diseases, to improve treatment strategies and patient outcomes for patients at high risk of developing long-term rheumatic diseases. Design, Setting, and Participants In this genetic association study of 4 disease genome-wide association study (GWAS) cohorts from 2013 to 2024 (JIA, rheumatoid arthritis [RA], systemic lupus erythematosus [SLE], and systemic sclerosis [SSc]), patients in the JIA cohort were recruited from the US, Australia, and Norway (with a UK cohort included in the meta-analyzed cohort), while patients in the other 3 cohorts were recruited from US and Western European countries. All analyses were conducted between September 2023 and April 2024. Exposures Genetic associations. Main Outcomes and Measures Genetic correlations and shared genomic loci between JIA and adult rheumatic diseases. Genetic correlation analyses and cross-trait meta-analysis were conducted on the JIA cohort and the summary statistics of the GWASs from adult rheumatic diseases (RA, SLE, and SSc). Mendelian randomization analyses were also conducted. Results This study included 33 207 patients across the 4 cohorts, with 4550 patients in the meta-analyzed JIA cohort (JIA cohort: 1485 patients with arthritis onset before 16 years; 1017 female [68.5%]; 10 352 controls; UK cohort: 3305 patients with JIA; 9196 controls), 143 61 patients in the RA cohort, 5201 patients in the SLE cohort; and 9095 patients in the SSc cohort. After the GWAS result of the JIA cohort was meta-analyzed with the UK JIA cohort, there was a total of 4550 JIA cases and 18 446 controls. The analysis revealed a significant global correlation between JIA and adult rheumatic diseases, with 84 regions harboring signals associated with multiple diseases. Cross-trait analyses uncovered novel disease loci and 20 loci associated with JIA and adult diseases. Mendelian randomization analysis revealed the significant association of 11 proteins with rheumatic disorders. Both shared, organ-specific, and disease-specific critical cell types were highlighted. Conclusions and Relevance In this genetic association study, there was significant genetic overlap between JIA and adult rheumatic diseases. These findings may help to refine JIA classification, risk stratification, and therapeutic strategy of repurposing adult disease drugs for pediatric patients with similar mechanisms.
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Affiliation(s)
- Jingxian Fan
- Department of Cell Biology, The Province and Ministry Cosponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Jian Hao
- Department of Rheumatology and Immunology, Tianjin Clinical Research Center for Rheumatic and Immune Diseases, Tianjin Medical University General Hospital, Tianjin, China
| | - Yuqiao Fu
- Department of Cell Biology, The Province and Ministry Cosponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
- Department of Bioinformatics, Tianjin Medical University, Tianjin, China
| | - Xiaoyang Liu
- Department of Cell Biology, The Province and Ministry Cosponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
- Department of Bioinformatics, Tianjin Medical University, Tianjin, China
| | - Hui-Qi Qu
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Joseph T Glessner
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Dandan Ji
- Department of Cell Biology, The Province and Ministry Cosponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Wei Liu
- Tianjin Children's Hospital, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Birth Defects for Prevention and Treatment, Tianjin, China
| | - Gang Zheng
- National Supercomputer Center in Tianjin, Tianjin, China
| | - Zhiyong Ding
- Mills Institute for Personalized Cancer Care, Fynn Biotechnologies Ltd, Jinan, China
| | - Shuzhong Cui
- Affiliated Cancer Hospital, Institute of Guangzhou Medical University, Guangzhou, China
| | - Qianghua Xia
- Department of Cell Biology, The Province and Ministry Cosponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
- Department of Bioinformatics, Tianjin Medical University, Tianjin, China
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Wei Wei
- Department of Rheumatology and Immunology, Tianjin Clinical Research Center for Rheumatic and Immune Diseases, Tianjin Medical University General Hospital, Tianjin, China
| | - Jin Li
- Department of Cell Biology, The Province and Ministry Cosponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
- Department of Rheumatology and Immunology, Tianjin Clinical Research Center for Rheumatic and Immune Diseases, Tianjin Medical University General Hospital, Tianjin, China
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Chase BA, Frigerio R, Rubin S, Franada T, Semenov I, Meyers S, Bergman-Bock S, Mark A, Freedom T, Marcus R, Dafer R, Wei J, Zheng SL, Xu J, Mulford AJ, Sanders AR, Pham A, Epshteyn A, Maraganore D, Markopoulou K. An Integrative Migraine Polygenic Risk Score Is Associated with Age at Onset But Not Chronification. J Clin Med 2024; 13:6483. [PMID: 39518622 PMCID: PMC11547092 DOI: 10.3390/jcm13216483] [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: 08/28/2024] [Revised: 10/21/2024] [Accepted: 10/24/2024] [Indexed: 11/16/2024] Open
Abstract
Background/Objective: Genome-wide association studies (GWASs) demonstrate a complex genetic landscape for migraine risk. Migraine polygenic risk scores (PRSs) developed from GWAS data may have utility for predicting disease course. We analyzed the strength of association between an integrative migraine PRS and age at onset and chronification. Methods: In this retrospective clinical/genetic case-control study, PGS004799 was calculated for adults with European ancestry from two real-world community cohorts. In the DodoNA cohort, 1653 treated, deeply phenotyped migraine cases, diagnosed using International Classification of Headache Disorders 3rd edition criteria, were followed for a mean (range) of 2.3 (1-10) years and compared to 3460 controls (without migraine diagnosis). In the GHI cohort, 2443 cases were identified using the first migraine ICD code as a proxy for migraine onset and compared to 8576 controls (without migraine ICD codes). PRS associations with age at onset (DodoNA) or first migraine ICD code (GHI) and chronification (DodoNA) were evaluated. Results: In both cohorts, PRS was higher in cases (DodoNA mean (range) cases: 0.82 (0.07-1.76), controls: 0.78 (0.04-1.56); t (5111) = -6.1, p = 1.4 × 10-9, GHI: cases: 0.79 (0.003-1.68), controls: 0.75 (-0.06-1.53); t (11,017) = -7.69, p = 1.6 × 10-14), and a higher PRS was associated with earlier onset in females (HR [95% CI] DodoNA: 2.1 [1.6-2.6, p < 0.001; GHI: 1.8 [1.4-2.1], p < 0.001) and in males (DodoNA: 2.5 [1.3-4.7], p = 0.005; GHI: 1.6 [1.1-2.6], p = 0.027). PRS was not different in cases with or without chronification (t (1651) = -1.67, p = 0.094) and was not associated with earlier chronification (1.2 [0.8-1.6], p = 0.424). Conclusions: Higher genetic risk was associated with earlier onset and increased risk of migraine well into adulthood, but not with chronification. This suggests that the PRS quantifies genetic susceptibility that is distinct from factors influencing disease course.
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Affiliation(s)
- Bruce A. Chase
- Department of Health Information Technology, Endeavor Health, Skokie, IL 60077, USA
- Pritzker School of Medicine, Chicago, IL 60637, USA
| | - Roberta Frigerio
- Pritzker School of Medicine, Chicago, IL 60637, USA
- Research Institute, Endeavor Health, Evanston, IL 60201, USA
| | - Susan Rubin
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
- University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA
| | - Tiffani Franada
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
| | - Irene Semenov
- Pritzker School of Medicine, Chicago, IL 60637, USA
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
| | - Steven Meyers
- Pritzker School of Medicine, Chicago, IL 60637, USA
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
| | | | - Angela Mark
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
- University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA
| | - Thomas Freedom
- Pritzker School of Medicine, Chicago, IL 60637, USA
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
| | - Revital Marcus
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
| | - Rima Dafer
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Jun Wei
- Center for Individualized Medicine, Endeavor Health, Evanston, IL 60201, USA
| | - Siqun L. Zheng
- Center for Individualized Medicine, Endeavor Health, Evanston, IL 60201, USA
| | - Jianfeng Xu
- Center for Individualized Medicine, Endeavor Health, Evanston, IL 60201, USA
| | | | - Alan R. Sanders
- Genomic Health Initiative, Endeavor Health, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637, USA
| | - Anna Pham
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
| | - Alexander Epshteyn
- Department of Health Information Technology, Endeavor Health, Skokie, IL 60077, USA
| | - Demetrius Maraganore
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
- Department of Neurology, Tulane University, New Orleans, LA 70112, USA
| | - Katerina Markopoulou
- Department of Neurology, Endeavor Health, Evanston, IL 60201, USA
- University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA
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TANISAWA KUMPEI, TABATA HIROKI, NAKAMURA NOBUHIRO, KAWAKAMI RYOKO, USUI CHIYOKO, ITO TOMOKO, KAWAMURA TAKUJI, TORII SUGURU, ISHII KAORI, MURAOKA ISAO, SUZUKI KATSUHIKO, SAKAMOTO SHIZUO, HIGUCHI MITSURU, OKA KOICHIRO. Polygenic Risk Score, Cardiorespiratory Fitness, and Cardiometabolic Risk Factors: WASEDA'S Health Study. Med Sci Sports Exerc 2024; 56:2026-2038. [PMID: 38768052 PMCID: PMC11419280 DOI: 10.1249/mss.0000000000003477] [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: 05/22/2024]
Abstract
PURPOSE This study estimated an individual's genetic liability to cardiometabolic risk factors by polygenic risk score (PRS) construction and examined whether high cardiorespiratory fitness (CRF) modifies the association between PRS and cardiometabolic risk factors. METHODS This cross-sectional study enrolled 1296 Japanese adults aged ≥40 yr. The PRS for each cardiometabolic trait (blood lipids, glucose, hypertension, and obesity) was calculated using the LDpred2 and clumping and thresholding methods. Participants were divided into low-, intermediate-, and high-PRS groups according to PRS tertiles for each trait. CRF was quantified as peak oxygen uptake (V̇O 2peak ) per kilogram body weight. Participants were divided into low-, intermediate-, and high-CRF groups according to the tertile V̇O 2peak value. RESULTS Linear regression analysis revealed a significant interaction between PRS for triglyceride (PRS TG ) and CRF groups on serum TG levels regardless of the PRS calculation method, and the association between PRS TG and TG levels was attenuated in the high-CRF group. Logistic regression analysis revealed a significant sub-additive interaction between LDpred2 PRS TG and CRF on the prevalence of high TG, indicating that high CRF attenuated the genetic predisposition to high TG. Furthermore, a significant sub-additive interaction between PRS for body mass index and CRF on obesity was detected regardless of the PRS calculation method. These significant interaction effects on high TG and obesity were diminished in the sensitivity analysis using V̇O 2peak per kilogram fat-free mass as the CRF index. Effects of PRSs for other cardiometabolic traits were not significantly attenuated in the high-CRF group regardless of PRS calculation methods. CONCLUSIONS The findings of the present study suggest that individuals with high CRF overcome the genetic predisposition to high TG levels and obesity.
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Affiliation(s)
- KUMPEI TANISAWA
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, JAPAN
| | - HIROKI TABATA
- Sportology Center, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, JAPAN
- Waseda Institute for Sport Sciences, Tokorozawa, Saitama, JAPAN
| | - NOBUHIRO NAKAMURA
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, JAPAN
| | - RYOKO KAWAKAMI
- Waseda Institute for Sport Sciences, Tokorozawa, Saitama, JAPAN
- Physical Fitness Research Institute, Meiji Yasuda Life Foundation of Health and Welfare, Hachioji, Tokyo, JAPAN
| | - CHIYOKO USUI
- Waseda Institute for Sport Sciences, Tokorozawa, Saitama, JAPAN
- Center for Liberal Education and Learning, Sophia University, Chiyoda-ku, Tokyo, JAPAN
| | - TOMOKO ITO
- Waseda Institute for Sport Sciences, Tokorozawa, Saitama, JAPAN
- Department of Food and Nutrition, Tokyo Kasei University, Itabashi-ku, Tokyo, JAPAN
| | - TAKUJI KAWAMURA
- Waseda Institute for Sport Sciences, Tokorozawa, Saitama, JAPAN
- Research Center for Molecular Exercise Science, Hungarian University of Sports Science, Budapest, HUNGARY
| | - SUGURU TORII
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, JAPAN
| | - KAORI ISHII
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, JAPAN
| | - ISAO MURAOKA
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, JAPAN
| | - KATSUHIKO SUZUKI
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, JAPAN
| | - SHIZUO SAKAMOTO
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, JAPAN
- Faculty of Sport Science, Surugadai University, Hanno, Saitama, JAPAN
| | - MITSURU HIGUCHI
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, JAPAN
| | - KOICHIRO OKA
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, JAPAN
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Bharti N, Banerjee R, Achalare A, Kasibhatla SM, Joshi R. Estimation of genetic variation in vitiligo associated genes: Population genomics perspective. BMC Genom Data 2024; 25:72. [PMID: 39060965 PMCID: PMC11282599 DOI: 10.1186/s12863-024-01254-6] [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: 06/12/2024] [Accepted: 07/16/2024] [Indexed: 07/28/2024] Open
Abstract
BACKGROUND Vitiligo is an auto-immune progressive depigmentation disorder of the skin due to loss of melanocytes. Genetic risk is one of the important factors for development of vitiligo. Preponderance of vitiligo in certain ethnicities is known which can be analysed by understanding the distribution of allele frequencies across normal populations. Earlier GWAS identified 108 risk alleles for vitiligo in Europeans and East Asians. In this study, 64 of these risk alleles were used for analysing their enrichment and depletion across populations (1000 Genomes Project and IndiGen) with reference to 1000 Genomes dataset. Genetic risk scores were calculated and Fisher's exact test was performed to understand statistical significance of their variation in each population with respect to 1000 Genomes dataset as reference. In addition to SNPs reported in GWAS, significant variation in allele frequencies of 1079 vitiligo-related genes were also analysed. Two-tailed Chi-square test and Bonferroni's multiple adjustment values along with fixation index (≥ 0.5) and minimum allele frequency (≥ 0.05) were calculated and used to prioritise the variants based on pairwise comparison across populations. RESULTS Risk alleles rs1043101 and rs10768122 belong to 3 prime UTR of glutamate receptor gene SLC1A2 are found to be highly enriched in the South Asian population when compared with the 'global normal' population. Intron variant rs4766578 (ATXN2) was found to be deleted in SAS, EAS and AFR and enriched in EUR and AMR1. This risk allele is found to be under positive selection in SAS, AMR1 and EUR. From the ancillary vitiligo gene list, nonsynonymous variant rs16891982 was found to be enriched in the European and the Admixed American populations and depleted in all others. rs2279238 and rs11039155 belonging to the LXR-α gene involved in regulation of metalloproteinase 2 and 9 (melanocyte precursors) were found to be associated with vitiligo in the North Indian population (in earlier study). CONCLUSION The differential enrichment/depletion profile of the risk alleles provides insight into the underlying inter-population variations. This would provide clues towards prioritisation of SNPs associated with vitiligo thereby elucidating its preponderance in different ethnic groups.
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Affiliation(s)
- Neeraj Bharti
- HPC-Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Innovation Park, Pashan, Pune, 411008, Maharashtra, India
| | - Ruma Banerjee
- HPC-Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Innovation Park, Pashan, Pune, 411008, Maharashtra, India
| | - Archana Achalare
- HPC-Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Innovation Park, Pashan, Pune, 411008, Maharashtra, India
| | - Sunitha Manjari Kasibhatla
- HPC-Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Innovation Park, Pashan, Pune, 411008, Maharashtra, India
| | - Rajendra Joshi
- HPC-Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Innovation Park, Pashan, Pune, 411008, Maharashtra, India.
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Roumi Z, Mirzababaei A, Abaj F, Davaneghi S, Aali Y, Mirzaei K. The interaction between polyphenol intake and genes (MC4R, Cav-1, and Cry1) related to body homeostasis and cardiometabolic risk factors in overweight and obese women: a cross-sectional study. Front Nutr 2024; 11:1410811. [PMID: 39104759 PMCID: PMC11299215 DOI: 10.3389/fnut.2024.1410811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 07/10/2024] [Indexed: 08/07/2024] Open
Abstract
Background Cardiovascular disease (CVD), which is an important global health challenge, is expanding. One of the main factors in the occurrence of CVD is a high genetic risk. The interaction between genetic risk in CVD and nutrition is debatable. Polyphenols are one of the important dietary components that may have a protective role in people who have a high genetic risk score (GRS) for cardiometabolic risk factors. This study, conducted in overweight and obese women, examines the interaction between polyphenol intake and specific genes (MC4r, Cav-1, and Cry1) related to maintaining body balance and their interaction with cardiometabolic risk factors. Methods This cross-sectional study included 391 women who were overweight or obese, aged 18 to 48 years, with a body mass index (BMI) between 25 and 40 kg/m2. Body composition was measured using the InBody 770 scanner. Total dietary polyphenol intake (TDPI) was assessed with a validated 147-item food frequency questionnaire (FFQ), and polyphenol intakes were determined using the Phenol-Explorer database. Serum samples underwent biochemical tests. The Genetic Risk Score (GRS) was calculated based on the risk alleles of three genes: MC4r, Cav-1, and Cry1. Results The mean ± standard deviation (SD) age and BMI of women were 36.67 (9.1) years and 30.98 (3.9) kg/m2, respectively. The high GRS and high TDPI group had a significant negative interaction with fasting blood glucose (FBS) (p = 0.01). Individuals who had a high GRS and a high phenolic acid intake were found to have a significant negative interaction with Triglyceride (p = 0.04). Similarly, individuals with high GRS and a high intake of flavonoids had a significant negative interaction with TG (p < 0.01) and a significant positive interaction with High-density lipoprotein (HDL) (p = 0.01) in the adjusted model. Conclusion According to our findings, those with a high GRS may have a protective effect on cardiometabolic risk factors by consuming high amounts of polyphenols. Further studies will be necessary in the future to validate this association.
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Affiliation(s)
- Zahra Roumi
- Department of Nutrition, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Atieh Mirzababaei
- Department of Nutrition, Science and Research Branch, Islamic Azad University, Tehran, Iran
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Faezeh Abaj
- Department of Nutrition, Dietetics and Food, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia
| | - Soheila Davaneghi
- MSC, School of Nutrition and Food Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Yasaman Aali
- Department of Nutrition, Science and Research Branch, Islamic Azad University, Tehran, Iran
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Khadijeh Mirzaei
- Department of Nutrition, Science and Research Branch, Islamic Azad University, Tehran, Iran
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16
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Habtewold TD, Wijesiriwardhana P, Biedrzycki RJ, Tekola-Ayele F. Genetic distance and ancestry proportion modify the association between maternal genetic risk score of type 2 diabetes and fetal growth. Hum Genomics 2024; 18:81. [PMID: 39030631 PMCID: PMC11264503 DOI: 10.1186/s40246-024-00645-1] [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: 02/12/2024] [Accepted: 06/27/2024] [Indexed: 07/21/2024] Open
Abstract
BACKGROUND Maternal genetic risk of type 2 diabetes (T2D) has been associated with fetal growth, but the influence of genetic ancestry is not yet fully understood. We aimed to investigate the influence of genetic distance (GD) and genetic ancestry proportion (GAP) on the association of maternal genetic risk score of T2D (GRST2D) with fetal weight and birthweight. METHODS Multi-ancestral pregnant women (n = 1,837) from the NICHD Fetal Growth Studies - Singletons cohort were included in the current analyses. Fetal weight (in grams, g) was estimated from ultrasound measurements of fetal biometry, and birthweight (g) was measured at delivery. GRST2D was calculated using T2D-associated variants identified in the latest trans-ancestral genome-wide association study and was categorized into quartiles. GD and GAP were estimated using genotype data of four reference populations. GD was categorized into closest, middle, and farthest tertiles, and GAP was categorized as highest, medium, and lowest. Linear regression analyses were performed to test the association of GRST2D with fetal weight and birthweight, adjusted for covariates, in each GD and GAP category. RESULTS Among women with the closest GD from African and Amerindigenous ancestries, the fourth and third GRST2D quartile was significantly associated with 5.18 to 7.48 g (weeks 17-20) and 6.83 to 25.44 g (weeks 19-27) larger fetal weight compared to the first quartile, respectively. Among women with middle GD from European ancestry, the fourth GRST2D quartile was significantly associated with 5.73 to 21.21 g (weeks 18-26) larger fetal weight. Furthermore, among women with middle GD from European and African ancestries, the fourth and second GRST2D quartiles were significantly associated with 117.04 g (95% CI = 23.88-210.20, p = 0.014) and 95.05 g (95% CI = 4.73-185.36, p = 0.039) larger birthweight compared to the first quartile, respectively. The absence of significant association among women with the closest GD from East Asian ancestry was complemented by a positive significant association among women with the highest East Asian GAP. CONCLUSIONS The association between maternal GRST2D and fetal growth began in early-second trimester and was influenced by GD and GAP. The results suggest the use of genetic GD and GAP could improve the generalizability of GRS.
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Affiliation(s)
- Tesfa Dejenie Habtewold
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6710B Rockledge Drive, Bethesda, MD, 20892-7004, USA
| | - Prabhavi Wijesiriwardhana
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6710B Rockledge Drive, Bethesda, MD, 20892-7004, USA
| | - Richard J Biedrzycki
- Glotech, Inc., contractor for Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6710B Rockledge Drive, Bethesda, MD, 20892-7004, USA
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6710B Rockledge Drive, Bethesda, MD, 20892-7004, USA.
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Treccani M, Veschetti L, Patuzzo C, Malerba G, Vaglio A, Martorana D. Genetic and Non-Genetic Contributions to Eosinophilic Granulomatosis with Polyangiitis: Current Knowledge and Future Perspectives. Curr Issues Mol Biol 2024; 46:7516-7529. [PMID: 39057087 PMCID: PMC11275403 DOI: 10.3390/cimb46070446] [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: 05/31/2024] [Revised: 07/12/2024] [Accepted: 07/15/2024] [Indexed: 07/28/2024] Open
Abstract
In this work, we present a comprehensive overview of the genetic and non-genetic complexity of eosinophilic granulomatosis with polyangiitis (EGPA). EGPA is a rare complex systemic disease that occurs in people presenting with severe asthma and high eosinophilia. After briefly introducing EGPA and its relationship with the anti-neutrophil cytoplasmic autoantibodies (ANCA)-associated vasculitis (AAVs), we delve into the complexity of this disease. At first, the two main biological actors, ANCA and eosinophils, are presented. Biological and clinical phenotypes related to ANCA positivity or negativity are explained, as well as the role of eosinophils and their pathological subtypes, pointing out their intricate relations with EGPA. Then, the genetics of EGPA are described, providing an overview of the research effort to unravel them. Candidate gene studies have investigated biologically relevant candidate genes; the more recent genome-wide association studies and meta-analyses, able to analyze the whole genome, have confirmed previous associations and discovered novel risk loci; in the end, family-based studies have dissected the contribution of rare variants and the heritability of EGPA. Then, we briefly present the environmental contribution to EGPA, reporting seasonal events and pollutants as triggering factors. In the end, the latest omic research is discussed and the most recent epigenomic, transcriptomic and microbiome studies are presented, highlighting the current challenges, open questions and suggesting approaches to unraveling this complex disease.
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Affiliation(s)
- Mirko Treccani
- GM Lab, Department of Surgery, Dentistry, Gynaecology and Paediatrics, University of Verona, 37134 Verona, Italy;
| | - Laura Veschetti
- Infections and Cystic Fibrosis Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, 20132 Milano, Italy;
- Vita-Salute San Raffaele University, 20132 Milano, Italy
| | - Cristina Patuzzo
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy;
| | - Giovanni Malerba
- GM Lab, Department of Surgery, Dentistry, Gynaecology and Paediatrics, University of Verona, 37134 Verona, Italy;
| | - Augusto Vaglio
- Nephrology and Dialysis Unit, Meyer Children’s Hospital IRCCS, 50139 Florence, Italy;
- Department of Biomedical Experimental and Clinical Sciences “Mario Serio”, University of Florence, 50121 Florence, Italy
| | - Davide Martorana
- Medical Genetics Unit, Department of Onco-Hematology, University Hospital of Parma, 43126 Parma, Italy;
- CoreLab Unit, Research Center, University Hospital of Parma, 43126 Parma, Italy
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18
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Saarinen A, Hietala J, Lyytikäinen LP, Hamal Mishra B, Sormunen E, Lavonius V, Kähönen M, Raitakari O, Lehtimäki T, Keltikangas-Järvinen L. Polygenic risk for schizophrenia predicting social trajectories in a general population sample. Psychol Med 2024; 54:1589-1597. [PMID: 38047377 DOI: 10.1017/s003329172300346x] [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] [Indexed: 12/05/2023]
Abstract
BACKGROUND We investigated (a) whether polygenic risk for schizophrenia predicts different trajectories of social development among those who have not developed psychoses and (b) whether possible associations are PRSSCZ-specific or evident also for any polygenic risk for mental disorders, e.g. for major depression. METHODS Participants came from the population-based Young Finns Study (n = 2377). We calculated a polygenic risk score for schizophrenia (PRSSCZ) and for major depression (PRSDEP). Diagnoses of psychotic disorders were derived from the hospital care register. Social development from adolescence to middle age was measured by (a) perceived social support from friends, family, and a close other, (b) perceived sociability, and (c) family structure (partnership status, number of children, age of first-time parenthood). RESULTS Among those without manifest psychoses, high PRSSCZ predicted lower experienced support from friends (B = -0.04, p = 0.009-0.035) and family (B = -0.04, p = 0.009-0.035) especially after early adulthood, and also lower perceived sociability (B = -0.05, p = 0.010-0.026). PRSSCZ was not related to family structure. PRSDEP did not predict any domain of social development. CONCLUSIONS Individuals at high PRSSCZ (not converted to psychosis) seem to experience a lower preference to be with others over being alone. Individuals with high (v. low) PRSSCZ seem to have a similar family structure in terms of partnership status or number of children but, nevertheless, they experience less support from their family. Among those not converted to psychosis in a typical age period, high PRSSCZ may predict a 'later risk phase' and reduced functional resilience when approaching middle age.
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Affiliation(s)
- Aino Saarinen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Helsinki University Central Hospital, Adolescent Psychiatry Outpatient Clinic, Helsinki, Finland
| | - Jarmo Hietala
- Department of Psychiatry, University of Turku, and Turku University Hospital, Turku, Finland
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Tampere, Finland
- Department of Cardiology, Heart Center, Tampere University Hospital, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Binisha Hamal Mishra
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Elina Sormunen
- Department of Psychiatry, University of Turku, and Turku University Hospital, Turku, Finland
| | - Veikka Lavonius
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Mika Kähönen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
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Yang PK, Jackson SL, Charest BR, Cheng YJ, Sun YV, Raghavan S, Litkowski EM, Legvold BT, Rhee MK, Oram RA, Kuklina EV, Vujkovic M, Reaven PD, Cho K, Leong A, Wilson PW, Zhou J, Miller DR, Sharp SA, Staimez LR, North KE, Highland HM, Phillips LS. Type 1 Diabetes Genetic Risk in 109,954 Veterans With Adult-Onset Diabetes: The Million Veteran Program (MVP). Diabetes Care 2024; 47:1032-1041. [PMID: 38608262 PMCID: PMC11116922 DOI: 10.2337/dc23-1927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 03/11/2024] [Indexed: 04/14/2024]
Abstract
OBJECTIVE To characterize high type 1 diabetes (T1D) genetic risk in a population where type 2 diabetes (T2D) predominates. RESEARCH DESIGN AND METHODS Characteristics typically associated with T1D were assessed in 109,594 Million Veteran Program participants with adult-onset diabetes, 2011-2021, who had T1D genetic risk scores (GRS) defined as low (0 to <45%), medium (45 to <90%), high (90 to <95%), or highest (≥95%). RESULTS T1D characteristics increased progressively with higher genetic risk (P < 0.001 for trend). A GRS ≥90% was more common with diabetes diagnoses before age 40 years, but 95% of those participants were diagnosed at age ≥40 years, and their characteristics resembled those of individuals with T2D in mean age (64.3 years) and BMI (32.3 kg/m2). Compared with the low-risk group, the highest-risk group was more likely to have diabetic ketoacidosis (low GRS 0.9% vs. highest GRS 3.7%), hypoglycemia prompting emergency visits (3.7% vs. 5.8%), outpatient plasma glucose <50 mg/dL (7.5% vs. 13.4%), a shorter median time to start insulin (3.5 vs. 1.4 years), use of a T1D diagnostic code (16.3% vs. 28.1%), low C-peptide levels if tested (1.8% vs. 32.4%), and glutamic acid decarboxylase antibodies (6.9% vs. 45.2%), all P < 0.001. CONCLUSIONS Characteristics associated with T1D were increased with higher genetic risk, and especially with the top 10% of risk. However, the age and BMI of those participants resemble those of people with T2D, and a substantial proportion did not have diagnostic testing or use of T1D diagnostic codes. T1D genetic screening could be used to aid identification of adult-onset T1D in settings in which T2D predominates.
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Affiliation(s)
- Peter K. Yang
- Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
- Atlanta Veterans Administration Medical Center, Atlanta, GA
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC
| | - Sandra L. Jackson
- Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Brian R. Charest
- Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA
| | - Yiling J. Cheng
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Yan V. Sun
- Atlanta Veterans Administration Medical Center, Atlanta, GA
- Rollins School of Public Health, Emory University, Atlanta, GA
| | - Sridharan Raghavan
- Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, CO
- University of Colorado School of Medicine, Denver, CO
| | - Elizabeth M. Litkowski
- Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, CO
- University of Colorado School of Medicine, Denver, CO
| | - Brian T. Legvold
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA
| | - Mary K. Rhee
- Atlanta Veterans Administration Medical Center, Atlanta, GA
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA
| | - Richard A. Oram
- College of Medicine and Health, University of Exeter Medical School, Devon, U.K
| | - Elena V. Kuklina
- Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Marijana Vujkovic
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | | | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA
- Brigham and Women’s Hospital, Boston, MA
| | - Aaron Leong
- Harvard Medical School, Boston, MA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA
| | - Peter W.F. Wilson
- Atlanta Veterans Administration Medical Center, Atlanta, GA
- Rollins School of Public Health, Emory University, Atlanta, GA
- College of Medicine and Health, University of Exeter Medical School, Devon, U.K
| | - Jin Zhou
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
- UCLA Department of Medicine, University of California, Los Angeles, CA
| | | | - Seth A. Sharp
- Division of Endocrinology and Diabetes, Stanford University, Palo Alto, CA
| | - Lisa R. Staimez
- Rollins School of Public Health, Emory University, Atlanta, GA
| | - Kari E. North
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC
| | - Heather M. Highland
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC
| | - Lawrence S. Phillips
- Atlanta Veterans Administration Medical Center, Atlanta, GA
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA
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Gandhi SE, Zerenner T, Nodehi A, Lawton MA, Marshall V, Al‐Hajraf F, Grosset KA, Morris HR, Hu MT, Ben‐Shlomo Y, Grosset DG. Motor Complications in Parkinson's Disease: Results from 3343 Patients Followed for up to 12 Years. Mov Disord Clin Pract 2024; 11:686-697. [PMID: 38587023 PMCID: PMC11145112 DOI: 10.1002/mdc3.14044] [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: 11/28/2023] [Revised: 02/26/2024] [Accepted: 03/19/2024] [Indexed: 04/09/2024] Open
Abstract
BACKGROUND Motor complications are well recognized in Parkinson's disease (PD), but their reported prevalence varies and functional impact has not been well studied. OBJECTIVES To quantify the presence, severity, impact and associated factors for motor complications in PD. METHODS Analysis of three large prospective cohort studies of recent-onset PD patients followed for up to 12 years. The MDS-UPDRS part 4 assessed motor complications and multivariable logistic regression tested for associations. Genetic risk score (GRS) for Parkinson's was calculated from 79 single nucleotide polymorphisms. RESULTS 3343 cases were included (64.7% male). Off periods affected 35.0% (95% CI 33.0, 37.0) at 4-6 years and 59.0% (55.6, 62.3) at 8-10 years. Dyskinesia affected 18.5% (95% CI 16.9, 20.2) at 4-6 years and 42.1% (38.7, 45.5) at 8-10 years. Dystonia affected 13.4% (12.1, 14.9) at 4-6 years and 22.8% (20.1, 25.9) at 8-10 years. Off periods consistently caused greater functional impact than dyskinesia. Motor complications were more common among those with higher drug doses, younger age at diagnosis, female gender, and greater dopaminergic responsiveness (in challenge tests), with associations emerging 2-4 years post-diagnosis. Higher Parkinson's GRS was associated with early dyskinesia (0.026 ≤ P ≤ 0.050 from 2 to 6 years). CONCLUSIONS Off periods are more common and cause greater functional impairment than dyskinesia. We confirm previously reported associations between motor complications with several demographic and medication factors. Greater dopaminergic responsiveness and a higher genetic risk score are two novel and significant independent risk factors for the development of motor complications.
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Affiliation(s)
- Sacha E. Gandhi
- School of Neuroscience and PsychologyUniversity of GlasgowGlasgowUnited Kingdom
| | - Tanja Zerenner
- Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Anahita Nodehi
- Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Michael A. Lawton
- Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | | | - Falah Al‐Hajraf
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical NeuroscienceOxford UniversityOxfordUnited Kingdom
- Department of Pharmacology and Toxicology, Faculty of MedicineKuwait UniversityKuwait CityKuwait
| | | | - Huw R. Morris
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of NeurologyUniversity College LondonLondonUnited Kingdom
| | - Michele T. Hu
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical NeuroscienceOxford UniversityOxfordUnited Kingdom
| | - Yoav Ben‐Shlomo
- Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Donald G. Grosset
- School of Neuroscience and PsychologyUniversity of GlasgowGlasgowUnited Kingdom
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21
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Liu L, Wu Y, Li Y, Li M. A Polygenic Risk Analysis for Identifying Ulcerative Colitis Patients with European Ancestry. Genes (Basel) 2024; 15:684. [PMID: 38927620 PMCID: PMC11202467 DOI: 10.3390/genes15060684] [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: 05/01/2024] [Revised: 05/19/2024] [Accepted: 05/24/2024] [Indexed: 06/28/2024] Open
Abstract
The incidence of ulcerative colitis (UC) has increased globally. As a complex disease, the genetic predisposition for UC could be estimated by the polygenic risk score (PRS), which aggregates the effects of a large number of genetic variants in a single quantity and shows promise in identifying individuals at higher lifetime risk of UC. Here, based on a cohort of 2869 UC cases and 2900 controls with genotype array datasets, we used PRSice-2 to calculate PRS, and systematically analyzed factors that could affect the power of PRS, including GWAS summary statistics, population stratification, and impact of variants. After leveraging a stepwise condition analysis, we eventually established the best PRS model, achieving an AUC of 0.713. Meanwhile, samples in the top 20% of the PRS distribution had a risk of UC more than ten times higher than samples in the lowest 20% (OR = 10.435, 95% CI 8.571-12.703). Our analyses demonstrated that including population-enriched, more disease-associated SNPs and using GWAS summary statistics from similar ethnic background can improve the power of PRS. Strictly following the principle of focusing on one population in all aspects of generating PRS can be a cost-effective way to apply genotype-array-derived PRS to practical risk estimation.
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Affiliation(s)
- Ling Liu
- College of Chemistry, Sichuan University, Chengdu 610065, China
| | - Yiming Wu
- College of Life Science, China West Normal University, Nanchong 637009, China
| | - Yizhou Li
- College of Cyber Science and Engineering, Sichuan University, Chengdu 610065, China
| | - Menglong Li
- College of Chemistry, Sichuan University, Chengdu 610065, China
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22
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Tannemann N, Erbel R, Nöthen MM, Jöckel KH, Pechlivanis S. Genetic polymorphisms affecting telomere length and their association with cardiovascular disease in the Heinz-Nixdorf-Recall study. PLoS One 2024; 19:e0303357. [PMID: 38743757 PMCID: PMC11093374 DOI: 10.1371/journal.pone.0303357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 04/23/2024] [Indexed: 05/16/2024] Open
Abstract
Short telomeres are associated with cardiovascular disease (CVD). We aimed to investigate, if genetically determined telomere-length effects CVD-risk in the Heinz-Nixdorf-Recall study (HNRS) population. We selected 14 single-nucleotide polymorphisms (SNPs) associated with telomere-length (p<10-8) from the literature and after exclusion 9 SNPs were included in the analyses. Additionally, a genetic risk score (GRS) using these 9 SNPs was calculated. Incident CVD was defined as fatal and non-fatal myocardial infarction, stroke, and coronary death. We included 3874 HNRS participants with available genetic data and had no known history of CVD at baseline. Cox proportional-hazards regression was used to test the association between the SNPs/GRS and incident CVD-risk adjusting for common CVD risk-factors. The analyses were further stratified by CVD risk-factors. During follow-up (12.1±4.31 years), 466 participants experienced CVD-events. No association between SNPs/GRS and CVD was observed in the adjusted analyses. However, the GRS, rs10936599, rs2487999 and rs8105767 increase the CVD-risk in current smoker. Few SNPs (rs10936599, rs2487999, and rs7675998) showed an increased CVD-risk, whereas rs10936599, rs677228 and rs4387287 a decreased CVD-risk, in further strata. The results of our study suggest different effects of SNPs/GRS on CVD-risk depending on the CVD risk-factor strata, highlighting the importance of stratified analyses in CVD risk-factors.
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Affiliation(s)
- Nico Tannemann
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
| | - Raimund Erbel
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
| | - Markus M. Nöthen
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Karl-Heinz Jöckel
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
| | - Sonali Pechlivanis
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Asthma and Allergy Prevention, Neuherberg, Germany
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23
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Shirizadeh A, Razavi Z, Saeedi V, Faradmal J, Roshanaei G, Hajilooi M, Morahan G, Solgi G. Family-based association of HLA-DRB1 and DQB1 alleles and haplotypes in a group of Iranian Type 1 diabetes children. HLA 2024; 103:e15446. [PMID: 38575369 DOI: 10.1111/tan.15446] [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: 10/21/2023] [Revised: 02/06/2024] [Accepted: 03/09/2024] [Indexed: 04/06/2024]
Abstract
This family-based study was conducted in a group of Iranians with Type 1 diabetes (T1D) to investigate the transmission from parents of risk and non-risk HLA alleles and haplotypes, and to estimate the genetic risk score for this disease within this population. A total of 240 T1D subjects including 111 parent-child trios (111 children with T1D, 133 siblings, and 222 parents) and 330 ethnically matched healthy individuals were recruited. High-resolution HLA typing for DRB1/DQB1 loci was performed for all study subjects (n = 925) using polymerase chain reaction-sequence-specific oligonucleotide probe method. The highest predisposing effect on developing T1D was conferred by the following haplotypes both in all subjects and in probands compared to controls: DRB1*04:05-DQB1*03:02 (Pc = 2.97e-06 and Pc = 6.04e-10, respectively), DRB1*04:02-DQB1*03:02 (Pc = 5.94e-17 and Pc = 3.86e-09, respectively), and DRB1*03:01-DQB1*02:01 (Pc = 8.26e-29 and Pc = 6.56e-16, respectively). Conversely, the major protective haplotypes included DRB1*13:01-DQB1*06:03 (Pc = 6.99e-08), DRB1*15:01-DQB1*06:02 (Pc = 2.97e-06) in the cases versus controls. Also, DRB1*03:01-DQB1*02:01/DRB1*04:02|05-DQB1*03:02 and DRB1*03:01-DQB1*02:01/DRB1*03:01-DQB1*02:01 diplotypes conferred the highest predisposing effect in the cases (Pc = 8.65e-17 and Pc = 6.26e-08, respectively) and in probands (Pc = 5.4e-15 and Pc = 0.001, respectively) compared to controls. Transmission disequilibrium test showed that the highest risk was conferred by DRB1*04:02-DQB1*03:02 (Pc = 3.26e-05) and DRB1*03:01-DQB1*02:01 (Pc = 1.78e-12) haplotypes and the highest protection by DRB1*14:01-DQB1*05:03 (Pc = 8.66e-05), DRB1*15:01-DQB1*06:02 (Pc = 0.002), and DRB1*11:01-DQB1*03:01 (Pc = 0.0003) haplotypes. Based on logistic regression analysis, carriage of risk haplotypes increased the risk of T1D development 24.5 times in the Iranian population (p = 5.61e-13). Also, receiver operating characteristic curve analysis revealed a high predictive power of those risk haplotypes in discrimination of susceptible from healthy individuals (area under curve: 0.88, p = 5.5e-32). Our study highlights the potential utility of genetic risk assessment based on HLA diplotypes for predicting T1D risk in individuals, particularly among family members of affected children in our population.
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Affiliation(s)
- Ata Shirizadeh
- Immunology Department, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Zahra Razavi
- Pediatrics Department, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Vahid Saeedi
- Pediatric Endocrinology and Metabolism Department, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Javad Faradmal
- Biostatistics Department, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Ghodratollah Roshanaei
- Biostatistics Department, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Mehrdad Hajilooi
- Immunology Department, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Grant Morahan
- Centre for Medical Research, University of Western Australia, Perth, Western Australia, Australia
| | - Ghasem Solgi
- Immunology Department, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
- Cancer Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
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24
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Schwarzerova J, Hurta M, Barton V, Lexa M, Walther D, Provaznik V, Weckwerth W. A perspective on genetic and polygenic risk scores-advances and limitations and overview of associated tools. Brief Bioinform 2024; 25:bbae240. [PMID: 38770718 PMCID: PMC11106636 DOI: 10.1093/bib/bbae240] [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: 10/03/2023] [Revised: 04/14/2024] [Accepted: 05/03/2024] [Indexed: 05/22/2024] Open
Abstract
Polygenetic Risk Scores are used to evaluate an individual's vulnerability to developing specific diseases or conditions based on their genetic composition, by taking into account numerous genetic variations. This article provides an overview of the concept of Polygenic Risk Scores (PRS). We elucidate the historical advancements of PRS, their advantages and shortcomings in comparison with other predictive methods, and discuss their conceptual limitations in light of the complexity of biological systems. Furthermore, we provide a survey of published tools for computing PRS and associated resources. The various tools and software packages are categorized based on their technical utility for users or prospective developers. Understanding the array of available tools and their limitations is crucial for accurately assessing and predicting disease risks, facilitating early interventions, and guiding personalized healthcare decisions. Additionally, we also identify potential new avenues for future bioinformatic analyzes and advancements related to PRS.
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Affiliation(s)
- Jana Schwarzerova
- Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia
- Molecular Systems Biology (MOSYS), Department of Functional and Evolutionary Ecology, University of Vienna, Vienna 1010, Austria
| | - Martin Hurta
- Department of Computer Systems, Faculty of Information Technology, Brno University of Technology, Brno 612 00, Czechia
| | - Vojtech Barton
- Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, Brno 62500, Czech Republic
| | - Matej Lexa
- Faculty of Informatics, Masaryk University, Botanicka 68a, Brno 60200, Czech Republic
| | - Dirk Walther
- Max-Planck-Institute of Molecular Plant Physiology, Potsdam 14476, Germany
| | - Valentine Provaznik
- Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia
- Department of Physiology, Faculty of Medicine, Masaryk University, Brno 62500, Czech Republic
| | - Wolfram Weckwerth
- Molecular Systems Biology (MOSYS), Department of Functional and Evolutionary Ecology, University of Vienna, Vienna 1010, Austria
- Vienna Metabolomics Center (VIME), University of Vienna, Vienna 1010, Austria
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25
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Ter Hark SE, Coenen MJH, Vos CF, Aarnoutse RE, Nolen WA, Birkenhager TK, van den Broek WW, Schellekens AFA, Verkes RJ, Janzing JGE. A genetic risk score to predict treatment nonresponse in psychotic depression. Transl Psychiatry 2024; 14:132. [PMID: 38431658 PMCID: PMC10908776 DOI: 10.1038/s41398-024-02842-x] [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: 07/14/2023] [Revised: 02/09/2024] [Accepted: 02/19/2024] [Indexed: 03/05/2024] Open
Abstract
Psychotic depression is a severe and difficult-to-treat subtype of major depressive disorder for which higher rates of treatment-resistant depression were found. Studies have been performed aiming to predict treatment-resistant depression or treatment nonresponse. However, most of these studies excluded patients with psychotic depression. We created a genetic risk score (GRS) based on a large treatment-resistant depression genome-wide association study. We tested whether this GRS was associated with nonresponse, nonremission and the number of prior adequate antidepressant trials in patients with a psychotic depression. Using data from a randomized clinical trial with patients with a psychotic depression (n = 122), we created GRS deciles and calculated positive prediction values (PPV), negative predictive values (NPV) and odds ratios (OR). Nonresponse and nonremission were assessed after 7 weeks of treatment with venlafaxine, imipramine or venlafaxine plus quetiapine. The GRS was negatively correlated with treatment response (r = -0.32, p = 0.0023, n = 88) and remission (r = -0.31, p = 0.0037, n = 88), but was not correlated with the number of prior adequate antidepressant trials. For patients with a GRS in the top 10%, we observed a PPV of 100%, a NPV of 73.7% and an OR of 52.4 (p = 0.00072, n = 88) for nonresponse. For nonremission, a PPV of 100%, a NPV of 51.9% and an OR of 21.3 (p = 0.036, n = 88) was observed for patients with a GRS in the top 10%. Overall, an increased risk for nonresponse and nonremission was seen in patients with GRSs in the top 40%. Our results suggest that a treatment-resistant depression GRS is predictive of treatment nonresponse and nonremission in psychotic depression.
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Affiliation(s)
- Sophie E Ter Hark
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands.
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
| | - Marieke J H Coenen
- Department of Clinical Chemistry, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Cornelis F Vos
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Rob E Aarnoutse
- Department of Pharmacy, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Willem A Nolen
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Tom K Birkenhager
- Department of Psychiatry, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | | | - Arnt F A Schellekens
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
- Nijmegen Institute for Scientist Practitioners in Addiction (NISPA), Radboud University, Nijmegen, The Netherlands
| | - Robbert-Jan Verkes
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Joost G E Janzing
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
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26
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Saarinen A, Marttila S, Mishra PP, Lyytikäinen L, Raitoharju E, Mononen N, Sormunen E, Kähönen M, Raitakari O, Hietala J, Keltikangas‐Järvinen L, Lehtimäki T. Polygenic risk for schizophrenia, social dispositions, and pace of epigenetic aging: Results from the Young Finns Study. Aging Cell 2024; 23:e14052. [PMID: 38031635 PMCID: PMC10928579 DOI: 10.1111/acel.14052] [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: 07/10/2023] [Revised: 10/26/2023] [Accepted: 11/15/2023] [Indexed: 12/01/2023] Open
Abstract
Schizophrenia is often regarded as a disorder of premature aging. We investigated (a) whether polygenic risk for schizophrenia (PRSsch ) relates to pace of epigenetic aging and (b) whether personal dispositions toward active and emotionally close relationships protect against accelerated epigenetic aging in individuals with high PRSsch . The sample came from the population-based Young Finns Study (n = 1348). Epigenetic aging was measured with DNA methylation aging algorithms such as AgeAccelHannum , EEAAHannum , IEAAHannum , IEAAHorvath , AgeAccelHorvath , AgeAccelPheno , AgeAccelGrim , and DunedinPACE. A PRSsch was calculated using summary statistics from the most comprehensive genome-wide association study of schizophrenia to date. Social dispositions were assessed in terms of extraversion, sociability, reward dependence, cooperativeness, and attachment security. We found that PRSsch did not have a statistically significant effect on any studied indicator of epigenetic aging. Instead, PRSsch had a significant interaction with reward dependence (p = 0.001-0.004), cooperation (p = 0.009-0.020), extraversion (p = 0.019-0.041), sociability (p = 0.003-0.016), and attachment security (p = 0.007-0.014) in predicting AgeAccelHannum , EEAAHannum , or IEAAHannum . Specifically, participants with high PRSsch appeared to display accelerated epigenetic aging at higher (vs. lower) levels of extraversion, sociability, attachment security, reward dependence, and cooperativeness. A rather opposite pattern was evident for those with low PRSsch . No such interactions were evident when predicting the other indicators of epigenetic aging. In conclusion, against our hypothesis, frequent social interactions may relate to accelerated epigenetic aging in individuals at risk for psychosis. We speculate that this may be explained by social-cognitive impairments (perceiving social situations as overwhelming or excessively arousing) or ending up in less supportive or deviant social groups.
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Affiliation(s)
- Aino Saarinen
- Department of Psychology and Logopedics, Faculty of MedicineUniversity of HelsinkiHelsinkiFinland
- Helsinki University Central HospitalAdolescent Psychiatry Outpatient ClinicHelsinkiFinland
| | - Saara Marttila
- Department of Molecular Epidemiology, Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Gerontology Research CenterTampere UniversityTampereFinland
| | - Pashupati P. Mishra
- Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Department of Clinical ChemistryFimlab LaboratoriesTampereFinland
- Finnish Cardiovascular Research CenterTampereFinland
| | - Leo‐Pekka Lyytikäinen
- Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Department of Clinical ChemistryFimlab LaboratoriesTampereFinland
- Finnish Cardiovascular Research CenterTampereFinland
- Department of Cardiology, Heart CenterTampere University HospitalTampereFinland
| | - Emma Raitoharju
- Department of Molecular Epidemiology, Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Cardiovascular Research Center Tampere, Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
| | - Nina Mononen
- Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Department of Clinical ChemistryFimlab LaboratoriesTampereFinland
- Finnish Cardiovascular Research CenterTampereFinland
- Cardiovascular Research Center Tampere, Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
| | - Elina Sormunen
- Department of PsychiatryUniversity of TurkuTurkuFinland
- Turku University HospitalTurkuFinland
| | - Mika Kähönen
- Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Department of Clinical PhysiologyTampere University HospitalTampereFinland
| | - Olli Raitakari
- Turku University HospitalTurkuFinland
- Research Centre of Applied and Preventive Cardiovascular MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchUniversity of TurkuTurkuFinland
- Department of Clinical Physiology and Nuclear MedicineTurku University HospitalTurkuFinland
| | - Jarmo Hietala
- Department of PsychiatryUniversity of TurkuTurkuFinland
- Turku University HospitalTurkuFinland
- Department of MedicineUniversity of TurkuTurkuFinland
- Division of MedicineTurku University HospitalTurkuFinland
| | | | - Terho Lehtimäki
- Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Department of Clinical ChemistryFimlab LaboratoriesTampereFinland
- Finnish Cardiovascular Research CenterTampereFinland
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27
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Lares-Villaseñor E, Guevara-Cruz M, Salazar-García S, Granados-Portillo O, Vega-Cárdenas M, Martinez-Leija ME, Medina-Vera I, González-Salazar LE, Arteaga-Sanchez L, Guízar-Heredia R, Hernández-Gómez KG, Serralde-Zúñiga AE, Pichardo-Ontiveros E, López-Barradas AM, Guevara-Pedraza L, Ordaz-Nava G, Avila-Nava A, Tovar AR, Cossío-Torres PE, de la Cruz-Mosso U, Aradillas-García C, Portales-Pérez DP, Noriega LG, Vargas-Morales JM. Genetic risk score for insulin resistance based on gene variants associated to amino acid metabolism in young adults. PLoS One 2024; 19:e0299543. [PMID: 38422035 PMCID: PMC10903913 DOI: 10.1371/journal.pone.0299543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 02/12/2024] [Indexed: 03/02/2024] Open
Abstract
Circulating concentration of arginine, alanine, aspartate, isoleucine, leucine, phenylalanine, proline, tyrosine, taurine and valine are increased in subjects with insulin resistance, which could in part be attributed to the presence of single nucleotide polymorphisms (SNPs) within genes associated with amino acid metabolism. Thus, the aim of this work was to develop a Genetic Risk Score (GRS) for insulin resistance in young adults based on SNPs present in genes related to amino acid metabolism. We performed a cross-sectional study that included 452 subjects over 18 years of age. Anthropometric, clinical, and biochemical parameters were assessed including measurement of serum amino acids by high performance liquid chromatography. Eighteen SNPs were genotyped by allelic discrimination. Of these, ten were found to be in Hardy-Weinberg equilibrium, and only four were used to construct the GRS through multiple linear regression modeling. The GRS was calculated using the number of risk alleles of the SNPs in HGD, PRODH, DLD and SLC7A9 genes. Subjects with high GRS (≥ 0.836) had higher levels of glucose, insulin, homeostatic model assessment- insulin resistance (HOMA-IR), total cholesterol and triglycerides, and lower levels of arginine than subjects with low GRS (p < 0.05). The application of a GRS based on variants within genes associated to amino acid metabolism may be useful for the early identification of subjects at increased risk of insulin resistance.
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Affiliation(s)
- Eunice Lares-Villaseñor
- Facultad de Ciencias Químicas, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | - Martha Guevara-Cruz
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Samuel Salazar-García
- Facultad de Ciencias Químicas, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | - Omar Granados-Portillo
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Mariela Vega-Cárdenas
- Laboratorio de Nutrición, Departamento de Ciencias en Investigación Aplicadas en Ambiente y Salud, Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | | | - Isabel Medina-Vera
- Departamento de Metodología de la Investigación, Instituto Nacional de Pediatría, Ciudad de México, México
| | - Luis E. González-Salazar
- Servicio de Nutriología Clínica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Liliana Arteaga-Sanchez
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Rocío Guízar-Heredia
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Karla G. Hernández-Gómez
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Aurora E. Serralde-Zúñiga
- Servicio de Nutriología Clínica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Edgar Pichardo-Ontiveros
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Adriana M. López-Barradas
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | | | - Guillermo Ordaz-Nava
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Azalia Avila-Nava
- Hospital Regional de Alta Especialidad de la Península de Yucatán, IMSS-Bienestar, Mérida, Yucatán, Mexico
| | - Armando R. Tovar
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Patricia E. Cossío-Torres
- Departamento de Salud Pública y Ciencias Médicas, Facultad de Medicina, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | - Ulises de la Cruz-Mosso
- Red de Inmunonutrición y Genómica Nutricional en las Enfermedades Autoinmunes, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, México
| | - Celia Aradillas-García
- Facultad de Medicina, Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | - Diana P. Portales-Pérez
- Facultad de Ciencias Químicas, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | - Lilia G. Noriega
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Juan M. Vargas-Morales
- Facultad de Ciencias Químicas, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
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28
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Sokary S, Almaghrbi H, Bawadi H. The Interaction Between Body Mass Index Genetic Risk Score and Dietary Intake on Weight Status: A Systematic Review. Diabetes Metab Syndr Obes 2024; 17:925-941. [PMID: 38435632 PMCID: PMC10908334 DOI: 10.2147/dmso.s452660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 02/15/2024] [Indexed: 03/05/2024] Open
Abstract
Background The escalating global obesity epidemic and the emergence of personalized medicine strategies point to the pressing need to investigate the interplay between genetic risk scores (GRSs), dietary intake, and their combined impact on weight status. This systematic review synthesizes evidence from diverse studies to elucidate how dietary patterns and individual foods interact with genetic predisposition to obesity. Methods Literature searches were conducted in the PubMed, Embase, Science Direct, and Scopus databases until August 2023, following PRISMA guidelines. Out of 575 articles, 15 articles examining the interaction between genetic risk score for body mass index and dietary intake on weight outcomes met the inclusion criteria. All included studies were cross-sectional in design and were assessed for quality using the Newcastle‒Ottawa Scale. Results Unhealthy dietary intake exacerbated the genetic predisposition to obesity, evident in studies assessing Western diet, sulfur microbial diet, and individual macronutrients, including saturated fatty acids, sugar-sweetened beverages and fried foods. Conversely, adhering to healthier dietary intake mitigated the genetic predisposition to obesity, as observed in studies involving Alternative Healthy Eating Index, Alternative Mediterranean Diet, Dietary Approach to Stop Hypertension scores, healthy plant-based diets, and specific foods such as fruits, vegetables, and n-3 polyunsaturated fatty acids. Conclusion This is the first systematic review to explore the interaction between genetics and dietary intake in shaping obesity outcomes. The findings have implications for tailored interventions; however, more controlled clinical trials with robust designs are needed to be able to recommend personalized nutrition based on nutrition for obesity prevention and management.
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Affiliation(s)
- Sara Sokary
- Department of Human Nutrition, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Heba Almaghrbi
- Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Hiba Bawadi
- Department of Human Nutrition, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
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29
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Hashimi M, Amin HA, Zagkos L, Day AC, Drenos F. Using genetics to investigate the association between lanosterol and cataract. Front Genet 2024; 15:1231521. [PMID: 38440190 PMCID: PMC10910428 DOI: 10.3389/fgene.2024.1231521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 02/06/2024] [Indexed: 03/06/2024] Open
Abstract
Background: Cataract is one of the most prevalent causes of blindness worldwide. Whilst surgery is the primary treatment for cataracts, it is not always an available option, particularly in developing countries. Non-surgical methods of treatment would increase treatment availability for more patients. Several studies have investigated how topical application of oxysterols, such as lanosterol, may break down aggregated proteins and restore lens transparency. However, the results are conflicting and inconclusive. Aim: In this study, we focus on combining genetic evidence for associations between lanosterol related genetic variation and cataract to explore whether lanosterol is a potentially suitable drug treatment option. Method: Using data from 45,449 available cataract cases from the UK Biobank, with participant ages ranging from 40-69, we conducted a genetic association study (GWAS) to assess the risk of cataract. Cataract cases were defined using diagnostic and operation codes. We focused on genetic variants in the lanosterol synthase gene region. We also compared our results with previously published genetic associations of phytosterol-to-lanosterol ratios. Finally, we performed a genetic risk score analysis to test the association between lanosterol within the cholesterol synthesis pathway and the risk of cataract. Results: No statistically significant single nucleotide polymorphisms (SNPs) associations with cataract were observed in the gene region of lanosterol synthase at a multiple testing adjusted significance threshold of p < 0.05/13. The comparison between cataract risk and genetic association of 8 phytosterol-to-lanosterol GWAS results also showed no evidence to support lanosterol's protective properties for cataract risk. No statistically significant association was found between the lanosterol within the cholesterol synthesis pathway genetic risk score and cataract outcomes (OR = 1.002 p = 0.568). Conclusion: There was no evidence observed for genetic associations between lanosterol and cataract risk. Our results do not support lanosterol's potential role in treating cataracts. Further research may be needed to address the effect of lanosterol on specific cataract subtypes.
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Affiliation(s)
- Munisa Hashimi
- Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, Uxbridge, United Kingdom
| | - Hasnat A. Amin
- Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, Uxbridge, United Kingdom
| | - Loukas Zagkos
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Alexander C. Day
- Moorfields Eye Hospital, London, United Kingdom
- UCL Institute of Ophthalmology, London, United Kingdom
| | - Fotios Drenos
- Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, Uxbridge, United Kingdom
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30
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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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Janardhanan M, Sen S, Shankarappa B, Purushottam M. Molecular genetics of neuropsychiatric illness: some musings. Front Genet 2023; 14:1203017. [PMID: 38028602 PMCID: PMC10646253 DOI: 10.3389/fgene.2023.1203017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Research into the genetic underpinnings of neuropsychiatric illness has occurred at many levels. As more information accumulates, it appears that many approaches may each offer their unique perspective. The search for low penetrance and common variants, that may mediate risk, has necessitated the formation of many international consortia, to pool resources, and achieve the large sample sizes needed to discover these variants. There has been the parallel development of statistical methods to analyse large datasets and present summary statistics which allows data comparison across studies. Even so, the results of studies on well-characterised clinical datasets of modest sizes can be enlightening and provide important clues to understanding these complex disorders. We describe the use of common variants, at multiallelic loci like TOMM40 and APOE to study dementia, weighted genetic risk scores for alcohol-induced liver cirrhosis and whole exome sequencing to identify rare variants in genes like PLA2G6 in familial psychoses and schizophrenia in our Indian population.
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Affiliation(s)
| | | | | | - Meera Purushottam
- Molecular Genetics Laboratory, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
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Fatumo S, Sathan D, Samtal C, Isewon I, Tamuhla T, Soremekun C, Jafali J, Panji S, Tiffin N, Fakim YJ. Polygenic risk scores for disease risk prediction in Africa: current challenges and future directions. Genome Med 2023; 15:87. [PMID: 37904243 PMCID: PMC10614359 DOI: 10.1186/s13073-023-01245-9] [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: 03/04/2023] [Accepted: 10/12/2023] [Indexed: 11/01/2023] Open
Abstract
Early identification of genetic risk factors for complex diseases can enable timely interventions and prevent serious outcomes, including mortality. While the genetics underlying many Mendelian diseases have been elucidated, it is harder to predict risk for complex diseases arising from the combined effects of many genetic variants with smaller individual effects on disease aetiology. Polygenic risk scores (PRS), which combine multiple contributing variants to predict disease risk, have the potential to influence the implementation for precision medicine. However, the majority of existing PRS were developed from European data with limited transferability to African populations. Notably, African populations have diverse genetic backgrounds, and a genomic architecture with smaller haplotype blocks compared to European genomes. Subsequently, growing evidence shows that using large-scale African ancestry cohorts as discovery for PRS development may generate more generalizable findings. Here, we (1) discuss the factors contributing to the poor transferability of PRS in African populations, (2) showcase the novel Africa genomic datasets for PRS development, (3) explore the potential clinical utility of PRS in African populations, and (4) provide insight into the future of PRS in Africa.
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Affiliation(s)
- Segun Fatumo
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda.
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria.
- Department of Non-Communicable Disease Epidemiology (NCDE), London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK.
| | - Dassen Sathan
- H3Africa Bioinformatics Network (H3ABioNet) Node, University of Mauritius, Reduit, Mauritius
| | - Chaimae Samtal
- Laboratory of Biotechnology, Environment, Agri-Food and Health, Faculty of Sciences Dhar El Mahraz-Sidi Mohammed Ben Abdellah University, 30000, Fez, Morocco
| | - Itunuoluwa Isewon
- Department of Computer and Information Sciences, Covenant University, P. M. B. 1023, Ota, Ogun State, Nigeria
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Km 10 Idiroko Road, P.M.B. 1023, Ota, Ogun State, Nigeria
- Covenant Applied Informatics and Communication African Centre of Excellence (CApIC-ACE), Covenant University, P.M.B. 1023, Ota, Ogun State, Nigeria
| | - Tsaone Tamuhla
- Division of Computational Biology, Integrative Biomedical Sciences Department, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa
| | - Chisom Soremekun
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria
- Department of Immunology and Molecular Biology, College of Health Science, Makerere University, Kampala, Uganda
| | - James Jafali
- Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi
- Clinical Infection, Microbiology & Immunology, The University of Liverpool, Liverpool, UK
| | - Sumir Panji
- Computational Biology Group, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, 7925, South Africa
| | - Nicki Tiffin
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa
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Cao Z, Hernandez DG, Li C, Berghausen J, Luo Z, Iwaki H, D'Aloisio AA, Huang X, Pinto JM, Sandler DP, Singleton AB, Chen H. Polygenic risk score for Parkinson's disease and olfaction among middle-aged to older women. Parkinsonism Relat Disord 2023; 115:105815. [PMID: 37611509 PMCID: PMC10592043 DOI: 10.1016/j.parkreldis.2023.105815] [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: 06/06/2023] [Revised: 08/08/2023] [Accepted: 08/15/2023] [Indexed: 08/25/2023]
Abstract
INTRODUCTION Olfactory impairment and Parkinson's disease (PD) may share common genetic and environmental risk factors. This study investigates the association of a PD polygenic risk score (PRS) with olfaction, and whether the associations are modified by environmental exposures of PM2.5, NO2, or smoking. METHODS This analysis included 3358 women (aged 50-80) from the Sister Study with genetic data and results from the Brief Smell Identification Test (B-SIT) administered in 2018-2019. PD PRS was calculated using 90 single nucleotide polymorphisms. Olfactory impairment was defined with different B-SIT cutoffs, and PD diagnosis was adjudicated via expert review. We report odds ratios (ORs) and 95% confidence intervals (CIs) from multivariable logistic regression. RESULTS As expected, PD PRS was strongly associated with the odds of having PD (OR highest vs. lowest quartile = 3.79 (1.64, 8.73)). The highest PRS quartile was also associated with olfactory impairment, with OR ranging from 1.24 (0.98, 1.56) for a B-SIT cutoff of 9 to 1.42 (1.04, 1.92) for a cutoff of 6. For individual B-SIT items, the highest PRS quartile was generally associated with lower odds of correctly identifying the odorant, albeit only statistically significant for pineapple (0.72 (0.56, 0.94), soap (0.76 (0.58, 0.99)) and rose (0.70 (0.54, 0.92)). The association of PD PRS with olfactory impairment was not modified by airborne environmental exposures or smoking. CONCLUSION These preliminary data suggest that high PD genetic susceptibility is associated with olfactory impairment in middle-aged and older women.
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Affiliation(s)
- Zichun Cao
- Department of Epidemiology and Biostatistics, Michigan State University College of Human Medicine, East Lansing, MI, USA.
| | - Dena G Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA.
| | - Chenxi Li
- Department of Epidemiology and Biostatistics, Michigan State University College of Human Medicine, East Lansing, MI, USA.
| | - Joos Berghausen
- Department of Pharmacology & Physiology, Georgetown University, Washington D.C., USA.
| | - Zhehui Luo
- Department of Epidemiology and Biostatistics, Michigan State University College of Human Medicine, East Lansing, MI, USA.
| | - Hirotaka Iwaki
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
| | - Aimee A D'Aloisio
- Social & Scientific Systems, a DLH Holdings Corporation, Durham, NC, USA.
| | - Xuemei Huang
- Department of Neurology, Pennsylvania State University College of Medicine, Hershey, PA, USA.
| | - Jayant M Pinto
- Department of Surgery, The University of Chicago, Chicago, IL, USA.
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA.
| | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA; Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
| | - Honglei Chen
- Department of Epidemiology and Biostatistics, Michigan State University College of Human Medicine, East Lansing, MI, USA.
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Almaghrbi H, Al-Shafai M, Al-Asmakh M, Bawadi H. Association of Vitamin D Genetic Risk Score with Noncommunicable Diseases: A Systematic Review. Nutrients 2023; 15:4040. [PMID: 37764823 PMCID: PMC10537716 DOI: 10.3390/nu15184040] [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: 08/18/2023] [Revised: 09/09/2023] [Accepted: 09/11/2023] [Indexed: 09/29/2023] Open
Abstract
Background and Aims: The genetic risk score (GRS) is an important tool for estimating the total genetic contribution or susceptibility to a certain outcome of interest in an individual, taking into account their genetic risk alleles. This study aims to systematically review the association between the GRS of low vitamin D with different noncommunicable diseases/markers. Methods: The article was first registered in PROSPERO CRD42023406929. PubMed and Embase were searched from the time of inception until March 2023 to capture all the literature related to the vitamin D genetic risk score (vD-GRS) in association with noncommunicable diseases. This was performed using comprehensive search terms including "Genetic Risk Score" OR "Genetics risk assessment" OR "Genome-wide risk score" AND "Vitamin D" OR 25(HO)D OR "25-hydroxyvitamin D". Results: Eleven eligible studies were included in this study. Three studies reported a significant association between vD-GRS and metabolic parameters, including body fat percentage, body mass index, glycated hemoglobin, and fasting blood glucose. Moreover, colorectal cancer overall mortality and the risk of developing arterial fibrillation were also found to be associated with genetically deprived vitamin D levels. Conclusions: This systematic review highlights the genetic contribution of low-vitamin-D-risk single nucleotides polymorphisms (SNPs) as an accumulative factor associated with different non-communicable diseases/markers, including cancer mortality and the risk of developing obesity, type 2 diabetes, and cardiovascular diseases such as arterial fibrillation.
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Affiliation(s)
- Heba Almaghrbi
- Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha P.O. Box 2713, Qatar; (H.A.); (M.A.-S.); (M.A.-A.)
| | - Mashael Al-Shafai
- Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha P.O. Box 2713, Qatar; (H.A.); (M.A.-S.); (M.A.-A.)
- Biomedical Research Center, Qatar University, Doha P.O. Box 2713, Qatar
| | - Maha Al-Asmakh
- Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha P.O. Box 2713, Qatar; (H.A.); (M.A.-S.); (M.A.-A.)
- Biomedical Research Center, Qatar University, Doha P.O. Box 2713, Qatar
| | - Hiba Bawadi
- Department of Human Nutrition, College of Health Sciences, QU Health, Qatar University, Doha P.O. Box 2713, Qatar
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Luckett AM, Weedon MN, Hawkes G, Leslie RD, Oram RA, Grant SFA. Utility of genetic risk scores in type 1 diabetes. Diabetologia 2023; 66:1589-1600. [PMID: 37439792 PMCID: PMC10390619 DOI: 10.1007/s00125-023-05955-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 05/23/2023] [Indexed: 07/14/2023]
Abstract
Iterative advances in understanding of the genetics of type 1 diabetes have identified >70 genetic regions associated with risk of the disease, including strong associations across the HLA class II region that account for >50% of heritability. The increased availability of genetic data combined with the decreased costs of generating these data, have facilitated the development of polygenic scores that aggregate risk variants from associated loci into a single number: either a genetic risk score (GRS) or a polygenic risk score (PRS). PRSs incorporate the risk of many possibly correlated variants from across the genome, even if they do not reach genome-wide significance, whereas GRSs estimate the cumulative contribution of a smaller subset of genetic variants that reach genome-wide significance. Type 1 diabetes GRSs have utility in diabetes classification, aiding discrimination between type 1 diabetes, type 2 diabetes and MODY. Type 1 diabetes GRSs are also being used in newborn screening studies to identify infants at risk of future presentation of the disease. Most early studies of type 1 diabetes genetics have been conducted in European ancestry populations, but, to develop accurate GRSs across diverse ancestries, large case-control cohorts from non-European populations are still needed. The current barriers to GRS implementation within healthcare are mainly related to a lack of guidance and knowledge on integration with other biomarkers and clinical variables. Once these limitations are addressed, there is huge potential for 'test and treat' approaches to be used to tailor care for individuals with type 1 diabetes.
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Affiliation(s)
- Amber M Luckett
- University of Exeter College of Medicine and Health, Exeter, UK
| | | | - Gareth Hawkes
- University of Exeter College of Medicine and Health, Exeter, UK
| | - R David Leslie
- Blizard Institute, Queen Mary University of London, London, UK.
| | - Richard A Oram
- University of Exeter College of Medicine and Health, Exeter, UK.
- Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK.
| | - Struan F A Grant
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Division of Diabetes and Endocrinology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Phulka JS, Ashraf M, Bajwa BK, Pare G, Laksman Z. Current State and Future of Polygenic Risk Scores in Cardiometabolic Disease: A Scoping Review. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2023; 16:286-313. [PMID: 37035923 DOI: 10.1161/circgen.122.003834] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/11/2023]
Abstract
A polygenic risk score (PRS) is derived from a genome-wide association study and represents an aggregate of thousands of single-nucleotide polymorphisms that provide a baseline estimate of an individual's genetic risk for a specific disease or trait at birth. However, it remains unclear how PRSs can be used in clinical practice. We provide an overview of the PRSs related to cardiometabolic disease and discuss the evidence supporting their clinical applications and limitations. The Preferred Reporting Items For Systematic Reviews and Meta-Analysis Extension for Scoping Reviews protocol was used to conduct a scoping review of the MEDLINE, EMBASE, and CENTRAL databases. Across the 4863 studies screened, 82 articles met the inclusion criteria. The most common PRS related to coronary artery disease, followed by hypertension and cerebrovascular disease. Limited ancestral diversity was observed in the study sample populations. Most studies included only individuals of European ancestry. The predictive performance of most PRSs was similar to or superior to traditional risk factors. More than half of the included studies reported an integrated risk model combining a derived PRS and clinical risk tools such as the Framingham Risk Score and Pooled Cohort Equations. The inclusion of a PRS into a clinical risk model tended to improve predictive accuracy consistently. This scoping review is the first of its kind and reports strong evidence for the clinical utility of PRSs in coronary artery disease, hypertension, cerebrovascular disease, and atrial fibrillation. However, most PRSs are generated in cohorts of European ancestry, which likely contributes to a lack of PRS transferability across different ancestral groups. Future prospective studies should focus on further establishing the clinical utility of PRSs and ensuring diversity is incorporated into genome-wide association study cohorts.
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Affiliation(s)
- Jobanjit S Phulka
- Heart Rhythm Services & Center for Cardiovascular Innovation, Division of Cardiology, University of British Columbia, Vancouver (J.S.P., M.A., B.K.B., Z.L.)
| | - Mishal Ashraf
- Heart Rhythm Services & Center for Cardiovascular Innovation, Division of Cardiology, University of British Columbia, Vancouver (J.S.P., M.A., B.K.B., Z.L.)
| | - Beenu K Bajwa
- Heart Rhythm Services & Center for Cardiovascular Innovation, Division of Cardiology, University of British Columbia, Vancouver (J.S.P., M.A., B.K.B., Z.L.)
| | - Guillaume Pare
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute; Thrombosis and Atherosclerosis Research Institute, Department of Health Research Methods, Evidence, and Impact, Department of Pathology & Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON, Canada (G.P.)
| | - Zachary Laksman
- Heart Rhythm Services & Center for Cardiovascular Innovation, Division of Cardiology, University of British Columbia, Vancouver (J.S.P., M.A., B.K.B., Z.L.)
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Drouet DE, Liu S, Crawford DC. Assessment of multi-population polygenic risk scores for lipid traits in African Americans. PeerJ 2023; 11:e14910. [PMID: 37214096 PMCID: PMC10198155 DOI: 10.7717/peerj.14910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 01/25/2023] [Indexed: 05/24/2023] Open
Abstract
Polygenic risk scores (PRS) based on genome-wide discoveries are promising predictors or classifiers of disease development, severity, and/or progression for common clinical outcomes. A major limitation of most risk scores is the paucity of genome-wide discoveries in diverse populations, prompting an emphasis to generate these needed data for trans-population and population-specific PRS construction. Given diverse genome-wide discoveries are just now being completed, there has been little opportunity for PRS to be evaluated in diverse populations independent from the discovery efforts. To fill this gap, we leverage here summary data from a recent genome-wide discovery study of lipid traits (HDL-C, LDL-C, triglycerides, and total cholesterol) conducted in diverse populations represented by African Americans, Hispanics, Asians, Native Hawaiians, Native Americans, and others by the Population Architecture using Genomics and Epidemiology (PAGE) Study. We constructed lipid trait PRS using PAGE Study published genetic variants and weights in an independent African American adult patient population linked to de-identified electronic health records and genotypes from the Illumina Metabochip (n = 3,254). Using multi-population lipid trait PRS, we assessed levels of association for their respective lipid traits, clinical outcomes (cardiovascular disease and type 2 diabetes), and common clinical labs. While none of the multi-population PRS were strongly associated with the tested trait or outcome, PRSLDL-Cwas nominally associated with cardiovascular disease. These data demonstrate the complexity in applying PRS to real-world clinical data even when data from multiple populations are available.
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Affiliation(s)
- Domenica E. Drouet
- Department of Medicine, Case Western Reserve University, Cleveland, OH, United States of America
| | - Shiying Liu
- Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States of America
| | - Dana C. Crawford
- Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States of America
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, United States of America
- Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, United States of America
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Ferrando-Bernal M. Ancient DNA suggests anaemia and low bone mineral density as the cause for porotic hyperostosis in ancient individuals. Sci Rep 2023; 13:6968. [PMID: 37117261 PMCID: PMC10147686 DOI: 10.1038/s41598-023-33405-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 04/12/2023] [Indexed: 04/30/2023] Open
Abstract
Porotic hyperostosis (PH) is a disease that had high prevalence during the Neolithic. Several hypotheses have been suggested to explain the origin of the disease, such as an iron deficiency diet, low B12 intake, malaria caused by Plasmodium spp., low haemoglobin levels or low vitamin D levels. None of these hypotheses have been tested genetically. Here, I calculated different genetic scores to test each hypothesis. Additionally, I calculated a genetic score of bone mineral density as it is a phenotype that seems to be selected in ancient Europeans. I apply these genetic scores on 80 ancient samples, 33 with diagnosed PH. The results seem to suggest anaemia and low bone mineral density as the main cause for this disease. Additionally, Neolithic individuals show the lowest genetic risk score for bone mineral density of all other periods tested here, which may explain the highest prevalence of the porotic hyperostosis during this age.
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Adam Y, Sadeeq S, Kumuthini J, Ajayi O, Wells G, Solomon R, Ogunlana O, Adetiba E, Iweala E, Brors B, Adebiyi E. Polygenic Risk Score in African populations: progress and challenges. F1000Res 2023; 11:175. [PMID: 37273966 PMCID: PMC10233318 DOI: 10.12688/f1000research.76218.2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/10/2023] [Indexed: 06/06/2023] Open
Abstract
Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects single nucleotide polymorphisms (SNPs) that contribute to the disease with low effect size making it more precise at individual level risk prediction. PRS analysis addresses the shortfall of GWAS by taking into account the SNPs/alleles with low effect size but play an indispensable role to the observed phenotypic/trait variance. PRS analysis has applications that investigate the genetic basis of several traits, which includes rare diseases. However, the accuracy of PRS analysis depends on the genomic data of the underlying population. For instance, several studies show that obtaining higher prediction power of PRS analysis is challenging for non-Europeans. In this manuscript, we review the conventional PRS methods and their application to sub-Saharan African communities. We conclude that lack of sufficient GWAS data and tools is the limiting factor of applying PRS analysis to sub-Saharan populations. We recommend developing Africa-specific PRS methods and tools for estimating and analyzing African population data for clinical evaluation of PRSs of interest and predicting rare diseases.
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Affiliation(s)
- Yagoub Adam
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, 112212, Nigeria
| | - Suraju Sadeeq
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Ogun State, 112212, Nigeria
- Dept Computer & Information Sciences, Covenant University, Ota, Ogun State, 112212, Nigeria
| | - Judit Kumuthini
- South African National Bioinformatics Institute, Life Sciences Building, University of Western Cape, Cape Town, South Africa
- Centre for Proteomic and Genomic Research, Cape Town, Western Cape, South Africa
| | - Olabode Ajayi
- South African National Bioinformatics Institute, Life Sciences Building, University of Western Cape, Cape Town, South Africa
- Centre for Proteomic and Genomic Research, Cape Town, Western Cape, South Africa
| | - Gordon Wells
- South African National Bioinformatics Institute, Life Sciences Building, University of Western Cape, Cape Town, South Africa
- Centre for Proteomic and Genomic Research, Cape Town, Western Cape, South Africa
| | - Rotimi Solomon
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, 112212, Nigeria
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Ogun State, 112212, Nigeria
- Dept of Biochemistry, Covenant University, Ota, Ogun State, 112212, Nigeria
| | - Olubanke Ogunlana
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, 112212, Nigeria
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Ogun State, 112212, Nigeria
- Dept of Biochemistry, Covenant University, Ota, Ogun State, 112212, Nigeria
| | - Emmanuel Adetiba
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Ogun State, 112212, Nigeria
- Dept of Electrical & Information Engineering (EIE), Covenant University, Ota, Ogun State, 112212, Nigeria
- HRA, Institute for Systems Science, Durban University of Technology, Durban, South Africa
| | - Emeka Iweala
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Ogun State, 112212, Nigeria
- Dept of Biochemistry, Covenant University, Ota, Ogun State, 112212, Nigeria
| | - Benedikt Brors
- Applied Bioinformatics Division, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Ezekiel Adebiyi
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, 112212, Nigeria
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Ogun State, 112212, Nigeria
- Dept Computer & Information Sciences, Covenant University, Ota, Ogun State, 112212, Nigeria
- Applied Bioinformatics Division, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
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Adam Y, Sadeeq S, Kumuthini J, Ajayi O, Wells G, Solomon R, Ogunlana O, Adetiba E, Iweala E, Brors B, Adebiyi E. Polygenic Risk Score in African populations: progress and challenges. F1000Res 2023; 11:175. [PMID: 37273966 PMCID: PMC10233318 DOI: 10.12688/f1000research.76218.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/10/2023] [Indexed: 11/23/2023] Open
Abstract
Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects single nucleotide polymorphisms (SNPs) that contribute to the disease with low effect size making it more precise at individual level risk prediction. PRS analysis addresses the shortfall of GWAS by taking into account the SNPs/alleles with low effect size but play an indispensable role to the observed phenotypic/trait variance. PRS analysis has applications that investigate the genetic basis of several traits, which includes rare diseases. However, the accuracy of PRS analysis depends on the genomic data of the underlying population. For instance, several studies show that obtaining higher prediction power of PRS analysis is challenging for non-Europeans. In this manuscript, we review the conventional PRS methods and their application to sub-Saharan African communities. We conclude that lack of sufficient GWAS data and tools is the limiting factor of applying PRS analysis to sub-Saharan populations. We recommend developing Africa-specific PRS methods and tools for estimating and analyzing African population data for clinical evaluation of PRSs of interest and predicting rare diseases.
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Affiliation(s)
- Yagoub Adam
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, 112212, Nigeria
| | - Suraju Sadeeq
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Ogun State, 112212, Nigeria
- Dept Computer & Information Sciences, Covenant University, Ota, Ogun State, 112212, Nigeria
| | - Judit Kumuthini
- South African National Bioinformatics Institute, Life Sciences Building, University of Western Cape, Cape Town, South Africa
- Centre for Proteomic and Genomic Research, Cape Town, Western Cape, South Africa
| | - Olabode Ajayi
- South African National Bioinformatics Institute, Life Sciences Building, University of Western Cape, Cape Town, South Africa
- Centre for Proteomic and Genomic Research, Cape Town, Western Cape, South Africa
| | - Gordon Wells
- South African National Bioinformatics Institute, Life Sciences Building, University of Western Cape, Cape Town, South Africa
- Centre for Proteomic and Genomic Research, Cape Town, Western Cape, South Africa
| | - Rotimi Solomon
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, 112212, Nigeria
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Ogun State, 112212, Nigeria
- Dept of Biochemistry, Covenant University, Ota, Ogun State, 112212, Nigeria
| | - Olubanke Ogunlana
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, 112212, Nigeria
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Ogun State, 112212, Nigeria
- Dept of Biochemistry, Covenant University, Ota, Ogun State, 112212, Nigeria
| | - Emmanuel Adetiba
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Ogun State, 112212, Nigeria
- Dept of Electrical & Information Engineering (EIE), Covenant University, Ota, Ogun State, 112212, Nigeria
- HRA, Institute for Systems Science, Durban University of Technology, Durban, South Africa
| | - Emeka Iweala
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Ogun State, 112212, Nigeria
- Dept of Biochemistry, Covenant University, Ota, Ogun State, 112212, Nigeria
| | - Benedikt Brors
- Applied Bioinformatics Division, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Ezekiel Adebiyi
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, 112212, Nigeria
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Ogun State, 112212, Nigeria
- Dept Computer & Information Sciences, Covenant University, Ota, Ogun State, 112212, Nigeria
- Applied Bioinformatics Division, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
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Limonova AS, Ershova AI, Kiseleva AV, Ramensky VE, Vyatkin YV, Kutsenko VA, Meshkov AN, Drapkina OM. Assessment of polygenic risk of hypertension. КАРДИОВАСКУЛЯРНАЯ ТЕРАПИЯ И ПРОФИЛАКТИКА 2023. [DOI: 10.15829/1728-8800-2022-3464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Hypertension (HTN) is a leading risk factor for the development of cardiovascular diseases. In recent decades, the rapid development of genetic tests, in particular genome-wide association study (GWAS), has made it possible to identify hundreds of nucleotide sequence variants associated with the development of HTN. One approach to improve the predictive power of genetic testing is to combine information about many nucleotide sequence variants into a single risk assessment system, often referred to as a genetic risk score. Within the framework of this review, the most significant publications on the study of the genetic risk score for HTN will be considered, and the features of their development and application will be discussed.
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Affiliation(s)
- A. S. Limonova
- National Medical Research Center for Therapy and Preventive Medicine
| | - A. I. Ershova
- National Medical Research Center for Therapy and Preventive Medicine
| | - A. V. Kiseleva
- National Medical Research Center for Therapy and Preventive Medicine
| | - V. E. Ramensky
- National Medical Research Center for Therapy and Preventive Medicine; Lomonosov Moscow State University
| | - Yu. V. Vyatkin
- National Medical Research Center for Therapy and Preventive Medicine; Novosibirsk National Research State University
| | - V. A. Kutsenko
- National Medical Research Center for Therapy and Preventive Medicine; Faculty of Mechanics and Mathematics, Lomonosov Moscow State University
| | - A. N. Meshkov
- National Medical Research Center for Therapy and Preventive Medicine; Pirogov Russian National Research Medical University
| | - O. M. Drapkina
- National Medical Research Center for Therapy and Preventive Medicine
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Affiliation(s)
- Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore,Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom,National Skin Centre, Singapore,Correspondence: Prof Marie Loh, Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore. E-mail:
| | - John Campbell Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore,Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
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Dib MJ, Ahmadi KR, Zagkos L, Gill D, Morris B, Elliott P, Dehghan A, Tzoulaki I. Associations of Genetically Predicted Vitamin B 12 Status across the Phenome. Nutrients 2022; 14:5031. [PMID: 36501061 PMCID: PMC9740080 DOI: 10.3390/nu14235031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 11/16/2022] [Accepted: 11/24/2022] [Indexed: 11/29/2022] Open
Abstract
Variation in vitamin B12 levels has been associated with a range of diseases across the life-course, the causal nature of which remains elusive. We aimed to interrogate genetically predicted vitamin B12 status in relation to a plethora of clinical outcomes available in the UK Biobank. Genome-wide association study (GWAS) summary data obtained from a Danish and Icelandic cohort of 45,576 individuals were used to identify 8 genetic variants associated with vitamin B12 levels, serving as genetic instruments for vitamin B12 status in subsequent analyses. We conducted a Mendelian randomisation (MR)-phenome-wide association study (PheWAS) of vitamin B12 status with 945 distinct phenotypes in 439,738 individuals from the UK Biobank using these 8 genetic instruments to proxy alterations in vitamin B12 status. We used external GWAS summary statistics for replication of significant findings. Correction for multiple testing was taken into consideration using a 5% false discovery rate (FDR) threshold. MR analysis identified an association between higher genetically predicted vitamin B12 status and lower risk of vitamin B deficiency (including all B vitamin deficiencies), serving as a positive control outcome. We further identified associations between higher genetically predicted vitamin B12 status and a reduced risk of megaloblastic anaemia (OR = 0.35, 95% CI: 0.20-0.50) and pernicious anaemia (0.29, 0.19-0.45), which was supported in replication analyses. Our study highlights that higher genetically predicted vitamin B12 status is potentially protective of risk of vitamin B12 deficiency associated with pernicious anaemia diagnosis, and reduces risk of megaloblastic anaemia. The potential use of genetically predicted vitamin B12 status in disease diagnosis, progression and management remains to be investigated.
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Affiliation(s)
- Marie-Joe Dib
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London SW7 2BX, UK
- British Heart Foundation Centre of Excellence, Imperial College London, London SW7 2BX, UK
| | - Kourosh R. Ahmadi
- Department of Nutritional Sciences, School of Biosciences and Medicine, University of Surrey, Guildford GU2 7XH, UK
| | - Loukas Zagkos
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London SW7 2BX, UK
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London SW7 2BX, UK
| | - Brooke Morris
- Baylor Biology Department, Baylor University, Waco, TX 76706, USA
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London SW7 2BX, UK
- British Heart Foundation Centre of Excellence, Imperial College London, London SW7 2BX, UK
- Dementia Research Centre, Imperial College London, London SW7 2BX, UK
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London SW7 2BX, UK
- British Heart Foundation Centre of Excellence, Imperial College London, London SW7 2BX, UK
- Dementia Research Centre, Imperial College London, London SW7 2BX, UK
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London SW7 2BX, UK
- British Heart Foundation Centre of Excellence, Imperial College London, London SW7 2BX, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina 45110, Greece
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Li J, Abedi V, Zand R. Dissecting Polygenic Etiology of Ischemic Stroke in the Era of Precision Medicine. J Clin Med 2022; 11:jcm11205980. [PMID: 36294301 PMCID: PMC9604604 DOI: 10.3390/jcm11205980] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 10/05/2022] [Accepted: 10/07/2022] [Indexed: 12/03/2022] Open
Abstract
Ischemic stroke (IS), the leading cause of death and disability worldwide, is caused by many modifiable and non-modifiable risk factors. This complex disease is also known for its multiple etiologies with moderate heritability. Polygenic risk scores (PRSs), which have been used to establish a common genetic basis for IS, may contribute to IS risk stratification for disease/outcome prediction and personalized management. Statistical modeling and machine learning algorithms have contributed significantly to this field. For instance, multiple algorithms have been successfully applied to PRS construction and integration of genetic and non-genetic features for outcome prediction to aid in risk stratification for personalized management and prevention measures. PRS derived from variants with effect size estimated based on the summary statistics of a specific subtype shows a stronger association with the matched subtype. The disruption of the extracellular matrix and amyloidosis account for the pathogenesis of cerebral small vessel disease (CSVD). Pathway-specific PRS analyses confirm known and identify novel etiologies related to IS. Some of these specific PRSs (e.g., derived from endothelial cell apoptosis pathway) individually contribute to post-IS mortality and, together with clinical risk factors, better predict post-IS mortality. In this review, we summarize the genetic basis of IS, emphasizing the application of methodologies and algorithms used to construct PRSs and integrate genetics into risk models.
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Affiliation(s)
- Jiang Li
- Department of Molecular and Functional Genomics, Weis Center for Research, Geisinger Health System, Danville, PA 17822, USA
| | - Vida Abedi
- Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, Hershey, PA 17033, USA
- Correspondence: (V.A.); (R.Z.)
| | - Ramin Zand
- Department of Neurology, College of Medicine, The Pennsylvania State University, Hershey, PA 17033, USA
- Neuroscience Institute, Geisinger Health System, 100 North Academy Avenue, Danville, PA 17822, USA
- Correspondence: (V.A.); (R.Z.)
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Kivioja A, Toivonen E, Tyrmi J, Ruotsalainen S, Ripatti S, Huhtala H, Jääskeläinen T, Heinonen S, Kajantie E, Kere J, Kivinen K, Pouta A, Saarela T, Laivuori H. Increased Risk of Preeclampsia in Women With a Genetic Predisposition to Elevated Blood Pressure. Hypertension 2022; 79:2008-2015. [PMID: 35862124 PMCID: PMC9370253 DOI: 10.1161/hypertensionaha.122.18996] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 06/07/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Preeclampsia causes significant maternal and perinatal morbidity. Genetic factors seem to affect the onset of the disease. We aimed to investigate whether the polygenic risk score for blood pressure (BP; BP-PRS) is associated with preeclampsia, its subtypes, and BP values during pregnancy. METHODS The analyses were performed in the FINNPEC study (Finnish Genetics of Pre-Eclampsia Consortium) cohort of 1514 preeclamptic and 983 control women. In a case-control setting, the data were divided into percentiles to compare women with high BP-PRS (HBP-PRS; >95th percentile) or low BP-PRS (≤5th percentile) to others. Furthermore, to evaluate the effect of BP-PRS on BP, we studied 3 cohorts: women with preeclampsia, hypertensive controls, and normotensive controls. RESULTS BP values were higher in women with HBP-PRS throughout the pregnancy. Preeclampsia was more common in women with HBP-PRS compared with others (71.8% and 60.1%, respectively; P=0.009), and women with low BP-PRS presented with preeclampsia less frequently than others (44.8% and 61.5%, respectively; P<0.001). HBP-PRS was associated with an increased risk for preeclampsia (odds ratio, 1.7 [95% CI, 1.1-2.5]). Furthermore, women with HBP-PRS presented with recurrent preeclampsia and preeclampsia with severe features more often. CONCLUSIONS Our results suggest that HBP-PRS is associated with an increased risk of preeclampsia, recurrent preeclampsia, and preeclampsia with severe features. Furthermore, women with HBP-PRS present higher BP values during pregnancy. The results strengthen the evidence pointing toward the role of genetic variants associated with BP regulation in the etiology of preeclampsia, especially its more severe forms.
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Affiliation(s)
- Anna Kivioja
- Department of Obstetrics and Gynecology, Tampere University Hospital, Finland (A.K., E.T., H.L.)
- Center for Child, Adolescent, and Maternal Health, Faculty of Medicine and Health Technology (A.K., E.T., J.T., H.L.), Tampere University, Finland
| | - Elli Toivonen
- Department of Obstetrics and Gynecology, Tampere University Hospital, Finland (A.K., E.T., H.L.)
- Center for Child, Adolescent, and Maternal Health, Faculty of Medicine and Health Technology (A.K., E.T., J.T., H.L.), Tampere University, Finland
| | - Jaakko Tyrmi
- Center for Child, Adolescent, and Maternal Health, Faculty of Medicine and Health Technology (A.K., E.T., J.T., H.L.), Tampere University, Finland
- Computational Medicine, Faculty of Medicine (J.T.), University of Oulu, Finland
- Center for Life Course Health Research, Faculty of Medicine (J.T.), University of Oulu, Finland
- Biocenter Oulu (J.T.), University of Oulu, Finland
| | - Sanni Ruotsalainen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science (S. Ruotsalainen, S. Ripatti, K.K., H.L.), University of Helsinki, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science (S. Ruotsalainen, S. Ripatti, K.K., H.L.), University of Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA (S. Ripatti)
| | - Heini Huhtala
- Faculty of Social Sciences (H.H.), Tampere University, Finland
| | - Tiina Jääskeläinen
- Medical and Clinical Genetics (T.J., H.L.), University of Helsinki and Helsinki University Hospital, Finland
| | - Seppo Heinonen
- Obsterics and Gynaecology (S.H.), University of Helsinki and Helsinki University Hospital, Finland
| | - Eero Kajantie
- PEDEGO Research Unit, Medical Research Center Oulu, Oulu University Hospital (E.K., A.P.), University of Oulu, Finland
- Children’s Hospital (E.K.), University of Helsinki and Helsinki University Hospital, Finland
- Public Health Promotion Unit (E.K.), University of Helsinki and Helsinki University Hospital, Finland
- Department of Clinical and Molecular Medicine, Norwegian University of Health and Technology, Trondheim, Norway (E.K.)
| | - Juha Kere
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden (J.K.)
| | - Katja Kivinen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science (S. Ruotsalainen, S. Ripatti, K.K., H.L.), University of Helsinki, Finland
| | - Anneli Pouta
- PEDEGO Research Unit, Medical Research Center Oulu, Oulu University Hospital (E.K., A.P.), University of Oulu, Finland
- Department of Government Services (A.P.), National Institute for Health and Welfare, Helsinki, Finland
| | - Tanja Saarela
- Department of Clinical Genetics, Kuopio University Hospital, Finland (T.S.)
| | - Hannele Laivuori
- Center for Child, Adolescent, and Maternal Health, Faculty of Medicine and Health Technology (A.K., E.T., J.T., H.L.), Tampere University, Finland
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science (S. Ruotsalainen, S. Ripatti, K.K., H.L.), University of Helsinki, Finland
- Medical and Clinical Genetics (T.J., H.L.), University of Helsinki and Helsinki University Hospital, Finland
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Schnurr TM, Katz SF, Justesen JM, O’Sullivan JW, Saliba‐Gustafsson P, Assimes TL, Carcamo‐Orive I, Ahmed A, Ashley EA, Hansen T, Knowles JW. Interactions of physical activity, muscular fitness, adiposity, and genetic risk for NAFLD. Hepatol Commun 2022; 6:1516-1526. [PMID: 35293152 PMCID: PMC9234625 DOI: 10.1002/hep4.1932] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 02/01/2022] [Accepted: 02/19/2022] [Indexed: 11/22/2022] Open
Abstract
Genetic predisposition and unhealthy lifestyle are risk factors for nonalcoholic fatty liver disease (NAFLD). We investigated whether the genetic risk of NAFLD is modified by physical activity, muscular fitness, and/or adiposity. In up to 242,524 UK Biobank participants without excessive alcohol intake or known liver disease, we examined cross-sectional interactions and joint associations of physical activity, muscular fitness, body mass index (BMI), and a genetic risk score (GRS) with alanine aminotransferase (ALT) levels and the proxy definition for suspected NAFLD of ALT levels > 30 U/L in women and >40 U/L in men. Genetic predisposition to NAFLD was quantified using a GRS consisting of 68 loci known to be associated with chronically elevated ALT. Physical activity was assessed using accelerometry, and muscular fitness was estimated by measuring handgrip strength. We found that increased physical activity and grip strength modestly attenuate genetic predisposition to elevation in ALT levels, whereas higher BMI markedly amplifies it (all p values < 0.001). Among those with normal weight and high level of physical activity, the odds of suspected NAFLD were 1.6-fold higher in those with high versus low genetic risk (reference group). In those with high genetic risk, the odds of suspected NAFLD were 12-fold higher in obese participants with low physical activity versus those with normal weight and high physical activity (odds ratio for NAFLD = 19.2 and 1.6, respectively, vs. reference group). Conclusion: In individuals with high genetic predisposition for NAFLD, maintaining a normal body weight and increased physical activity may reduce the risk of NAFLD.
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Affiliation(s)
- Theresia M. Schnurr
- Department of MedicineDivision of Cardiovascular Medicine and Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
- Novo Nordisk Foundation Center for Basic Metabolic ResearchUniversity of CopenhagenKobenhavnDenmark
| | - Sophia Figueroa Katz
- Department of MedicineDivision of Cardiovascular Medicine and Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
- Cleveland Clinic Lerner College of Medicine of Case Western Reserve UniversityClevelandOhioUSA
| | - Johanne M. Justesen
- Department of MedicineDivision of Cardiovascular Medicine and Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
- Novo Nordisk Foundation Center for Basic Metabolic ResearchUniversity of CopenhagenKobenhavnDenmark
| | - Jack W. O’Sullivan
- Department of MedicineDivision of Cardiovascular Medicine and Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
| | - Peter Saliba‐Gustafsson
- Department of MedicineDivision of Cardiovascular Medicine and Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
- Cardiovascular Medicine UnitDepartment of MedicineCenter for Molecular Medicine at BioClinicumKarolinska University HospitalKarolinska InstitutetStockholmSweden
| | - Themistocles L. Assimes
- Department of MedicineDivision of Cardiovascular Medicine and Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
- VA Palo Alto Health Care SystemPalo AltoCaliforniaUSA
| | - Ivan Carcamo‐Orive
- Department of MedicineDivision of Cardiovascular Medicine and Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
- Stanford Diabetes Research CenterStanfordCaliforniaUSA
| | - Aijaz Ahmed
- Division of Gastroenterology and HepatologyStanford University School of MedicineStanfordCaliforniaUSA
| | - Euan A. Ashley
- Department of MedicineDivision of Cardiovascular Medicine and Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
- Department of GeneticsStanford UniversityStanfordCaliforniaUSA
- Department of Biomedical Data ScienceStanford UniversityStanfordCaliforniaUSA
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic ResearchUniversity of CopenhagenKobenhavnDenmark
| | - Joshua W. Knowles
- Department of MedicineDivision of Cardiovascular Medicine and Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
- Stanford Diabetes Research CenterStanfordCaliforniaUSA
- Stanford Prevention Research CenterStanfordCaliforniaUSA
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Jakovljevic A, Jacimovic J, Georgiou AC, Nikolic N, Aminoshariae A, van der Waal SV, Nagendrababu V. Single nucleotide polymorphisms as a predisposing factor for the development of apical periodontitis-An umbrella review. Int Endod J 2022; 55:700-713. [PMID: 35476797 DOI: 10.1111/iej.13756] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 04/23/2022] [Accepted: 04/25/2022] [Indexed: 12/26/2022]
Abstract
BACKGROUND The interaction between heredity and different environmental factors in the modification of apical periodontitis (AP) susceptibility and prediction of its progression remain poorly elucidated. OBJECTIVES This umbrella review aimed to (i) analyse the available relevant systematic reviews in an attempt to determine the association between genotype and allelic distribution of different single-nucleotide polymorphisms (SNPs) and the development of AP, (ii) report deficiencies and gaps in knowledge in this area and (iii) present recommendations to conduct future clinical studies and systematic reviews. METHODS A literature search was conducted using Clarivate Analytics' Web of Science, Scopus, PubMed and Cochrane Database of Systematic Reviews, from inception to October 2021, with no language restrictions, including a grey literature search. Systematic reviews with/without meta-analysis evaluating genotype and allelic distribution of different SNPs between adult patients with/ without AP were included. All other type of studies were excluded. The methodological quality was assessed using the A MeaSurement Tool to Assess systematic Reviews (AMSTAR)-2 tool. Two independent reviewers were involved in study selection, data extraction and appraising the included reviews; disagreements were resolved by a third reviewer. RESULTS The current study includes five systematic reviews. Three reviews performed meta-analysis. Three reviews were graded by AMSTAR 2 as 'critically low' quality, whereas the other two were graded as 'low' and 'moderate' quality. Two reviews indicated that carriers of specific genotypes and alleles of tumour necrosis factor-alpha (TNF-α) -308 G > A and interleukin 1-beta (IL-1β) + 3954 C/T gene polymorphisms are more susceptible to an acute and persistent form of AP. However, high heterogeneity was observed. DISCUSSION The statistical heterogeneity within included systematic reviews was a consequence of clinical and methodological diversity amongst primary studies. Although some of the included reviews suggested that carriers of specific genotype and/or allele of TNF-α -308 G > A and IL-1β + 3954 C/T SNPs are more susceptible to AP, their conclusions should be interpreted with caution. CONCLUSIONS No candidate genes could be identified as a definitive genetic risk or protective factor for the development and progression of AP, and further high-quality genome-wide association studies are warranted.
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Affiliation(s)
- Aleksandar Jakovljevic
- Department of Pathophysiology, School of Dental Medicine, University of Belgrade, Belgrade, Serbia
| | - Jelena Jacimovic
- Central Library, School of Dental Medicine, University of Belgrade, Belgrade, Serbia
| | - Athina Christina Georgiou
- Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam, University of Amsterdam and Vrije Universiteit, Amsterdam, the Netherlands
- Department of Endodontics, Academic Centre for Dentistry Amsterdam, University of Amsterdam and Vrije Universiteit, Amsterdam, the Netherlands
| | - Nadja Nikolic
- Laboratory for Basic Science, School of Dental Medicine, University of Belgrade, Belgrade, Serbia
| | - Anita Aminoshariae
- Department of Endodontics, School of Dental Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Suzette V van der Waal
- Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam, University of Amsterdam and Vrije Universiteit, Amsterdam, the Netherlands
- Department of Endodontics, Academic Centre for Dentistry Amsterdam, University of Amsterdam and Vrije Universiteit, Amsterdam, the Netherlands
| | - Venkateshbabu Nagendrababu
- Department of Preventive and Restorative Dentistry, College of Dental Medicine, University of Sharjah, Sharjah, UAE
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Sun C, Xu J, Tao J, Dong Y, Chen H, Jia Z, Ma Y, Zhang M, Wei S, Tang G, Lyu H, Jiang Y. Mobile-Based and Self-Service Tool (iPed) to Collect, Manage, and Visualize Pedigree Data: Development Study. JMIR Form Res 2022; 6:e36914. [PMID: 35737451 PMCID: PMC9264120 DOI: 10.2196/36914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 05/15/2022] [Accepted: 06/06/2022] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Pedigree data (family history) are indispensable for genetics studies and the assessment of individuals' disease susceptibility. With the popularity of genetics testing, the collection of pedigree data is becoming more common. However, it can be time-consuming, laborious, and tedious for clinicians to investigate all pedigree data for each patient. A self-service robot could inquire about patients' family history in place of professional clinicians or genetic counselors. OBJECTIVE The aim of this study was to develop a mobile-based and self-service tool to collect and visualize pedigree data, not only for professionals but also for those who know little about genetics. METHODS There are 4 main aspects in the iPed construction, including interface building, data processing, data storage, and data visualization. The user interface was built using HTML, JavaScript libraries, and Cascading Style Sheets (version 3; Daniel Eden). Processing of the submitted data is carried out by PHP programming language. MySQL is used to document and manage the pedigree data. PHP calls the R script to accomplish the visualization. RESULTS iPed is freely available to all users through the iPed website. No software is required to be installed, no pedigree files need to be prepared, and no knowledge of genetics or programs is required. The users can easily complete their pedigree data collection and visualization on their own and through a dialogue with iPed. Meanwhile, iPed provides a database that stores all users' information. Therefore, when the users need to construct new pedigree trees for other genetic traits or modify the pedigree trees that have already been created, unnecessary duplication of operations can be avoided. CONCLUSIONS iPed is a mobile-based and self-service tool that could be used by both professionals and nonprofessionals at any time and from any place. It reduces the amount of time required to collect, manage, and visualize pedigree data.
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Affiliation(s)
- Chen Sun
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Jing Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Junxian Tao
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yu Dong
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Haiyan Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Zhe Jia
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yingnan Ma
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Mingming Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Siyu Wei
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Guoping Tang
- The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Hongchao Lyu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yongshuai Jiang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
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Stroke and Etiopathogenesis: What Is Known? Genes (Basel) 2022; 13:genes13060978. [PMID: 35741740 PMCID: PMC9222702 DOI: 10.3390/genes13060978] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 05/13/2022] [Accepted: 05/17/2022] [Indexed: 02/05/2023] Open
Abstract
Background: A substantial portion of stroke risk remains unexplained, and a contribution from genetic factors is supported by recent findings. In most cases, genetic risk factors contribute to stroke risk as part of a multifactorial predisposition. A major challenge in identifying the genetic determinants of stroke is fully understanding the complexity of the phenotype. Aims: Our narrative review is needed to improve our understanding of the biological pathways underlying the disease and, through this understanding, to accelerate the identification of new drug targets. Methods: We report, the research in the literature until February 2022 in this narrative review. The keywords are stroke, causes, etiopathogenesis, genetic, epigenetic, ischemic stroke. Results: While better risk prediction also remains a long-term goal, its implementation is still complex given the small effect-size of genetic risk variants. Some authors encourage the use of stroke genetic panels for stroke risk assessment and further stroke research. In addition, new biomarkers for the genetic causes of stroke and new targets for gene therapy are on the horizon. Conclusion: We summarize the latest evidence and perspectives of ischemic stroke genetics that may be of interest to the physician and useful for day-to-day clinical work in terms of both prevention and treatment of ischemic stroke.
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Johansen M, Joensen S, Restorff M, Stórá T, Christy D, Gustavsson EK, Bian J, Guo Y, Farrer MJ, Petersen MS. Polygenic risk of Alzheimer's disease in the Faroe Islands. Eur J Neurol 2022; 29:2192-2200. [PMID: 35384166 DOI: 10.1111/ene.15351] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 04/01/2022] [Indexed: 11/28/2022]
Abstract
INTRODUCTION The Faroe Islands are a geographically isolated population in the North Atlantic with a similar prevalence Alzheimer's disease (AD) and all cause dementia as other European nations. However, the genetic risk underlying Alzheimer's disease and other dementia susceptibility has yet to be elucidated. METHODS Forty-nine single nucleotide polymorphisms (SNPs) were genotyped in 174 patients with AD and other dementias and 159 healthy controls. Single variant and polygenic risk score (PRS) associations, with/without APOE variability, were assessed by logistic regression. Performance was examined using receiver operating characteristics 'area under the curve' analysis (ROC AUC). RESULTS APOE rs429358 was associated with AD in the Faroese cohort after correction for multiple testing (OR=6.32, CI[3.98-10.05], p=6.31e-15 ), with suggestive evidence for three other variants: NECTIN2 rs41289512 (OR 2.05, CI[1.20-3.51], p=0.01), HLA-DRB1 rs6931277 (OR 0.67, CI[0.48-0.94], p=0.02), and APOE rs7412 [ε2] (OR 0.28, CI[0.11-0.73], p=0.01). PRS were associated with AD with or without the inclusion of APOE (PRS+APOE OR=4.5. CI[2.90-5.85, p=4.56e-15 and PRS-APOE OR=1.53, CI[1.21-1.98], p=6.82e-4 ). AD ROC AUC analyses demonstrated a PRS+APOE AUC=80.3% and PRS-APOE AUC=63.4%. However, PRS+APOE was also significantly associated with all cause dementia (OR=3.39, CI[2.51-4.71], p= 2.50e-14 ) with an AUC=76.9%, i.e. all cause dementia did show similar results albeit less significant. DISCUSSION In the Faroe Islands, SNP analyses highlighted APOE and immunogenomic variability in AD and dementia risk. PRS+APOE , based on 25 SNPs/loci, had excellent sensitivity and specificity for Alzheimer's disease with AUC of 80.3%. High PRS were also associated with an earlier onset of late-onset AD.
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Affiliation(s)
- Malan Johansen
- Center of Health Science, University of the Faroe Islands, Vestarabryggja 15, Tórshavn, Faroe Islands.,Department of Occupational Medicine and Public Health, The Faroese Hospital System, Sigmundargøta 5, Tórshavn, Faroe Islands
| | - Sofus Joensen
- The Dementia Clinic, Psychiatric Center, National Hospital of the Faroe Islands, J. C. Svabos gøta 41-49, Tórshavn, Faroe Islands
| | - Marjun Restorff
- The Dementia Clinic, Psychiatric Center, National Hospital of the Faroe Islands, J. C. Svabos gøta 41-49, Tórshavn, Faroe Islands
| | - Tórmóður Stórá
- The Dementia Clinic, Psychiatric Center, National Hospital of the Faroe Islands, J. C. Svabos gøta 41-49, Tórshavn, Faroe Islands
| | - Darren Christy
- Centre for Applied Neurogenetics, University of British Columbia, C201-4500 Oak Street, Vancouver, BC, Canada
| | - Emil K Gustavsson
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, 30 Guilford Street, London, UK.,Department of Neurodegenerative Disease, Institute of Neurology, University College London, Queen Square, London, UK
| | - Jiang Bian
- Department of Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, 2004 Mowry RD, Gainesville, FL, USA
| | - Yi Guo
- Department of Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, 2004 Mowry RD, Gainesville, FL, USA
| | - Matthew J Farrer
- Centre for Applied Neurogenetics, University of British Columbia, C201-4500 Oak Street, Vancouver, BC, Canada.,McKnight Brain Institute, Department of Neurology, University of Florida, 1149 Newell Drive, Gainesville, FL, USA
| | - Maria Skaalum Petersen
- Center of Health Science, University of the Faroe Islands, Vestarabryggja 15, Tórshavn, Faroe Islands.,Department of Occupational Medicine and Public Health, The Faroese Hospital System, Sigmundargøta 5, Tórshavn, Faroe Islands
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