1
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Beck JJ, Slunecka JL, Johnson BN, Van Asselt AJ, Finnicum CT, Ageton C, Krie A, Nickles H, Cowan K, Maxwell J, Boomsma DI, de Geus E, Ehli EA, Hottenga JJ. Breast Cancer Polygenic Risk Score Validation and Effects of Variable Imputation. Cancers (Basel) 2024; 16:1578. [PMID: 38672660 PMCID: PMC11048743 DOI: 10.3390/cancers16081578] [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: 02/29/2024] [Revised: 03/30/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
Breast cancer (BC) is a complex disease affecting one in eight women in the USA. Advances in population genomics have led to the development of polygenic risk scores (PRSs) with the potential to augment current risk models, but replication is often limited. We evaluated 2 robust PRSs with 313 and 3820 SNPs and the effects of multiple genotype imputation replications in BC cases and control populations. Biological samples from BC cases and cancer-free controls were drawn from three European ancestry cohorts. Genotyping on the Illumina Global Screening Array was followed by stringent quality control measures and 20 genotype imputation replications. A total of 468 unrelated cases and 4337 controls were scored, revealing significant differences in mean PRS percentiles between cases and controls (p < 0.001) for both SNP sets (313-SNP PRS: 52.81 and 48.07; 3820-SNP PRS: 55.45 and 49.81), with receiver operating characteristic curve analysis showing area under the curve values of 0.596 and 0.603 for the 313-SNP and 3820-SNP PRS, respectively. PRS fluctuations (from ~2-3% up to 9%) emerged across imputation iterations. Our study robustly reaffirms the predictive capacity of PRSs for BC by replicating their performance in an independent BC population and showcases the need to average imputed scores for reliable outcomes.
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Affiliation(s)
- Jeffrey J. Beck
- Avera Genetics, Avera McKennan Hospital & University Health Center, Sioux Falls, SD 57105, USA (E.A.E.)
| | - John L. Slunecka
- Avera Genetics, Avera McKennan Hospital & University Health Center, Sioux Falls, SD 57105, USA (E.A.E.)
| | - Brandon N. Johnson
- Avera Genetics, Avera McKennan Hospital & University Health Center, Sioux Falls, SD 57105, USA (E.A.E.)
| | - Austin J. Van Asselt
- Avera Genetics, Avera McKennan Hospital & University Health Center, Sioux Falls, SD 57105, USA (E.A.E.)
| | - Casey T. Finnicum
- Avera Genetics, Avera McKennan Hospital & University Health Center, Sioux Falls, SD 57105, USA (E.A.E.)
| | | | - Amy Krie
- Avera Cancer Institute, Sioux Falls, SD 57105, USA
| | | | - Kenneth Cowan
- Fred and Pamela Buffet Cancer Center and Eppley Institute for Research in Cancer at University of Nebraska Medical Center, Omaha, NE 68105, USA
| | - Jessica Maxwell
- Fred and Pamela Buffet Cancer Center and Eppley Institute for Research in Cancer at University of Nebraska Medical Center, Omaha, NE 68105, USA
| | - Dorret I. Boomsma
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands (J.-J.H.)
| | - Eco de Geus
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands (J.-J.H.)
| | - Erik A. Ehli
- Avera Genetics, Avera McKennan Hospital & University Health Center, Sioux Falls, SD 57105, USA (E.A.E.)
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands (J.-J.H.)
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2
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Hubers N, Hagenbeek FA, Pool R, Déjean S, Harms AC, Roetman PJ, van Beijsterveldt CEM, Fanos V, Ehli EA, Vermeiren RRJM, Bartels M, Hottenga JJ, Hankemeier T, van Dongen J, Boomsma DI. Integrative multi-omics analysis of genomic, epigenomic, and metabolomics data leads to new insights for Attention-Deficit/Hyperactivity Disorder. Am J Med Genet B Neuropsychiatr Genet 2024; 195:e32955. [PMID: 37534875 DOI: 10.1002/ajmg.b.32955] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 06/13/2023] [Accepted: 07/11/2023] [Indexed: 08/04/2023]
Abstract
The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out-of-sample prediction in NTR participants (N = 258, cases = 14.3%) and in a clinical sample (N = 145, cases = 51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD.
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Affiliation(s)
- Nikki Hubers
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Sébastien Déjean
- Toulouse Mathematics Institute, UMR 5219, University of Toulouse, CNRS, Toulouse, France
| | - Amy C Harms
- Division of Analytical Biosciences, Leiden Academic Center for Drug Research, Leiden University, Leiden, the Netherlands
- The Netherlands Metabolomics Centre, Leiden, The Netherlands
| | - Peter J Roetman
- LUMC-Curium, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Vassilios Fanos
- Department of Surgical Sciences, University of Cagliari and Neonatal Intensive Care Unit, Cagliari, Italy
| | - Erik A Ehli
- Avera Institute for Human Genetics, Sioux Falls, South Dakota, USA
| | - Robert R J M Vermeiren
- LUMC-Curium, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Leiden, the Netherlands
- Youz, Parnassia Group, the Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Thomas Hankemeier
- Division of Analytical Biosciences, Leiden Academic Center for Drug Research, Leiden University, Leiden, the Netherlands
- The Netherlands Metabolomics Centre, Leiden, The Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
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3
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Gordon SD, Duffy DL, Whiteman DC, Olsen CM, McAloney K, Adsett JM, Garden NA, Cross SM, List-Armitage SE, Brown J, Beck JJ, Mbarek H, Medland SE, Montgomery GW, Martin NG. GWAS of Dizygotic Twinning in an Enlarged Australian Sample of Mothers of DZ Twins. Twin Res Hum Genet 2023:1-12. [PMID: 37994447 DOI: 10.1017/thg.2023.45] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Female fertility is a complex trait with age-specific changes in spontaneous dizygotic (DZ) twinning and fertility. To elucidate factors regulating female fertility and infertility, we conducted a genome-wide association study (GWAS) on mothers of spontaneous DZ twins (MoDZT) versus controls (3273 cases, 24,009 controls). This is a follow-up study to the Australia/New Zealand (ANZ) component of that previously reported (Mbarek et al., 2016), with a sample size almost twice that of the entire discovery sample meta-analysed in the previous article (and five times the ANZ contribution to that), resulting from newly available additional genotyping and representing a significant increase in power. We compare analyses with and without male controls and show unequivocally that it is better to include male controls who have been screened for recent family history, than to use only female controls. Results from the SNP based GWAS identified four genomewide significant signals, including one novel region, ZFPM1 (Zinc Finger Protein, FOG Family Member 1), on chromosome 16. Previous signals near FSHB (Follicle Stimulating Hormone beta subunit) and SMAD3 (SMAD Family Member 3) were also replicated (Mbarek et al., 2016). We also ran the GWAS with a dominance model that identified a further locus ADRB2 on chr 5. These results have been contributed to the International Twinning Genetics Consortium for inclusion in the next GWAS meta-analysis (Mbarek et al., in press).
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Affiliation(s)
- Scott D Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - David L Duffy
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - David C Whiteman
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Catherine M Olsen
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Kerrie McAloney
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jessica M Adsett
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Natalie A Garden
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Simone M Cross
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | - Joy Brown
- Independent researcher, Invercargill, New Zealand
| | - Jeffrey J Beck
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, South Dakota, USA
| | | | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Grant W Montgomery
- Institute of Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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Beck JJ, Ahmed T, Finnicum CT, Zwinderman K, Ehli EA, Boomsma DI, Hottenga JJ. Genetic Ancestry Estimates within Dutch Family Units and Across Genotyping Arrays: Insights from Empirical Analysis Using Two Estimation Methods. Genes (Basel) 2023; 14:1497. [PMID: 37510400 PMCID: PMC10379078 DOI: 10.3390/genes14071497] [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: 06/13/2023] [Revised: 07/12/2023] [Accepted: 07/20/2023] [Indexed: 07/30/2023] Open
Abstract
Accurate inference of genetic ancestry is crucial for population-based association studies, accounting for population heterogeneity and structure. This study analyzes genome-wide SNP data from the Netherlands Twin Register to compare genetic ancestry estimates. The focus is on the comparison of ancestry estimates between family members and individuals genotyped on multiple arrays (Affymetrix 6.0, Affymetrix Axiom, and Illumina GSA). Two conventional methods, principal component analysis and ADMIXTURE, were implemented to estimate ancestry, each serving its specific purpose, rather than for direct comparison. The results reveal that as the degree of genetic relatedness decreases, the Euclidean distances of genetic ancestry estimates between family members significantly increase (empirical p < 0.001), regardless of the estimation method and genotyping array. Ancestry estimates among individuals genotyped on multiple arrays also show statistically significant differences (empirical p < 0.001). Additionally, this study investigates the relationship between the ancestry estimates of non-identical twin offspring with ancestrally diverse parents and those with ancestrally similar parents. The results indicate a statistically significant weak correlation between the variation in ancestry estimates among offspring and differences in ancestry estimates among parents (Spearman's rho: 0.07, p = 0.005). This study highlights the utility of current methods in inferring genetic ancestry, emphasizing the importance of reference population composition in determining ancestry estimates.
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Affiliation(s)
- Jeffrey J Beck
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD 57105, USA
| | - Talitha Ahmed
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
| | - Casey T Finnicum
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD 57105, USA
| | - Koos Zwinderman
- Department of Clinical Epidemiology, Biostatistics, and Bioinformatics, Academic Medical Center Amsterdam, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Public Health (APH) Research Institute, 1081 BT Amsterdam, The Netherlands
| | - Erik A Ehli
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD 57105, USA
| | - Dorret I Boomsma
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD 57105, USA
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
- Amsterdam Public Health (APH) Research Institute, 1081 BT Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
- Amsterdam Public Health (APH) Research Institute, 1081 BT Amsterdam, The Netherlands
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5
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Hagenbeek FA, van Dongen J, Pool R, Roetman PJ, Harms AC, Hottenga JJ, Kluft C, Colins OF, van Beijsterveldt CEM, Fanos V, Ehli EA, Hankemeier T, Vermeiren RRJM, Bartels M, Déjean S, Boomsma DI. Integrative Multi-omics Analysis of Childhood Aggressive Behavior. Behav Genet 2023; 53:101-117. [PMID: 36344863 PMCID: PMC9922241 DOI: 10.1007/s10519-022-10126-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 10/25/2022] [Indexed: 11/09/2022]
Abstract
This study introduces and illustrates the potential of an integrated multi-omics approach in investigating the underlying biology of complex traits such as childhood aggressive behavior. In 645 twins (cases = 42%), we trained single- and integrative multi-omics models to identify biomarkers for subclinical aggression and investigated the connections among these biomarkers. Our data comprised transmitted and two non-transmitted polygenic scores (PGSs) for 15 traits, 78,772 CpGs, and 90 metabolites. The single-omics models selected 31 PGSs, 1614 CpGs, and 90 metabolites, and the multi-omics model comprised 44 PGSs, 746 CpGs, and 90 metabolites. The predictive accuracy for these models in the test (N = 277, cases = 42%) and independent clinical data (N = 142, cases = 45%) ranged from 43 to 57%. We observed strong connections between DNA methylation, amino acids, and parental non-transmitted PGSs for ADHD, Autism Spectrum Disorder, intelligence, smoking initiation, and self-reported health. Aggression-related omics traits link to known and novel risk factors, including inflammation, carcinogens, and smoking.
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Affiliation(s)
- Fiona A. Hagenbeek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7-10, 1081 BT Amsterdam, The Netherlands ,Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7-10, 1081 BT Amsterdam, The Netherlands ,Amsterdam Public Health Research Institute, Amsterdam, The Netherlands ,Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7-10, 1081 BT Amsterdam, The Netherlands ,Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Peter J. Roetman
- Department of Child and Adolescent Psychiatry, LUMC-Curium, Leiden University Medical Center, Leiden, The Netherlands
| | - Amy C. Harms
- Division of Analytical Biosciences, Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands ,The Netherlands Metabolomics Centre, Leiden, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7-10, 1081 BT Amsterdam, The Netherlands
| | | | - Olivier F. Colins
- Department of Child and Adolescent Psychiatry, LUMC-Curium, Leiden University Medical Center, Leiden, The Netherlands ,Department Special Needs Education, Ghent University, Ghent, Belgium
| | | | - Vassilios Fanos
- Department of Surgical Sciences, University of Cagliari and Neonatal Intensive Care Unit, Cagliari, Italy
| | - Erik A. Ehli
- Avera Institute for Human Genetics, Sioux Falls, South Dakota USA
| | - Thomas Hankemeier
- Division of Analytical Biosciences, Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands ,The Netherlands Metabolomics Centre, Leiden, The Netherlands
| | - Robert R. J. M. Vermeiren
- Department of Child and Adolescent Psychiatry, LUMC-Curium, Leiden University Medical Center, Leiden, The Netherlands ,Youz, Parnassia Psychiatric Institute, The Hague, The Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7-10, 1081 BT Amsterdam, The Netherlands ,Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Sébastien Déjean
- Toulouse Mathematics Institute, University of Toulouse, CNRS, Toulouse, France
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7-10, 1081 BT Amsterdam, The Netherlands ,Amsterdam Public Health Research Institute, Amsterdam, The Netherlands ,Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
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6
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van der Laan CM, Morosoli-García JJ, van de Weijer SGA, Colodro-Conde L, Lupton MK, Mitchell BL, McAloney K, Parker R, Burns JM, Hickie IB, Pool R, Hottenga JJ, Martin NG, Medland SE, Nivard MG, Boomsma DI. Continuity of Genetic Risk for Aggressive Behavior Across the Life-Course. Behav Genet 2021; 51:592-606. [PMID: 34390460 PMCID: PMC8390412 DOI: 10.1007/s10519-021-10076-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 06/23/2021] [Indexed: 11/24/2022]
Abstract
We test whether genetic influences that explain individual differences in aggression in early life also explain individual differences across the life-course. In two cohorts from The Netherlands (N = 13,471) and Australia (N = 5628), polygenic scores (PGSs) were computed based on a genome-wide meta-analysis of childhood/adolescence aggression. In a novel analytic approach, we ran a mixed effects model for each age (Netherlands: 12-70 years, Australia: 16-73 years), with observations at the focus age weighted as 1, and decaying weights for ages further away. We call this approach a 'rolling weights' model. In The Netherlands, the estimated effect of the PGS was relatively similar from age 12 to age 41, and decreased from age 41-70. In Australia, there was a peak in the effect of the PGS around age 40 years. These results are a first indication from a molecular genetics perspective that genetic influences on aggressive behavior that are expressed in childhood continue to play a role later in life.
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Affiliation(s)
- Camiel M van der Laan
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands.
- The Netherlands Institute for the Study of Crime and Law Enforcement, Amsterdam, The Netherlands.
| | | | - Steve G A van de Weijer
- The Netherlands Institute for the Study of Crime and Law Enforcement, Amsterdam, The Netherlands
| | | | | | | | - Kerrie McAloney
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Richard Parker
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jane M Burns
- Faculty of Health Sciences, The University of Sydney, Sydney, Australia
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
| | - René Pool
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
| | - Jouke-Jan Hottenga
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
| | | | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Michel G Nivard
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
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Slunecka JL, van der Zee MD, Beck JJ, Johnson BN, Finnicum CT, Pool R, Hottenga JJ, de Geus EJC, Ehli EA. Implementation and implications for polygenic risk scores in healthcare. Hum Genomics 2021; 15:46. [PMID: 34284826 PMCID: PMC8290135 DOI: 10.1186/s40246-021-00339-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 06/11/2021] [Indexed: 12/15/2022] Open
Abstract
Increasing amounts of genetic data have led to the development of polygenic risk scores (PRSs) for a variety of diseases. These scores, built from the summary statistics of genome-wide association studies (GWASs), are able to stratify individuals based on their genetic risk of developing various common diseases and could potentially be used to optimize the use of screening and preventative treatments and improve personalized care for patients. Many challenges are yet to be overcome, including PRS validation, healthcare professional and patient education, and healthcare systems integration. Ethical challenges are also present in how this information is used and the current lack of diverse populations with PRSs available. In this review, we discuss the topics above and cover the nature of PRSs, visualization schemes, and how PRSs can be improved. With these tools on the horizon for multiple diseases, scientists, clinicians, health systems, regulatory bodies, and the public should discuss the uses, benefits, and potential risks of PRSs.
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Affiliation(s)
- John L Slunecka
- Avera Institute for Human Genetics, Avera McKennan & University Health Center, Sioux Falls, SD, USA.
| | - Matthijs D van der Zee
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jeffrey J Beck
- Avera Institute for Human Genetics, Avera McKennan & University Health Center, Sioux Falls, SD, USA
| | - Brandon N Johnson
- Avera Institute for Human Genetics, Avera McKennan & University Health Center, Sioux Falls, SD, USA
| | - Casey T Finnicum
- Avera Institute for Human Genetics, Avera McKennan & University Health Center, Sioux Falls, SD, USA
| | - René Pool
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Erik A Ehli
- Avera Institute for Human Genetics, Avera McKennan & University Health Center, Sioux Falls, SD, USA
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8
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Abstract
Here we provide an update of the 2013 report on the Nigerian Twin and Sibling Registry (NTSR). The major aim of the NTSR is to understand genetic and environmental influences and their interplay in psychological and mental health development in Nigerian children and adolescents. Africans have the highest twin birth rates among all human populations, and Nigeria is the most populous country in Africa. Due to its combination of large population and high twin birth rates, Nigeria has one of the largest twin populations in the world. In this article, we provide current updates on the NTSR samples recruited, recruitment procedures, zygosity assessment and findings emerging from the NTSR.
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9
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Avera Twin Register Growing Through Online Consenting and Survey Collection. Twin Res Hum Genet 2019; 22:686-690. [DOI: 10.1017/thg.2019.73] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
AbstractThe aim of the Avera Twin Register (ATR) is to establish a prospective longitudinal repository of twins, multiples, siblings and family members’ biological samples to study environmental and genetic influences on health and disease. Also, it is our intention to contribute to international genome-wide association study (GWAS) twin consortia when appropriate sample size is achieved within the ATR. The ATR is young compared with existing registers and continues to collect a longitudinal repository of biological specimens, survey data and health information. Data and biological specimens were originally collected via face-to-face appointments or the postal department and consisted of paper-informed consents and questionnaires. Enrollment of the ATR began on May 18, 2016 and is located in Sioux Falls, South Dakota, a rural and frontier area in the Central United States with a regional population of approximately 880,000. The original target area for the ATR was South Dakota and the four surrounding states: Minnesota, Iowa, North Dakota and Nebraska. The ATR has found a need to expand that area based on twin and multiple siblings who live in various areas surrounding these states. A description of the state of the ATR today and its transition to online data collection and informed consent will be presented. The ATR collects longitudinal data on lifestyle, including diet and activity levels, aging, plus complex traits and diseases. All twins and multiples participating in the ATR are genotyped on the Illumina Global Screening Array and receive zygosity results.
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