Polygenic Score Data (PGS)

Latest ReleaseApril 2018 (V2.0)
Data AlertsNone reported for this product

Complex health outcomes or behaviors of interest to the research community are often highly polygenic, or reflect the aggregate effect of many different genes so the use of single genetic variants or candidate genes may not capture the dynamic nature of more complex phenotypes. A polygenic score (PGS) aggregates millions of individual loci across the human genome and weights them by the strength of their association to produce a single quantitative measure of genetic risk. This maximizes statistical power when modeling gene-environment (G x E) interactions.

PGS for a variety of phenotypes have been constructed as part of this public data release for HRS respondents who provided salivary DNA between 2006 and 2012. These scores will help harmonize research across studies. PGS for each phenotype are based on a single, replicated genome-wide association study (GWAS). These scores will be updated as sufficiently large GWAS are published for new phenotypes or as meta-analyses for existing phenotypes are updated.

Phenotype of GWAS meta-analysis GWAS meta-analysis citation Release 1
(May 2017)
Release 2
(April 2018)
Educational Attainment 2*Okbay (SSGAC, 2016)12006-2012
Height Wood (GIANT, 2014)22006-20102006-2012
Body Mass Index (BMI)Locke (GIANT, 2015)32006-20102006-2012
Waist Circumference (WC)Shungin (GIANT, 2015)42006-20102006-2012
Waist-to-Hip Ratio (WHR)Shungin (GIANT, 2015)42006-20102006-2012
Diastolic Blood Pressure (DBP)Ehret (ICBP, 2011)52006-2010Removed, see section II. H. in documentation
Systolic Blood Pressure (SBP)Ehret (ICBP, 2011)52006-2010Removed, see section II. H. in documentation
Pulse Pressure (PP)Wain (ICBP, 2011)62006-2010Removed, see section II. H. in documentation
Mean Arterial Pressure (MAP)Wain (ICBP, 2011)62006-2010Removed, see section II. H. in documentation
Alzheimer's Disease (AD)Lambert (IGAP, 2013)72006-20102006-2012
General Cognition*Davies (CHARGE, 2015)82006-20102006-2012
SchizophreniaRipke (PGC, 2014)92006-20102006-2012
Smoking Initiation (ever/never)Furberg (TAG, 2010)102006-20102006-2012
Subjective Wellbeing*Okbay (SSGAC, 2016)112006-20102006-2012
Neuroticism*Okbay (SSGAC, 2016)122006-20102006-2012
Depressive Symptoms*Okbay (SSGAC, 2016)132006-20102006-2012
Longevity*Broer (CHARGE, 2015)142006-2012
Number of Cigarettes Smoked per Day (CPD)Furberg (TAG, 2010)152006-2012
Coronary Artery Disease (CAD)Schunkert (CARDIoGRAM, 2011)162006-2012
Myocardial Infarction (MI)Nikpay (CARDIoGRAMplusC4D, 2015)172006-2012
Type II Diabetes (T2D)Morris (DIAGRAM, 2012)182006-2012
Attention Deficit/Hyperactivity Disorder (ADHD) PGC 2010Neale (PGC, 2010)192006-2012
Attention Deficit/Hyperactivity Disorder (ADHD) PGC 2017Demontis (PGC, 2017)202006-2012
Autism Anney (PGC, 2017)212006-2012
Bipolar Disorder (BIP)Sklar (PGC, 2011)222006-2012
Mental health cross disorderSmoller (PGC, 2013)232006-2012
Age at MenarchePerry (ReproGen, 2014)242006-2012
Age at MenopausePerry (ReproGen, 2014)242006-2012
Plasma CortisolBolton (CORNET, 2014)252006-2012
Major Depressive Disorder (MDD)Ripke (PGC, 2013)262006-2012
Extraversionvan den Berg (GPC, 2016)272006-2012

* The GWAS Meta-analysis was re-analyzed without the HRS cohort to produce weights independent of the HRS contribution.

References

  1. Okbay (SSGAC, 2016) Okbay A, Beauchamp, JP, Fontana, MA, Lee, JJ, Pers, TH, Rietveld, CA, ... & Oskarsson, S (2016). Genome-wide association study identifies 74 loci associated with educational attainment, Nature, 533(7604), 539.
  2. Wood (GIANT, 2014) Wood AR, Esko, T, Yang, J, Vedantam, S, Pers, TH, Gustafsson, S, ... & Amin, N (2014). Defining the role of common variation in the genomic and biological architecture of adult human height, Nature Genetics, 46(11), 1173-1186.
  3. Locke (GIANT, 2015) Locke AE, Kahali, B, Berndt, SI, Justice, AE, Pers, TH, Day, FR, ... & Croteau-chonka, DC (2015). Genetic studies of body mass index yield new insights for obesity biology, Nature, 518(7538), 197-206.
  4. Shungin (GIANT, 2015) Shungin D, Winkler, TW, Croteau-Chonka, DC, Ferreira, T, Locke, AE, Mägi, R, ... & Workalemahu, T (2015). New genetic loci link adipose and insulin biology to body fat distribution, Nature, 518(7538), 187.
  5. Ehret (ICBP, 2011) Ehret GB, Munroe, PB, Rice, KM, Bochud, M, Johnson, AD, Chasman, DI, ... & Okamura, T (2011). Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk, Nature, 478(7367), 103-109.
  6. Wain (ICBP, 2011) Wain LV, Verwoert, GC, O'Reilly, PF, Shi, G, Johnson, T, Johnson, AD, ... & Ehret, GB (2011). Genome-wide association study identifies six new loci influencing pulse pressure and mean arterial pressure, Nature Genetics, 43(10), 1005-1011.
  7. Lambert (IGAP, 2013) Lambert JC, Ibrahim-Verbaas CA, Harold D, et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease, Nature Genetics, 2013;45(12):1452-1458.
  8. Davies (CHARGE, 2015) Davies G, Armstrong, N, Bis JC, Bressler J, Chouraki V, Giddaluru S, ... & Van Der Lee SJ (2015). Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N= 53,949). Molecular Psychiatry, 20(2), 183
  9. Ripke (PGC, 2014) Ripke S, Neale BM, Corvin A, Walters JT, Farh KH, Holmans PA, ... & Pers, TH (2014). Biological insights from 108 schizophrenia-associated genetic loci, Nature, 511(7510), 421-427.
  10. Furberg (TAG, 2010) Tobacco and Genetics Consortium(2010). Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nature Genetics, 42(5), 441-447.
  11. Okbay (SSGAC, 2016) Okbay A, Baselmans BM, De Neve JE, Turley P, Nivard MG, Fontana MA, ... & Gratten J (2016). Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nature Genetics, 48(6), 624-633.
  12. Okbay (SSGAC, 2016) Okbay A, Baselmans BM, De Neve JE, Turley P, Nivard MG, Fontana MA, ... & Gratten J (2016). Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nature Genetics, 48(6), 624-633.
  13. Okbay (SSGAC, 2016) Okbay A, Baselmans BM, De Neve JE, Turley P, Nivard MG, Fontana MA, ... & Gratten J (2016). Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nature Genetics, 48(6), 624-633.
  14. Broer (CHARGE, 2015) Broer L, Buchman AS, Deelen J, Evans DS, Faul JD, Lunetta KL, ... & Yu L (2014). GWAS of longevity in CHARGE consortium confirms APOE and FOXO3 candidacy. Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences, 70(1), 110-118.
  15. Furberg (TAG, 2010) Tobacco and Genetics Consortium(2010)Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nature Genetics, 42(5), 441-447.
  16. Schunkert (CARDIoGRAM, 2011) Schunkert H, König IR, Kathiresan S, Reilly MP, Assimes TL, Holm H, ... & Absher D (2011). Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nature Genetics, 43(4), 333-338.
  17. Nikpay (CARDIoGRAMplusC4D, 2015) CARDIoGRAMplusC4D Consortium (2015). A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nature Genetics, 47(10), 1121-1130.
  18. Morris (DIAGRAM, 2012) Morris AP, Voight BF, Teslovich TM, Ferreira T, Segre AV, Steinthorsdottir V, ... & Prokopenko I (2012). Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes, Nature Genetics, 44(9), 981-990.
  19. Neale (PGC, 2010) Neale BM, Medland SE, Ripke S, Asherson P, Franke B, Lesch KP, ... & Daly M (2010). Meta-analysis of genome-wide association studies of attention-deficit/hyperactivity disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 49(9), 884-897.
  20. Demontis (PGC, 2017) Demontis D, Walters RK, Martin J, Mattheisen M, Als TD, Agerbo E, ... & Neale BM (2017). Discovery Of The First Genome-Wide Significant Risk Loci For ADHDBioRxiv. https://doi.org/10.1101/145581.
  21. Anney (PGC, 2017) Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium, Anney RJ, Ripke S, Anttila V, Grove J, Holmans P, ... & Neale B (2017). Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q2432 and a significant overlap with schizophrenia. Molecular Autism, 8, 1-17.
  22. Sklar (PGC, 2011) Psychiatric GWAS Consortium Bipolar Disorder Working Group (2011). Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4, Nature Genetics, 43(10), 977-983.
  23. Smoller (PGC, 2013) Cross-Disorder Group of the Psychiatric Genomics Consortium (2013). Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. The Lancet, 381(9875), 1371-1379."
  24. Perry (ReproGen, 2014) Perry JR, Day F, Elks CE, Sulem P, Thompson DJ, Ferreira T, ... & Albrecht E (2014). Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche, Nature, 514(7520), 92-97.
  25. Bolton (CORNET, 2014) Bolton JL, Hayward C, Direk N, Lewis JG, Hammond GL, Hill LA, ... & Rudan I (2014). Genome wide association identifies common variants at the SERPINA6/SERPINA1 locus influencing plasma cortisol and corticosteroid binding globulinPLoS. Genetics, 10(7), e1004474.
  26. Ripke (PGC, 2013) Ripke S, Wray NR, Lewis CM, Hamilton SP, Weissman MM, Breen G, ... & Heath AC (2013). A mega-analysis of genome-wide association studies for major depressive disorder. Molecular Psychiatry, 18(4), 497-511.
  27. van den Berg (GPC, 2016) van den Berg SM, de Moor MHM, Verweij KJH, Krueger RF, Luciano M, Arias Vasquez A, ... & Boomsma DI (2016). Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium. Behavior Genetics, 46(2), 170-182 https://doi.org/10.1007/s10519-015-9735-5.