Polygenic Score Data (PGS)

Latest ReleaseOctober 2018 (V3.0)
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)
Release 3
(October 2018)
Educational Attainment 2* Okbay (SSGAC, 2016)1 2006-2012 2006-2012
Height Wood (GIANT, 2014)2 2006-2010 2006-2012 2006-2012
Body Mass Index (BMI)** Locke (GIANT, 2015)3 2006-2010 2006-2012 2006-2012
Waist Circumference (WC) Shungin (GIANT, 2015)4 2006-2010 2006-2012 2006-2012
Waist-to-Hip Ratio (WHR) Shungin (GIANT, 2015)4 2006-2010 2006-2012 2006-2012
Diastolic Blood Pressure (DBP) Ehret (ICBP, 2011)5 2006-2010 Removed, see section II. H. in documentation
Systolic Blood Pressure (SBP) Ehret (ICBP, 2011)5 2006-2010 Removed, see section II. H. in documentation
Pulse Pressure (PP) Wain (ICBP, 2011)6 2006-2010 Removed, see section II. H. in documentation
Mean Arterial Pressure (MAP) Wain (ICBP, 2011)6 2006-2010 Removed, see section II. H. in documentation
Alzheimer's Disease (AD) Lambert (IGAP, 2013)7 2006-2010 2006-2012 2006-2012
General Cognition* Davies (CHARGE, 2015)8 2006-2010 2006-2012 2006-2012
Schizophrenia Ripke (PGC, 2014)9 2006-2010 2006-2012 2006-2012
Smoking Initiation (ever/never) Furberg (TAG, 2010)10 2006-2010 2006-2012 2006-2012
Subjective Wellbeing* Okbay (SSGAC, 2016)11 2006-2010 2006-2012 2006-2012
Neuroticism* Okbay (SSGAC, 2016)12 2006-2010 2006-2012 2006-2012
Depressive Symptoms* Okbay (SSGAC, 2016)13 2006-2010 2006-2012 2006-2012
Longevity* Broer (CHARGE, 2015)14 2006-2012 2006-2012
Number of Cigarettes Smoked per Day (CPD) Furberg (TAG, 2010)15 2006-2012 2006-2012
Coronary Artery Disease (CAD) Schunkert (CARDIoGRAM, 2011)16 2006-2012 2006-2012
Myocardial Infarction (MI) Nikpay (CARDIoGRAMplusC4D, 2015)17 2006-2012 2006-2012
Type II Diabetes (T2D) Morris (DIAGRAM, 2012)18 2006-2012 2006-2012
Attention Deficit/Hyperactivity Disorder (ADHD) PGC 2010 Neale (PGC, 2010)19 2006-2012 2006-2012
Attention Deficit/Hyperactivity Disorder (ADHD) PGC 2017 Demontis (PGC, 2017)20 2006-2012 2006-2012
Autism Anney (PGC, 2017)21 2006-2012 2006-2012
Bipolar Disorder (BIP) Sklar (PGC, 2011)22 2006-2012 2006-2012
Mental health cross disorder Smoller (PGC, 2013)23 2006-2012 2006-2012
Age at Menarche Perry (ReproGen, 2014)24 2006-2012 2006-2012
Age at Menopause Day (ReproGen, 2015)25 2006-2012 2006-2012
Plasma Cortisol Bolton (CORNET, 2014)26 2006-2012 2006-2012
Major Depressive Disorder (MDD) Ripke (PGC, 2013)27 2006-2012 2006-2012
Extraversion van den Berg (GPC, 2016)28 2006-2012 2006-2012
Antisocial Behavior Tielbeek (BROAD, 2017)29 2006-2012
Educational Attainment 3* Lee (SSGAC, 2018)30 2006-2012
Obsessive Compulsive Disorder (OCD) (IOCDF-GC and OCGAS, 2017)31 2006-2012
Age at first birth (combined, female, male) Barban (Sociogenome, 2016)32 2006-2012
Number children ever born (combined, female, male) Barban (Sociogenome, 2016)33 2006-2012
Major Depressive Disorder 2 (MDD2) Wray (PGC, 2018)34 2006-2012
Post Traumatic Stress Disorder (PTSD: combined, European, African) Duncan (PGC, 2018)35 2006-2012
High Density Lipoprotein (HDL) Willer (GLGC, 2013)36 2006-2012
Low Density Lipoprotein (LDL) Willer (GLGC, 2013)37 2006-2012
Total Cholesterol (TC) Willer (GLGC, 2013)38 2006-2012
Anxiety (factor score, case-control) Otowa (ANGST, 2016)39 2006-2012

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

**The GWAS Meta-analysis includes HRS and has not been re-run without the HRS

All other GWAS did not include HRS

References

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  2. 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 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 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 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.
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  7. 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.
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  12. 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 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 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. Tobacco and Genetics Consortium(2010)Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nature Genetics, 42(5), 441-447.
  16. 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. 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 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 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 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. 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. 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. 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 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.
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  26. 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.
  27. 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.
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