Polygenic indexes

Our Aim

We aim to generate and make polygenic indexes (PGI) available for all CLS cohorts using a standardised pipeline which is transparent, efficient, and updatable. Our approach to sharing these data seeks to balance the need to make data available to enable research with the ethical need to avoid potential risks.

PGI will be derived for multiple health and social traits (below), and made available on the UKDS via special license agreement.

We are aiming for a full release of the PGI in 2025, though this is dependent on internal capacity. We will email genetics data applicants when the data are available. For further updates please email clsdata@ucl.ac.uk.

In the interim, we have a selection of PGI that can be obtained via application to the CLS DAC (see Introduction). These PGI are available for the NCDS, BCS, Next Steps, and MCS (parents and children).

Current PGI available via the DAC (last updated 31/03/2025)

Forthcoming additional PGI for full release

Anthropometrics

Brain structure and cognition

Health behaviours

Mental health

Personality

Physical health

Social outcomes

References

Aragam, K. G., Jiang, T., Goel, A., Kanoni, S., Wolford, B. N., Atri, D. S., Weeks, E. M., Wang, M., Hindy, G., Zhou, W., Grace, C., Roselli, C., Marston, N. A., Kamanu, F. K., Surakka, I., Venegas, L. M., Sherliker, P., Koyama, S., Ishigaki, K., … CARDIoGRAMplusC4D Consortium. 2022. Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants. Nature Genetics, 5412, 1803–1815. https://doi.org/10.1038/s41588-022-01233-6

Baselmans, B. M. L., Jansen, R., Ip, H. F., van Dongen, J., Abdellaoui, A., van de Weijer, M. P., Bao, Y., Smart, M., Kumari, M., Willemsen, G., Hottenga, J. J., BIOS consortium, Social Science Genetic Association Consortium, Boomsma, D. I., de Geus, E. J. C., Nivard, M. G., & Bartels, M. (2019). Multivariate genome-wide analyses of the well-being spectrum. Nature genetics, 51(3), 445–451. https://doi.org/10.1038/s41588-018-0320-8

Bellenguez, C., Küçükali, F., Jansen, I. E., Kleineidam, L., Moreno-Grau, S., Amin, N., Naj, A. C., Campos-Martin, R., Grenier-Boley, B., Andrade, V., Holmans, P. A., Boland, A., Damotte, V., van der Lee, S. J., Costa, M. R., Kuulasmaa, T., Yang, Q., de Rojas, I., Bis, J. C., … et al. 2022. New insights into the genetic etiology of Alzheimer’s disease and related dementias. Nature Genetics, 544, 412–436. https://doi.org/10.1038/s41588-022-01024-z

Bi, W., Fritsche, L. G., Mukherjee, B., Kim, S., & Lee, S. 2020. A Fast and Accurate Method for Genome-Wide Time-to-Event Data Analysis and Its Application to UK Biobank. American Journal of Human Genetics, 1072, 222–233. https://doi.org/10.1016/j.ajhg.2020.06.003

Chiou, J., Geusz, R. J., Okino, M.-L., Han, J. Y., Miller, M., Melton, R., Beebe, E., Benaglio, P., Huang, S., Korgaonkar, K., Heller, S., Kleger, A., Preissl, S., Gorkin, D. U., Sander, M., & Gaulton, K. J. 2021. Interpreting type 1 diabetes risk with genetics and single-cell epigenomics. Nature, 5947863, 398–402. https://doi.org/10.1038/s41586-021-03552-w

Christakoudi, S., Evangelou, E., Riboli, E., & Tsilidis, K. K. 2021. GWAS of allometric body-shape indices in UK Biobank identifies loci suggesting associations with morphogenesis, organogenesis, adrenal cell renewal and cancer. Scientific Reports, 111, 10688. https://doi.org/10.1038/s41598-021-89176-6

Cole, J. B., Florez, J. C., & Hirschhorn, J. N. 2020. Comprehensive genomic analysis of dietary habits in UK Biobank identifies hundreds of genetic associations. Nature Communications, 111, 1467. https://doi.org/10.1038/s41467-020-15193-0

Day, F. R., Thompson, D. J., Helgason, H., Chasman, D. I., Finucane, H., Sulem, P., Ruth, K. S., Whalen, S., Sarkar, A. K., Albrecht, E., Altmaier, E., Amini, M., Barbieri, C. M., Boutin, T., Campbell, A., Demerath, E., Giri, A., He, C., Hottenga, J. J., … et al. 2017. Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk. Nature Genetics, 496, 834–841. https://doi.org/10.1038/ng.3841

Demontis, D., Walters, G. B., Athanasiadis, G., Walters, R., Therrien, K., Nielsen, T. T., Farajzadeh, L., Voloudakis, G., Bendl, J., Zeng, B., Zhang, W., Grove, J., Als, T. D., Duan, J., Satterstrom, F. K., Bybjerg-Grauholm, J., Bækved-Hansen, M., Gudmundsson, O. O., Magnusson, S. H., … Børglum, A. D. 2023. Genome-wide analyses of ADHD identify 27 risk loci, refine the genetic architecture and implicate several cognitive domains. Nature Genetics, 552, 198–208. https://doi.org/10.1038/s41588-022-01285-8

Downie, C. G., Dimos, S. F., Bien, S. A., Hu, Y., Darst, B. F., Polfus, L. M., Wang, Y., Wojcik, G. L., Tao, R., Raffield, L. M., Armstrong, N. D., Polikowsky, H. G., Below, J. E., Correa, A., Irvin, M. R., Rasmussen-Torvik, L. J. F., Carlson, C. S., Phillips, L. S., Liu, S., … Highland, H. M. 2022. Multi-ethnic GWAS and fine-mapping of glycaemic traits identify novel loci in the PAGE Study. Diabetologia, 653, 477–489. https://doi.org/10.1007/s00125-021-05635-9

Forstner, A. J., Awasthi, S., Wolf, C., Maron, E., Erhardt, A., Czamara, D., Eriksson, E., Lavebratt, C., Allgulander, C., Friedrich, N., Becker, J., Hecker, J., Rambau, S., Conrad, R., Geiser, F., McMahon, F. J., Moebus, S., Hess, T., Buerfent, B. C., … Schumacher, J. 2021. Genome-wide association study of panic disorder reveals genetic overlap with neuroticism and depression. Molecular Psychiatry, 268, 4179–4190. https://doi.org/10.1038/s41380-019-0590-2

Grove, J., Ripke, S., Als, T. D., Mattheisen, M., Walters, R. K., Won, H., Pallesen, J., Agerbo, E., Andreassen, O. A., Anney, R., Awashti, S., Belliveau, R., Bettella, F., Buxbaum, J. D., Bybjerg-Grauholm, J., Bækvad-Hansen, M., Cerrato, F., Chambert, K., Christensen, J. H., … Børglum, A. D. 2019. Identification of common genetic risk variants for autism spectrum disorder. Nature Genetics, 513, 431–444. https://doi.org/10.1038/s41588-019-0344-8

Gupta, P., Galimberti, M., Liu, Y., Beck, S., Wingo, A., Wingo, T., Adhikari, K., Kranzler, H. R., VA Million Veteran Program, Stein, M. B., Gelernter, J., & Levey, D. F. 2024. A genome-wide investigation into the underlying genetic architecture of personality traits and overlap with psychopathology. Nature Human Behaviour. https://doi.org/10.1038/s41562-024-01951-3

Han, Y., Jia, Q., Jahani, P. S., Hurrell, B. P., Pan, C., Huang, P., Gukasyan, J., Woodward, N. C., Eskin, E., Gilliland, F. D., Akbari, O., Hartiala, J. A., & Allayee, H. 2020. Genome-wide analysis highlights contribution of immune system pathways to the genetic architecture of asthma. Nature Communications, 111, 1776. https://doi.org/10.1038/s41467-020-15649-3

Hatoum, A. S., Colbert, S. M. C., Johnson, E. C., Huggett, S. B., Deak, J. D., Pathak, G., Jennings, M. V., Paul, S. E., Karcher, N. R., Hansen, I., Baranger, D. A. A., Edwards, A., Grotzinger, A., Substance Use Disorder Working Group of the Psychiatric Genomics Consortium, Tucker-Drob, E. M., Kranzler, H. R., Davis, L. K., Sanchez-Roige, S., Polimanti, R., … Agrawal, A. 2023. Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders. Nature. Mental Health, 13, 210–223. https://doi.org/10.1038/s44220-023-00034-y

Hill, W. D., Davies, N. M., Ritchie, S. J., Skene, N. G., Bryois, J., Bell, S., Di Angelantonio, E., Roberts, D. J., Xueyi, S., Davies, G., Liewald, D. C. M., Porteous, D. J., Hayward, C., Butterworth, A. S., McIntosh, A. M., Gale, C. R., & Deary, I. J. 2019. Genome-wide analysis identifies molecular systems and 149 genetic loci associated with income. Nature Communications, 101, 5741. https://doi.org/10.1038/s41467-019-13585-5

Howard, D. M., Adams, M. J., Clarke, T.-K., Hafferty, J. D., Gibson, J., Shirali, M., Coleman, J. R. I., Hagenaars, S. P., Ward, J., Wigmore, E. M., Alloza, C., Shen, X., Barbu, M. C., Xu, E. Y., Whalley, H. C., Marioni, R. E., Porteous, D. J., Davies, G., Deary, I. J., … McIntosh, A. M. 2019. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nature Neuroscience, 223, 343–352. https://doi.org/10.1038/s41593-018-0326-7

Ishigaki, K., Sakaue, S., Terao, C., Luo, Y., Sonehara, K., Yamaguchi, K., Amariuta, T., Too, C. L., Laufer, V. A., Scott, I. C., Viatte, S., Takahashi, M., Ohmura, K., Murasawa, A., Hashimoto, M., Ito, H., Hammoudeh, M., Emadi, S. A., Masri, B. K., … Raychaudhuri, S. 2022. Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis. Nature Genetics, 5411, 1640–1651. https://doi.org/10.1038/s41588-022-01213-w

Jones, G., Trajanoska, K., Santanasto, A.J. et al. Genome-wide meta-analysis of muscle weakness identifies 15 susceptibility loci in older men and women. Nat Commun 12, 654 (2021). https://doi.org/10.1038/s41467-021-20918-w

Karlsson Linnér, R., Mallard, T.T., Barr, P.B. et al. Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction. Nat Neurosci 24, 1367–1376 (2021). https://doi.org/10.1038/s41593-021-00908-3

Keaton, J. M., Kamali, Z., Xie, T., Vaez, A., Williams, A., Goleva, S. B., Ani, A., Evangelou, E., Hellwege, J. N., Yengo, L., Young, W. J., Traylor, M., Giri, A., Zheng, Z., Zeng, J., Chasman, D. I., Morris, A. P., Caulfield, M. J., Hwang, S.-J., … Warren, H. R. 2024. Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits. Nature Genetics, 565, 778–791. https://doi.org/10.1038/s41588-024-01714-w

Koskeridis, F., Evangelou, E., Said, S., Boyle, J. J., Elliott, P., Dehghan, A., & Tzoulaki, I. 2022. Pleiotropic genetic architecture and novel loci for C-reactive protein levels. Nature Communications, 131, 6939. https://doi.org/10.1038/s41467-022-34688-6

Lee, J.J., Wedow, R., Okbay, A. et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet 50, 1112–1121 (2018). https://doi.org/10.1038/s41588-018-0147-3

Liu, M., Jiang, Y., Wedow, R., Li, Y., Brazel, D. M., Chen, F., Datta, G., Davila-Velderrain, J., McGuire, D., Tian, C., Zhan, X., 23andMe Research Team, HUNT All-In Psychiatry, Choquet, H., Docherty, A. R., Faul, J. D., Foerster, J. R., Fritsche, L. G., Gabrielsen, M. E., … Vrieze, S. 2019. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use. Nature Genetics, 512, 237–244. https://doi.org/10.1038/s41588-018-0307-5

Liu, N., Zhang, L., Tian, T., Cheng, J., Zhang, B., Qiu, S., Geng, Z., Cui, G., Zhang, Q., Liao, W., Yu, Y., Zhang, H., Gao, B., Xu, X., Han, T., Yao, Z., Qin, W., Liu, F., Liang, M., … CHIMGEN Consortium. 2023. Cross-ancestry genome-wide association meta-analyses of hippocampal and subfield volumes. Nature Genetics, 557, 1126–1137. https://doi.org/10.1038/s41588-023-01425-8

Mullins, N., Forstner, A. J., O’Connell, K. S., Coombes, B., Coleman, J. R. I., Qiao, Z., Als, T. D., Bigdeli, T. B., Børte, S., Bryois, J., Charney, A. W., Drange, O. K., Gandal, M. J., Hagenaars, S. P., Ikeda, M., Kamitaki, N., Kim, M., Krebs, K., Panagiotaropoulou, G., … et al. 2021. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology. Nature Genetics, 536, 817–829. https://doi.org/10.1038/s41588-021-00857-4

Nalls, M. A., Blauwendraat, C., Vallerga, C. L., Heilbron, K., Bandres-Ciga, S., Chang, D., Tan, M., Kia, D. A., Noyce, A. J., Xue, A., Bras, J., Young, E., von Coelln, R., Simón-Sánchez, J., Schulte, C., Sharma, M., Krohn, L., Pihlstrøm, L., Siitonen, A., … International Parkinson’s Disease Genomics Consortium. 2019. Identification of novel risk loci, causal insights, and heritable risk for Parkinson’s disease: a meta-analysis of genome-wide association studies. Lancet Neurology, 1812, 1091–1102. https://doi.org/10.1016/S1474-44221930320-5

Okbay, A., Wu, Y., Wang, N., Jayashankar, H., Bennett, M., Nehzati, S. M., Sidorenko, J., Kweon, H., Goldman, G., Gjorgjieva, T., Jiang, Y., Hicks, B., Tian, C., Hinds, D. A., Ahlskog, R., Magnusson, P. K. E., Oskarsson, S., Hayward, C., Campbell, A., … Young, A. I. 2022. Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals. Nature Genetics, 544, 437–449. https://doi.org/10.1038/s41588-022-01016-z

Pilling, L. C., Kuo, C.-L., Sicinski, K., Tamosauskaite, J., Kuchel, G. A., Harries, L. W., Herd, P., Wallace, R., Ferrucci, L., & Melzer, D. 2017. Human longevity: 25 genetic loci associated in 389,166 UK biobank participants. Aging, 912, 2504–2520. https://doi.org/10.18632/aging.101334

Pulit, S. L., Stoneman, C., Morris, A. P., Wood, A. R., Glastonbury, C. A., Tyrrell, J., … & Lindgren, C. M. (2019). Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Human molecular genetics, 28(1), 166-174.

Ruth, K. S., Day, F. R., Hussain, J., Martínez-Marchal, A., Aiken, C. E., Azad, A., Thompson, D. J., Knoblochova, L., Abe, H., Tarry-Adkins, J. L., Gonzalez, J. M., Fontanillas, P., Claringbould, A., Bakker, O. B., Sulem, P., Walters, R. G., Terao, C., Turon, S., Horikoshi, M., … et al. 2021. Genetic insights into biological mechanisms governing human ovarian ageing. Nature, 5967872, 393–397. https://doi.org/10.1038/s41586-021-03779-7

Savage, J. E., Jansen, P. R., Stringer, S., Watanabe, K., Bryois, J., de Leeuw, C. A., Nagel, M., Awasthi, S., Barr, P. B., Coleman, J. R. I., Grasby, K. L., Hammerschlag, A. R., Kaminski, J. A., Karlsson, R., Krapohl, E., Lam, M., Nygaard, M., Reynolds, C. A., Trampush, J. W., … Posthuma, D. 2018. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nature Genetics, 507, 912–919. https://doi.org/10.1038/s41588-018-0152-6

Sinnott-Armstrong, N., Tanigawa, Y., Amar, D., Mars, N., Benner, C., Aguirre, M., Venkataraman, G. R., Wainberg, M., Ollila, H. M., Kiiskinen, T., Havulinna, A. S., Pirruccello, J. P., Qian, J., Shcherbina, A., FinnGen, Rodriguez, F., Assimes, T. L., Agarwala, V., Tibshirani, R., … Rivas, M. A. 2021. Genetics of 35 blood and urine biomarkers in the UK Biobank. Nature Genetics, 532, 185–194. https://doi.org/10.1038/s41588-020-00757-z

Suzuki, K., Hatzikotoulas, K., Southam, L., Taylor, H. J., Yin, X., Lorenz, K. M., Mandla, R., Huerta-Chagoya, A., Melloni, G. E. M., Kanoni, S., Rayner, N. W., Bocher, O., Arruda, A. L., Sonehara, K., Namba, S., Lee, S. S. K., Preuss, M. H., Petty, L. E., Schroeder, P., … et al. 2024. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. Nature, 6278003, 347–357. https://doi.org/10.1038/s41586-024-07019-6

Timmers, P. R., Mounier, N., Lall, K., Fischer, K., Ning, Z., Feng, X., Bretherick, A. D., Clark, D. W., eQTLGen Consortium, Shen, X., Esko, T., Kutalik, Z., Wilson, J. F., & Joshi, P. K. 2019. Genomics of 1 million parent lifespans implicates novel pathways and common diseases and distinguishes survival chances. ELife, 8. https://doi.org/10.7554/eLife.39856

Trubetskoy, V., Pardiñas, A. F., Qi, T., Panagiotaropoulou, G., Awasthi, S., Bigdeli, T. B., Bryois, J., Chen, C.-Y., Dennison, C. A., Hall, L. S., Lam, M., Watanabe, K., Frei, O., Ge, T., Harwood, J. C., Koopmans, F., Magnusson, S., Richards, A. L., Sidorenko, J., … et al. 2022. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature, 6047906, 502–508. https://doi.org/10.1038/s41586-022-04434-5

Vogelezang, S., Bradfield, J. P., Ahluwalia, T. S., Curtin, J. A., Lakka, T. A., Grarup, N., Scholz, M., van der Most, P. J., Monnereau, C., Stergiakouli, E., Heiskala, A., Horikoshi, M., Fedko, I. O., Vilor-Tejedor, N., Cousminer, D. L., Standl, M., Wang, C. A., Viikari, J., Geller, F., … Felix, J. F. 2020. Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits. PLoS Genetics, 1610, e1008718. https://doi.org/10.1371/journal.pgen.1008718

Warrington, N. M., Beaumont, R. N., Horikoshi, M., Day, F. R., Helgeland, Ø., Laurin, C., Bacelis, J., Peng, S., Hao, K., Feenstra, B., Wood, A. R., Mahajan, A., Tyrrell, J., Robertson, N. R., Rayner, N. W., Qiao, Z., Moen, G.-H., Vaudel, M., Marsit, C. J., … et al. 2019. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors. Nature Genetics, 515, 804–814. https://doi.org/10.1038/s41588-019-0403-1

Yengo, L., Sidorenko, J., Kemper, K. E., Zheng, Z., Wood, A. R., Weedon, M. N., Frayling, T. M., Hirschhorn, J., Yang, J., Visscher, P. M., & GIANT Consortium. 2018. Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry. Human Molecular Genetics, 2720, 3641–3649. https://doi.org/10.1093/hmg/ddy271