Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-03T00:21:50.329Z Has data issue: false hasContentIssue false
  • English
  • Français

Multifactorial disorders and polygenic risk scores: predicting common diseases and the possibility of adverse selection in life and protection insurance

Published online by Cambridge University Press:  14 August 2020

Jessye M. Maxwell ,
Richard A. Russell ,
Hei Man Wu ,
Natasha Sharapova ,
Peter Banthorpe ,
Paul F O’Reilly  and
Cathryn M Lewis
Jessye M. Maxwell
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK
Richard A. Russell
Affiliation:
Global Research and Data Analytics, RGA Reinsurance Company, London, UK
Hei Man Wu
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, New York, NY, USA
Natasha Sharapova
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK
Peter Banthorpe
Affiliation:
Global Research and Data Analytics, RGA Reinsurance Company, London, UK
Paul F O’Reilly
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, New York, NY, USA
Cathryn M Lewis*
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK Department of Medical and Molecular Genetics, King’s College London, London, UK
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

During the past decade, genetics research has allowed scientists and clinicians to explore the human genome in detail and reveal many thousands of common genetic variants associated with disease. Genetic risk scores, known as polygenic risk scores (PRSs), aggregate risk information from the most important genetic variants into a single score that describes an individual’s genetic predisposition to a given disease. This article reviews recent developments in the predictive utility of PRSs in relation to a person’s susceptibility to breast cancer and coronary artery disease. Prognostic models for these disorders are built using data from the UK Biobank, controlling for typical clinical and underwriting risk factors. Furthermore, we explore the possibility of adverse selection where genetic information about multifactorial disorders is available for insurance purchasers but not for underwriters. We demonstrate that prediction of multifactorial diseases, using PRSs, provides population risk information additional to that captured by normal underwriting risk factors. This research using the UK Biobank is in the public interest as it contributes to our understanding of predicting risk of disease in the population. Further research is imperative to understand how PRSs could cause adverse selection if consumers use this information to alter their insurance purchasing behaviour.

Keywords

Adverse selectionGeneticsPolygenic riskMultifactorial disorderLife insuranceCritical illness insurance
Type
Original Research Paper
Information
Annals of Actuarial Science , Volume 15 , Issue 3 , November 2021 , pp. 488 - 503
Copyright
© Institute and Faculty of Actuaries 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

†

The online version of this article has been updated since original publication. A notice detailing the changes has also been published

References

Abraham, G., Havulinna, A.S., Bhalala, O.G., Byars, S.G., De Livera, A.M., Yetukuri, L., Tikkanen, E., Perola, M., Schunkert, H., Sijbrands, E.J., Palotie, A., Samani, N.J., Salomaa, V., Ripatti, S. & Inouye, M. (2016). Genomic prediction of coronary heart disease. European Heart Journal, 37(43), 3267–3278.10.1093/eurheartj/ehw450CrossRefGoogle ScholarPubMed
Allen, N.E., Sudlow, C., Peakman, T., Collins, R. & UK, Biobank. (2014). UK biobank data: come and get it. Science Translational Medicine, 6, 224ed4.10.1126/scitranslmed.3008601CrossRefGoogle Scholar
Antoniou, A., Pharoah, P.D., Narod, S., Risch, H.A., Eyfjord, J.E., Hopper, J.L., Loman, N., Olsson, H., Johannsson, O., Borg, A., Pasini, B., Radice, P., Manoukian, S., Eccles, D.M., Tang, N., Olah, E., Anton-Culver, H., Warner, E., Lubinski, J., Gronwald, J., Gorski, B., Tulinius, H., Thorlacius, S., Eerola, H., Nevanlinna, H., Syrjäkoski, K., Kallioniemi, O.P., Thompson, D., Evans, C., Peto, J., Lalloo, F., Evans, D.G. & Easton, D.F. (2003) Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case Series unselected for family history: a combined analysis of 22 studies. American Journal of Human Genetics, 72(5), 1117–1130.10.1086/375033CrossRefGoogle ScholarPubMed
Batty, D.G., Gale, C.R., Kivimaki, M., Deary, I.J. & Bell, S. (2020). Comparison of risk factor associations in UK Biobank against representative, general population based studies with conventional response rates: prospective cohort study and individual participant meta-analysis. BMJ, 368, m131.10.1136/bmj.m131CrossRefGoogle Scholar
Cancer Research UK. (2018). Breast cancer statistics – Breast Cancer Risk. Available online at the address cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/breast-cancer#heading-Four [accessed Jan-2019].Google Scholar
Choi, S.W., O’Reilly, P.F. (2019). PRSice-2: Polygenic Risk Score software for biobank-scale data. Gigascience, 8(7), giz082.10.1093/gigascience/giz082CrossRefGoogle ScholarPubMed
Dudbridge, F. (2013). Power and predictive accuracy of polygenic risk scores. PLoS Genet, 9(3), e1003348.10.1371/journal.pgen.1003348CrossRefGoogle ScholarPubMed
Fry, A., Littlejohns, T.J., Sudlow, C., et al. (2017). Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population. American Journal of Epidemiology, 186(9), 1029–1034.10.1093/aje/kwx246CrossRefGoogle ScholarPubMed
Hollands, G.J., French, D.P., Griffin, S.J., Prevost, A.T., Sutton, S., King, S. & Marteau, T.M. (2016). The impact of communicating genetic risks of disease on risk-reducing health behaviour: systematic review with meta-analysis. British Medical Journal (Clinical research ed.), 352, i1102.Google ScholarPubMed
Howard, R.C.W. (2014). Genetic testing model: if underwriters had no access to known results. Ottowa: Canadian Institute of Actuaries. Available online at the address www.cia-ica.ca/docs/default-source/2014/214082e.pdf [accessed Jan-2019].Google Scholar
Howard, R.C.W. (2016). Genetic Testing Model for CI: If Underwriters of Individual Critical Illness Insurance Had No Access to Known Results of Genetic Tests. Canadian Institute of Actuaries Report to CIA Research Committee. Available online at the address www.cia-ica.ca/docs/default-source/2016/216002e.pdf [accessed Jan-2019].Google Scholar
Khera, A.V., Emdin, C.A., Drake, I., Natarajan, P., Bick, A.G., Cook, N.R., Chasman, D. I, Baber, U., Mehran, R., Rader, D.J., Fuster, V., Boerwinkle, E., Melander, O., Orho-Melander, M., Ridker, P.M. & Kathiresan, S. (2016). Genetic risk, adherence to a healthy lifestyle, and coronary disease. The New England Journal of Medicine, 375(24), 2349–2358.CrossRefGoogle ScholarPubMed
Khera, A.V., Chaffin, M., Aragam, K.G., Haas, M.E., Roselli, C., Choi, S.H., Natarajan, P., Lander, E.S., Lubitz, S.A., Ellinor, P.T. & Kathiresan, S. (2018). Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nature Genetics, 50(9), 1219–1224.CrossRefGoogle ScholarPubMed
Kuchenbaecker, K.B., Hopper, J.L., Barnes, D.R., Phillips, K.A., Mooij, T.M., Roos-Blom, M.J., Jervis, S., Van Leeuwen, F.E., Milne, R.L., Andrieu, N. & Goldgar, D.E. (2017). Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. Journal of the American Medical Association, 317(23), 2402–2416.CrossRefGoogle ScholarPubMed
Lowden, J.A. (2004). Genetic risks and mortality rates. In M.A. Rothstein, (Ed.), Genetics and Life Insurance: Medical Underwriting and Social Policy (pp. 95–118, 108). MIT Press, Cambridge, MA.Google Scholar
MacDonald, A.S. (2000). Human Genetics and insurance issues. In I. Torrance (Ed.), Bio-ethics for the New Millennium. St. Andrew Press, Edinburgh.Google Scholar
MacDonald, A.S. (2001). Genetic information and insurance. Genetics Law Monitor, 2(1), 1–5.Google Scholar
Macdonald, A. & McIvor, K. (2009). Modelling adverse selection in the presence of a common genetic disorder: the breast cancer polygene. ASTIN Bulletin, 39(2), 373–402.CrossRefGoogle Scholar
Macdonald, A. & Tapadar, P. (2010). Multifactorial genetic disorders and adverse selection: epidemiology meets economics. Journal of Risk and Insurance, 77, 155–182.CrossRefGoogle Scholar
Macdonald, A. & Yu, F. (2011). The impact of genetic information on the insurance industry: conclusions from the ‘bottom-up’ modelling programme. Astin Bulletin, 41(2), 343–376.Google Scholar
Mann, G.J., Thorne, H., Balleine, R.L., Butow, P.N., Clarke, C.L., Edkins, E., Evans, G.M., Fereday, S., Haan, E., Gattas, M., Giles, G.G., Goldblatt, J., Hopper, J.L., Kirk, J., Leary, J.A., Lindeman, G., Niedermayr, E., Phillips, K.A., Picken, S., Pupo, G.M., Saunders, C., Scott, C.L., Spurdle, A.B., Suthers, G., Tucker, K., Chenevix-Trench, G. & Kathleen Cuningham Consortium for Research in Familial Breast Cancer. (2006). Analysis of cancer risk and BRCA1 and BRCA2 mutation prevalence in the kConFab familial breast cancer resource. Breast Cancer Research, 8(1), R12.CrossRefGoogle ScholarPubMed
Mavaddat, N., Michailidou, K., Dennis, J., Lush, M., Fachal, L., Lee, A., Tyrer, J.P., Chen, T.H., Wang, Q., Bolla, M.K., Yang, X., Adank, M.A., Ahearn, T., Aittomäki, K., Allen, J., Andrulis, I.L., Anton-Culver, H., Antonenkova, N.N., Arndt, V., Aronson, K.J., Auer, P.L., Auvinen, P., Barrdahl, M., Beane Freeman, L.E., Beckmann, M.W., Behrens, S., Benitez, J., Bermisheva, M., Bernstein, L., Blomqvist, C., Bogdanova, N.V., Bojesen, S.E., Bonanni, B., Børresen-Dale, A.L., Brauch, H., Bremer, M., Brenner, H., Brentnall, A., Brock, I.W., Brooks-Wilson, A., Brucker, S.Y., Brüning, T., Burwinkel, B., Campa, D., Carter, B.D., Castelao, J.E., Chanock, S.J., Chlebowski, R., Christiansen, H., Clarke, C.L., Collée, J.M., Cordina-Duverger, E., Cornelissen, S., Couch, F.J., Cox, A., Cross, S.S., Czene, K., Daly, M.B., Devilee, P., Dörk, T., Dos-Santos-Silva, I., Dumont, M., Durcan, L., Dwek, M., Eccles, D.M., Ekici, A.B., Eliassen, A.H., Ellberg, C., Engel, C., Eriksson, M., Evans, D.G., Fasching, P.A., Figueroa, J., Fletcher, O., Flyger, H., Försti, A., Fritschi, L., Gabrielson, M., Gago-Dominguez, M., Gapstur, S.M., García-Sáenz, J.A., Gaudet, M.M., Georgoulias, V., Giles, G.G., Gilyazova, I.R., Glendon, G., Goldberg, M.S., Goldgar, D.E., González-Neira, A., Grenaker Alnæs, G.I., Grip, M., Gronwald, J., Grundy, A., Guénel, P., Haeberle, L., Hahnen, E., Haiman, C.A., Håkansson, N., Hamann, U., Hankinson, S.E., Harkness, E.F., Hart, S.N., He, W., Hein, A., Heyworth, J., Hillemanns, P., Hollestelle, A., Hooning, M.J., Hoover, R.N., Hopper, J.L., Howell, A., Huang, G., Humphreys, K., Hunter, D.J., Jakimovska, M., Jakubowska, A., Janni, W., John, E.M., Johnson, N., Jones, M.E., Jukkola-Vuorinen, A., Jung, A., Kaaks, R., Kaczmarek, K., Kataja, V., Keeman, R., Kerin, M.J., Khusnutdinova, E., Kiiski, J.I., Knight, J.A., Ko, Y.D., Kosma, V.M., Koutros, S., Kristensen, V.N., Krüger, U., Kühl, T., Lambrechts, D., Le Marchand, L., Lee, E., Lejbkowicz, F., Lilyquist, J., Lindblom, A., Lindström, S., Lissowska, J., Lo, W.Y., Loibl, S., Long, J., Lubiński, J., Lux, M.P., MacInnis, R.J., Maishman, T., Makalic, E., Maleva Kostovska, I., Mannermaa, A., Manoukian, S., Margolin, S., Martens, J.W.M., Martinez, M.E., Mavroudis, D., McLean, C., Meindl, A., Menon, U., Middha, P., Miller, N., Moreno, F., Mulligan, A.M., Mulot, C., Muñoz-Garzon, V.M., Neuhausen, S.L., Nevanlinna, H., Neven, P., Newman, W.G., Nielsen, S.F., Nordestgaard, B.G., Norman, A., Offit, K., Olson, J.E., Olsson, H., Orr, N., Pankratz, V.S., Park-Simon, T.W., Perez, J.I.A., Pérez-Barrios, C., Peterlongo, P., Peto, J., Pinchev, M., Plaseska-Karanfilska, D., Polley, E.C., Prentice, R., Presneau, N., Prokofyeva, D., Purrington, K., Pylkäs, K., Rack, B., Radice, P., Rau-Murthy, R., Rennert, G., Rennert, H.S., Rhenius, V., Robson, M., Romero, A., Ruddy, K.J., Ruebner, M., Saloustros, E., Sandler, D.P., Sawyer, E.J., Schmidt, D.F., Schmutzler, R.K., Schneeweiss, A., Schoemaker, M.J., Schumacher, F., Schürmann, P., Schwentner, L., Scott, C., Scott, R.J., Seynaeve, C., Shah, M., Sherman, M.E., Shrubsole, M.J., Shu, X.O., Slager, S., Smeets, A., Sohn, C., Soucy, P., Southey, M.C., Spinelli, J.J., Stegmaier, C., Stone, J., Swerdlow, A.J., Tamimi, R.M., Tapper, W.J., Taylor, J.A., Terry, M.B., Thöne, K., Tollenaar, R.A.E.M., Tomlinson, I., Truong, T., Tzardi, M., Ulmer, H.U., Untch, M., Vachon, C.M., van Veen, E.M., Vijai, J., Weinberg, C.R., Wendt, C., Whittemore, A.S., Wildiers, H., Willett, W., Winqvist, R., Wolk, A., Yang, X.R., Yannoukakos, D., Zhang, Y., Zheng, W., Ziogas, A., ABCTB Investigators, kConFab/AOCS Investigators, NBCS Collaborators, Dunning, A.M., Thompson, D.J., Chenevix-Trench, G., Chang-Claude, J., Schmidt, M.K., Hall, P., Milne, R.L., Pharoah, P.D.P., Antoniou, A.C., Chatterjee, N., Kraft, P., García-Closas, M., Simard, J. & Easton, D.F. (2019). Polygenic risk scores for prediction of breast cancer and breast cancer subtypes. American Journal of Human Genetics, 104, 21–34.CrossRefGoogle ScholarPubMed
McGuire, A., Brown, J.A., Malone, C., McLaughlin, R. & Kerin, M.J. (2015). Effects of age on the detection and management of breast cancer. Cancers (Basel), 7(2), 908–929.CrossRefGoogle ScholarPubMed
Michailidou, K., Lindström, S., Dennis, J., Beesley, J., Hui, S., Kar, S., Lemaçon, A., Soucy, P., Glubb, D., Rostamianfar, A., Bolla, M.K., Wang, Q., Tyrer, J., Dicks, E., Lee, A., Wang, Z., Allen, J., Keeman, R., Eilber, U., French, J.D., Qing Chen, X., Fachal, L., McCue, K., McCart Reed, A.E., Ghoussaini, M., Carroll, J.S., Jiang, X., Finucane, H., Adams, M., Adank, M.A., Ahsan, H., Aittomäki, K., Anton-Culver, H., Antonenkova, N.N., Arndt, V., Aronson, K.J., Arun, B., Auer, P.L., Bacot, F., Barrdahl, M., Baynes, C., Beckmann, M.W., Behrens, S., Benitez, J., Bermisheva, M., Bernstein, L., Blomqvist, C., Bogdanova, N.V., Bojesen, S.E., Bonanni, B., Børresen-Dale, A.L., Brand, J.S., Brauch, H., Brennan, P., Brenner, H., Brinton, L., Broberg, P., Brock, I.W., Broeks, A., Brooks-Wilson, A., Brucker, S.Y., Brüning, T., Burwinkel, B., Butterbach, K., Cai, Q., Cai, H., Caldés, T., Canzian, F., Carracedo, A., Carter, B.D., Castelao, J.E., Chan, T.L., David Cheng, T.Y., Seng Chia, K., Choi, J.Y., Christiansen, H., Clarke, C.L., NBCS Collaborators, Collée, M., Conroy, D.M., Cordina-Duverger, E., Cornelissen, S., Cox, D.G., Cox, A., Cross, S.S., Cunningham, J.M., Czene, K., Daly, M.B., Devilee, P., Doheny, K.F., Dörk, T., Dos-Santos-Silva, I., Dumont, M., Durcan, L., Dwek, M., Eccles, D.M., Ekici, A.B., Eliassen, A.H., Ellberg, C., Elvira, M., Engel, C., Eriksson, M., Fasching, P.A., Figueroa, J., Flesch-Janys, D., Fletcher, O., Flyger, H., Fritschi, L., Gaborieau, V., Gabrielson, M., Gago-Dominguez, M., Gao, Y.T., Gapstur, S.M., García-Sáenz, J.A., Gaudet, M.M., Georgoulias, V., Giles, G.G., Glendon, G., Goldberg, M.S., Goldgar, D.E., González-Neira, A., Grenaker Alnæs, G.I., Grip, M., Gronwald, J., Grundy, A., Guénel, P., Haeberle, L., Hahnen, E., Haiman, C.A., Håkansson, N., Hamann, U., Hamel, N., Hankinson, S., Harrington, P., Hart, S.N., Hartikainen, J.M., Hartman, M., Hein, A., Heyworth, J., Hicks, B., Hillemanns, P., Ho, D.N., Hollestelle, A., Hooning, M.J., Hoover, R.N., Hopper, J.L., Hou, M.F., Hsiung, C.N., Huang, G., Humphreys, K., Ishiguro, J., Ito, H., Iwasaki, M., Iwata, H., Jakubowska, A., Janni, W., John, E.M., Johnson, N., Jones, K., Jones, M., Jukkola-Vuorinen, A., Kaaks, R., Kabisch, M., Kaczmarek, K., Kang, D., Kasuga, Y., Kerin, M.J., Khan, S., Khusnutdinova, E., Kiiski, J.I., Kim, S.W., Knight, J.A., Kosma, V.M., Kristensen, V.N., Krüger, U., Kwong, A., Lambrechts, D., Le Marchand, L., Lee, E., Lee, M.H., Lee, J.W., Neng Lee, C., Lejbkowicz, F., Li, J., Lilyquist, J., Lindblom, A., Lissowska, J., Lo, W.Y., Loibl, S., Long, J., Lophatananon, A., Lubinski, J., Luccarini, C., Lux, M.P., Ma, E.S.K., MacInnis, R.J., Maishman, T., Makalic, E., Malone, K.E., Kostovska, I.M., Mannermaa, A., Manoukian, S., Manson, J.E., Margolin, S., Mariapun, S., Martinez, M.E., Matsuo, K., Mavroudis, D., McKay, J., McLean, C., Meijers-Heijboer, H., Meindl, A., Menéndez, P., Menon, U., Meyer, J., Miao, H., Miller, N., Taib, N.A.M., Muir, K., Mulligan, A.M., Mulot, C., Neuhausen, S.L., Nevanlinna, H., Neven, P., Nielsen, S.F., Noh, D.Y., Nordestgaard, B.G., Norman, A., Olopade, O.I., Olson, J.E., Olsson, H., Olswold, C., Orr, N., Pankratz, V.S., Park, S.K., Park-Simon, T.W., Lloyd, R., Perez, J.I.A., Peterlongo, P., Peto, J., Phillips, K.A., Pinchev, M., Plaseska-Karanfilska, D., Prentice, R., Presneau, N., Prokofyeva, D., Pugh, E., Pylkäs, K., Rack, B., Radice, P., Rahman, N., Rennert, G., Rennert, H.S., Rhenius, V., Romero, A., Romm, J., Ruddy, K.J., Rüdiger, T., Rudolph, A., Ruebner, M., Rutgers, E.J.T., Saloustros, E., Sandler, D.P., Sangrajrang, S., Sawyer, E.J., Schmidt, D.F., Schmutzler, R.K., Schneeweiss, A., Schoemaker, M.J., Schumacher, F., Schürmann, P., Scott, R.J., Scott, C., Seal, S., Seynaeve, C., Shah, M., Sharma, P., Shen, C.Y., Sheng, G., Sherman, M.E., Shrubsole, M.J., Shu, X.O., Smeets, A., Sohn, C., Southey, M.C., Spinelli, J.J., Stegmaier, C., Stewart-Brown, S., Stone, J., Stram, D.O., Surowy, H., Swerdlow, A., Tamimi, R., Taylor, J.A., Tengström, M., Teo, S.H., Beth Terry, M., Tessier, D.C., Thanasitthichai, S., Thöne, K., Tollenaar, R.A.E.M., Tomlinson, I., Tong, L., Torres, D., Truong, T., Tseng, C.C., Tsugane, S., Ulmer, H.U., Ursin, G., Untch, M., Vachon, C., van Asperen, C.J., Van Den Berg, D., van den Ouweland, A.M.W., van der Kolk, L., van der Luijt, R.B., Vincent, D., Vollenweider, J., Waisfisz, Q., Wang-Gohrke, S., Weinberg, C.R., Wendt, C., Whittemore, A.S., Wildiers, H., Willett, W., Winqvist, R., Wolk, A., Wu, A.H., Xia, L., Yamaji, T., Yang, X.R., Har Yip, C., Yoo, K.Y., Yu, J.C., Zheng, W., Zheng, Y., Zhu, B., Ziogas, A., Ziv, E., ABCTB Investigators, ConFab/AOCS Investigators, Lakhani, S.R., Antoniou, A.C., Droit, A., Andrulis, I.L., Amos, C.I., Couch, F.J., Pharoah, P.D.P., Chang-Claude, J., Hall, P., Hunter, D.J., Milne, R.L., García-Closas, M., Schmidt, M.K., Chanock, S.J., Dunning, A.M., Edwards, S.L., Bader, G.D., Chenevix-Trench, G., Simard, J., Kraft, P. & Easton, D.F. (2017). Association analysis identifies 65 new breast cancer risk loci. Nature, 551, 92–94.CrossRefGoogle ScholarPubMed
MIT Technology Review. (2018). 2017 was the year consumer DNA testing blew up. Available online at the address www.technologyreview.com/s/610233/2017-was-the-year-consumer-dna-testing-blew-up/ [accessed Jan-2019].Google Scholar
Nikpay, M., Goel, A., Won, H.H., Hall, L.M., Willenborg, C., Kanoni, S. & Saleheen, D. (2015). A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nature Genetics, 47, 1121–1130.Google ScholarPubMed
Nordestgaard, B.G., Chapman, M.J., Humphries, S.E., Ginsberg, H.N., Masana, L., Descamps, O.S., Wiklund, O., Hegele, R.A., Raal, F.J., Defesche, J.C., Wiegman, A., Santos, R.D., Watts, G.F., Parhofer, K.G., Hovingh, G.K., Kovanen, P.T., Boileau, C., Averna, M., Borén, J., Bruckert, E., Catapano, A.L., Kuivenhoven, J.A., Pajukanta, P., Ray, K., Stalenhoef, A.F., Stroes, E., Taskinen, M.R., Tybjærg-Hansen, A. & European Atherosclerosis Society Consensus Panel. (2013). Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: consensus statement of the European Atherosclerosis Society. European Heart Journal, 34(45), 3478–90a.CrossRefGoogle ScholarPubMed
Prince, A.E.R. (2018). Comparative perspectives: regulating insurer use of genetic information. European Journal of Human Genetics. doi: 10.1038/s41431-018-0293-1. [Epub ahead of print]Google ScholarPubMed
Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., Downey, P., Elliott, P., Green, J., Landray, M., Liu, B., Matthews, P., Ong, G., Pell, J., Silman, A., Young, A., Sprosen, T., Peakman, T. & Collins, R. (2015). UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Medicine, 12(3), e1001779.CrossRefGoogle ScholarPubMed
Tada, H., Melander, O., Louie, J.Z., Catanese, J.J., Rowland, C.M., Devlin, J.J., Kathiresan, S. & Shiffman, D. (2016). Risk prediction by genetic risk scores for coronary heart disease is independent of self-reported family history. European Heart Journal, 37, 561–567.CrossRefGoogle ScholarPubMed
The Wellcome Trust Case Control Consortium. (2007). Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447(7145), 661–678.CrossRefGoogle Scholar
Visscher, P.M., Wray, N.R., Zhang, Q., Sklar, P., McCarthy, M.I., Brown, M.A. & Yang, J. (2017). 10 Years of GWAS Discovery: Biology, Function, and Translation. American Journal of Human Genetics 101(1), 5–22.CrossRefGoogle Scholar
Yang, J., Benyamin, B., McEvoy, B.P., Gordon, S., Henders, A.K., Nyholt, D.R., Madden, P.A., Heath, A.C., Martin, N.G., Montgomery, G.W., et al. (2010). Common SNPs explain a large proportion of the heritability for human height. Nature Genetics 42(7), 565–569.CrossRefGoogle ScholarPubMed
Supplementary material: File

Maxwell et al. supplementary material

Maxwell et al. supplementary material

Download Maxwell et al. supplementary material(File)
File 31.6 KB