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2. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

Author

Lee, JJ, Wedow, R, Okbay, A, Kong, E, Maghzian, O, Zacher, M, Tuan Anh, N-V, Bowers, P, Sidorenko, J, Linner, RK, Fontana, MA, Kundu, T, Lee, C, Li, H, Li, R, Royer, R, Timshel, PN, Walters, RK, Willoughby, EA, Yengo, L, Alver, M, Bao, Y, Clark, DW, Day, FR, Furlotte, NA, Joshi, PK, Kemper, KE, Kleinman, A, Langenberg, C, Magi, R, Trampush, JW, Verma, SS, Wu, Y, Lam, Mei, Zhao, JH, Zheng, Z, Boardman, JD, Campbell, H, Freese, J, Harris, KM, Hayward, C, Herd, P, Kumari, M, Lencz, T, Luan, JA, Malhotra, AK, Metspalu, A, Milani, L, Ong, KK, Perry, JRB, Porteous, DJ, Ritchie, MD, Smart, MC, Smith, BH, Tung, JY, Wareham, NJ, Wilson, JF, Beauchamp, JP, Conley, DC, Esko, T, Lehrer, SF, Magnusson, PKE, Oskarsson, S, Pers, TH, Robinson, MR, Thom, K, Watson, C, Chabris, CF, Meyer, MN, Laibson, DI, Yang, Jiaqi, Johannesson, M, Koellinger, PD, Turley, P, Visscher, PM, Benjamin, DJ, Cesarini, D, Lee, JJ, Wedow, R, Okbay, A, Kong, E, Maghzian, O, Zacher, M, Tuan Anh, N-V, Bowers, P, Sidorenko, J, Linner, RK, Fontana, MA, Kundu, T, Lee, C, Li, H, Li, R, Royer, R, Timshel, PN, Walters, RK, Willoughby, EA, Yengo, L, Alver, M, Bao, Y, Clark, DW, Day, FR, Furlotte, NA, Joshi, PK, Kemper, KE, Kleinman, A, Langenberg, C, Magi, R, Trampush, JW, Verma, SS, Wu, Y, Lam, Mei, Zhao, JH, Zheng, Z, Boardman, JD, Campbell, H, Freese, J, Harris, KM, Hayward, C, Herd, P, Kumari, M, Lencz, T, Luan, JA, Malhotra, AK, Metspalu, A, Milani, L, Ong, KK, Perry, JRB, Porteous, DJ, Ritchie, MD, Smart, MC, Smith, BH, Tung, JY, Wareham, NJ, Wilson, JF, Beauchamp, JP, Conley, DC, Esko, T, Lehrer, SF, Magnusson, PKE, Oskarsson, S, Pers, TH, Robinson, MR, Thom, K, Watson, C, Chabris, CF, Meyer, MN, Laibson, DI, Yang, Jiaqi, Johannesson, M, Koellinger, PD, Turley, P, Visscher, PM, Benjamin, DJ, and Cesarini, D

Published
2018

3. An epigenome-wide association study meta-analysis of educational attainment

Author

Linner, RK, Marioni, RE, Rietveld, Niels, Simpkin, AJ, Davies, NM, Watanabe, K, Armstrong, NJ, Auro, K, Baumbach, C, Bonder, MJ, Buchwald, J, Fiorito, G, Ismail, K, Iurato, S, Joensuu, A, Karell, P, Kasela, S, Lahti, J, Mcrae, AF, Mandaviya, Pooja, Seppala, I, Wang, Y, Baglietto, L, Binder, EB, Harris, SE, Hodge, AM, Horvath, S, Hurme, M, Johannesson, M, Latvala, A, Mather, KA, Medland, SE, Metspalu, A, Milani, L, Milne, RL, Pattie, A, Pedersen, NL, Peters, A, Polidoro, S, Raikkonen, K, Severi, G, Starr, JM, Stolk, Lisette, Waldenberger, M, Eriksson, JG, Esko, T, Franke, L, Gieger, C, Giles, GG, Hagg, S, Jousilahti, P, Kaprio, J, Kahonen, M, Lehtimaki, T, Martin, NG, van Meurs, Joyce, Ollikainen, M, Perola, M, Posthuma, D, Raitakari, OT, Sachdev, PS, Taskesen, E, Uitterlinden, André, Vineis, P, Wijmenga, C, Wright, MJ, Relton, C, Smith, GD, Deary, IJ, Koellinger, PD, Benjamin, DJ, Linner, RK, Marioni, RE, Rietveld, Niels, Simpkin, AJ, Davies, NM, Watanabe, K, Armstrong, NJ, Auro, K, Baumbach, C, Bonder, MJ, Buchwald, J, Fiorito, G, Ismail, K, Iurato, S, Joensuu, A, Karell, P, Kasela, S, Lahti, J, Mcrae, AF, Mandaviya, Pooja, Seppala, I, Wang, Y, Baglietto, L, Binder, EB, Harris, SE, Hodge, AM, Horvath, S, Hurme, M, Johannesson, M, Latvala, A, Mather, KA, Medland, SE, Metspalu, A, Milani, L, Milne, RL, Pattie, A, Pedersen, NL, Peters, A, Polidoro, S, Raikkonen, K, Severi, G, Starr, JM, Stolk, Lisette, Waldenberger, M, Eriksson, JG, Esko, T, Franke, L, Gieger, C, Giles, GG, Hagg, S, Jousilahti, P, Kaprio, J, Kahonen, M, Lehtimaki, T, Martin, NG, van Meurs, Joyce, Ollikainen, M, Perola, M, Posthuma, D, Raitakari, OT, Sachdev, PS, Taskesen, E, Uitterlinden, André, Vineis, P, Wijmenga, C, Wright, MJ, Relton, C, Smith, GD, Deary, IJ, Koellinger, PD, and Benjamin, DJ

Abstract

The epigenome is associated with biological factors, such as disease status, and environmental factors, such as smoking, alcohol consumption and body mass index. Although there is a widespread perception that environmental influences on the epigenome are pervasive and profound, there has been little evidence to date in humans with respect to environmental factors that are biologically distal. Here we provide evidence on the associations between epigenetic modifications—in our case, CpG methylation—and educational attainment (EA), a biologically distal environmental factor that is arguably among the most important life-shaping experiences for individuals. Specifically, we report the results of an epigenome-wide association study meta-analysis of EA based on data from 27 cohort studies with a total of 10?767 individuals. We find nine CpG probes significantly associated with EA. However, robustness analyses show that all nine probes have previously been found to be associated with smoking. Only two associations remain when we perform a sensitivity analysis in the subset of never-smokers, and these two probes are known to be strongly associated with maternal smoking during pregnancy, and thus their association with EA could be due to correlation between EA and maternal smoking. Moreover, the effect sizes of the associations with EA are far smaller than the known associations with the biologically proximal environmental factors alcohol consumption, body mass index, smoking and maternal smoking during pregnancy. Follow-up analyses that combine the effects of many probes also point to small methylation associations with EA that are highly correlated with the combined effects of smoking. If our findings regarding EA can be generalized to other biologically distal environmental factors, then they cast doubt on the hypothesis that such factors have large effects on the epigenome.

Published
2017

4. Association Between Psychiatric Polygenic Scores, Healthcare Utilization and Comorbidity Burden.

Author

Kirchner HL, Rocha D, Linner RK, Wilimitis D, Walsh CG, Ripperger M, Lee H, Liu Z, Davis L, Hu Y, Chabris CF, and Smoller JW

Abstract

Purpose: To estimate the association of psychiatric polygenic scores with healthcare utilization and comorbidity burden., Methods: Observational cohort study (N = 118,882) of adolescent and adult biobank participants with linked electronic health records (EHRs) from three diverse study sites; (Massachusetts General Brigham, Vanderbilt University Medical Center, Geisinger). Polygenic scores (PGS) were derived from the largest available GWAS of major depressive depression, bipolar disorder, and schizophrenia at the time of analysis. Negative binomial regression models were used to estimate the association between each psychiatric PGS and healthcare utilization and comorbidity burden. Healthcare utilization was measured as frequency of emergency department (ED), inpatient (IP), and outpatient (OP) visits. Comorbidity burden was defined by the Elixhauser Comorbidity Index and the Charlson Comorbidity Index., Results: Participants had a median follow-up duration of 12 years in the EHR. Individuals in the top decile of polygenic score for major depressive disorder had significantly more ED visits (RR=1.22, 95% CI; 1.17, 1.29) compared to those the lowest decile. Increases were also observed with IP and comorbidity burden. Among those diagnosed with depression and in the highest decile of the PGS, there was an increase in all utilization types (ED: RR=1.56, 95% CI 1.41, 1.72; OP: RR=1.16, 95% CI 1.08, 1.24; IP: RR=1.23, 95% CI 1.12, 1.36) post-diagnosis. No clinically significant results were observed with bipolar and schizophrenia polygenic scores., Conclusions: Polygenic score for depression is modestly associated with increased healthcare resource utilization and comorbidity burden, in the absence of diagnosis. Following a diagnosis of depression, the PGS was associated with further increases in healthcare utilization. These findings suggest that depression genetic risk is associated with utilization and burden of chronic disease in real-world settings., Competing Interests: Conflict of Interest: JWS is a member of the Scientific Advisory Board of Sensorium Therapeutics (with equity), and has received grant support from Biogen, Inc. He is PI of a collaborative study of the genetics of depression and bipolar disorder sponsored by 23andMe for which 23andMe provides analysis time as in-kind support but no payments.

Published
2023
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