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3. Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications

Author

Sterenborg, R.B.T.M., Steinbrenner, I., Li, Yong, Bujnis, M.N., Naito, T., Marouli, E., Galesloot, T.E., Babajide, O., Andreasen, L., Astrup, A., Åsvold, B.O., Bandinelli, S., Beekman, M., Beilby, J.P., Bork-Jensen, J., Boutin, T., Brody, J.A., Brown, S.J., Brumpton, B., Campbell, P.J., Cappola, A.R., Ceresini, G., Chaker, L., Chasman, D.I., Concas, M.P., Coutinho de Almeida, Rodrigo, Cross, S.M., Cucca, F., Deary, I.J., Kjaergaard, A.D., Echouffo Tcheugui, J.B., Ellervik, C., Eriksson, J.G., Ferrucci, L., Freudenberg, J., Fuchsberger, C., Gieger, C., Giulianini, F., Gögele, M., Graham, S.E., Grarup, N., Gunjača, I., Hansen, T., Harding, B.N., Harris, S.E., Haunsø, S., Hayward, C., Hui, J., Ittermann, T., Jukema, J.W., Kajantie, E., Kanters, J.K., Kårhus, L.L., Kiemeney, L.A.L.M., Kühnel, B., Lahti, J., Langenberg, C., Lapauw, B., Leese, G., Li, Shuo, Liewald, D.C.M., Linneberg, A., Lominchar, J.V.T., Luan, Jian'an, Martin, N.G., Matana, A., Meima, M.E., Meitinger, T., Meulenbelt, I., Mitchell, B.D., Møllehave, L.T., Mora, S., Naitza, S., Nauck, M., Netea-Maier, R.T., Noordam, R., Nursyifa, C., Okada, Y., Onano, S., Papadopoulou, A., Palmer, C.N.A., Pattaro, C., Pedersen, O., Peters, A., Pietzner, M., Polašek, O., Pramstaller, P.P., Psaty, B.M., Punda, A., Ray, D., Redmond, P., Richards, J.B., Ridker, P.M., Russ, T.C., Ryan, K.A., Olesen, M.S., Schultheiss, U.T., Selvin, E., Siddiqui, M.K., Teumer, A., Medici, M., Sterenborg, R.B.T.M., Steinbrenner, I., Li, Yong, Bujnis, M.N., Naito, T., Marouli, E., Galesloot, T.E., Babajide, O., Andreasen, L., Astrup, A., Åsvold, B.O., Bandinelli, S., Beekman, M., Beilby, J.P., Bork-Jensen, J., Boutin, T., Brody, J.A., Brown, S.J., Brumpton, B., Campbell, P.J., Cappola, A.R., Ceresini, G., Chaker, L., Chasman, D.I., Concas, M.P., Coutinho de Almeida, Rodrigo, Cross, S.M., Cucca, F., Deary, I.J., Kjaergaard, A.D., Echouffo Tcheugui, J.B., Ellervik, C., Eriksson, J.G., Ferrucci, L., Freudenberg, J., Fuchsberger, C., Gieger, C., Giulianini, F., Gögele, M., Graham, S.E., Grarup, N., Gunjača, I., Hansen, T., Harding, B.N., Harris, S.E., Haunsø, S., Hayward, C., Hui, J., Ittermann, T., Jukema, J.W., Kajantie, E., Kanters, J.K., Kårhus, L.L., Kiemeney, L.A.L.M., Kühnel, B., Lahti, J., Langenberg, C., Lapauw, B., Leese, G., Li, Shuo, Liewald, D.C.M., Linneberg, A., Lominchar, J.V.T., Luan, Jian'an, Martin, N.G., Matana, A., Meima, M.E., Meitinger, T., Meulenbelt, I., Mitchell, B.D., Møllehave, L.T., Mora, S., Naitza, S., Nauck, M., Netea-Maier, R.T., Noordam, R., Nursyifa, C., Okada, Y., Onano, S., Papadopoulou, A., Palmer, C.N.A., Pattaro, C., Pedersen, O., Peters, A., Pietzner, M., Polašek, O., Pramstaller, P.P., Psaty, B.M., Punda, A., Ray, D., Redmond, P., Richards, J.B., Ridker, P.M., Russ, T.C., Ryan, K.A., Olesen, M.S., Schultheiss, U.T., Selvin, E., Siddiqui, M.K., Teumer, A., and Medici, M.

Abstract

Contains fulltext : 304858.pdf (Publisher’s version ) (Open Access), To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.

Published
2024

13. Identifying the Common Genetic Basis of Antidepressant Response

Author

Pain, O. Hodgson, K. Trubetskoy, V. Ripke, S. Marshe, V.S. Adams, M.J. Byrne, E.M. Campos, A.I. Carrillo-Roa, T. Cattaneo, A. Als, T.D. Souery, D. Dernovsek, M.Z. Fabbri, C. Hayward, C. Henigsberg, N. Hauser, J. Kennedy, J.L. Lenze, E.J. Lewis, G. Müller, D.J. Martin, N.G. Mulsant, B.H. Mors, O. Perroud, N. Porteous, D.J. Rentería, M.E. Reynolds, C.F., III Rietschel, M. Uher, R. Wigmore, E.M. Maier, W. Wray, N.R. Aitchison, K.J. Arolt, V. Baune, B.T. Biernacka, J.M. Bondolfi, G. Domschke, K. Kato, M. Li, Q.S. Liu, Y.-L. Serretti, A. Tsai, S.-J. Turecki, G. Weinshilboum, R. Kasper, S. Zohar, J. Montgomery, S. Albani, D. Forloni, G. Ferentinos, P. Rujescu, D. Mendlewicz, J. Mattheisen, M. Trzaskowski, M. Abdellaoui, A. Agerbo, E. Air, T.M. Andlauer, T.F.M. Bacanu, S.-A. Bækvad-Hansen, M. Beekman, A.T.F. Bigdeli, T.B. Binder, E.B. Bryois, J. Buttenschøn, H.N. Bybjerg-Grauholm, J. Cai, N. Castelao, E. Christensen, J.H. Clarke, T.-K. Coleman, J.R.I. Colodro-Conde, L. Couvy-Duchesne, B. Craddock, N. Crawford, G.E. Davies, G. Deary, I.J. Degenhardt, F. Derks, E.M. Direk, N. Dolan, C.V. Dunn, E.C. Eley, T.C. Escott-Price, V. Hassan Kiadeh, F.F. Finucane, H.K. Foo, J.C. Forstner, A.J. Frank, J. Gaspar, H.A. Gill, M. Goes, F.S. Gordon, S.D. Grove, J. Hall, L.S. Hansen, C.S. Hansen, T.F. Herms, S. Hickie, I.B. Hoffmann, P. Homuth, G. Horn, C. Hottenga, J.-J. Hougaard, D.M. Howard, D.M. Ising, M. Jansen, R. Jones, I. Jones, L.A. Jorgenson, E. Knowles, J.A. Kohane, I.S. Kraft, J. Kretzschmar, W.W. Kutalik, Z. Li, Y. Lind, P.A. MacIntyre, D.J. MacKinnon, D.F. Maier, R.M. Marchini, J. Mbarek, H. McGrath, P. McGuffin, P. Medland, S.E. Mehta, D. Middeldorp, C.M. Mihailov, E. Milaneschi, Y. Milani, L. Mondimore, F.M. Montgomery, G.W. Mostafavi, S. Mullins, N. Nauck, M. Ng, B. Nivard, M.G. Nyholt, D.R. O'Reilly, P.F. Oskarsson, H. Owen, M.J. Painter, J.N. Pedersen, C.B. Pedersen, M.G. Peterson, R.E. Peyrot, W.J. Pistis, G. Posthuma, D. Quiroz, J.A. Qvist, P. Rice, J.P. Riley, B.P and Pain, O. Hodgson, K. Trubetskoy, V. Ripke, S. Marshe, V.S. Adams, M.J. Byrne, E.M. Campos, A.I. Carrillo-Roa, T. Cattaneo, A. Als, T.D. Souery, D. Dernovsek, M.Z. Fabbri, C. Hayward, C. Henigsberg, N. Hauser, J. Kennedy, J.L. Lenze, E.J. Lewis, G. Müller, D.J. Martin, N.G. Mulsant, B.H. Mors, O. Perroud, N. Porteous, D.J. Rentería, M.E. Reynolds, C.F., III Rietschel, M. Uher, R. Wigmore, E.M. Maier, W. Wray, N.R. Aitchison, K.J. Arolt, V. Baune, B.T. Biernacka, J.M. Bondolfi, G. Domschke, K. Kato, M. Li, Q.S. Liu, Y.-L. Serretti, A. Tsai, S.-J. Turecki, G. Weinshilboum, R. Kasper, S. Zohar, J. Montgomery, S. Albani, D. Forloni, G. Ferentinos, P. Rujescu, D. Mendlewicz, J. Mattheisen, M. Trzaskowski, M. Abdellaoui, A. Agerbo, E. Air, T.M. Andlauer, T.F.M. Bacanu, S.-A. Bækvad-Hansen, M. Beekman, A.T.F. Bigdeli, T.B. Binder, E.B. Bryois, J. Buttenschøn, H.N. Bybjerg-Grauholm, J. Cai, N. Castelao, E. Christensen, J.H. Clarke, T.-K. Coleman, J.R.I. Colodro-Conde, L. Couvy-Duchesne, B. Craddock, N. Crawford, G.E. Davies, G. Deary, I.J. Degenhardt, F. Derks, E.M. Direk, N. Dolan, C.V. Dunn, E.C. Eley, T.C. Escott-Price, V. Hassan Kiadeh, F.F. Finucane, H.K. Foo, J.C. Forstner, A.J. Frank, J. Gaspar, H.A. Gill, M. Goes, F.S. Gordon, S.D. Grove, J. Hall, L.S. Hansen, C.S. Hansen, T.F. Herms, S. Hickie, I.B. Hoffmann, P. Homuth, G. Horn, C. Hottenga, J.-J. Hougaard, D.M. Howard, D.M. Ising, M. Jansen, R. Jones, I. Jones, L.A. Jorgenson, E. Knowles, J.A. Kohane, I.S. Kraft, J. Kretzschmar, W.W. Kutalik, Z. Li, Y. Lind, P.A. MacIntyre, D.J. MacKinnon, D.F. Maier, R.M. Marchini, J. Mbarek, H. McGrath, P. McGuffin, P. Medland, S.E. Mehta, D. Middeldorp, C.M. Mihailov, E. Milaneschi, Y. Milani, L. Mondimore, F.M. Montgomery, G.W. Mostafavi, S. Mullins, N. Nauck, M. Ng, B. Nivard, M.G. Nyholt, D.R. O'Reilly, P.F. Oskarsson, H. Owen, M.J. Painter, J.N. Pedersen, C.B. Pedersen, M.G. Peterson, R.E. Peyrot, W.J. Pistis, G. Posthuma, D. Quiroz, J.A. Qvist, P. Rice, J.P. Riley, B.P

Abstract

Background: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. Methods: Genome-wide analysis of remission (nremit = 1852, nnonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism–based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. Results: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism–based heritability was significantly different from zero for remission (h2 = 0.132, SE = 0.056) but not for percentage improvement (h2 = −0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. Conclusions: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizo

Published
2022

14. Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning

Author

Lahti, J., Tuominen, S., Yang, Q., Pergola, G., Ahmad, S., Amin, N., Armstrong, N.J., Beiser, A., Bey, K., Bis, J.C., Boerwinkle, E., Bressler, J., Campbell, A., Campbell, H., Chen, Q., Corley, J., Cox, S.R., Davies, G., De Jager, P.L., Derks, E.M., Faul, J.D., Fitzpatrick, A.L., Fohner, A.E., Ford, I., Fornage, M., Gerring, Z., Grabe, H.J., Grodstein, F., Gudnason, V., Simonsick, E., Holliday, E.G., Joshi, P.K., Kajantie, E., Kaprio, J., Karell, P., Kleineidam, L., Knol, M.J., Kochan, N.A., Kwok, J.B., Leber, M., Lam, M., Lee, T., Li, S., Loukola, A., Luck, T., Marioni, R.E., Mather, K.A., Medland, S., Mirza, S.S., Nalls, M.A., Nho, K., O’Donnell, A., Oldmeadow, C., Painter, J., Pattie, A., Reppermund, S., Risacher, S.L., Rose, R.J., Sadashivaiah, V., Scholz, M., Satizabal, C.L., Schofield, P.W., Schraut, K.E., Scott, R.J., Simino, J., Smith, A.V., Smith, J.A., Stott, D.J., Surakka, I., Teumer, A., Thalamuthu, A., Trompet, S., Turner, S.T., van der Lee, S.J., Villringer, A., Völker, U., Wilson, R.S., Wittfeld, K., Vuoksimaa, E., Xia, R., Yaffe, K., Yu, L., Zare, H., Zhao, W., Ames, D., Attia, J., Bennett, D.A., Brodaty, H., Chasman, D.I., Goldman, A.L., Hayward, C., Ikram, M.A., Jukema, J.W., Kardia, S.L.R., Lencz, T., Loeffler, M., Mattay, V.S., Palotie, A., Psaty, B.M., Ramirez, A., Ridker, P.M., Riedel-Heller, S.G., Sachdev, P.S., Saykin, A.J., Scherer, M., Schofield, P.R., Sidney, S., Starr, J.M., Trollor, J., Ulrich, W., Wagner, M., Weir, D.R., Wilson, J.F., Wright, M.J., Weinberger, D.R., Debette, S., Eriksson, J.G., Mosley, T.H., Launer, L.J., van Duijn, C.M., Deary, I.J., Seshadri, S., Räikkönen, K., Lahti, J., Tuominen, S., Yang, Q., Pergola, G., Ahmad, S., Amin, N., Armstrong, N.J., Beiser, A., Bey, K., Bis, J.C., Boerwinkle, E., Bressler, J., Campbell, A., Campbell, H., Chen, Q., Corley, J., Cox, S.R., Davies, G., De Jager, P.L., Derks, E.M., Faul, J.D., Fitzpatrick, A.L., Fohner, A.E., Ford, I., Fornage, M., Gerring, Z., Grabe, H.J., Grodstein, F., Gudnason, V., Simonsick, E., Holliday, E.G., Joshi, P.K., Kajantie, E., Kaprio, J., Karell, P., Kleineidam, L., Knol, M.J., Kochan, N.A., Kwok, J.B., Leber, M., Lam, M., Lee, T., Li, S., Loukola, A., Luck, T., Marioni, R.E., Mather, K.A., Medland, S., Mirza, S.S., Nalls, M.A., Nho, K., O’Donnell, A., Oldmeadow, C., Painter, J., Pattie, A., Reppermund, S., Risacher, S.L., Rose, R.J., Sadashivaiah, V., Scholz, M., Satizabal, C.L., Schofield, P.W., Schraut, K.E., Scott, R.J., Simino, J., Smith, A.V., Smith, J.A., Stott, D.J., Surakka, I., Teumer, A., Thalamuthu, A., Trompet, S., Turner, S.T., van der Lee, S.J., Villringer, A., Völker, U., Wilson, R.S., Wittfeld, K., Vuoksimaa, E., Xia, R., Yaffe, K., Yu, L., Zare, H., Zhao, W., Ames, D., Attia, J., Bennett, D.A., Brodaty, H., Chasman, D.I., Goldman, A.L., Hayward, C., Ikram, M.A., Jukema, J.W., Kardia, S.L.R., Lencz, T., Loeffler, M., Mattay, V.S., Palotie, A., Psaty, B.M., Ramirez, A., Ridker, P.M., Riedel-Heller, S.G., Sachdev, P.S., Saykin, A.J., Scherer, M., Schofield, P.R., Sidney, S., Starr, J.M., Trollor, J., Ulrich, W., Wagner, M., Weir, D.R., Wilson, J.F., Wright, M.J., Weinberger, D.R., Debette, S., Eriksson, J.G., Mosley, T.H., Launer, L.J., van Duijn, C.M., Deary, I.J., Seshadri, S., and Räikkönen, K.

Abstract

Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.

Published
2022

20. Genome-wide association study of circulating interleukin 6 levels identifies novel loci

Author

Ahluwalia, T.S., Prins, B.P., Abdollahi, M., Armstrong, N.J., Aslibekyan, S., Bain, L., Jefferis, B., Baumert, J., Beekman, M., Ben-Shlomo, Y., Bis, J.C., Mitchell, B.D., Geus, E. de, Delgado, G.E., Marek, D., Eriksson, J., Kajantie, E., Kanoni, S., Kemp, J.P., Lu, C., Marioni, R.E., McLachlan, S., Milaneschi, Y., Nolte, I.M., Petrelis, A.M., Porcu, E., Sabater-Lleal, M., Naderi, E., Seppala, I., Shah, T., Singhal, G., Standl, M., Teumer, A., Thalamuthu, A., Thiering, E., Trompet, S., Ballantyne, C.M., Benjamin, E.J., Casas, J.P., Toben, C., Dedoussis, G., Deelen, J., Durda, P., Engmann, J., Feitosa, M.F., Grallert, H., Hammarstedt, A., Harris, S.E., Homuth, G., Hottenga, J.J., Jalkanen, S., Jamshidi, Y., Jawahar, M.C., Jess, T., Kivimaki, M., Kleber, M.E., Lahti, J., Liu, Y., Marques-Vidal, P., Mellstrom, D., Mooijaart, S.P., Muller-Nurasyid, M., Penninx, B., Revez, J.A., Rossing, P., Raikkonen, K., Sattar, N., Scharnagl, H., Sennblad, B., Silveira, A., St Pourcain, B., Timpson, N.J., Trollor, J., Dongen, J. van, Heemst, D. van, Visvikis-Siest, S., Vollenweider, P., Volker, U., Waldenberger, M., Willemsen, G., Zabaneh, D., Morris, R.W., Arnett, D.K., Baune, B.T., Boomsma, D.I., Chang, Y.P.C., Deary, I.J., Deloukas, P., Eriksson, J.G., Evans, D.M., Ferreira, M.A., Gaunt, T., Gudnason, V., Hamsten, A., Heinrich, J., Hingorani, A., Humphries, S.E., Jukema, J.W., Koenig, W., Kumari, M., Kutalik, Z., Lawlor, D.A., Lehtimaki, T., Marz, W., Mather, K.A., Naitza, S., Nauck, M., Ohlsson, C., Price, J.F., Raitakari, O., Rice, K., Sachdev, P.S., Slagboom, E., Sorensen, T.I.A., Spector, T., Stacey, D., Stathopoulou, M.G., Tanaka, T., Wannamethee, S.G., Whincup, P., Rotter, J.I., Dehghan, A., Boerwinkle, E., Psaty, B.M., Snieder, H., Alizadeh, B.Z., and CHARGE Inflammation Working Grp

Abstract

Interleukin 6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67428 (n(discovery)=52654 and n(replication)=14774) individuals of European ancestry. The inverse variance fixed effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on chromosome (Chr) 2q14, (P-combined=1.8x10(-11)), HLA-DRB1/DRB5 rs660895 on Chr6p21 (P-combined=1.5x10(-10)) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (P-combined=1.2x10(-122)). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology.

Published
2021

21. Antioxidant and B vitamin intake in relation to cognitive function in later life in the Lothian Birth Cohort 1936

Author

McNeill, G., Jia, X., Whalley, L.J., Fox, H.C., Corley, J., Gow, A.J., Brett, C.E., Starr, J.M., and Deary, I.J.

Subjects
Psychological aspects, Nutritional aspects, Usage, Demographic aspects, Food and nutrition, Health aspects, Cognition -- Nutritional aspects -- Demographic aspects -- Usage -- Psychological aspects -- Health aspects, Elderly -- Food and nutrition -- Psychological aspects -- Health aspects, Antioxidants (Nutrients) -- Health aspects -- Usage -- Psychological aspects, Vitamin B complex -- Health aspects -- Usage -- Psychological aspects -- Nutritional aspects, Dietary supplements -- Usage -- Health aspects -- Psychological aspects, Aged -- Food and nutrition -- Psychological aspects -- Health aspects, Antioxidants -- Health aspects -- Usage -- Psychological aspects, Vitamin B -- Health aspects -- Usage -- Psychological aspects -- Nutritional aspects
Abstract

Introduction Decline in cognitive function occurs as a normal part of the aging process, although the rate and extent of this decline vary widely between individuals. Two recent studies have [...], Background/Objectives: Cross-sectional and longitudinal studies provide some evidence for an association between intake of antioxidants and B vitamins, and cognitive function in later life, but intervention studies have not provided clear evidence of beneficial effects. The possibility that those with higher cognitive ability during earlier adult life consume more nutrient-rich diets in later life could provide an alternative explanation for the associations seen in observational studies. Methods: Survey of 1091 men and women born in 1936 living in Edinburgh, Scotland, in whom previous cognitive ability was available from intelligence quotient (IQ) measurements at age 11 years. At age 70 years, participants carried out a range of cognitive tests and completed a semiquantitative food-frequency questionnaire (FFQ). Results: A total of 882 participants returned completed FFQs from which intake of [beta]-carotene, vitamin C, B12, folate and riboflavin was estimated. IQ at age 11 years was positively associated with dietary intake of vitamin C (P = 0.048) and inversely associated with dietary intake of riboflavin (P < 0.001) at age 70 years, and was higher in those taking folate supplements at age 70 years (P < 0.005). Weak associations between intake of vitamins B12, C, riboflavin and folate and cognitive performance at age 70 years were attenuated by adjustment for confounding variables, including IQ at age 11 years. In the fully adjusted models, the proportion of total variance in cognitive function at age 70 years accounted for by intake of these nutrients was less than 1%. Conclusion: These results provide no evidence for a clinically significant beneficial association between intake of these antioxidants and B vitamins, and cognitive function at age 70 years. European Journal of Clinical Nutrition (2011) 65, 619-626; doi: 10.1038/ejcn.2011.2; published online 23 February 2011 Keywords: cognition; antioxidants; vitamin B complex; dietary supplements; aged

Published
2011
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23. Cognitive visual perceptual deficits in patients with delirium

Author

Brown, L.J.E., McGrory, S., McLaren, L., Starr, J.M., Deary, I.J., and MacLullich, A.M.J.

Subjects
Delirium -- Diagnosis, Delirium -- Development and progression, Vision disorders -- Risk factors, Cognition disorders -- Care and treatment, Cognition disorders -- Diagnosis, Health, Psychology and mental health
Published
2009

24. Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics

Author

Lam, M. Chen, C.-Y. Ge, T. Xia, Y. Hill, D.W. Trampush, J.W. Yu, J. Knowles, E. Davies, G. Stahl, E.A. Huckins, L. Liewald, D.C. Djurovic, S. Melle, I. Christoforou, A. Reinvang, I. DeRosse, P. Lundervold, A.J. Steen, V.M. Espeseth, T. Räikkönen, K. Widen, E. Palotie, A. Eriksson, J.G. Giegling, I. Konte, B. Hartmann, A.M. Roussos, P. Giakoumaki, S. Burdick, K.E. Payton, A. Ollier, W. Chiba-Falek, O. Koltai, D.C. Need, A.C. Cirulli, E.T. Voineskos, A.N. Stefanis, N.C. Avramopoulos, D. Hatzimanolis, A. Smyrnis, N. Bilder, R.M. Freimer, N.B. Cannon, T.D. London, E. Poldrack, R.A. Sabb, F.W. Congdon, E. Conley, E.D. Scult, M.A. Dickinson, D. Straub, R.E. Donohoe, G. Morris, D. Corvin, A. Gill, M. Hariri, A.R. Weinberger, D.R. Pendleton, N. Bitsios, P. Rujescu, D. Lahti, J. Le Hellard, S. Keller, M.C. Andreassen, O.A. Deary, I.J. Glahn, D.C. Huang, H. Liu, C. Malhotra, A.K. Lencz, T.

Abstract

Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify “druggable” targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing. © 2021, The Author(s).

Published
2021

25. Retinal microvascular abnormalities and cognitive dysfunction: a systematic review

Author

Ding, J., Patton, N., Deary, I.J., Strachan, M.W.J., Fowkes, F.G.R., Mitchell, R.J., and Price, J.F.

Subjects
Retinal diseases -- Care and treatment, Retinal diseases -- Demographic aspects, Retinal diseases -- Research, Cognition disorders in old age -- Research, Diabetics -- Psychological aspects, Diabetics -- Research, Health
Published
2008

26. Association of common genetic variants with brain microbleeds

Author

Knol, M.J., Lu, D.W., Traylor, M., Adams, H.H.H., Romero, J.R.J., Smith, A.V., Fornage, M., Hofer, E., Liu, J.F., Hostettler, I.C., Luciano, M., Trompet, S., Giese, A.K., Hilal, S., Akker, E.B. van den, Vojinovic, D., Li, S., Sigurdsson, S., Lee, S.J. van der, Jack, C.R., Wilson, D., Yilmaz, P., Satizabal, C.L., Liewald, D.C.M., Grond, J. van der, Chen, C., Saba, Y., Lugt, A. van der, Bastin, M.E., Windham, B.G., Cheng, C.Y., Pirpamer, L., Kantarci, K., Himali, J.J., Yang, Q., Morris, Z., Beiser, A.S., Tozer, D.J., Vernooij, M.W., Amin, N., Beekman, M., Koh, J.Y., Stott, D.J., Houlden, H., Schmidt, R., Gottesman, R.F., MacKinnon, A.D., DeCarli, C., Gudnason, V., Deary, I.J., Duijn, C.M. van, Slagboom, P.E., Wong, T.Y., Rost, N.S., Jukema, J.W., Mosley, T.H., Werring, D.J., Schmidt, H., Wardlaw, J.M., Ikram, M.A., Seshadri, S., Launer, L.J., Markus, H.S., Neurology, Amsterdam Neuroscience - Neurodegeneration, Epidemiology, Neurosciences, Clinical Genetics, and Radiology & Nuclear Medicine

Subjects
0301 basic medicine, medicine.medical_specialty, education.field_of_study, business.industry, Population, Genome-wide association study, Single-nucleotide polymorphism, Odds ratio, Gastroenterology, Hyperintensity, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Internal medicine, Genetic predisposition, medicine, Neurology (clinical), Allele, business, education, 030217 neurology & neurosurgery, Genetic association
Abstract

ObjectiveTo identify common genetic variants associated with the presence of brain microbleeds (BMBs).MethodsWe performed genome-wide association studies in 11 population-based cohort studies and 3 case–control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMBs were rated on susceptibility-weighted or T2*-weighted gradient echo MRI sequences, and further classified as lobar or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of APOE ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMBs.ResultsBMBs were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the APOE region reached genome-wide significance for its association with BMB (lead single nucleotide polymorphism rs769449; odds ratio [OR]any BMB [95% confidence interval (CI)] 1.33 [1.21–1.45]; p = 2.5 × 10−10). APOE ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19–1.50]; p = 1.0 × 10−6) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86–1.25]; p = 0.68). APOE ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB.ConclusionsGenetic variants in the APOE region are associated with the presence of BMB, most likely due to the APOE ε4 allele count related to a higher number of strictly lobar BMBs. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.

Published
2020
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27. Cerebral small vessel disease genomics and its implications across the lifespan

Author

Sargurupremraj, M., Suzuki, H., Jian, X.Q., Sarnowski, C., Evans, T.E., Bis, J.C., Eiriksdottir, G., Sakaue, S., Terzikhan, N., Habes, M., Zhao, W., Armstrong, N.J., Hofer, E., Yanek, L.R., Hagenaars, S.P., Kumar, R.B., Akker, E.B. van den, McWhirter, R.E., Trompet, S., Mishra, A., Saba, Y., Satizabal, C.L., Beaudet, G., Petit, L., Tsuchida, A., Zago, L., Schilling, S., Sigurdsson, S., Gottesman, R.F., Lewis, C.E., Aggarwal, N.T., Lopez, O.L., Smith, J.A., Hernandez, M.C.V., Grond, J. van der, Wright, M.J., Knol, M.J., Dorr, M., Thomson, R.J., Bordes, C., Grand, Q. le, Duperron, M.G., Smith, A.V., Knopman, D.S., Schreiner, P.J., Evans, D.A., Rotter, J.I., Beiser, A.S., Maniega, S.M., Beekman, M., Trollor, J., Stott, D.J., Vernooij, M.W., Wittfeld, K., Niessen, W.J., Soumare, A., Boerwinkle, E., Sidney, S., Turner, S.T., Davies, G., Thalamuthu, A., Volker, U., Buchem, M.A. van, Bryan, R.N., Dupuis, J., Bastin, M.E., Ames, D., Teumer, A., Amouyel, P., Kwok, J.B., Bulow, R., Deary, I.J., Schofield, P.R., Brodaty, H., Jiang, J.Y., Tabara, Y., Setoh, K., Miyamoto, S., Yoshida, K., Nagata, M., Kamatani, Y., Matsuda, F., Psaty, B.M., Bennett, D.A., Jager, P.L. de, Mosley, T.H., Sachdev, P.S., Schmidt, R., Warren, H.R., Evangelou, E., Tregouet, D.A., Ikram, M.A., Wen, W., DeCarli, C., Srikanth, V.K., Jukema, J.W., Slagboom, E.P., Kardia, S.L.R., Okada, Y., Mazoyer, B., Wardlaw, J.M., Nyquist, P.A., Mather, K.A., Grabe, H.J., Schmidt, H., Duijn, C.M. van, Gudnason, V., Longstreth, W.T., Launer, L.J., Lathrop, M., Seshadri, S., Tzourio, C., Adams, H.H., Matthews, P.M., Fornage, M., Debette, S., Int Network Thrombosis INVENT Cons, and Int Headache Genomics Consortium I

Subjects
Adult, Male, Science, BLOOD-PRESSURE, Risk Assessment, behavioral disciplines and activities, GENETIC ARCHITECTURE, Young Adult, Alzheimer Disease, Risk Factors, mental disorders, WHITE-MATTER HYPERINTENSITIES, WIDE ASSOCIATION, Humans, International Headache Genomics Consortium (IHGC), CELL-TYPES, Medical History Taking, METAANALYSIS, AGING RESEARCH, Aged, RISK, Aged, 80 and over, Science & Technology, Mendelian Randomization Analysis, Middle Aged, COGNITIVE IMPAIRMENT, White Matter, Multidisciplinary Sciences, Stroke, Diffusion Tensor Imaging, Genetic Loci, Cerebral Small Vessel Diseases, Hypertension, MENDELIAN RANDOMIZATION, Science & Technology - Other Topics, Female, International Network against Thrombosis (INVENT) Consortium, Genome-Wide Association Study
Abstract

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p=2.5x10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials. White matter hyperintensities (WMH) are a common brain-imaging feature of cerebral small vessel disease. Here, the authors carry out a GWAS and followup analyses for WMH-volume, implicating several variants with potential for risk stratification and drug targeting.

Published
2020

28. Assessment of Bidirectional Relationships Between Physical Activity and Depression Among Adults A 2-Sample Mendelian Randomization Study

Author

Choi, K.W., Chen, C.Y., Stein, M.B., Klimentidis, Y.C., Wang, M.J., Koenen, K.C., Smoller, J.W., Wray, N.R., Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E.M., Abdellaoui, A., Adams, M.J., Agerbo, E., Air, T., Andlauer, T.F.M., Bacanu, S.A., Baekvad-Hansen, M., Beekman, A.T.F., Bigdeli, T.B., Binder, E.B., Blackwood, D.H.R., Bryois, J., Buttenschon, H.N., Bybjerg-Grauholm, J., Cai, N., Castelao, E., Hvarregaard, J., Christensen, J.H., Clarke, T.K., Coleman, J.R.I., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Crawford, G.E., Davies, G., Deary, I.J., Degenhardt, F., Derks, E.M., Direk, N., Dolan, C.V., Dunn, E.C., Eley, T.C., Escott-Price, V., Kiadeh, F.F.H., Finucane, H.K., Forstner, A.J., Frank, J., Gaspar, H.A., Gill, M., Goes, F.S., Gordon, S.D., Grove, J., Hall, L.S., Hansen, C.S., Hansen, T.F., Herms, S., Hickie, I.B., Hoffmann, P., Homuth, G., Horn, C., Hottenga, J.J., Hougaard, D.M., Ising, M., Jansen, R., Jorgenson, E., Knowles, J.A., Kohane, I.S., Kraft, J., Kretzschmar, W., Krogh, J., Kutalik, Z., Li, Y.H., Lind, P.A., MacIntyre, D.J., MacKinnon, D.F., Maier, R.M., Marchini, J., McGrath, P., McGuffin, P., Medland, S.E., Mehta, D., Middeldorp, C.M., Mihailov, E., Milaneschi, Y., Milani, L., Mondimore, F.M., Montgomery, G.W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M.G., Nyholt, D.R., O'Reilly, P.F., Oskarsson, H., Owen, M.J., Painter, J.N., Pedersen, C.B., Pedersen, M.G., Peterson, R.E., Pettersson, E., Peyrot, W.J., Pistis, G., Posthuma, D., Quiroz, J.A., Qvist, P., Rice, J.P., Riley, B.P., Rivera, M., Saeed, S., Schoevers, R., Schulte, E.C., Shen, L., Shi, J.X., Shyn, S.I., Sigurdsson, E., Sinnamon, G.C.B., Smit, J.H., Smith, D.J., Stefansson, H., Steinberg, S., Streit, F., Strohmaier, J., Tansey, K.E., Teismann, H., Teumer, A., Thompson, W., Thomson, P.A., Thorgeirsson, T.E., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A.G., Umbricht, D., Auwera, S. van der, Hemert, A.M. van, Viktorin, A., Visscher, P.M., Wang, Y.P., Webb, B.T., Weinsheimer, S.M., Wellmann, J., Willemsen, G., Witt, S.H., Wu, Y., Xi, H.L.S., Yang, J., Zhang, F.T., Arolt, V., Baune, B.T., Berger, K., Boomsma, D.I., Cichon, S., Dannlowski, U., Geus, E.J.C. de, DePaulo, J.R., Domenici, E., Domschke, K., Esko, T., Grabe, H.J., Hamilton, S.P., Hayward, C., Heath, A.C., Kendler, K.S., Kloiber, S., Lewis, G., Li, Q.Q.S., Lucae, S., Madden, P.A.F., Magnusson, P.K., Martin, N.G., McIntosh, A.M., Metspalu, A., Mors, O., Mortensen, P.B., Nordentoft, M., Nothen, M.M., O'Donovan, M.C., Paciga, S.A., Pedersen, N.L., Penninx, B.W.J.H., Perlis, R.H., Porteous, D.J., Potash, J.B., Preisig, M., Rietschel, M., Schaefer, C., Schulze, T.G., Stefansson, K., Tiemeier, H., Uher, R., Volzke, H., Weissman, M.M., Werge, T., Lewis, C.M., Levinson, D.F., Breen, G., Borglum, A.D., Sullivan, P.F., Major Depressive Disorder Working, Epidemiology, Internal Medicine, Child and Adolescent Psychiatry / Psychology, Psychiatry, Biological Psychology, APH - Methodology, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, APH - Mental Health, and Adult Psychiatry

Subjects
Adult, DISORDER, medicine.medical_specialty, Genome-wide association study, EXERCISE, CAUSALITY, 03 medical and health sciences, 0302 clinical medicine, SDG 3 - Good Health and Well-being, PEOPLE, Internal medicine, Accelerometry, Mendelian randomization, SCHIZOPHRENIA, Humans, Medicine, ANXIETY, Exercise, RISK, Depressive Disorder, Major, business.industry, Case-control study, SEDENTARY BEHAVIOR, Mendelian Randomization Analysis, Odds ratio, ASSOCIATION, Protective Factors, medicine.disease, 030227 psychiatry, Psychiatry and Mental health, Sample size determination, Case-Control Studies, Meta-analysis, Major depressive disorder, Self Report, business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Importance: Increasing evidence shows that physical activity is associated with reduced risk for depression, pointing to a potential modifiable target for prevention. However, the causality and direction of this association are not clear; physical activity may protect against depression, and/or depression may result in decreased physical activity.Objective: To examine bidirectional relationships between physical activity and depression using a genetically informed method for assessing potential causal inference.Design, Setting, and Participants: This 2-sample mendelian randomization (MR) used independent top genetic variants associated with 2 physical activity phenotypes-self-reported (n = 377 234) and objective accelerometer-based (n = 91 084)-and with major depressive disorder (MDD) (n = 143 265) as genetic instruments from the largest available, nonoverlapping genome-wide association studies (GWAS). GWAS were previously conducted in diverse observational cohorts, including the UK Biobank (for physical activity) and participating studies in the Psychiatric Genomics Consortium (for MDD) among adults of European ancestry. Mendelian randomization estimates from each genetic instrument were combined using inverse variance weighted meta-analysis, with alternate methods (eg, weighted median, MR Egger, MR-Pleiotropy Residual Sum and Outlier [PRESSO]) and multiple sensitivity analyses to assess horizontal pleiotropy and remove outliers. Data were analyzed from May 10 through July 31, 2018.Main Outcomes and Measures: MDD and physical activity.Results: GWAS summary data were available for a combined sample size of 611 583 adult participants. Mendelian randomization evidence suggested a protective relationship between accelerometer-based activity and MDD (odds ratio [OR], 0.74 for MDD per 1-SD increase in mean acceleration; 95% CI, 0.59-0.92; P = .006). In contrast, there was no statistically significant relationship between MDD and accelerometer-based activity (β = -0.08 in mean acceleration per MDD vs control status; 95% CI, -0.47 to 0.32; P = .70). Furthermore, there was no significant relationship between self-reported activity and MDD (OR, 1.28 for MDD per 1-SD increase in metabolic-equivalent minutes of reported moderate-to-vigorous activity; 95% CI, 0.57-3.37; P = .48), or between MDD and self-reported activity (β = 0.02 per MDD in standardized metabolic-equivalent minutes of reported moderate-to-vigorous activity per MDD vs control status; 95% CI, -0.008 to 0.05; P = .15).Conclusions and Relevance: Using genetic instruments identified from large-scale GWAS, robust evidence supports a protective relationship between objectively assessed-but not self-reported-physical activity and the risk for MDD. Findings point to the importance of objective measurement of physical activity in epidemiologic studies of mental health and support the hypothesis that enhancing physical activity may be an effective prevention strategy for depression.

Published
2019
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29. Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders

Author

Nabais, M.F., Laws, S.M., Lin, T., Vallerga, C.L., Armstrong, N.J., Blair, I.P., Kwok, J.B., Mather, K.A., Mellick, G.D., Sachdev, P.S., Wallace, L., Henders, A.K., Zwamborn, R.A.J., Hop, P.J., Lunnon, K., Pishva, E., Roubroeks, J.A.Y., Soininen, H., Tsolaki, M., Mecocci, P., Lovestone, S., Kłoszewska, I., Vellas, B., Furlong, S., Garton, F.C., Henderson, R.D., Mathers, S., McCombe, P.A., Needham, M., Ngo, S.T., Nicholson, G., Pamphlett, R., Rowe, D.B., Steyn, F.J., Williams, K.L., Anderson, T.J., Bentley, S.R., Dalrymple-Alford, J., Fowder, J., Gratten, J., Halliday, G., Hickie, I.B., Kennedy, M., Lewis, S.J.G., Montgomery, G.W., Pearson, J., Pitcher, T.L., Silburn, P., Zhang, F., Visscher, P.M., Yang, J., Stevenson, A.J., Hillary, R.F., Marioni, R.E., Harris, S.E., Deary, I.J., Jones, A.R., Shatunov, A., Iacoangeli, A., van Rheenen, W., van den Berg, L.H., Shaw, P.J., Shaw, C.E., Morrison, K.E., Al-Chalabi, A., Veldink, J.H., Hannon, E., Mill, J., Wray, N.R., McRae, A.F., Nabais, M.F., Laws, S.M., Lin, T., Vallerga, C.L., Armstrong, N.J., Blair, I.P., Kwok, J.B., Mather, K.A., Mellick, G.D., Sachdev, P.S., Wallace, L., Henders, A.K., Zwamborn, R.A.J., Hop, P.J., Lunnon, K., Pishva, E., Roubroeks, J.A.Y., Soininen, H., Tsolaki, M., Mecocci, P., Lovestone, S., Kłoszewska, I., Vellas, B., Furlong, S., Garton, F.C., Henderson, R.D., Mathers, S., McCombe, P.A., Needham, M., Ngo, S.T., Nicholson, G., Pamphlett, R., Rowe, D.B., Steyn, F.J., Williams, K.L., Anderson, T.J., Bentley, S.R., Dalrymple-Alford, J., Fowder, J., Gratten, J., Halliday, G., Hickie, I.B., Kennedy, M., Lewis, S.J.G., Montgomery, G.W., Pearson, J., Pitcher, T.L., Silburn, P., Zhang, F., Visscher, P.M., Yang, J., Stevenson, A.J., Hillary, R.F., Marioni, R.E., Harris, S.E., Deary, I.J., Jones, A.R., Shatunov, A., Iacoangeli, A., van Rheenen, W., van den Berg, L.H., Shaw, P.J., Shaw, C.E., Morrison, K.E., Al-Chalabi, A., Veldink, J.H., Hannon, E., Mill, J., Wray, N.R., and McRae, A.F.

Abstract

Background People with neurodegenerative disorders show diverse clinical syndromes, genetic heterogeneity, and distinct brain pathological changes, but studies report overlap between these features. DNA methylation (DNAm) provides a way to explore this overlap and heterogeneity as it is determined by the combined effects of genetic variation and the environment. In this study, we aim to identify shared blood DNAm differences between controls and people with Alzheimer’s disease, amyotrophic lateral sclerosis, and Parkinson’s disease. Results We use a mixed-linear model method (MOMENT) that accounts for the effect of (un)known confounders, to test for the association of each DNAm site with each disorder. While only three probes are found to be genome-wide significant in each MOMENT association analysis of amyotrophic lateral sclerosis and Parkinson’s disease (and none with Alzheimer’s disease), a fixed-effects meta-analysis of the three disorders results in 12 genome-wide significant differentially methylated positions. Predicted immune cell-type proportions are disrupted across all neurodegenerative disorders. Protein inflammatory markers are correlated with profile sum-scores derived from disease-associated immune cell-type proportions in a healthy aging cohort. In contrast, they are not correlated with MOMENT DNAm-derived profile sum-scores, calculated using effect sizes of the 12 differentially methylated positions as weights. Conclusions We identify shared differentially methylated positions in whole blood between neurodegenerative disorders that point to shared pathogenic mechanisms. These shared differentially methylated positions may reflect causes or consequences of disease, but they are unlikely to reflect cell-type proportion differences.

Published
2021

30. DNA methylation of blood cells is associated with prevalent type 2 diabetes in a meta-analysis of four European cohorts

Author

Juvinao-Quintero, D.L. (Diana L.), Marioni, R.E. (Riccardo), Ochoa Rosales, C.P. (Carolina), Russ, T.C. (Tom C.), Deary, I.J. (Ian), Meurs, J.B.J. (Joyce) van, Voortman, R.G. (Trudy), Hivert, M.-F. (Marie-France), Sharp, G.C. (Gemma C.), Relton, C.L. (Caroline), Elliott, H.R. (Hannah R.), Juvinao-Quintero, D.L. (Diana L.), Marioni, R.E. (Riccardo), Ochoa Rosales, C.P. (Carolina), Russ, T.C. (Tom C.), Deary, I.J. (Ian), Meurs, J.B.J. (Joyce) van, Voortman, R.G. (Trudy), Hivert, M.-F. (Marie-France), Sharp, G.C. (Gemma C.), Relton, C.L. (Caroline), and Elliott, H.R. (Hannah R.)

Abstract

Background: Type 2 diabetes (T2D) is a heterogeneous disease with well-known genetic and environmental risk factors contributing to its prevalence. Epigenetic mech

Published
2021
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31. Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging.

Author

McCartney D.L., Min J.L., Richmond R.C., Lu A.T., Sobczyk M.K., Davies G., Broer L., Guo X., Jeong A., Jung J., Kasela S., Katrinli S., Kuo P.-L., Matias-Garcia P.R., Mishra P.P., Nygaard M., Palviainen T., Patki A., Raffield L.M., Ratliff S.M., Richardson T.G., Robinson O., Soerensen M., Sun D., Tsai P.-C., van der Zee M.D., Walker R.M., Wang X., Wang Y., Xia R., Xu Z., Yao J., Zhao W., Correa A., Boerwinkle E., Dugue P.-A., Durda P., Elliott H.R., Gieger C., de Geus E.J.C., Harris S.E., Hemani G., Imboden M., Kahonen M., Kardia S.L.R., Kresovich J.K., Li S., Lunetta K.L., Mangino M., Mason D., McIntosh A.M., Mengel-From J., Moore A.Z., Murabito J.M., Ollikainen M., Pankow J.S., Pedersen N.L., Peters A., Polidoro S., Porteous D.J., Raitakari O., Rich S.S., Sandler D.P., Sillanpaa E., Smith A.K., Southey M.C., Strauch K., Tiwari H., Tanaka T., Tillin T., Uitterlinden A.G., Van Den Berg D.J., van Dongen J., Wilson J.G., Wright J., Yet I., Arnett D., Bandinelli S., Bell J.T., Binder A.M., Boomsma D.I., Chen W., Christensen K., Conneely K.N., Elliott P., Ferrucci L., Fornage M., Hagg S., Hayward C., Irvin M., Kaprio J., Lawlor D.A., Lehtimaki T., Lohoff F.W., Milani L., Milne R.L., Probst-Hensch N., Reiner A.P., Ritz B., Rotter J.I., Smith J.A., Taylor J.A., van Meurs J.B.J., Vineis P., Waldenberger M., Deary I.J., Relton C.L., Horvath S., Marioni R.E., McCartney D.L., Min J.L., Richmond R.C., Lu A.T., Sobczyk M.K., Davies G., Broer L., Guo X., Jeong A., Jung J., Kasela S., Katrinli S., Kuo P.-L., Matias-Garcia P.R., Mishra P.P., Nygaard M., Palviainen T., Patki A., Raffield L.M., Ratliff S.M., Richardson T.G., Robinson O., Soerensen M., Sun D., Tsai P.-C., van der Zee M.D., Walker R.M., Wang X., Wang Y., Xia R., Xu Z., Yao J., Zhao W., Correa A., Boerwinkle E., Dugue P.-A., Durda P., Elliott H.R., Gieger C., de Geus E.J.C., Harris S.E., Hemani G., Imboden M., Kahonen M., Kardia S.L.R., Kresovich J.K., Li S., Lunetta K.L., Mangino M., Mason D., McIntosh A.M., Mengel-From J., Moore A.Z., Murabito J.M., Ollikainen M., Pankow J.S., Pedersen N.L., Peters A., Polidoro S., Porteous D.J., Raitakari O., Rich S.S., Sandler D.P., Sillanpaa E., Smith A.K., Southey M.C., Strauch K., Tiwari H., Tanaka T., Tillin T., Uitterlinden A.G., Van Den Berg D.J., van Dongen J., Wilson J.G., Wright J., Yet I., Arnett D., Bandinelli S., Bell J.T., Binder A.M., Boomsma D.I., Chen W., Christensen K., Conneely K.N., Elliott P., Ferrucci L., Fornage M., Hagg S., Hayward C., Irvin M., Kaprio J., Lawlor D.A., Lehtimaki T., Lohoff F.W., Milani L., Milne R.L., Probst-Hensch N., Reiner A.P., Ritz B., Rotter J.I., Smith J.A., Taylor J.A., van Meurs J.B.J., Vineis P., Waldenberger M., Deary I.J., Relton C.L., Horvath S., and Marioni R.E.

Abstract

Background: Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Result(s): Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion(s): This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.Copyright © 2021, The Author(s).

Published
2021

32. Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group

Author

Jia, T., Chu, C., Liu, Y., van Dongen, J., Papastergios, E., Armstrong, Nicola, Bastin, M.E., Carrillo-Roa, T., den Braber, A., Harris, M., Jansen, R., Liu, J., Luciano, M., Ori, A.P.S., Roiz Santiañez, R., Ruggeri, B., Sarkisyan, D., Shin, J., Sungeun, K., Tordesillas Gutiérrez, D., van’t Ent, D., Ames, D., Artiges, E., Bakalkin, G., Banaschewski, T., Bokde, A.L.W., Brodaty, H., Bromberg, U., Brouwer, R., Büchel, C., Burke Quinlan, E., Cahn, W., de Zubicaray, G.I., Ehrlich, S., Ekström, T.J., Flor, H., Fröhner, J.H., Frouin, V., Garavan, H., Gowland, P., Heinz, A., Hoare, J., Ittermann, B., Jahanshad, N., Jiang, J., Kwok, J.B., Martin, N.G., Martinot, J.L., Mather, K.A., McMahon, K.L., McRae, A.F., Nees, F., Papadopoulos Orfanos, D., Paus, T., Poustka, L., Sämann, P.G., Schofield, P.R., Smolka, M.N., Stein, D.J., Strike, L.T., Teeuw, J., Thalamuthu, A., Trollor, J., Walter, H., Wardlaw, J.M., Wen, W., Whelan, R., Apostolova, L.G., Binder, E.B., Boomsma, D.I., Calhoun, V., Crespo-Facorro, B., Deary, I.J., Hulshoff Pol, H., Ophoff, R.A., Pausova, Z., Sachdev, P.S., Saykin, A., Wright, M.J., Thompson, P.M., Schumann, G., Desrivières, S., Jia, T., Chu, C., Liu, Y., van Dongen, J., Papastergios, E., Armstrong, Nicola, Bastin, M.E., Carrillo-Roa, T., den Braber, A., Harris, M., Jansen, R., Liu, J., Luciano, M., Ori, A.P.S., Roiz Santiañez, R., Ruggeri, B., Sarkisyan, D., Shin, J., Sungeun, K., Tordesillas Gutiérrez, D., van’t Ent, D., Ames, D., Artiges, E., Bakalkin, G., Banaschewski, T., Bokde, A.L.W., Brodaty, H., Bromberg, U., Brouwer, R., Büchel, C., Burke Quinlan, E., Cahn, W., de Zubicaray, G.I., Ehrlich, S., Ekström, T.J., Flor, H., Fröhner, J.H., Frouin, V., Garavan, H., Gowland, P., Heinz, A., Hoare, J., Ittermann, B., Jahanshad, N., Jiang, J., Kwok, J.B., Martin, N.G., Martinot, J.L., Mather, K.A., McMahon, K.L., McRae, A.F., Nees, F., Papadopoulos Orfanos, D., Paus, T., Poustka, L., Sämann, P.G., Schofield, P.R., Smolka, M.N., Stein, D.J., Strike, L.T., Teeuw, J., Thalamuthu, A., Trollor, J., Walter, H., Wardlaw, J.M., Wen, W., Whelan, R., Apostolova, L.G., Binder, E.B., Boomsma, D.I., Calhoun, V., Crespo-Facorro, B., Deary, I.J., Hulshoff Pol, H., Ophoff, R.A., Pausova, Z., Sachdev, P.S., Saykin, A., Wright, M.J., Thompson, P.M., Schumann, G., and Desrivières, S.

Abstract

DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)—three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions.

Published
2021

34. Childhood IQ and cardiovascular disease in adulthood: prospective observational study linking the Scottish Mental Survey 1932 and the Midspan studies

Author

Hart, C.L., Taylor, M.D., Smith, G. Davey, Whalley, L.J., Starr, J.M., Hole, D.J., Wilson, V., and Deary, I.J.

Subjects
Heart diseases -- Causes of, Heart diseases -- Research, Intellect -- Health aspects, Intelligence levels -- Health aspects, Health, Social sciences
Abstract

This study investigated the influence of childhood IQ on the relationships between risk factors and cardiovascular disease (CVD), coronary heart disease (CHD) and stroke in adulthood. Participants were from the Midspan prospective cohort studies which were conducted on adults in Scotland in the 1970s. Data on risk factors were collected from a questionnaire and at a screening examination, and participants were followed up for 25 years for hospital admissions and mortality. 938 Midspan participants were successfully matched with their age 11 IQ from the Scottish Mental Survey 1932, in which 1921-born children attending schools in Scotland took a cognitive ability test. Childhood IQ was negatively correlated with diastolic and systolic blood pressure, and positively correlated with height and respiratory function in adulthood. For each of CVD, CHD and stroke, defined as either a hospital admission or death, there was an increased relative rate per standard deviation decrease (15 points) in childhood IQ of 1.11 (95% confidence interval 1.01-1.23), 1.16 (l.03-1.32) and 1.10 (0.88-1.36), respectively. With events divided into those first occurring before and those first occurring after the age of 65, the relationships between childhood IQ and CVD, CHD and stroke were only seen before age 65 and not after age 65. Blood pressure, height, respiratory function and smoking were associated with CVD events. Relationships were stronger in the early compared to the later period for smoking and FEV1, and stronger in the later compared to the earlier period for blood pressure. Adjustment for childhood IQ had small attenuating effects on the risk factor--CVD relationship before age 65 and no effects after age 65. Adjustment for risk factors attenuated the childhood IQ--CVD relationship by a small amount before age 65. Childhood IQ was associated with CVD risk factors and events and can be considered an important new risk factor. Keywords: Cardiovascular disease; Cohort; Mental ability; Mortality; Risk factors; Scotland

Published
2004

35. Enlarged perivascular spaces are associated with cognitive function in healthy elderly men

Author

MacLullich, A.M., Wardlaw, J.M., Ferguson, K.J., Starr, J.M., Seckl, J.R., and Deary, I.J.

Subjects
Aged men -- Health aspects, Cognition in old age -- Complications and side effects, Cognition in old age -- Observations, Magnetic resonance imaging -- Methods, Basal ganglia -- Abnormalities, Basal ganglia -- Observations, Health, Psychology and mental health
Published
2004

36. Increased blood--brain barrier permeability in type II diabetes demonstrated by gadolinium magnetic resonance imaging. (Paper)

Author

Starr, J.M., Wardlaw, J., Ferguson, K., MacLullich, A., Deary, I.J., and Marshall, I.

Subjects
Physiological aspects, Blood-brain barrier -- Physiological aspects, Type 2 diabetes -- Physiological aspects
Abstract

Objectives: Patients with type II diabetes are at increased risk of cognitive impairment. The retinal and renal complications of diabetes follow microvascular damage permitting small arterioles to leak, hence the [...]

Published
2003

37. Brain white matter lesions detected by magnetic resosnance imaging are associated with balance and gait speed. (Paper)

Author

Starr, J.M., Leaper, S.A., Murray, A.D., Lemmon, H.A., Staff, R.T., Deary, I.J., and Whalley, L.J.

Subjects
Usage, Physiological aspects, Medical examination, Brain -- Medical examination -- Physiological aspects -- Usage, Equilibrium (Physiology) -- Physiological aspects -- Usage, Human locomotion -- Physiological aspects -- Usage, Magnetic resonance imaging -- Usage -- Physiological aspects
Abstract

Objective: To investigate the relations between premorbid and current mental ability, mood, and white matter signal abnormalities detected by T2 weighted brain magnetic resonance imaging (MRI) and impairment of balance [...]

Published
2003

39. Intelligence in early adulthood and subsequent risk of unintentional injury over two decades: cohort study of 1 109 475 Swedish men

Author

Whitley, E., Batty, G.D., Gale, C.R., Deary, I.J., Tynelius, P., and Rasmussen, F.

Subjects
Intellect -- Research, Intellect -- Health aspects, Intelligence levels -- Research, Intelligence levels -- Health aspects, Wounds and injuries -- Research, Wounds and injuries -- Prognosis, Wounds and injuries -- Demographic aspects, Wounds and injuries -- Risk factors, Health, Social sciences
Published
2010

40. Associations between vascular risk factors and brain MRI indices in UK Biobank

Author

Cox, S.R., Lyall, Donald M., Ritchie, S.J., Bastin, M.E., Harris, M.A., Buchanan, C.R., Fawns-Ritchie, C., Barbu, M.C., de Nooij, L., Reus, L.M., Alloza, C., Shen, X., Neilson, E., Alderson, H.L., Hunter, S., Liewald, D.C., Whalley, H.C., McIntosh, A.M., Lawrie, S.J., Pell, Jill P., Tucker-Drob, E.M., Wardlaw, J.M., Gale, C.R., Deary, I.J., Neurology, and Amsterdam Neuroscience - Neurodegeneration

Subjects
Adult, Male, brain, Fast Track Clinical Research, Imaging, Diffusion, Risk Factors, Humans, Aged, Biological Specimen Banks, White matter, diffusion, Brain, Middle Aged, Magnetic Resonance Imaging, United Kingdom, Editor's Choice, Cerebrovascular Disorders, cortex, Cortex, Female, vascular risk, Vascular risk, white matter, MRI
Abstract

Aims: Several factors are known to increase risk for cerebrovascular disease and dementia, but there is limited evidence on associations between multiple vascular risk factors (VRFs) and detailed aspects of brain macrostructure and microstructure in large community-dwelling populations across middle and older age. Methods and Results: Associations between VRFs (smoking, hypertension, pulse pressure, diabetes, hypercholesterolaemia, body mass index, and waist–hip ratio) and brain structural and diffusion MRI markers were examined in UK Biobank (N = 9722, age range 44–79 years). A larger number of VRFs was associated with greater brain atrophy, lower grey matter volume, and poorer white matter health. Effect sizes were small (brain structural R2 ≤1.8%). Higher aggregate vascular risk was related to multiple regional MRI hallmarks associated with dementia risk: lower frontal and temporal cortical volumes, lower subcortical volumes, higher white matter hyperintensity volumes, and poorer white matter microstructure in association and thalamic pathways. Smoking pack years, hypertension and diabetes showed the most consistent associations across all brain measures. Hypercholesterolaemia was not uniquely associated with any MRI marker.Conclusion: Higher levels of VRFs were associated with poorer brain health across grey and white matter macrostructure and microstructure. Effects are mainly additive, converging upon frontal and temporal cortex, subcortical structures, and specific classes of white matter fibres. Though effect sizes were small, these results emphasize the vulnerability of brain health to vascular factors even in relatively healthy middle and older age, and the potential to partly ameliorate cognitive decline by addressing these malleable risk factors.

Published
2019
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41. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function (vol 9, 2098, 2018)

Author

Davies, G., Lam, M., Harris, S.E., Trampush, J.W., Luciano, M., Hill, W.D., Hagenaars, S.P., Ritchie, S.J., Marioni, R.E., Fawns-Ritchie, C., Liewald, D.C.M., Okely, J.A., Ahola-Olli, A.V., Barnes, C.L.K., Bertram, L., Bis, J.C., Burdick, K.E., Christoforou, A., DeRosse, P., Djurovic, S., Espeseth, T., Giakoumaki, S., Giddaluru, S., Gustavson, D.E., Hayward, C., Hofer, E., Ikram, M.A., Karlsson, R., Knowles, E., Lahti, J., Leber, M., Li, S., Mather, K.A., Melle, I., Morris, D., Oldmeadow, C., Palviainen, T., Payton, A., Pazoki, R., Petrovic, K., Reynolds, C.A., Sargurupremraj, M., Scholz, M., Smith, J.A., Smith, A.V., Terzikhan, N., Thalamuthu, A., Trompet, S., Lee, S.J. van der, Ware, E.B., Windham, B.G., Wright, M.J., Yang, J.Y., Yu, J., Ames, D., Amin, N., Amouyel, P., Andreassen, O.A., Armstrong, N.J., Assareh, A.A., Attia, J.R., Attix, D., Avramopoulos, D., Bennett, D.A., Bohmer, A.C., Boyle, P.A., Brodaty, H., Campbell, H., Cannon, T.D., Cirulli, E.T., Congdon, E., Conley, E.D., Corley, J., Cox, S.R., Dale, A.M., Dehghan, A., Dick, D., Dickinson, D., Eriksson, J.G., Evangelou, E., Faul, J.D., Ford, I., Freimer, N.A., Gao, H., Giegling, I., Gillespie, N.A., Gordon, S.D., Gottesman, R.F., Griswold, M.E., Gudnason, V., Harris, T.B., Hartmann, A.M., Hatzimanolis, A., Heiss, G., Holliday, E.G., Joshi, P.K., Kahonen, M., Kardia, S.L.R., Karlsson, I., Kleineidam, L., Knopman, D.S., Kochan, N.A., Konte, B., Kwok, J.B., Hellard, S. le, Lee, T., Lehtimaki, T., Li, S.C., Lill, C.M., Liu, T., Koini, M., London, E., Longstreth, W.T., Lopez, O.L., Loukola, A., Luck, T., Lundervold, A.J., Lundquist, A., Lyytikainen, L.P., Martin, N.G., Montgomery, G.W., Murray, A.D., Need, A.C., Noordam, R., Nyberg, L., Ollier, W., Papenberg, G., Pattie, A., Polasek, O., Poldrack, R.A., Psaty, B.M., Reppermund, S., Riedel-Heller, S.G., Rose, R.J., Rotter, J.I., Roussos, P., Rovio, S.P., Saba, Y., Sabb, F.W., Sachdev, P.S., Satizabal, C.L., Schmid, M., Scott, R.J., Scult, M.A., Simino, J., Slagboom, P.E., Smyrnis, N., Soumare, A., Stefanis, N.C., Stott, D.J., Straub, R.E., Sundet, K., Taylor, A.M., Taylor, K.D., Tzoulaki, I., Tzourio, C., Uitterlinden, A., Vitart, V., Voineskos, A.N., Kaprio, J., Wagner, M., Wagner, H., Weinhold, L., Wen, K.H., Widen, E., Yang, Q., Zhao, W., Adams, H.H.H., Arking, D.E., Bilder, R.M., Bitsios, P., Boerwinkle, E., Chiba-Falek, O., Corvin, A., Jager, P.L. de, Debette, S., Donohoe, G., Elliott, P., Fitzpatrick, A.L., Gill, M., Glahn, D.C., Hagg, S., Hansell, N.K., Hariri, A.R., Ikram, M.K., Jukema, J.W., Vuoksimaa, E., Keller, M.C., Kremen, W.S., Launer, L., Lindenberger, U., Palotie, A., Pedersen, N.L., Pendleton, N., Porteous, D.J., Raikkonen, K., Raitakari, O.T., Ramirez, A., Reinvang, I., Rudan, I., Rujescu, D., Schmidt, R., Schmidt, H., Schofield, P.W., Schofield, P.R., Starr, J.M., Steen, V.M., Trollor, J.N., Turner, S.T., Duijn, C.M. van, Villringer, A., Weinberger, D.R., Weir, D.R., Wilson, J.F., Malhotra, A., McIntosh, A.M., Gale, C.R., Seshadri, S., Mosley, T.H., Bressler, J., Lencz, T., and Deary, I.J.

Published
2019

42. Identification of common genetic risk variants for autism spectrum disorder

Author

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., Baekvad-Hansen, M., Cerrato, F., Chambert, K., Christensen, J.H., Churchhouse, C., Dellenvall, K., Demontis, D., Rubeis, S. de, Devlin, B., Djurovic, S., Dumont, A.L., Goldstein, J.I., Hansen, C.S., Hauberg, M.E., Hollegaard, M.V., Hope, S., Howrigan, D.P., Huang, H., Hultman, C.M., Klei, L., Maller, J., Martin, J., Martin, A.R., Moran, J.L., Nyegaard, M., Naeland, T., Palmer, D.S., Palotie, A., Pedersen, C.B., Pedersen, M.G., dPoterba, T., Poulsen, J.B., St Pourcain, B., Qvist, P., Rehnstrom, K., Reichenberg, A., Reichert, J., Robinson, E.B., Roeder, K., Roussos, P., Saemundsen, E., Sandin, S., Satterstrom, F.K., Smith, G.D., Stefansson, H., Steinberg, S., Stevens, C.R., Sullivan, P.F., Turley, P., Walters, G.B., Xu, X.Y., Stefansson, K., Geschwind, D.H., Nordentoft, M., Hougaard, D.M., Werge, T., Mors, O., Mortensen, P.B., Neale, B.M., Daly, M.J., Borglum, A.D., Wray, N.R., Trzaskowski, M., Byrne, E.M., Abdellaoui, A., Adams, M.J., Air, T.M., Andlauer, T.F.M., Bacanu, S.A., Beekman, A.T.F., Bigdeli, T.B., Binder, E.B., Blackwood, D.H.R., Bryois, J., Buttenschon, H.N., Cai, N., Castelao, E., Clarke, T.K., Coleman, J.R.I., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Crawford, G.E., Davies, G., Deary, I.J., Degenhardt, F., Derks, E.M., Direk, N., Dolan, C.V., Dunn, E.C., Eley, T.C., Escott-Price, V., Kiadeh, F.F.H., Finucane, H.K., Forstner, A.J., Frank, J., Gaspar, H.A., Gill, M., Goes, F.S., Gordon, S.D., Hall, L.S., Hansen, T.F., Herms, S., Hickie, I.B., Hoffmann, P., Homuth, G., Horn, C., Hottenga, J.J., Ising, M., Jansen, R., Jorgenson, E., Knowles, J.A., Kohane, I.S., Kraft, J., Kretzschmar, W.W., Krogh, J., Kutalik, Z., Li, Y., Lind, P.A., MacIntyre, D.J., MacKinnon, D.F., Maier, R.M., Maier, W., Marchini, J., Mbarek, H., McGrath, P., McGuffin, P., Medland, S.E., Mehta, D., Middeldorp, C.M., Mihailov, E., Milaneschi, Y., Milani, L., Mondimore, F.M., Montgomery, G.W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M.G., Nyholt, D.R., O'Reilly, P.F., Oskarsson, H., Owen, M.J., Painter, J.N., Peterson, R.E., Pettersson, E., Peyrot, W.J., Pistis, G., Posthuma, D., Quiroz, J.A., Rice, J.P., Riley, B.P., Rivera, M., Mirza, S.S., Schoevers, R., Schulte, E.C., Shen, L., Shi, J.X., Shyn, S.I., Sigurdsson, E., Sinnamon, G.C.B., Smit, J.H., Smith, D.J., Streit, F., Strohmaier, J., Tansey, K.E., Teismann, H., Teumer, A., Thompson, W., Thomson, P.A., Thorgeirsson, T.E., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A.G., Umbricht, D., Auwera, S. van der, Hemert, A.M. van, Viktorin, A., Visscher, P.M., Wang, Y.P., Webb, B.T., Weinsheimer, S.M., Wellmann, J., Willemsen, G., Witt, S.H., Wu, Y., Xi, H.S., Yang, J., Zhang, F.T., Arolt, V., Baune, B.T., Berger, K., Boomsma, D.I., Cichon, S., Dannlowski, U., Geus, E.J.C. de, DePaulo, J.R., Domenici, E., Domschke, K., Esko, T., Grabe, H.J., Hamilton, S.P., Hayward, C., Heath, A.C., Kendler, K.S., Kloiber, S., Lewis, G., Li, Q.S., Lucae, S., Madden, P.A.F., Magnusson, P.K., Martin, N.G., McIntosh, A.M., Metspalu, A., Muller-Myhsok, B., Nothen, M.M., O'Donovan, M.C., Paciga, S.A., Pedersen, N.L., Penninx, B.W.J.H., Perlis, R.H., Porteous, D.J., Potash, J.B., Preisig, M., Rietschel, M., Schaefer, C., Schulze, T.G., Smoller, J.W., Tiemeier, H., Uher, R., Volzke, H., Weissman, M.M., Lewis, C.M., Levinson, D.F., Breen, G., Agee, M., Alipanahi, B., Auton, A., Bell, R.K., Bryc, K., Elson, S.L., Fontanillas, P., Furlotte, N.A., Hromatka, B.S., Huber, K.E., Kleinman, A., Litterman, N.K., McIntyre, M.H., Mountain, J.L., Noblin, E.S., Northover, C.A.M., Pitts, S.J., Sathirapongsasuti, J.F., Sazonova, O.V., Shelton, J.F., Shringarpure, S., Tung, J.Y., Vacic, V., Wilson, C.H., Psychiat Genomics Consortium, BUPGEN, 23andMe Re, Biological Psychology, APH - Methodology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, APH - Mental Health, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, Adult Psychiatry, Psychiatry, Human genetics, Amsterdam Reproduction & Development (AR&D), VU University medical center, APH - Digital Health, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Perceptual and Cognitive Neuroscience (PCN), Clinical Cognitive Neuropsychiatry Research Program (CCNP), Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium, BUPGEN, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Me Research Team, Epidemiology, and Child and Adolescent Psychiatry / Psychology

Subjects
Male, Netherlands Twin Register (NTR), Multifactorial Inheritance, Autism Spectrum Disorder, Denmark, LD SCORE REGRESSION, LOCI, Genome-wide association study, DE-NOVO, 0302 clinical medicine, Polymorphism (computer science), Risk Factors, SYNAPTIC PLASTICITY, CELL-SURFACE, Child, Genetics, 0303 health sciences, HERITABILITY, Genetic Predisposition to Disease/genetics, 1184 Genetics, developmental biology, physiology, Polymorphism, Single Nucleotide/genetics, Phenotype, 3. Good health, Schizophrenia, Autism spectrum disorder, Child, Preschool, Genome-Wide Association Study/methods, Female, SIMONS SIMPLEX COLLECTION, Adolescent, Biology, NEURITE OUTGROWTH, Polymorphism, Single Nucleotide, behavioral disciplines and activities, Article, 03 medical and health sciences, mental disorders, medicine, Humans, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, SDG 2 - Zero Hunger, Multifactorial Inheritance/genetics, METAANALYSIS, 030304 developmental biology, Case-control study, Heritability, medicine.disease, Autism Spectrum Disorder/genetics, Case-Control Studies, 3111 Biomedicine, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Published in final edited form as: Nat Genet. 2019 March ; 51(3): 431–444. doi:10.1038/s41588-019-0344-8., Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 ASD cases and 27,969 controls that identifies five genome-wide significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), seven additional loci shared with other traits are identified at equally strict significance levels. Dissecting the polygenic architecture, we find both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis and establish that GWAS performed at scale will be much more productive in the near term in ASD., The iPSYCH project is funded by the Lundbeck Foundation (grant numbers R102-A9118 and R155-2014-1724) and the universities and university hospitals of Aarhus and Copenhagen. Genotyping of iPSYCH and PGC samples was supported by grants from the Lundbeck Foundation, the Stanley Foundation, the Simons Foundation (SFARI 311789 to MJD), and NIMH (5U01MH094432–02 to MJD). The Danish National Biobank resource was supported by the Novo Nordisk Foundation. Data handling and analysis on the GenomeDK HPC facility was supported by NIMH (1U01MH109514–01 to M O’Donovan and ADB). High-performance computer capacity for handling and statistical analysis of iPSYCH data on the GenomeDK HPC facility was provided by the Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark (grant to ADB). Drs. S De Rubeis and JD Buxbaum were supported by NIH grants MH097849 (to JDB) and MH111661 (to JDB), and by the Seaver Foundation (to SDR and JDB). Dr J Martin was supported by the Wellcome Trust (grant no: 106047). O. Andreassen received funding from Research Council of Norway (#213694, #223273, #248980, #248778), Stiftelsen KG Jebsen and South-East Norway Health Authority. We thank the research participants and employees of 23andMe for making this work possible.

Published
2019
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45. IQ in late adolescence/early adulthood, risk factors in middle age and later all-cause mortality in men: the Vietnam Experience Study

Author

Batty, G.D., Shipley, M.J., Mortensen, L.H., Boyle, S.H., Barefoot, J., Gronbaek, M., Gale, C.R., and Deary, I.J.

Subjects
Intellect -- Research, Intellect -- Demographic aspects, Intelligence levels -- Research, Intelligence levels -- Demographic aspects, Intelligence tests -- Usage, Social classes -- Influence, Social classes -- Psychological aspects, Cognition -- Research, Cognition -- Demographic aspects, Health, Social sciences
Published
2008

47. Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults

Author

Hofer, E., Roshchupkin, G.V., Adams, H.H.H., Knol, M.J., Lin, H., Li, S., Zare, H., Ahmad, S., Armstrong, N.J., Satizabal, C.L., Bernard, M., Bis, J.C., Gillespie, N.A., Luciano, M., Mishra, A., Scholz, M., Teumer, A., Xia, R., Jian, X., Mosley, T.H., Saba, Y., Pirpamer, L., Seiler, S., Becker, J.T., Carmichael, O., Rotter, J.I., Psaty, B.M., Lopez, O.L., Amin, N., van der Lee, S.J., Yang, Q., Himali, J.J., Maillard, P., Beiser, A.S., DeCarli, C., Karama, S., Lewis, L., Harris, M., Bastin, M.E., Deary, I.J., Veronica Witte, A., Beyer, F., Loeffler, M., Mather, K.A., Schofield, P.R., Thalamuthu, A., Kwok, J.B., Wright, M.J., Ames, D., Trollor, J., Jiang, J., Brodaty, H., Wen, W., Vernooij, M.W., Hofman, A., Uitterlinden, A.G., Niessen, W.J., Wittfeld, K., Bülow, R., Völker, U., Pausova, Z., Bruce Pike, G., Maingault, S., Crivello, F., Tzourio, C., Amouyel, P., Mazoyer, B., Neale, M.C., Franz, C.E., Lyons, M.J., Panizzon, M.S., Andreassen, O.A., Dale, A.M., Logue, M.A., Grasby, K.L., Jahanshad, N., Painter, J.N., Colodro-Conde, L., Bralten, J., Hibar, D.P., Lind, P.A., Pizzagalli, F., Stein, J.L., Thompson, P.M., Medland, S.E., Sachdev, P.S., Kremen, W.S., Wardlaw, J.M., Villringer, A., van Duijn, C.M., Grabe, H.J., Longstreth, W.T., Fornage, M., Paus, T., Debette, S., Arfan Ikram, M., Schmidt, H., Schmidt, R., Seshadri, S., Hofer, E., Roshchupkin, G.V., Adams, H.H.H., Knol, M.J., Lin, H., Li, S., Zare, H., Ahmad, S., Armstrong, N.J., Satizabal, C.L., Bernard, M., Bis, J.C., Gillespie, N.A., Luciano, M., Mishra, A., Scholz, M., Teumer, A., Xia, R., Jian, X., Mosley, T.H., Saba, Y., Pirpamer, L., Seiler, S., Becker, J.T., Carmichael, O., Rotter, J.I., Psaty, B.M., Lopez, O.L., Amin, N., van der Lee, S.J., Yang, Q., Himali, J.J., Maillard, P., Beiser, A.S., DeCarli, C., Karama, S., Lewis, L., Harris, M., Bastin, M.E., Deary, I.J., Veronica Witte, A., Beyer, F., Loeffler, M., Mather, K.A., Schofield, P.R., Thalamuthu, A., Kwok, J.B., Wright, M.J., Ames, D., Trollor, J., Jiang, J., Brodaty, H., Wen, W., Vernooij, M.W., Hofman, A., Uitterlinden, A.G., Niessen, W.J., Wittfeld, K., Bülow, R., Völker, U., Pausova, Z., Bruce Pike, G., Maingault, S., Crivello, F., Tzourio, C., Amouyel, P., Mazoyer, B., Neale, M.C., Franz, C.E., Lyons, M.J., Panizzon, M.S., Andreassen, O.A., Dale, A.M., Logue, M.A., Grasby, K.L., Jahanshad, N., Painter, J.N., Colodro-Conde, L., Bralten, J., Hibar, D.P., Lind, P.A., Pizzagalli, F., Stein, J.L., Thompson, P.M., Medland, S.E., Sachdev, P.S., Kremen, W.S., Wardlaw, J.M., Villringer, A., van Duijn, C.M., Grabe, H.J., Longstreth, W.T., Fornage, M., Paus, T., Debette, S., Arfan Ikram, M., Schmidt, H., Schmidt, R., and Seshadri, S.

Abstract

Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.

Published
2020

48. Genome wide association study of circulating interleukin 6 levels identifies novel loci

Author

Ahluwalia, T.S., Armstrong, N.J., Aslibekyan, S., Beekman, M., Cheng, Y., deGeus, E., Delgado, G.E., Marek, D., Kanoni, S., Nolte, I.M., Porcu, E., Seppälä, I., Standl, M., Teumer, A., Thalamuthu, A., Trompet, S., Benjamin, E.J., Feitosa, M.F., Homuth, G., Lahti, J., Liu, Y., Timpson, N.J., Visvikis-Siest, S., Völker, U., Baune, B.T., Boomsma, D., Deary, I.J., Evans, D.M., Ferreira, M.A., Gaunt, T., Gudnason, V., Hamsten, A., Humphries, S.E., Koeing, W., Kumari, M., Lawlor, D.A., Nauck, M., Price, J.F., Sørensen, T.I.A., Stacey, D., Stathopoulou, M.G., Tanaka, T., Wannamethee, S.G., Rotter, J.I., Dehghan, A., Boerwinkle, E., Sneider, H., Psaty, B.M., Prins, B.P., Alizadeh, B.Z., Ahluwalia, T.S., Armstrong, N.J., Aslibekyan, S., Beekman, M., Cheng, Y., deGeus, E., Delgado, G.E., Marek, D., Kanoni, S., Nolte, I.M., Porcu, E., Seppälä, I., Standl, M., Teumer, A., Thalamuthu, A., Trompet, S., Benjamin, E.J., Feitosa, M.F., Homuth, G., Lahti, J., Liu, Y., Timpson, N.J., Visvikis-Siest, S., Völker, U., Baune, B.T., Boomsma, D., Deary, I.J., Evans, D.M., Ferreira, M.A., Gaunt, T., Gudnason, V., Hamsten, A., Humphries, S.E., Koeing, W., Kumari, M., Lawlor, D.A., Nauck, M., Price, J.F., Sørensen, T.I.A., Stacey, D., Stathopoulou, M.G., Tanaka, T., Wannamethee, S.G., Rotter, J.I., Dehghan, A., Boerwinkle, E., Sneider, H., Psaty, B.M., Prins, B.P., and Alizadeh, B.Z.

Abstract

Interleukin-6 (IL-6) is a multifunctional cytokine with both pro and anti-inflammatory properties, synthesized by a wide range of tissues and cell types. Increased levels of circulating IL-6 in blood is associated with the pathophysiology of complex disorders like type 2 diabetes, cardiovascular and autoimmune diseases. Albeit, IL-6 levels are heritable with estimates up to 61%, only a few common genetic loci associated with circulating IL-6 levels have been identified. We therefore conducted a two stage (discovery and replication) meta genome-wide association study (GWAS) of circulating serum IL-6 concentrations comprising up to 67,428 individuals of european ancestry. About 2.5 million single nucleotide polymorphisms (SNPs) were available for testing after imputation to Hap Map 2 reference panel. We conducted an inverse variance based fixed effects meta-analysis. We identified three IL-6 associated, independent signals on chromosomes (chr) 2q14, 6p21 and 1q21, reaching genome-wide significance (p < 5.0 × 10−8) in the combined meta-analyses. Among the identified loci IL1F10/IL1RN (chr 2q14, p = 1.8 × 10−11), and HLA-DRB1/DRB5 (chr 6p21, p =1.5 × 10−10) were novel while IL6R (chr 1q21, p = 1.2 × 10−122) was a known locus. Our study identifies 2 novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology.

Published
2020

49. Association of common genetic variants with brain microbleeds

Author

Knol, M.J. (Maria), Lu, Dongwei, Traylor, M. (Matthew), Adams, H.H.H. (Hieab), Romero, J.R. (Jose Rafael), Smith, A.V. (Davey), Fornage, M. (Myriam), Hofer, E. (Edith), Liu, J. (Juan), Hostettler, Isabel C., Luciano, M. (Michelle), Trompet, S. (Stella), Giese, A.-K. (Anne-Katrin), Hilal, S. (Saima), Akker, E.B. (Erik) van den, Vojinović, D. (Dina), S. Li (Shuo), Sigurdsson, S. (Sigurdur), Lee, S.J. (Sven) van der, Jack Jr., C.R. (Clifford), Wilson, D. (Dana), Yilmaz, P. (Pinar), Satizabal, C.L. (Claudia), Liewald, D.C.M. (David), Grond, J. (Jeroen) van der, Chen, C. (Christopher), Saba, Y. (Yasaman), Lugt, A. (Aad) van der, Bastin, M.E. (Mark), Windham, B.G. (Gwen), Cheng, C-Y. (Ching-Yu), Pirpamer, Lukas, Kantarci, Kejal, Himali, J.J. (Jayandra), Yang, Q. (Qiong), Morris, Zoe, Beiser, A. (Alexa), Tozer, Daniel J., Vernooij, M.W. (Meike), Amin, N. (Najaf), Beekman, M. (Marian), Koh, J.Y. (Jia Yu), Stott, D.J.M. (David), Houlden, H. (Henry), Schmidt, R. (Reinhold), Gottesman, R.F. (Rebecca), MacKinnon, Andrew D., DeCarli, C. (Charles), Guonason, V. (Vilmundur), Deary, I.J. (Ian), Duijn, C.M. (Cornelia) van, Slagboom, P.E. (Eline), Wong, T.Y. (Tien Yin), Rost, N.S. (Natalia), Jukeme, J.W. (J. Wouter), Mosley, T.H. (Thomas), Werring, D.J. (David), Schmidt, H. (Helena), Wardlaw, J.M. (J.), Ikram, M.A. (Arfan), Seshadri, S. (Sudha), Launer, L.J. (Lenore), Markus, H.S. (Hugh S.), Knol, M.J. (Maria), Lu, Dongwei, Traylor, M. (Matthew), Adams, H.H.H. (Hieab), Romero, J.R. (Jose Rafael), Smith, A.V. (Davey), Fornage, M. (Myriam), Hofer, E. (Edith), Liu, J. (Juan), Hostettler, Isabel C., Luciano, M. (Michelle), Trompet, S. (Stella), Giese, A.-K. (Anne-Katrin), Hilal, S. (Saima), Akker, E.B. (Erik) van den, Vojinović, D. (Dina), S. Li (Shuo), Sigurdsson, S. (Sigurdur), Lee, S.J. (Sven) van der, Jack Jr., C.R. (Clifford), Wilson, D. (Dana), Yilmaz, P. (Pinar), Satizabal, C.L. (Claudia), Liewald, D.C.M. (David), Grond, J. (Jeroen) van der, Chen, C. (Christopher), Saba, Y. (Yasaman), Lugt, A. (Aad) van der, Bastin, M.E. (Mark), Windham, B.G. (Gwen), Cheng, C-Y. (Ching-Yu), Pirpamer, Lukas, Kantarci, Kejal, Himali, J.J. (Jayandra), Yang, Q. (Qiong), Morris, Zoe, Beiser, A. (Alexa), Tozer, Daniel J., Vernooij, M.W. (Meike), Amin, N. (Najaf), Beekman, M. (Marian), Koh, J.Y. (Jia Yu), Stott, D.J.M. (David), Houlden, H. (Henry), Schmidt, R. (Reinhold), Gottesman, R.F. (Rebecca), MacKinnon, Andrew D., DeCarli, C. (Charles), Guonason, V. (Vilmundur), Deary, I.J. (Ian), Duijn, C.M. (Cornelia) van, Slagboom, P.E. (Eline), Wong, T.Y. (Tien Yin), Rost, N.S. (Natalia), Jukeme, J.W. (J. Wouter), Mosley, T.H. (Thomas), Werring, D.J. (David), Schmidt, H. (Helena), Wardlaw, J.M. (J.), Ikram, M.A. (Arfan), Seshadri, S. (Sudha), Launer, L.J. (Lenore), and Markus, H.S. (Hugh S.)

Published
2020
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50. Cerebral small vessel disease genomics and its implications across the lifespan

Author

Sargurupremraj, M. (Muralidharan), Suzuki, H. (Hideaki), Jian, X. (Xueqiu), Sarnowski, C., Evans, T.E (Tavia), Bis, J.C. (Joshua), Eiriksdottir, G. (Gudny), Sakaue, S. (Saori), Terzikhan, N. (Natalie), Habes, M. (Mohamad), Zhao, W. (Wei), Armstrong, N.J. (Nicola J.), Hofer, E. (Edith), Yanek, L.R. (Lisa), Hagenaars, S.P. (Saskia P.), Kumar, R.B. (Rajan B.), Akker, E.B. (Erik) van den, McWhirter, R.E. (Rebekah E.), Trompet, S. (Stella), Mishra, A. (Aniket), Saba, Y. (Yasaman), Satizabal, C.L. (Claudia), Beaudet, G. (Gregory), Petit, L. (Laurent), Tsuchida, A. (Ami), Zago, L. (Laure), Schilling, S. (Sabrina), Sigurdsson, S. (Stefan), Gottesman, R.F. (Rebecca), Lewis, C.E. (Cora E.), Aggarwal, N.T. (Neelum T.), Lopez, O.L. (Oscar), Smith, J.A. (Jennifer A), Valdés Hernández, M.C. (Maria C.), van der Grond, J. (Jeroen), Wright, M.J. (Margaret), Knol, M.J. (Maria J.), Dörr, M. (Marcus), Thomson, R. (Russell), Bordes, C. (Constance), Le Grand, Q. (Quentin), Duperron, M.-G. (Marie-Gabrielle), Smith, A.V. (Albert), Knopman, D.S. (David), Schreiner, P.J. (Pamela), Evans, D.A. (Denis A.), Rotter, J.I. (Jerome I.), Beiser, A. (Alexa), Maniega, S.M. (Susana Muñoz), Beekman, M. (Marian), Trollor, J., Stott, D.J. (David. J.), Vernooij, M.W. (Meike), Wittfeld, K. (Katharina), Niessen, W.J. (Wiro), Soumaré, A. (Aicha), Boerwinkle, E.A. (Eric), Sidney, S. (Stephen), Turner, S.T. (Stephen), Davies, G. (Gail), Thalamuthu, A. (Anbupalam), Völker, U. (Uwe), Buchem, M.A. (Mark) van, Bryan, R.N. (R. Nick), Amin, N. (Najaf), Bastin, M.E. (Mark), Ames, D.J. (David), Teumer, A. (Alexander), Amouyel, P. (Philippe), Kwok, J.B. (John B.), Bülow, R. (Robin), Deary, I.J. (Ian), Schofield, P.R. (Peter R.), Brodaty, H. (Henry), Jiang, J. (Jiyang), Tabara, Y. (Yasuharu), Setoh, K. (Kazuya), Miyamoto, S. (Susumu), Yoshida, K. (Kazumichi), Nagata, M. (Manabu), Kamatani, Y. (Yoichiro), Matsuda, F. (Fumihiko), Psaty, B.M. (Bruce), Bennett, D.A. (David), De Jager, P., Mosley, T.H. (Thomas H.), Sachdev, P.S. (Perminder), Schmidt, R. (Reinhold), Warren, H. (Helen), Evangelou, E. (Evangelos), Trégouët, D.-A. (David-Alexandre), Andrade, M. (Mariza) de, Basu, S. (Saonli), Berr, C. (Claudine), Brody, J.A. (Jennifer A.), Chasman, D.I. (Daniel I.), Dartigues, J.-F., Folsom, A.R. (Aaron), Germain, M. (Marine), de Haan, H. (Hugoline), Heit, J.A. (John), Houwing-Duitermaat, J. (Jeanine), Kabrhel, C. (Christopher), Kraft, P. (Peter), Legal, G. (Grégoire), Lindström, S. (Sara), Monajemi, R. (Ramin), Morange, P.-E. (P.), Psaty, B.M. (Bruce M.), Reitsma, P.H. (Pieter H.), Jarvelin, M.-R. (Marjo-Riitta), Rose, L.M. (Lynda M.), Peyvandi, F. (Flora), Saut, N. (Noemie), Slagboom, E. (Eline), Smadja, D. (David), Smith, N.L. (Nicholas L.), Suchon, P. (Pierre), Tang, W. (Weihong), Taylor, K.D. (Kent D.), Tregouet, D.-A. (David-Alexandre), Tzourio, C. (Christophe), Visser, M.C.H. (Marieke) de, Hylckama Vlieg, A. (Astrid) van, Weng, L.-C., Wiggins, K.L. (Kerri L.), Gormley, A.M., Anttila, V. (Verneri), Winsvold, B.S. (Bendik S.), Palta, P. (Priit), Esko, T. (Tõnu), Pers, T.H. (Tune H.), Farh, K.-H. (Kai-How), Cuenca-Leon, E. (Ester), Muona, M. (Mikko), Furlotte, N.A. (Nicholas A.), Kurth, T. (Tobias), Ingason, A. (Andres), McMahon, G. (George), Ligthart, L. (Lannie), Terwindt, G.M. (Gisela M.), Todt, U. (Unda), Freilinger, T.M. (Tobias M.), Ran, C. (Caroline), Gordon, S.G. (Scott G.), Stam, A.H. (Anine), Steinberg, S. (Stacy), Borck, G. (Guntram), Koiranen, M. (Markku), Quaye, L. (Lydia), Adams, H.H.H. (Hieab H. H.), Lehtimäki, T. (Terho), Sarin, A.-P., Wedenoja, J. (Juho), Hinds, D.A. (David A.), Buring, J.E. (Julie), Schürks, M. (Markus), Ridker, P.M. (Paul M.), Gudlaug Hrafnsdottir, M. (Maria), Stefansson, H. (Hreinn), Ring, S.M. (Susan M.), Hottenga, J.J. (Jouke Jan), Penninx, B.W.J.H. (Brenda), Färkkilä, M. (Markus), Artto, V. (Ville), Kaunisto, M.A. (Mari), Vepsäläinen, S. (Salli), Malik, R. (Rainer), Heath, A.C. (Andrew), Madden, P.A.F. (Pamela A. F.), Martin, N.G. (Nicholas), Montgomery, G.W. (Grant), Kurki, M. (Mitja), Kals, M. (Mart), Mägi, R. (Reedik), Pärn, K. (Kalle), Hämäläinen, E. (Eija), Huang, H. (Hailiang), Byrnes, A.E. (Andrea E.), Franke, L. (Lude), Huang, J. (Jie), Stergiakouli, E. (Evie), Lee, P.H. (Phil H.), Sandor, C. (Cynthia), Webber, C. (Caleb), Cader, Z. (Zameel), Müller-Myhsok, B. (B.), Schreiber, S. (Stefan), Meitinger, T. (Thomas), Hagen, K. (Knut), Salomaa, V. (Veikko), Heikkilä, K. (Kauko), Loehrer, E. (Elizabeth), Uitterlinden, A.G. (André), Hofman, A. (Albert), Duijn, C.M. (Cornelia) van, Cherkas, L. (Lynn), Pedersen, L.M. (Linda M.), Stubhaug, A. (Audun), Nielsen, C.S. (Christopher S.), Männikkö, M. (Minna), Mihailov, E. (Evelin), Milani, L. (Lili), Esserlind, A.-L. (Ann-Louise), Francke Christensen, A. (Anne), Folkmann Hansen, T. (Thomas), Werge, T. (Thomas), Kaprio, J. (Jaakko), Aromaa, A. (Arpo), Raitakari, O. (Olli), Ikram, M.A. (M. Arfan), Spector, T.D. (Timothy), Järvelin, M.-R. (Marjo-Riitta), Metspalu, A. (Andres), Kubisch, C. (Christian), Beckmann, J.S. (Jacques), Ferrari, M.D. (Michel), Belin, A.C. (Andrea C.), Wessman, M. (Maija), van den Maagdenberg, A.M.J.M. (Arn M. J. M.), Zwart, J-A. (John-Anker), Boomsma, D.I. (Dorret), Davey Smith, G. (George), Eriksson, N. (Nicholas), Daly, M.J. (Mark), Neale, B.M. (Benjamin), Olesen, J. (Jes), Chasman, D.I. (Daniel), Nyholt, D.R. (Dale), Palotie, A. (Aarno), Ikram, M.A. (Arfan), Wen, W. (Wei), DeCarli, C. (Charles), Srikanth, V. (Velandai), Jukema, J.W. (Jan Wouter), Slagboom, P.E. (Eline), Kardia, S.L.R. (Sharon), Okada, Y. (Yukinori), Mazoyer, B. (Bernard), Wardlaw, J.M. (J.), Nyquist, P. (Paul), Mather, R., Grabe, H.J. (Hans Jörgen), Schmidt, H. (Helena), Van Duijn, C.M. (Cornelia M.), Gudnason, V. (Vilmundur), Longstreth Jr, W.T., Launer, L.J. (Lenore), Lathrop, M. (Mark), Seshadri, S. (Sudha), Adams, H.H.H. (Hieab), Matthews, P.M. (P.), Fornage, M. (Myriam), Debette, S. (Stéphanie), Sargurupremraj, M. (Muralidharan), Suzuki, H. (Hideaki), Jian, X. (Xueqiu), Sarnowski, C., Evans, T.E (Tavia), Bis, J.C. (Joshua), Eiriksdottir, G. (Gudny), Sakaue, S. (Saori), Terzikhan, N. (Natalie), Habes, M. (Mohamad), Zhao, W. (Wei), Armstrong, N.J. (Nicola J.), Hofer, E. (Edith), Yanek, L.R. (Lisa), Hagenaars, S.P. (Saskia P.), Kumar, R.B. (Rajan B.), Akker, E.B. (Erik) van den, McWhirter, R.E. (Rebekah E.), Trompet, S. (Stella), Mishra, A. (Aniket), Saba, Y. (Yasaman), Satizabal, C.L. (Claudia), Beaudet, G. (Gregory), Petit, L. (Laurent), Tsuchida, A. (Ami), Zago, L. (Laure), Schilling, S. (Sabrina), Sigurdsson, S. (Stefan), Gottesman, R.F. (Rebecca), Lewis, C.E. (Cora E.), Aggarwal, N.T. (Neelum T.), Lopez, O.L. (Oscar), Smith, J.A. (Jennifer A), Valdés Hernández, M.C. (Maria C.), van der Grond, J. (Jeroen), Wright, M.J. (Margaret), Knol, M.J. (Maria J.), Dörr, M. (Marcus), Thomson, R. (Russell), Bordes, C. (Constance), Le Grand, Q. (Quentin), Duperron, M.-G. (Marie-Gabrielle), Smith, A.V. (Albert), Knopman, D.S. (David), Schreiner, P.J. (Pamela), Evans, D.A. (Denis A.), Rotter, J.I. (Jerome I.), Beiser, A. (Alexa), Maniega, S.M. (Susana Muñoz), Beekman, M. (Marian), Trollor, J., Stott, D.J. (David. J.), Vernooij, M.W. (Meike), Wittfeld, K. (Katharina), Niessen, W.J. (Wiro), Soumaré, A. (Aicha), Boerwinkle, E.A. (Eric), Sidney, S. (Stephen), Turner, S.T. (Stephen), Davies, G. (Gail), Thalamuthu, A. (Anbupalam), Völker, U. (Uwe), Buchem, M.A. (Mark) van, Bryan, R.N. (R. Nick), Amin, N. (Najaf), Bastin, M.E. (Mark), Ames, D.J. (David), Teumer, A. (Alexander), Amouyel, P. (Philippe), Kwok, J.B. (John B.), Bülow, R. (Robin), Deary, I.J. (Ian), Schofield, P.R. (Peter R.), Brodaty, H. (Henry), Jiang, J. (Jiyang), Tabara, Y. (Yasuharu), Setoh, K. (Kazuya), Miyamoto, S. (Susumu), Yoshida, K. (Kazumichi), Nagata, M. (Manabu), Kamatani, Y. (Yoichiro), Matsuda, F. (Fumihiko), Psaty, B.M. (Bruce), Bennett, D.A. (David), De Jager, P., Mosley, T.H. (Thomas H.), Sachdev, P.S. (Perminder), Schmidt, R. (Reinhold), Warren, H. (Helen), Evangelou, E. (Evangelos), Trégouët, D.-A. (David-Alexandre), Andrade, M. (Mariza) de, Basu, S. (Saonli), Berr, C. (Claudine), Brody, J.A. (Jennifer A.), Chasman, D.I. (Daniel I.), Dartigues, J.-F., Folsom, A.R. (Aaron), Germain, M. (Marine), de Haan, H. (Hugoline), Heit, J.A. (John), Houwing-Duitermaat, J. (Jeanine), Kabrhel, C. (Christopher), Kraft, P. (Peter), Legal, G. (Grégoire), Lindström, S. (Sara), Monajemi, R. (Ramin), Morange, P.-E. (P.), Psaty, B.M. (Bruce M.), Reitsma, P.H. (Pieter H.), Jarvelin, M.-R. (Marjo-Riitta), Rose, L.M. (Lynda M.), Peyvandi, F. (Flora), Saut, N. (Noemie), Slagboom, E. (Eline), Smadja, D. (David), Smith, N.L. (Nicholas L.), Suchon, P. (Pierre), Tang, W. (Weihong), Taylor, K.D. (Kent D.), Tregouet, D.-A. (David-Alexandre), Tzourio, C. (Christophe), Visser, M.C.H. (Marieke) de, Hylckama Vlieg, A. (Astrid) van, Weng, L.-C., Wiggins, K.L. (Kerri L.), Gormley, A.M., Anttila, V. (Verneri), Winsvold, B.S. (Bendik S.), Palta, P. (Priit), Esko, T. (Tõnu), Pers, T.H. (Tune H.), Farh, K.-H. (Kai-How), Cuenca-Leon, E. (Ester), Muona, M. (Mikko), Furlotte, N.A. (Nicholas A.), Kurth, T. (Tobias), Ingason, A. (Andres), McMahon, G. (George), Ligthart, L. (Lannie), Terwindt, G.M. (Gisela M.), Todt, U. (Unda), Freilinger, T.M. (Tobias M.), Ran, C. (Caroline), Gordon, S.G. (Scott G.), Stam, A.H. (Anine), Steinberg, S. (Stacy), Borck, G. (Guntram), Koiranen, M. (Markku), Quaye, L. (Lydia), Adams, H.H.H. (Hieab H. H.), Lehtimäki, T. (Terho), Sarin, A.-P., Wedenoja, J. (Juho), Hinds, D.A. (David A.), Buring, J.E. (Julie), Schürks, M. (Markus), Ridker, P.M. (Paul M.), Gudlaug Hrafnsdottir, M. (Maria), Stefansson, H. (Hreinn), Ring, S.M. (Susan M.), Hottenga, J.J. (Jouke Jan), Penninx, B.W.J.H. (Brenda), Färkkilä, M. (Markus), Artto, V. (Ville), Kaunisto, M.A. (Mari), Vepsäläinen, S. (Salli), Malik, R. (Rainer), Heath, A.C. (Andrew), Madden, P.A.F. (Pamela A. F.), Martin, N.G. (Nicholas), Montgomery, G.W. (Grant), Kurki, M. (Mitja), Kals, M. (Mart), Mägi, R. (Reedik), Pärn, K. (Kalle), Hämäläinen, E. (Eija), Huang, H. (Hailiang), Byrnes, A.E. (Andrea E.), Franke, L. (Lude), Huang, J. (Jie), Stergiakouli, E. (Evie), Lee, P.H. (Phil H.), Sandor, C. (Cynthia), Webber, C. (Caleb), Cader, Z. (Zameel), Müller-Myhsok, B. (B.), Schreiber, S. (Stefan), Meitinger, T. (Thomas), Hagen, K. (Knut), Salomaa, V. (Veikko), Heikkilä, K. (Kauko), Loehrer, E. (Elizabeth), Uitterlinden, A.G. (André), Hofman, A. (Albert), Duijn, C.M. (Cornelia) van, Cherkas, L. (Lynn), Pedersen, L.M. (Linda M.), Stubhaug, A. (Audun), Nielsen, C.S. (Christopher S.), Männikkö, M. (Minna), Mihailov, E. (Evelin), Milani, L. (Lili), Esserlind, A.-L. (Ann-Louise), Francke Christensen, A. (Anne), Folkmann Hansen, T. (Thomas), Werge, T. (Thomas), Kaprio, J. (Jaakko), Aromaa, A. (Arpo), Raitakari, O. (Olli), Ikram, M.A. (M. Arfan), Spector, T.D. (Timothy), Järvelin, M.-R. (Marjo-Riitta), Metspalu, A. (Andres), Kubisch, C. (Christian), Beckmann, J.S. (Jacques), Ferrari, M.D. (Michel), Belin, A.C. (Andrea C.), Wessman, M. (Maija), van den Maagdenberg, A.M.J.M. (Arn M. J. M.), Zwart, J-A. (John-Anker), Boomsma, D.I. (Dorret), Davey Smith, G. (George), Eriksson, N. (Nicholas), Daly, M.J. (Mark), Neale, B.M. (Benjamin), Olesen, J. (Jes), Chasman, D.I. (Daniel), Nyholt, D.R. (Dale), Palotie, A. (Aarno), Ikram, M.A. (Arfan), Wen, W. (Wei), DeCarli, C. (Charles), Srikanth, V. (Velandai), Jukema, J.W. (Jan Wouter), Slagboom, P.E. (Eline), Kardia, S.L.R. (Sharon), Okada, Y. (Yukinori), Mazoyer, B. (Bernard), Wardlaw, J.M. (J.), Nyquist, P. (Paul), Mather, R., Grabe, H.J. (Hans Jörgen), Schmidt, H. (Helena), Van Duijn, C.M. (Cornelia M.), Gudnason, V. (Vilmundur), Longstreth Jr, W.T., Launer, L.J. (Lenore), Lathrop, M. (Mark), Seshadri, S. (Sudha), Adams, H.H.H. (Hieab), Matthews, P.M. (P.), Fornage, M. (Myriam), and Debette, S. (Stéphanie)

Abstract

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.

Published
2020
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