Search

Your search keyword '"Most, P.J. van der"' showing total 17 results
Start Over Author "Most, P.J. van der"
17 results on '"Most, P.J. van der"'

1. Genetic insights into resting heart rate and its role in cardiovascular disease.

Author

Vegte, Y.J. van de, Eppinga, R.N., Ende, M.Y. van der, Hagemeijer, Y.P., Mahendran, Y., Salfati, E., Smith, A.V., Tan, V.Y., Arking, D.E., Ntalla, I., Appel, E.V., Schurmann, C., Brody, J.A., Rueedi, R., Polasek, O., Sveinbjornsson, G., Lecoeur, C., Ladenvall, C., Zhao, J.H., Isaacs, A., Wang, L., Luan, Jian'an, Hwang, S.J., Mononen, N., Auro, K., Jackson, A.U., Bielak, L.F., Zeng, L., Shah, N., Nethander, M., Campbell, A., Rankinen, T., Pechlivanis, S., Qi, L., Zhao, Wei, Rizzi, F., Tanaka, T., Robino, A., Cocca, M., Lange, L., Müller-Nurasyid, M., Roselli, C., Zhang, W, Kleber, M.E., Guo, X., Lin, H.J., Pavani, F., Galesloot, T.E., Noordam, R., Milaneschi, Y., Schraut, K.E., Hoed, M. den, Degenhardt, F., Trompet, S., Berg, M.E. van den, Pistis, G., Tham, Y.C., Weiss, S., Sim, X.S., Li, H.L., Most, P.J. van der, Nolte, I.M., Lyytikäinen, L.P., Said, M.A., Witte, D.R., Iribarren, C., Launer, L., Ring, S.M., Vries, P.S. de, Sever, P., Linneberg, A., Bottinger, E.P., Padmanabhan, S., Psaty, B.M., Sotoodehnia, N., Kolcic, I., Arnar, D.O., Gudbjartsson, D.F., Holm, H., Balkau, B., Silva, C.T., Newton-Cheh, C.H., Nikus, K., Salo, P., Mohlke, K.L., Peyser, P.A., Schunkert, H., Lorentzon, M., Lahti, J., Rao, D.C., Cornelis, M.C., Faul, J.D., Smith, J.A., Stolarz-Skrzypek, K., Bandinelli, S., Concas, M.P., Sinagra, G., Meitinger, T., Waldenberger, M., Sinner, M.F., Strauch, K., Delgado, G.E., Taylor, K.D., Yao, J., Foco, L., Melander, O., Graaf, J. de, Mutsert, R. de, Geus, E.J.C. de, Johansson, Å., Joshi, P.K., Lind, L., Franke, A., Macfarlane, P.W., Tarasov, K.V., Tan, N., Felix, S.B., Tai, E.S., Quek, D.Q., Snieder, H., Ormel, J., Ingelsson, M., Lindgren, C., Morris, A.P., Raitakari, O.T., Hansen, T., Assimes, T., Gudnason, V., Timpson, N.J., Morrison, A.C., Munroe, P.B., Strachan, D.P., Grarup, N., Loos, R.J.F., Heckbert, S.R., Vollenweider, P., Hayward, C., Stefansson, K., Froguel, P., Groop, L., Wareham, N.J., Duijn, C.M. van, Feitosa, M.F., O'Donnell, C.J., Kähönen, M., Perola, M., Boehnke, M., Kardia, S.L.R., Erdmann, J., Palmer, C.N.A., Ohlsson, C., Porteous, D.J., Eriksson, J.G., Bouchard, C., Moebus, S., Kraft, P., Weir, D.R., Cusi, D., Ferrucci, L., Ulivi, S., Girotto, G., Correa, A., Kääb, S., Peters, A., Chambers, J.C., Kooner, J.S., März, W., Rotter, J.I., Hicks, A.A., Smith, J.G., Kiemeney, L.A.L.M., Mook-Kanamori, D.O., Penninx, B.W.J.H., Gyllensten, U., Wilson, J.F., Burgess, S., Sundström, J., Lieb, W., Jukema, J.W., Eijgelsheim, M., Lakatta, E.L.M., Cheng, C.Y., Dörr, M., Wong, T.Y., Sabanayagam, C., Oldehinkel, A.J., Riese, H., Lehtimäki, T., Verweij, N., Harst, P. van der, Vegte, Y.J. van de, Eppinga, R.N., Ende, M.Y. van der, Hagemeijer, Y.P., Mahendran, Y., Salfati, E., Smith, A.V., Tan, V.Y., Arking, D.E., Ntalla, I., Appel, E.V., Schurmann, C., Brody, J.A., Rueedi, R., Polasek, O., Sveinbjornsson, G., Lecoeur, C., Ladenvall, C., Zhao, J.H., Isaacs, A., Wang, L., Luan, Jian'an, Hwang, S.J., Mononen, N., Auro, K., Jackson, A.U., Bielak, L.F., Zeng, L., Shah, N., Nethander, M., Campbell, A., Rankinen, T., Pechlivanis, S., Qi, L., Zhao, Wei, Rizzi, F., Tanaka, T., Robino, A., Cocca, M., Lange, L., Müller-Nurasyid, M., Roselli, C., Zhang, W, Kleber, M.E., Guo, X., Lin, H.J., Pavani, F., Galesloot, T.E., Noordam, R., Milaneschi, Y., Schraut, K.E., Hoed, M. den, Degenhardt, F., Trompet, S., Berg, M.E. van den, Pistis, G., Tham, Y.C., Weiss, S., Sim, X.S., Li, H.L., Most, P.J. van der, Nolte, I.M., Lyytikäinen, L.P., Said, M.A., Witte, D.R., Iribarren, C., Launer, L., Ring, S.M., Vries, P.S. de, Sever, P., Linneberg, A., Bottinger, E.P., Padmanabhan, S., Psaty, B.M., Sotoodehnia, N., Kolcic, I., Arnar, D.O., Gudbjartsson, D.F., Holm, H., Balkau, B., Silva, C.T., Newton-Cheh, C.H., Nikus, K., Salo, P., Mohlke, K.L., Peyser, P.A., Schunkert, H., Lorentzon, M., Lahti, J., Rao, D.C., Cornelis, M.C., Faul, J.D., Smith, J.A., Stolarz-Skrzypek, K., Bandinelli, S., Concas, M.P., Sinagra, G., Meitinger, T., Waldenberger, M., Sinner, M.F., Strauch, K., Delgado, G.E., Taylor, K.D., Yao, J., Foco, L., Melander, O., Graaf, J. de, Mutsert, R. de, Geus, E.J.C. de, Johansson, Å., Joshi, P.K., Lind, L., Franke, A., Macfarlane, P.W., Tarasov, K.V., Tan, N., Felix, S.B., Tai, E.S., Quek, D.Q., Snieder, H., Ormel, J., Ingelsson, M., Lindgren, C., Morris, A.P., Raitakari, O.T., Hansen, T., Assimes, T., Gudnason, V., Timpson, N.J., Morrison, A.C., Munroe, P.B., Strachan, D.P., Grarup, N., Loos, R.J.F., Heckbert, S.R., Vollenweider, P., Hayward, C., Stefansson, K., Froguel, P., Groop, L., Wareham, N.J., Duijn, C.M. van, Feitosa, M.F., O'Donnell, C.J., Kähönen, M., Perola, M., Boehnke, M., Kardia, S.L.R., Erdmann, J., Palmer, C.N.A., Ohlsson, C., Porteous, D.J., Eriksson, J.G., Bouchard, C., Moebus, S., Kraft, P., Weir, D.R., Cusi, D., Ferrucci, L., Ulivi, S., Girotto, G., Correa, A., Kääb, S., Peters, A., Chambers, J.C., Kooner, J.S., März, W., Rotter, J.I., Hicks, A.A., Smith, J.G., Kiemeney, L.A.L.M., Mook-Kanamori, D.O., Penninx, B.W.J.H., Gyllensten, U., Wilson, J.F., Burgess, S., Sundström, J., Lieb, W., Jukema, J.W., Eijgelsheim, M., Lakatta, E.L.M., Cheng, C.Y., Dörr, M., Wong, T.Y., Sabanayagam, C., Oldehinkel, A.J., Riese, H., Lehtimäki, T., Verweij, N., and Harst, P. van der

Abstract

Contains fulltext : 296013.pdf (Publisher’s version ) (Open Access), Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.

Published
2023

2. Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention

Author

Wang, Zhe, Emmerich, A., Pillon, N.J., Moore, T., Hemerich, D., Cornelis, M.C., Mazzaferro, E., Broos, S., Ahluwalia, T.S., Bartz, T.M., Bentley, A.R., Bielak, L.F., Chong, M., Chu, A.Y., Berry, D., Dorajoo, R., Dueker, N.D., Kasbohm, E., Feenstra, B., Feitosa, M.F., Gieger, C., Graff, M, Hall, L.M., Haller, T., Hartwig, F.P., Hillis, D.A., Huikari, V., Heard-Costa, N., Holzapfel, C., Jackson, A.U., Johansson, Å., Jørgensen, A.M., Kaakinen, M.A., Karlsson, R., Kerr, K.F., Kim, Boram, Koolhaas, C.M., Kutalik, Z., Lagou, V., Lind, P.A., Lorentzon, M., Lyytikäinen, L.P., Mangino, M., Metzendorf, C., Monroe, K.R., Pacolet, A., Pérusse, L., Pool, R., Richmond, R.C., Rivera, N.V., Robiou-du-Pont, S., Schraut, K.E., Schulz, C.A., Stringham, H.M., Tanaka, T., Teumer, A., Turman, C., Most, P.J. van der, Vanmunster, M., Rooij, F.J. van, Vliet-Ostaptchouk, J.V. Van, Zhang, Xiaoshuai, Zhao, J.H., Zhao, W, Balkhiyarova, Z., Balslev-Harder, M.N., Baumeister, S.E., Beilby, J., Blangero, J., Boomsma, D.I., Brage, S., Braund, P.S., Brody, J.A., Bruinenberg, M., Ekelund, U., Liu, C.T., Cole, J.W., Collins, F.S., Cupples, L.A., Esko, T., Enroth, S., Faul, J.D., Fernandez-Rhodes, L., Fohner, A.E., Franco, O.H., Galesloot, T.E., Gordon, S.D.S., Grarup, N., Hartman, C.A., Heiss, G., Hui, J., Illig, T., Jago, R., James, A., Joshi, P.K., Jung, T., Kähönen, M., Kilpeläinen, T.O., Koh, W.P., Kolcic, I., Kiemeney, L.A.L.M., Loos, R.J.F., Hoed, Marcel Den, Wang, Zhe, Emmerich, A., Pillon, N.J., Moore, T., Hemerich, D., Cornelis, M.C., Mazzaferro, E., Broos, S., Ahluwalia, T.S., Bartz, T.M., Bentley, A.R., Bielak, L.F., Chong, M., Chu, A.Y., Berry, D., Dorajoo, R., Dueker, N.D., Kasbohm, E., Feenstra, B., Feitosa, M.F., Gieger, C., Graff, M, Hall, L.M., Haller, T., Hartwig, F.P., Hillis, D.A., Huikari, V., Heard-Costa, N., Holzapfel, C., Jackson, A.U., Johansson, Å., Jørgensen, A.M., Kaakinen, M.A., Karlsson, R., Kerr, K.F., Kim, Boram, Koolhaas, C.M., Kutalik, Z., Lagou, V., Lind, P.A., Lorentzon, M., Lyytikäinen, L.P., Mangino, M., Metzendorf, C., Monroe, K.R., Pacolet, A., Pérusse, L., Pool, R., Richmond, R.C., Rivera, N.V., Robiou-du-Pont, S., Schraut, K.E., Schulz, C.A., Stringham, H.M., Tanaka, T., Teumer, A., Turman, C., Most, P.J. van der, Vanmunster, M., Rooij, F.J. van, Vliet-Ostaptchouk, J.V. Van, Zhang, Xiaoshuai, Zhao, J.H., Zhao, W, Balkhiyarova, Z., Balslev-Harder, M.N., Baumeister, S.E., Beilby, J., Blangero, J., Boomsma, D.I., Brage, S., Braund, P.S., Brody, J.A., Bruinenberg, M., Ekelund, U., Liu, C.T., Cole, J.W., Collins, F.S., Cupples, L.A., Esko, T., Enroth, S., Faul, J.D., Fernandez-Rhodes, L., Fohner, A.E., Franco, O.H., Galesloot, T.E., Gordon, S.D.S., Grarup, N., Hartman, C.A., Heiss, G., Hui, J., Illig, T., Jago, R., James, A., Joshi, P.K., Jung, T., Kähönen, M., Kilpeläinen, T.O., Koh, W.P., Kolcic, I., Kiemeney, L.A.L.M., Loos, R.J.F., and Hoed, Marcel Den

Abstract

Contains fulltext : 282313.pdf (Publisher’s version ) (Open Access), Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type II(A) muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.

Published
2022

3. Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention

Author

Wang, Zhe, Emmerich, A., Pillon, N.J., Moore, T., Hemerich, D., Cornelis, M.C., Mazzaferro, E., Broos, S., Ahluwalia, T.S., Bartz, T.M., Bentley, A.R., Bielak, L.F., Chong, M., Chu, A.Y., Berry, D., Dorajoo, R., Dueker, N.D., Kasbohm, E., Feenstra, B., Feitosa, M.F., Gieger, C., Graff, M, Hall, L.M., Haller, T., Hartwig, F.P., Hillis, D.A., Huikari, V., Heard-Costa, N., Holzapfel, C., Jackson, A.U., Johansson, Å., Jørgensen, A.M., Kaakinen, M.A., Karlsson, R., Kerr, K.F., Kim, Boram, Koolhaas, C.M., Kutalik, Z., Lagou, V., Lind, P.A., Lorentzon, M., Lyytikäinen, L.P., Mangino, M., Metzendorf, C., Monroe, K.R., Pacolet, A., Pérusse, L., Pool, R., Richmond, R.C., Rivera, N.V., Robiou-du-Pont, S., Schraut, K.E., Schulz, C.A., Stringham, H.M., Tanaka, T., Teumer, A., Turman, C., Most, P.J. van der, Vanmunster, M., Rooij, F.J. van, Vliet-Ostaptchouk, J.V. Van, Zhang, Xiaoshuai, Zhao, J.H., Zhao, W, Balkhiyarova, Z., Balslev-Harder, M.N., Baumeister, S.E., Beilby, J., Blangero, J., Boomsma, D.I., Brage, S., Braund, P.S., Brody, J.A., Bruinenberg, M., Ekelund, U., Liu, C.T., Cole, J.W., Collins, F.S., Cupples, L.A., Esko, T., Enroth, S., Faul, J.D., Fernandez-Rhodes, L., Fohner, A.E., Franco, O.H., Galesloot, T.E., Gordon, S.D.S., Grarup, N., Hartman, C.A., Heiss, G., Hui, J., Illig, T., Jago, R., James, A., Joshi, P.K., Jung, T., Kähönen, M., Kilpeläinen, T.O., Koh, W.P., Kolcic, I., Kiemeney, L.A.L.M., Loos, R.J.F., Hoed, Marcel Den, Wang, Zhe, Emmerich, A., Pillon, N.J., Moore, T., Hemerich, D., Cornelis, M.C., Mazzaferro, E., Broos, S., Ahluwalia, T.S., Bartz, T.M., Bentley, A.R., Bielak, L.F., Chong, M., Chu, A.Y., Berry, D., Dorajoo, R., Dueker, N.D., Kasbohm, E., Feenstra, B., Feitosa, M.F., Gieger, C., Graff, M, Hall, L.M., Haller, T., Hartwig, F.P., Hillis, D.A., Huikari, V., Heard-Costa, N., Holzapfel, C., Jackson, A.U., Johansson, Å., Jørgensen, A.M., Kaakinen, M.A., Karlsson, R., Kerr, K.F., Kim, Boram, Koolhaas, C.M., Kutalik, Z., Lagou, V., Lind, P.A., Lorentzon, M., Lyytikäinen, L.P., Mangino, M., Metzendorf, C., Monroe, K.R., Pacolet, A., Pérusse, L., Pool, R., Richmond, R.C., Rivera, N.V., Robiou-du-Pont, S., Schraut, K.E., Schulz, C.A., Stringham, H.M., Tanaka, T., Teumer, A., Turman, C., Most, P.J. van der, Vanmunster, M., Rooij, F.J. van, Vliet-Ostaptchouk, J.V. Van, Zhang, Xiaoshuai, Zhao, J.H., Zhao, W, Balkhiyarova, Z., Balslev-Harder, M.N., Baumeister, S.E., Beilby, J., Blangero, J., Boomsma, D.I., Brage, S., Braund, P.S., Brody, J.A., Bruinenberg, M., Ekelund, U., Liu, C.T., Cole, J.W., Collins, F.S., Cupples, L.A., Esko, T., Enroth, S., Faul, J.D., Fernandez-Rhodes, L., Fohner, A.E., Franco, O.H., Galesloot, T.E., Gordon, S.D.S., Grarup, N., Hartman, C.A., Heiss, G., Hui, J., Illig, T., Jago, R., James, A., Joshi, P.K., Jung, T., Kähönen, M., Kilpeläinen, T.O., Koh, W.P., Kolcic, I., Kiemeney, L.A.L.M., Loos, R.J.F., and Hoed, Marcel Den

Abstract

Contains fulltext : 282313.pdf (Publisher’s version ) (Open Access), Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type II(A) muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.

Published
2022

4. Genome-Wide Association meta-analysis of age at first cannabis use

Author

Minica, C.C., Verweij, K.J.H., Most, P.J. van der, Mbarek, H., Bernard, M., Eijk, K.R. van, Lind, P.A., Liu, M.Z., Maciejewski, D.F., Palviainen, T., Sánchez-Mora, C., Sherva, R., Taylor, M., Walters, R.K., Abdellaoui, A., Bigdeli, T.B., Branje, S.J.T., Brown, S.A., Casas, M., Corley, R.P., Smith, G.D., Davies, G.E., Ehli, E.A., Farrer, L.A., Fedko, I.O., Garcia-Martinez, I., Gordon, S.D., Hartman, C.A., Heath, A.C., Hickie, I.B., Hickman, M., Hopfer, C.J., Hottenga, J.J., Kahn, R.S., Kaprio, J., Korhonen, T., Kranzler, H.R., Krauter, K., Lier, P.A.C. van, Madden, P.A.F., Medland, S.E., Neale, M.C., Meeus, W.H.J., Montgomery, G.W., Nolte, I.M., Oldehinkel, A.J., Pausova, Z., Ramos-Quiroga, J.A., Richarte, V., Rose, R.J., Shin, J., Stallings, M.C., Wall, T.L., Ware, J.J., Wright, M.J., Zhao, H., Koot, J.M., Paus, T., Hewitt, J.K., Ribasés, M., Loukola, A., Boks, M.P.M., Snieder, H., Munafò, M.R., Gelernter, J., Boomsma, D.I., Martin, N.G., Gillespie, N.A., Vink, J.M., Derks, E.M., Minica, C.C., Verweij, K.J.H., Most, P.J. van der, Mbarek, H., Bernard, M., Eijk, K.R. van, Lind, P.A., Liu, M.Z., Maciejewski, D.F., Palviainen, T., Sánchez-Mora, C., Sherva, R., Taylor, M., Walters, R.K., Abdellaoui, A., Bigdeli, T.B., Branje, S.J.T., Brown, S.A., Casas, M., Corley, R.P., Smith, G.D., Davies, G.E., Ehli, E.A., Farrer, L.A., Fedko, I.O., Garcia-Martinez, I., Gordon, S.D., Hartman, C.A., Heath, A.C., Hickie, I.B., Hickman, M., Hopfer, C.J., Hottenga, J.J., Kahn, R.S., Kaprio, J., Korhonen, T., Kranzler, H.R., Krauter, K., Lier, P.A.C. van, Madden, P.A.F., Medland, S.E., Neale, M.C., Meeus, W.H.J., Montgomery, G.W., Nolte, I.M., Oldehinkel, A.J., Pausova, Z., Ramos-Quiroga, J.A., Richarte, V., Rose, R.J., Shin, J., Stallings, M.C., Wall, T.L., Ware, J.J., Wright, M.J., Zhao, H., Koot, J.M., Paus, T., Hewitt, J.K., Ribasés, M., Loukola, A., Boks, M.P.M., Snieder, H., Munafò, M.R., Gelernter, J., Boomsma, D.I., Martin, N.G., Gillespie, N.A., Vink, J.M., and Derks, E.M.

Abstract

Contains fulltext : 195854.pdf (publisher's version ) (Closed access), Background and aims: Cannabis is one of the most commonly used substances among adolescents and young adults. Earlier age at cannabis initiation is linked to adverse life outcomes including multi-substance use and dependence. This study estimated the heritability of age at first cannabis use and identify associations with genetic variants. Methods: A twin-based heritability analysis using 8,055 twins from three cohorts was performed. We then carried-out a genome wide survival meta-analysis of age at first cannabis use in a discovery sample of 24,953 individuals from nine European, North American, and Australian cohorts, and a replication sample of 3,735 individuals. Results: The twin-based heritability for age at first cannabis use was 38% (95% confidence interval [CI] 19-60%). Shared and unique environmental factors explained 39% (95% CI 20-56%) and 22% (95% CI 16-29%). The genome wide survival meta-analysis identified five SNPs on chromosome 16 within the Calcium-transporting ATPase gene (ATP2C2) at P < 5E-08. All five SNPs are in high LD (r2>0.8) with the strongest association at the intronic variant rs1574587 (P=4.09E-09). Gene-based tests of association identified the ATP2C2 gene on 16q24.1 (P=1.33e-06). Although the five SNPs and ATP2C2 did not replicate, ATP2C2 has been associated with cocaine dependence in a previous study. ATP2B2, which is a member of the same calcium signalling pathway, has been previously associated with opioid dependence. SNP-based heritability for age at first cannabis use was non-significant. Conclusion: Age at cannabis initiation appears to be moderately heritable in Western countries, and individual differences in onset can be explained by separate but correlated genetic liabilities. The significant association between age of initiation and ATP2C2 is consistent with the role of calcium signalling mechanisms in substance use disorders.

Published
2018

5. Genome-Wide Association meta-analysis of age at first cannabis use

Author

Minica, C.C., Verweij, K.J.H., Most, P.J. van der, Mbarek, H., Bernard, M., Eijk, K.R. van, Lind, P.A., Liu, M.Z., Maciejewski, D.F., Palviainen, T., Sánchez-Mora, C., Sherva, R., Taylor, M., Walters, R.K., Abdellaoui, A., Bigdeli, T.B., Branje, S.J.T., Brown, S.A., Casas, M., Corley, R.P., Smith, G.D., Davies, G.E., Ehli, E.A., Farrer, L.A., Fedko, I.O., Garcia-Martinez, I., Gordon, S.D., Hartman, C.A., Heath, A.C., Hickie, I.B., Hickman, M., Hopfer, C.J., Hottenga, J.J., Kahn, R.S., Kaprio, J., Korhonen, T., Kranzler, H.R., Krauter, K., Lier, P.A.C. van, Madden, P.A.F., Medland, S.E., Neale, M.C., Meeus, W.H.J., Montgomery, G.W., Nolte, I.M., Oldehinkel, A.J., Pausova, Z., Ramos-Quiroga, J.A., Richarte, V., Rose, R.J., Shin, J., Stallings, M.C., Wall, T.L., Ware, J.J., Wright, M.J., Zhao, H., Koot, J.M., Paus, T., Hewitt, J.K., Ribasés, M., Loukola, A., Boks, M.P.M., Snieder, H., Munafò, M.R., Gelernter, J., Boomsma, D.I., Martin, N.G., Gillespie, N.A., Vink, J.M., Derks, E.M., Minica, C.C., Verweij, K.J.H., Most, P.J. van der, Mbarek, H., Bernard, M., Eijk, K.R. van, Lind, P.A., Liu, M.Z., Maciejewski, D.F., Palviainen, T., Sánchez-Mora, C., Sherva, R., Taylor, M., Walters, R.K., Abdellaoui, A., Bigdeli, T.B., Branje, S.J.T., Brown, S.A., Casas, M., Corley, R.P., Smith, G.D., Davies, G.E., Ehli, E.A., Farrer, L.A., Fedko, I.O., Garcia-Martinez, I., Gordon, S.D., Hartman, C.A., Heath, A.C., Hickie, I.B., Hickman, M., Hopfer, C.J., Hottenga, J.J., Kahn, R.S., Kaprio, J., Korhonen, T., Kranzler, H.R., Krauter, K., Lier, P.A.C. van, Madden, P.A.F., Medland, S.E., Neale, M.C., Meeus, W.H.J., Montgomery, G.W., Nolte, I.M., Oldehinkel, A.J., Pausova, Z., Ramos-Quiroga, J.A., Richarte, V., Rose, R.J., Shin, J., Stallings, M.C., Wall, T.L., Ware, J.J., Wright, M.J., Zhao, H., Koot, J.M., Paus, T., Hewitt, J.K., Ribasés, M., Loukola, A., Boks, M.P.M., Snieder, H., Munafò, M.R., Gelernter, J., Boomsma, D.I., Martin, N.G., Gillespie, N.A., Vink, J.M., and Derks, E.M.

Abstract

Contains fulltext : 195854.pdf (publisher's version ) (Closed access), Background and aims: Cannabis is one of the most commonly used substances among adolescents and young adults. Earlier age at cannabis initiation is linked to adverse life outcomes including multi-substance use and dependence. This study estimated the heritability of age at first cannabis use and identify associations with genetic variants. Methods: A twin-based heritability analysis using 8,055 twins from three cohorts was performed. We then carried-out a genome wide survival meta-analysis of age at first cannabis use in a discovery sample of 24,953 individuals from nine European, North American, and Australian cohorts, and a replication sample of 3,735 individuals. Results: The twin-based heritability for age at first cannabis use was 38% (95% confidence interval [CI] 19-60%). Shared and unique environmental factors explained 39% (95% CI 20-56%) and 22% (95% CI 16-29%). The genome wide survival meta-analysis identified five SNPs on chromosome 16 within the Calcium-transporting ATPase gene (ATP2C2) at P < 5E-08. All five SNPs are in high LD (r2>0.8) with the strongest association at the intronic variant rs1574587 (P=4.09E-09). Gene-based tests of association identified the ATP2C2 gene on 16q24.1 (P=1.33e-06). Although the five SNPs and ATP2C2 did not replicate, ATP2C2 has been associated with cocaine dependence in a previous study. ATP2B2, which is a member of the same calcium signalling pathway, has been previously associated with opioid dependence. SNP-based heritability for age at first cannabis use was non-significant. Conclusion: Age at cannabis initiation appears to be moderately heritable in Western countries, and individual differences in onset can be explained by separate but correlated genetic liabilities. The significant association between age of initiation and ATP2C2 is consistent with the role of calcium signalling mechanisms in substance use disorders.

Published
2018

6. Genome-Wide Association meta-analysis of age at first cannabis use

Author

Minica, C.C., Verweij, K.J.H., Most, P.J. van der, Mbarek, H., Bernard, M., Eijk, K.R. van, Lind, P.A., Liu, M.Z., Maciejewski, D.F., Palviainen, T., Sánchez-Mora, C., Sherva, R., Taylor, M., Walters, R.K., Abdellaoui, A., Bigdeli, T.B., Branje, S.J.T., Brown, S.A., Casas, M., Corley, R.P., Smith, G.D., Davies, G.E., Ehli, E.A., Farrer, L.A., Fedko, I.O., Garcia-Martinez, I., Gordon, S.D., Hartman, C.A., Heath, A.C., Hickie, I.B., Hickman, M., Hopfer, C.J., Hottenga, J.J., Kahn, R.S., Kaprio, J., Korhonen, T., Kranzler, H.R., Krauter, K., Lier, P.A.C. van, Madden, P.A.F., Medland, S.E., Neale, M.C., Meeus, W.H.J., Montgomery, G.W., Nolte, I.M., Oldehinkel, A.J., Pausova, Z., Ramos-Quiroga, J.A., Richarte, V., Rose, R.J., Shin, J., Stallings, M.C., Wall, T.L., Ware, J.J., Wright, M.J., Zhao, H., Koot, J.M., Paus, T., Hewitt, J.K., Ribasés, M., Loukola, A., Boks, M.P.M., Snieder, H., Munafò, M.R., Gelernter, J., Boomsma, D.I., Martin, N.G., Gillespie, N.A., Vink, J.M., Derks, E.M., Minica, C.C., Verweij, K.J.H., Most, P.J. van der, Mbarek, H., Bernard, M., Eijk, K.R. van, Lind, P.A., Liu, M.Z., Maciejewski, D.F., Palviainen, T., Sánchez-Mora, C., Sherva, R., Taylor, M., Walters, R.K., Abdellaoui, A., Bigdeli, T.B., Branje, S.J.T., Brown, S.A., Casas, M., Corley, R.P., Smith, G.D., Davies, G.E., Ehli, E.A., Farrer, L.A., Fedko, I.O., Garcia-Martinez, I., Gordon, S.D., Hartman, C.A., Heath, A.C., Hickie, I.B., Hickman, M., Hopfer, C.J., Hottenga, J.J., Kahn, R.S., Kaprio, J., Korhonen, T., Kranzler, H.R., Krauter, K., Lier, P.A.C. van, Madden, P.A.F., Medland, S.E., Neale, M.C., Meeus, W.H.J., Montgomery, G.W., Nolte, I.M., Oldehinkel, A.J., Pausova, Z., Ramos-Quiroga, J.A., Richarte, V., Rose, R.J., Shin, J., Stallings, M.C., Wall, T.L., Ware, J.J., Wright, M.J., Zhao, H., Koot, J.M., Paus, T., Hewitt, J.K., Ribasés, M., Loukola, A., Boks, M.P.M., Snieder, H., Munafò, M.R., Gelernter, J., Boomsma, D.I., Martin, N.G., Gillespie, N.A., Vink, J.M., and Derks, E.M.

Abstract

Contains fulltext : 195854.pdf (publisher's version ) (Closed access), Background and aims: Cannabis is one of the most commonly used substances among adolescents and young adults. Earlier age at cannabis initiation is linked to adverse life outcomes including multi-substance use and dependence. This study estimated the heritability of age at first cannabis use and identify associations with genetic variants. Methods: A twin-based heritability analysis using 8,055 twins from three cohorts was performed. We then carried-out a genome wide survival meta-analysis of age at first cannabis use in a discovery sample of 24,953 individuals from nine European, North American, and Australian cohorts, and a replication sample of 3,735 individuals. Results: The twin-based heritability for age at first cannabis use was 38% (95% confidence interval [CI] 19-60%). Shared and unique environmental factors explained 39% (95% CI 20-56%) and 22% (95% CI 16-29%). The genome wide survival meta-analysis identified five SNPs on chromosome 16 within the Calcium-transporting ATPase gene (ATP2C2) at P < 5E-08. All five SNPs are in high LD (r2>0.8) with the strongest association at the intronic variant rs1574587 (P=4.09E-09). Gene-based tests of association identified the ATP2C2 gene on 16q24.1 (P=1.33e-06). Although the five SNPs and ATP2C2 did not replicate, ATP2C2 has been associated with cocaine dependence in a previous study. ATP2B2, which is a member of the same calcium signalling pathway, has been previously associated with opioid dependence. SNP-based heritability for age at first cannabis use was non-significant. Conclusion: Age at cannabis initiation appears to be moderately heritable in Western countries, and individual differences in onset can be explained by separate but correlated genetic liabilities. The significant association between age of initiation and ATP2C2 is consistent with the role of calcium signalling mechanisms in substance use disorders.

Published
2018

7. The International Cannabis Consortium: What did we learn about the genetics of cannabis

Author

Verweij, K.J.H., Minica, C.C., Stringer, S., Most, P.J. van der, Mbarek, H., Nivard, M.G., Abdellaoui, A., Hottenga, J.J., Martin, N.G., Boomsma, D.I., Gillespie, N.A., Derks, E.M., Vink, J.M., Verweij, K.J.H., Minica, C.C., Stringer, S., Most, P.J. van der, Mbarek, H., Nivard, M.G., Abdellaoui, A., Hottenga, J.J., Martin, N.G., Boomsma, D.I., Gillespie, N.A., Derks, E.M., and Vink, J.M.

Abstract

Item does not contain fulltext, Background: Cannabis is the most frequently used and abused illicit drug worldwide and cannabis (ab)use is associated with social, physical, and psychological problems. Twin and family studies have shown that cannabis use and abuse are heritable traits. The International Cannabis Consortium was initiated with the aim of identifying genetic risk variants for cannabis use phenotypes by meta-analysing data from many contributing cohorts. The (partly preliminary) results of the International Cannabis Consortium will be presented: genome-wide association (GWA) meta-analyses on lifetime cannabis use and age at initiation of use. Additionally, findings from several follow-up studies will be presented, including the genetic association of cannabis use with use of other substances, schizophrenia, and conduct disorder. Methods: GWA analyses of lifetime cannabis use were performed by each contributing group independently (13 groups, total N=32,330) and were subsequently meta-analysed. We tested for replication, and the SNP results were used to perform a gene-based test of association. We also estimated the total SNP-based heritability and the genetic correlation between lifetime cannabis use and cigarette use based on LD-score regression analysis. Secondly, we meta-analysed GWA results of age at initiation of cannabis use from 8 groups (N=24,222) using a survival analysis. Again SNP results are followed up by a gene-based test of association and an estimate of SNP-based heritability. In follow-up projects, LD-score regression analyses were used to determine the genetic correlation of cannabis use with nicotine, alcohol, and caffeine use, as well as schizophrenia and conduct disorder. We also created polygenic risk scores for cannabis use in an independent target sample and determined to what extent these polygenic scores predicted conduct symptoms. Results: Although none of the SNPs were significantly associated with lifetime cannabis use, the gene-based analysis identified 4

Published
2017

8. The International Cannabis Consortium: What did we learn about the genetics of cannabis

Author

Verweij, K.J.H., Minica, C.C., Stringer, S., Most, P.J. van der, Mbarek, H., Nivard, M.G., Abdellaoui, A., Hottenga, J.J., Martin, N.G., Boomsma, D.I., Gillespie, N.A., Derks, E.M., Vink, J.M., Verweij, K.J.H., Minica, C.C., Stringer, S., Most, P.J. van der, Mbarek, H., Nivard, M.G., Abdellaoui, A., Hottenga, J.J., Martin, N.G., Boomsma, D.I., Gillespie, N.A., Derks, E.M., and Vink, J.M.

Abstract

Item does not contain fulltext, Background: Cannabis is the most frequently used and abused illicit drug worldwide and cannabis (ab)use is associated with social, physical, and psychological problems. Twin and family studies have shown that cannabis use and abuse are heritable traits. The International Cannabis Consortium was initiated with the aim of identifying genetic risk variants for cannabis use phenotypes by meta-analysing data from many contributing cohorts. The (partly preliminary) results of the International Cannabis Consortium will be presented: genome-wide association (GWA) meta-analyses on lifetime cannabis use and age at initiation of use. Additionally, findings from several follow-up studies will be presented, including the genetic association of cannabis use with use of other substances, schizophrenia, and conduct disorder. Methods: GWA analyses of lifetime cannabis use were performed by each contributing group independently (13 groups, total N=32,330) and were subsequently meta-analysed. We tested for replication, and the SNP results were used to perform a gene-based test of association. We also estimated the total SNP-based heritability and the genetic correlation between lifetime cannabis use and cigarette use based on LD-score regression analysis. Secondly, we meta-analysed GWA results of age at initiation of cannabis use from 8 groups (N=24,222) using a survival analysis. Again SNP results are followed up by a gene-based test of association and an estimate of SNP-based heritability. In follow-up projects, LD-score regression analyses were used to determine the genetic correlation of cannabis use with nicotine, alcohol, and caffeine use, as well as schizophrenia and conduct disorder. We also created polygenic risk scores for cannabis use in an independent target sample and determined to what extent these polygenic scores predicted conduct symptoms. Results: Although none of the SNPs were significantly associated with lifetime cannabis use, the gene-based analysis identified 4

Published
2017

9. The International Cannabis Consortium: What did we learn about the genetics of cannabis

Author

Verweij, K.J.H., Minica, C.C., Stringer, S., Most, P.J. van der, Mbarek, H., Nivard, M.G., Abdellaoui, A., Hottenga, J.J., Martin, N.G., Boomsma, D.I., Gillespie, N.A., Derks, E.M., Vink, J.M., Verweij, K.J.H., Minica, C.C., Stringer, S., Most, P.J. van der, Mbarek, H., Nivard, M.G., Abdellaoui, A., Hottenga, J.J., Martin, N.G., Boomsma, D.I., Gillespie, N.A., Derks, E.M., and Vink, J.M.

Abstract

Item does not contain fulltext, Background: Cannabis is the most frequently used and abused illicit drug worldwide and cannabis (ab)use is associated with social, physical, and psychological problems. Twin and family studies have shown that cannabis use and abuse are heritable traits. The International Cannabis Consortium was initiated with the aim of identifying genetic risk variants for cannabis use phenotypes by meta-analysing data from many contributing cohorts. The (partly preliminary) results of the International Cannabis Consortium will be presented: genome-wide association (GWA) meta-analyses on lifetime cannabis use and age at initiation of use. Additionally, findings from several follow-up studies will be presented, including the genetic association of cannabis use with use of other substances, schizophrenia, and conduct disorder. Methods: GWA analyses of lifetime cannabis use were performed by each contributing group independently (13 groups, total N=32,330) and were subsequently meta-analysed. We tested for replication, and the SNP results were used to perform a gene-based test of association. We also estimated the total SNP-based heritability and the genetic correlation between lifetime cannabis use and cigarette use based on LD-score regression analysis. Secondly, we meta-analysed GWA results of age at initiation of cannabis use from 8 groups (N=24,222) using a survival analysis. Again SNP results are followed up by a gene-based test of association and an estimate of SNP-based heritability. In follow-up projects, LD-score regression analyses were used to determine the genetic correlation of cannabis use with nicotine, alcohol, and caffeine use, as well as schizophrenia and conduct disorder. We also created polygenic risk scores for cannabis use in an independent target sample and determined to what extent these polygenic scores predicted conduct symptoms. Results: Although none of the SNPs were significantly associated with lifetime cannabis use, the gene-based analysis identified 4

Published
2017

10. Genome-wide association study of lifetime cannabis use based on a large meta-analytic sample of 32330 subjects from the International Cannabis Consortium

Author

Stringer, S., Minica, C.C., Verweij, K.J.H., Mbarek, H., Bernard, M., Derringer, J.L., Eijk, K.R. van, Isen, J.D., Loukola, A., Maciejewski, D.F., Mihailov, E., Most, P.J. van der, Sánchez-Mora, C., Roos, L., Sherva, R., Walters, R., Ware, J.J., Abdellaoui, A., Bigdeli, T.B., Branje, S.J.T., Brown, S.A., Bruinenberg, M., Casas, M., Esko, T., Garcia-Martinez, I., Gordon, S.D., Harris, J.M., Hartman, C.A., Henders, A.K., Heath, A.C., Hickie, I.B., Hickman, M., Hopfer, C.J., Hottenga, J.J., Huizink, A.C., Irons, D.E., Kahn, R.S., Korhonen, T., Kranzler, H.R., Krauter, K., Lier, P.A.C. van, Lubke, G.H., Madden, P.A.F., Mägi, R., McGue, M.K., Medland, S.E., Meeus, W.H.J., Miller, M.B., Montgomery, G.W., Nivard, M.G., Nolte, I.M., Oldehinkel, A.J., Pausova, Z., Qaiser, B., Quaye, L., Ramos-Quiroga, J.A., Richarte, V., Rose, R.J., Shin, J., Stallings, M.C., Stiby, A.I., Wall, T.L., Wright, M.J., Koot, J.M., Paus, T., Hewitt, J.K., Ribasés, M., Kaprio, J., Boks, M.P.M., Snieder, H., Spector, T., Munafò, M.R., Metspalu, A., Gelernter, J., Boomsma, D.I., Iacono, W.G., Martin, N.G., Gillespie, N.A., Derks, E.M., Vink, J.M., Stringer, S., Minica, C.C., Verweij, K.J.H., Mbarek, H., Bernard, M., Derringer, J.L., Eijk, K.R. van, Isen, J.D., Loukola, A., Maciejewski, D.F., Mihailov, E., Most, P.J. van der, Sánchez-Mora, C., Roos, L., Sherva, R., Walters, R., Ware, J.J., Abdellaoui, A., Bigdeli, T.B., Branje, S.J.T., Brown, S.A., Bruinenberg, M., Casas, M., Esko, T., Garcia-Martinez, I., Gordon, S.D., Harris, J.M., Hartman, C.A., Henders, A.K., Heath, A.C., Hickie, I.B., Hickman, M., Hopfer, C.J., Hottenga, J.J., Huizink, A.C., Irons, D.E., Kahn, R.S., Korhonen, T., Kranzler, H.R., Krauter, K., Lier, P.A.C. van, Lubke, G.H., Madden, P.A.F., Mägi, R., McGue, M.K., Medland, S.E., Meeus, W.H.J., Miller, M.B., Montgomery, G.W., Nivard, M.G., Nolte, I.M., Oldehinkel, A.J., Pausova, Z., Qaiser, B., Quaye, L., Ramos-Quiroga, J.A., Richarte, V., Rose, R.J., Shin, J., Stallings, M.C., Stiby, A.I., Wall, T.L., Wright, M.J., Koot, J.M., Paus, T., Hewitt, J.K., Ribasés, M., Kaprio, J., Boks, M.P.M., Snieder, H., Spector, T., Munafò, M.R., Metspalu, A., Gelernter, J., Boomsma, D.I., Iacono, W.G., Martin, N.G., Gillespie, N.A., Derks, E.M., and Vink, J.M.

Abstract

Contains fulltext : 156357.pdf (publisher's version ) (Open Access), Cannabis is the most widely produced and consumed illicit psychoactive substance worldwide. Occasional cannabis use can progress to frequent use, abuse and dependence with all known adverse physical, psychological and social consequences. Individual differences in cannabis initiation are heritable (40-48%). The International Cannabis Consortium was established with the aim to identify genetic risk variants of cannabis use. We conducted a meta-analysis of genome-wide association data of 13 cohorts (N=32330) and four replication samples (N=5627). In addition, we performed a gene-based test of association, estimated single-nucleotide polymorphism (SNP)-based heritability and explored the genetic correlation between lifetime cannabis use and cigarette use using LD score regression. No individual SNPs reached genome-wide significance. Nonetheless, gene-based tests identified four genes significantly associated with lifetime cannabis use: NCAM1, CADM2, SCOC and KCNT2. Previous studies reported associations of NCAM1 with cigarette smoking and other substance use, and those of CADM2 with body mass index, processing speed and autism disorders, which are phenotypes previously reported to be associated with cannabis use. Furthermore, we showed that, combined across the genome, all common SNPs explained 13-20% (P<0.001) of the liability of lifetime cannabis use. Finally, there was a strong genetic correlation (rg=0.83; P=1.85 × 10-8) between lifetime cannabis use and lifetime cigarette smoking implying that the SNP effect sizes of the two traits are highly correlated. This is the largest meta-analysis of cannabis GWA studies to date, revealing important new insights into the genetic pathways of lifetime cannabis use. Future functional studies should explore the impact of the identified genes on the biological mechanisms of cannabis use.

Published
2016

11. Genome-wide association study identifies 74 loci associated with educational attainment

Author

Okbay, A., Beauchamp, J.P., Fontana, M.A., Lee, J.J., Pers, T.H., Rietveld, C.A., Turley, P., Chen, G.B., Emilsson, V., Meddens, S.F., Oskarsson, S., Pickrell, J.K., Thom, K., Timshel, P., Vlaming, R. de, Abdellaoui, A., Ahluwalia, T.S., Bacelis, J., Baumbach, C., Bjornsdottir, G., Brandsma, J.H., Pina Concas, M., Derringer, J., Furlotte, N.A., Galesloot, T.E., Girotto, G., Gupta, R, Hall, L.M., Harris, S.E., Hofer, E., Horikoshi, M., Huffman, J.E., Kaasik, K., Kalafati, I.P., Karlsson, R., Kong, A., Lahti, J., Lee, S.J. van der, deLeeuw, C., Lind, P.A., Lindgren, K.O., Liu, T., Mangino, M., Marten, J., Mihailov, E., Miller, M.B., Most, P.J. van der, Oldmeadow, C., Payton, A., Pervjakova, N., Peyrot, W.J., Qian, Y., Raitakari, O., Rueedi, R., Salvi, E., Schmidt, B., Schraut, K.E., Shi, J., Smith, A.V., Poot, R.A., Pourcain, B. St, Teumer, A., Thorleifsson, G., Verweij, N., Vuckovic, D., Wellmann, J., Westra, H.J., Yang, J., Zhao, W., Zhu, Z., Alizadeh, B.Z., Amin, N., Bakshi, A., Baumeister, S.E., Biino, G., Bonnelykke, K., Boyle, P.A., Campbell, H., Cappuccio, F.P., Davies, G., Neve, J.E. De, Deloukas, P., Demuth, I., Ding, J., Eibich, P., Eisele, L., Eklund, N., Evans, D.M., Faul, J.D., Feitosa, M.F., Forstner, A.J., Gandin, I., Gunnarsson, B., Halldorsson, B.V., Harris, T.B., Heath, A.C., Hocking, L.J., Holliday, E.G., Homuth, G., Horan, M.A., Franke, B., Kiemeney, L.A.L.M., et al., Okbay, A., Beauchamp, J.P., Fontana, M.A., Lee, J.J., Pers, T.H., Rietveld, C.A., Turley, P., Chen, G.B., Emilsson, V., Meddens, S.F., Oskarsson, S., Pickrell, J.K., Thom, K., Timshel, P., Vlaming, R. de, Abdellaoui, A., Ahluwalia, T.S., Bacelis, J., Baumbach, C., Bjornsdottir, G., Brandsma, J.H., Pina Concas, M., Derringer, J., Furlotte, N.A., Galesloot, T.E., Girotto, G., Gupta, R, Hall, L.M., Harris, S.E., Hofer, E., Horikoshi, M., Huffman, J.E., Kaasik, K., Kalafati, I.P., Karlsson, R., Kong, A., Lahti, J., Lee, S.J. van der, deLeeuw, C., Lind, P.A., Lindgren, K.O., Liu, T., Mangino, M., Marten, J., Mihailov, E., Miller, M.B., Most, P.J. van der, Oldmeadow, C., Payton, A., Pervjakova, N., Peyrot, W.J., Qian, Y., Raitakari, O., Rueedi, R., Salvi, E., Schmidt, B., Schraut, K.E., Shi, J., Smith, A.V., Poot, R.A., Pourcain, B. St, Teumer, A., Thorleifsson, G., Verweij, N., Vuckovic, D., Wellmann, J., Westra, H.J., Yang, J., Zhao, W., Zhu, Z., Alizadeh, B.Z., Amin, N., Bakshi, A., Baumeister, S.E., Biino, G., Bonnelykke, K., Boyle, P.A., Campbell, H., Cappuccio, F.P., Davies, G., Neve, J.E. De, Deloukas, P., Demuth, I., Ding, J., Eibich, P., Eisele, L., Eklund, N., Evans, D.M., Faul, J.D., Feitosa, M.F., Forstner, A.J., Gandin, I., Gunnarsson, B., Halldorsson, B.V., Harris, T.B., Heath, A.C., Hocking, L.J., Holliday, E.G., Homuth, G., Horan, M.A., Franke, B., Kiemeney, L.A.L.M., and et al.

Abstract

Contains fulltext : 167137.pdf (publisher's version ) (Closed access), Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

Published
2016

12. A Genome-Wide Association Meta-Analysis of Attention-Deficit/Hyperactivity Disorder Symptoms in Population-Based Pediatric Cohorts

Author

Middeldorp, C.M., Hammerschlag, A.R., Ouwens, K.G., Groen-Blokhuis, M.M., Pourcain, B. St, Greven, C.U., Pappa, I., Tiesler, C.M., Ang, W., Nolte, I.M., Vilor-Tejedor, N., Bacelis, J., Ebejer, J.L., Zhao, H., Davies, G.E., Ehli, E.A., Evans, D.M., Fedko, I.O., Guxens, M., Hottenga, J.J., Hudziak, J.J., Jugessur, A., Kemp, J.P., Krapohl, E., Martin, N.G., Murcia, M., Myhre, R., Ormel, J., Ring, S.M., Standl, M., Stergiakouli, E., Stoltenberg, C., Thiering, E., Timpson, N.J., Trzaskowski, M., Most, P.J. van der, Wang, C., Nyholt, D.R., Medland, S.E., Neale, B., Jacobsson, B., Sunyer, J., Hartman, C.A., Whitehouse, A.J.O., Pennell, C.E., Heinrich, J., Plomin, R., Smith, G., Tiemeier, H., Posthuma, D., Boomsma, D.I., Middeldorp, C.M., Hammerschlag, A.R., Ouwens, K.G., Groen-Blokhuis, M.M., Pourcain, B. St, Greven, C.U., Pappa, I., Tiesler, C.M., Ang, W., Nolte, I.M., Vilor-Tejedor, N., Bacelis, J., Ebejer, J.L., Zhao, H., Davies, G.E., Ehli, E.A., Evans, D.M., Fedko, I.O., Guxens, M., Hottenga, J.J., Hudziak, J.J., Jugessur, A., Kemp, J.P., Krapohl, E., Martin, N.G., Murcia, M., Myhre, R., Ormel, J., Ring, S.M., Standl, M., Stergiakouli, E., Stoltenberg, C., Thiering, E., Timpson, N.J., Trzaskowski, M., Most, P.J. van der, Wang, C., Nyholt, D.R., Medland, S.E., Neale, B., Jacobsson, B., Sunyer, J., Hartman, C.A., Whitehouse, A.J.O., Pennell, C.E., Heinrich, J., Plomin, R., Smith, G., Tiemeier, H., Posthuma, D., and Boomsma, D.I.

Abstract

Contains fulltext : 165989.pdf (publisher's version ) (Closed access), OBJECTIVE: The aims of this study were to elucidate the influence of common genetic variants on childhood attention-deficit/hyperactivity disorder (ADHD) symptoms, to identify genetic variants that explain its high heritability, and to investigate the genetic overlap of ADHD symptom scores with ADHD diagnosis. METHOD: Within the EArly Genetics and Lifecourse Epidemiology (EAGLE) consortium, genome-wide single nucleotide polymorphisms (SNPs) and ADHD symptom scores were available for 17,666 children (<13 years of age) from nine population-based cohorts. SNP-based heritability was estimated in data from the three largest cohorts. Meta-analysis based on genome-wide association (GWA) analyses with SNPs was followed by gene-based association tests, and the overlap in results with a meta-analysis in the Psychiatric Genomics Consortium (PGC) case-control ADHD study was investigated. RESULTS: SNP-based heritability ranged from 5% to 34%, indicating that variation in common genetic variants influences ADHD symptom scores. The meta-analysis did not detect genome-wide significant SNPs, but three genes, lying close to each other with SNPs in high linkage disequilibrium (LD), showed a gene-wide significant association (p values between 1.46 x 10(-6) and 2.66 x 10(-6)). One gene, WASL, is involved in neuronal development. Both SNP- and gene-based analyses indicated overlap with the PGC meta-analysis results with the genetic correlation estimated at 0.96. CONCLUSION: The SNP-based heritability for ADHD symptom scores indicates a polygenic architecture, and genes involved in neurite outgrowth are possibly involved. Continuous and dichotomous measures of ADHD appear to assess a genetically common phenotype. A next step is to combine data from population-based and case-control cohorts in genetic association studies to increase sample size and to improve statistical power for identifying genetic variants.

Published
2016

13. Genome-wide association study of lifetime cannabis use based on a large meta-analytic sample of 32330 subjects from the International Cannabis Consortium

Author

Stringer, S., Minica, C.C., Verweij, K.J.H., Mbarek, H., Bernard, M., Derringer, J.L., Eijk, K.R. van, Isen, J.D., Loukola, A., Maciejewski, D.F., Mihailov, E., Most, P.J. van der, Sánchez-Mora, C., Roos, L., Sherva, R., Walters, R., Ware, J.J., Abdellaoui, A., Bigdeli, T.B., Branje, S.J.T., Brown, S.A., Bruinenberg, M., Casas, M., Esko, T., Garcia-Martinez, I., Gordon, S.D., Harris, J.M., Hartman, C.A., Henders, A.K., Heath, A.C., Hickie, I.B., Hickman, M., Hopfer, C.J., Hottenga, J.J., Huizink, A.C., Irons, D.E., Kahn, R.S., Korhonen, T., Kranzler, H.R., Krauter, K., Lier, P.A.C. van, Lubke, G.H., Madden, P.A.F., Mägi, R., McGue, M.K., Medland, S.E., Meeus, W.H.J., Miller, M.B., Montgomery, G.W., Nivard, M.G., Nolte, I.M., Oldehinkel, A.J., Pausova, Z., Qaiser, B., Quaye, L., Ramos-Quiroga, J.A., Richarte, V., Rose, R.J., Shin, J., Stallings, M.C., Stiby, A.I., Wall, T.L., Wright, M.J., Koot, J.M., Paus, T., Hewitt, J.K., Ribasés, M., Kaprio, J., Boks, M.P.M., Snieder, H., Spector, T., Munafò, M.R., Metspalu, A., Gelernter, J., Boomsma, D.I., Iacono, W.G., Martin, N.G., Gillespie, N.A., Derks, E.M., Vink, J.M., Stringer, S., Minica, C.C., Verweij, K.J.H., Mbarek, H., Bernard, M., Derringer, J.L., Eijk, K.R. van, Isen, J.D., Loukola, A., Maciejewski, D.F., Mihailov, E., Most, P.J. van der, Sánchez-Mora, C., Roos, L., Sherva, R., Walters, R., Ware, J.J., Abdellaoui, A., Bigdeli, T.B., Branje, S.J.T., Brown, S.A., Bruinenberg, M., Casas, M., Esko, T., Garcia-Martinez, I., Gordon, S.D., Harris, J.M., Hartman, C.A., Henders, A.K., Heath, A.C., Hickie, I.B., Hickman, M., Hopfer, C.J., Hottenga, J.J., Huizink, A.C., Irons, D.E., Kahn, R.S., Korhonen, T., Kranzler, H.R., Krauter, K., Lier, P.A.C. van, Lubke, G.H., Madden, P.A.F., Mägi, R., McGue, M.K., Medland, S.E., Meeus, W.H.J., Miller, M.B., Montgomery, G.W., Nivard, M.G., Nolte, I.M., Oldehinkel, A.J., Pausova, Z., Qaiser, B., Quaye, L., Ramos-Quiroga, J.A., Richarte, V., Rose, R.J., Shin, J., Stallings, M.C., Stiby, A.I., Wall, T.L., Wright, M.J., Koot, J.M., Paus, T., Hewitt, J.K., Ribasés, M., Kaprio, J., Boks, M.P.M., Snieder, H., Spector, T., Munafò, M.R., Metspalu, A., Gelernter, J., Boomsma, D.I., Iacono, W.G., Martin, N.G., Gillespie, N.A., Derks, E.M., and Vink, J.M.

Abstract

Contains fulltext : 156357.pdf (publisher's version ) (Open Access), Cannabis is the most widely produced and consumed illicit psychoactive substance worldwide. Occasional cannabis use can progress to frequent use, abuse and dependence with all known adverse physical, psychological and social consequences. Individual differences in cannabis initiation are heritable (40-48%). The International Cannabis Consortium was established with the aim to identify genetic risk variants of cannabis use. We conducted a meta-analysis of genome-wide association data of 13 cohorts (N=32330) and four replication samples (N=5627). In addition, we performed a gene-based test of association, estimated single-nucleotide polymorphism (SNP)-based heritability and explored the genetic correlation between lifetime cannabis use and cigarette use using LD score regression. No individual SNPs reached genome-wide significance. Nonetheless, gene-based tests identified four genes significantly associated with lifetime cannabis use: NCAM1, CADM2, SCOC and KCNT2. Previous studies reported associations of NCAM1 with cigarette smoking and other substance use, and those of CADM2 with body mass index, processing speed and autism disorders, which are phenotypes previously reported to be associated with cannabis use. Furthermore, we showed that, combined across the genome, all common SNPs explained 13-20% (P<0.001) of the liability of lifetime cannabis use. Finally, there was a strong genetic correlation (rg=0.83; P=1.85 × 10-8) between lifetime cannabis use and lifetime cigarette smoking implying that the SNP effect sizes of the two traits are highly correlated. This is the largest meta-analysis of cannabis GWA studies to date, revealing important new insights into the genetic pathways of lifetime cannabis use. Future functional studies should explore the impact of the identified genes on the biological mechanisms of cannabis use.

Published
2016

14. Genome-wide association study identifies 74 loci associated with educational attainment

Author

Okbay, A., Beauchamp, J.P., Fontana, M.A., Lee, J.J., Pers, T.H., Rietveld, C.A., Turley, P., Chen, G.B., Emilsson, V., Meddens, S.F., Oskarsson, S., Pickrell, J.K., Thom, K., Timshel, P., Vlaming, R. de, Abdellaoui, A., Ahluwalia, T.S., Bacelis, J., Baumbach, C., Bjornsdottir, G., Brandsma, J.H., Pina Concas, M., Derringer, J., Furlotte, N.A., Galesloot, T.E., Girotto, G., Gupta, R, Hall, L.M., Harris, S.E., Hofer, E., Horikoshi, M., Huffman, J.E., Kaasik, K., Kalafati, I.P., Karlsson, R., Kong, A., Lahti, J., Lee, S.J. van der, deLeeuw, C., Lind, P.A., Lindgren, K.O., Liu, T., Mangino, M., Marten, J., Mihailov, E., Miller, M.B., Most, P.J. van der, Oldmeadow, C., Payton, A., Pervjakova, N., Peyrot, W.J., Qian, Y., Raitakari, O., Rueedi, R., Salvi, E., Schmidt, B., Schraut, K.E., Shi, J., Smith, A.V., Poot, R.A., Pourcain, B. St, Teumer, A., Thorleifsson, G., Verweij, N., Vuckovic, D., Wellmann, J., Westra, H.J., Yang, J., Zhao, W., Zhu, Z., Alizadeh, B.Z., Amin, N., Bakshi, A., Baumeister, S.E., Biino, G., Bonnelykke, K., Boyle, P.A., Campbell, H., Cappuccio, F.P., Davies, G., Neve, J.E. De, Deloukas, P., Demuth, I., Ding, J., Eibich, P., Eisele, L., Eklund, N., Evans, D.M., Faul, J.D., Feitosa, M.F., Forstner, A.J., Gandin, I., Gunnarsson, B., Halldorsson, B.V., Harris, T.B., Heath, A.C., Hocking, L.J., Holliday, E.G., Homuth, G., Horan, M.A., Franke, B., Kiemeney, L.A.L.M., et al., Okbay, A., Beauchamp, J.P., Fontana, M.A., Lee, J.J., Pers, T.H., Rietveld, C.A., Turley, P., Chen, G.B., Emilsson, V., Meddens, S.F., Oskarsson, S., Pickrell, J.K., Thom, K., Timshel, P., Vlaming, R. de, Abdellaoui, A., Ahluwalia, T.S., Bacelis, J., Baumbach, C., Bjornsdottir, G., Brandsma, J.H., Pina Concas, M., Derringer, J., Furlotte, N.A., Galesloot, T.E., Girotto, G., Gupta, R, Hall, L.M., Harris, S.E., Hofer, E., Horikoshi, M., Huffman, J.E., Kaasik, K., Kalafati, I.P., Karlsson, R., Kong, A., Lahti, J., Lee, S.J. van der, deLeeuw, C., Lind, P.A., Lindgren, K.O., Liu, T., Mangino, M., Marten, J., Mihailov, E., Miller, M.B., Most, P.J. van der, Oldmeadow, C., Payton, A., Pervjakova, N., Peyrot, W.J., Qian, Y., Raitakari, O., Rueedi, R., Salvi, E., Schmidt, B., Schraut, K.E., Shi, J., Smith, A.V., Poot, R.A., Pourcain, B. St, Teumer, A., Thorleifsson, G., Verweij, N., Vuckovic, D., Wellmann, J., Westra, H.J., Yang, J., Zhao, W., Zhu, Z., Alizadeh, B.Z., Amin, N., Bakshi, A., Baumeister, S.E., Biino, G., Bonnelykke, K., Boyle, P.A., Campbell, H., Cappuccio, F.P., Davies, G., Neve, J.E. De, Deloukas, P., Demuth, I., Ding, J., Eibich, P., Eisele, L., Eklund, N., Evans, D.M., Faul, J.D., Feitosa, M.F., Forstner, A.J., Gandin, I., Gunnarsson, B., Halldorsson, B.V., Harris, T.B., Heath, A.C., Hocking, L.J., Holliday, E.G., Homuth, G., Horan, M.A., Franke, B., Kiemeney, L.A.L.M., and et al.

Abstract

Contains fulltext : 167137.pdf (publisher's version ) (Closed access), Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

Published
2016

15. A Genome-Wide Association Meta-Analysis of Attention-Deficit/Hyperactivity Disorder Symptoms in Population-Based Pediatric Cohorts

Author

Middeldorp, C.M., Hammerschlag, A.R., Ouwens, K.G., Groen-Blokhuis, M.M., Pourcain, B. St, Greven, C.U., Pappa, I., Tiesler, C.M., Ang, W., Nolte, I.M., Vilor-Tejedor, N., Bacelis, J., Ebejer, J.L., Zhao, H., Davies, G.E., Ehli, E.A., Evans, D.M., Fedko, I.O., Guxens, M., Hottenga, J.J., Hudziak, J.J., Jugessur, A., Kemp, J.P., Krapohl, E., Martin, N.G., Murcia, M., Myhre, R., Ormel, J., Ring, S.M., Standl, M., Stergiakouli, E., Stoltenberg, C., Thiering, E., Timpson, N.J., Trzaskowski, M., Most, P.J. van der, Wang, C., Nyholt, D.R., Medland, S.E., Neale, B., Jacobsson, B., Sunyer, J., Hartman, C.A., Whitehouse, A.J.O., Pennell, C.E., Heinrich, J., Plomin, R., Smith, G., Tiemeier, H., Posthuma, D., Boomsma, D.I., Middeldorp, C.M., Hammerschlag, A.R., Ouwens, K.G., Groen-Blokhuis, M.M., Pourcain, B. St, Greven, C.U., Pappa, I., Tiesler, C.M., Ang, W., Nolte, I.M., Vilor-Tejedor, N., Bacelis, J., Ebejer, J.L., Zhao, H., Davies, G.E., Ehli, E.A., Evans, D.M., Fedko, I.O., Guxens, M., Hottenga, J.J., Hudziak, J.J., Jugessur, A., Kemp, J.P., Krapohl, E., Martin, N.G., Murcia, M., Myhre, R., Ormel, J., Ring, S.M., Standl, M., Stergiakouli, E., Stoltenberg, C., Thiering, E., Timpson, N.J., Trzaskowski, M., Most, P.J. van der, Wang, C., Nyholt, D.R., Medland, S.E., Neale, B., Jacobsson, B., Sunyer, J., Hartman, C.A., Whitehouse, A.J.O., Pennell, C.E., Heinrich, J., Plomin, R., Smith, G., Tiemeier, H., Posthuma, D., and Boomsma, D.I.

Abstract

Contains fulltext : 165989.pdf (publisher's version ) (Closed access), OBJECTIVE: The aims of this study were to elucidate the influence of common genetic variants on childhood attention-deficit/hyperactivity disorder (ADHD) symptoms, to identify genetic variants that explain its high heritability, and to investigate the genetic overlap of ADHD symptom scores with ADHD diagnosis. METHOD: Within the EArly Genetics and Lifecourse Epidemiology (EAGLE) consortium, genome-wide single nucleotide polymorphisms (SNPs) and ADHD symptom scores were available for 17,666 children (<13 years of age) from nine population-based cohorts. SNP-based heritability was estimated in data from the three largest cohorts. Meta-analysis based on genome-wide association (GWA) analyses with SNPs was followed by gene-based association tests, and the overlap in results with a meta-analysis in the Psychiatric Genomics Consortium (PGC) case-control ADHD study was investigated. RESULTS: SNP-based heritability ranged from 5% to 34%, indicating that variation in common genetic variants influences ADHD symptom scores. The meta-analysis did not detect genome-wide significant SNPs, but three genes, lying close to each other with SNPs in high linkage disequilibrium (LD), showed a gene-wide significant association (p values between 1.46 x 10(-6) and 2.66 x 10(-6)). One gene, WASL, is involved in neuronal development. Both SNP- and gene-based analyses indicated overlap with the PGC meta-analysis results with the genetic correlation estimated at 0.96. CONCLUSION: The SNP-based heritability for ADHD symptom scores indicates a polygenic architecture, and genes involved in neurite outgrowth are possibly involved. Continuous and dichotomous measures of ADHD appear to assess a genetically common phenotype. A next step is to combine data from population-based and case-control cohorts in genetic association studies to increase sample size and to improve statistical power for identifying genetic variants.

Published
2016

16. Genome-wide association study identifies 74 loci associated with educational attainment

Author

Okbay, A., Beauchamp, J.P., Fontana, M.A., Lee, J.J., Pers, T.H., Rietveld, C.A., Turley, P., Chen, G.B., Emilsson, V., Meddens, S.F., Oskarsson, S., Pickrell, J.K., Thom, K., Timshel, P., Vlaming, R. de, Abdellaoui, A., Ahluwalia, T.S., Bacelis, J., Baumbach, C., Bjornsdottir, G., Brandsma, J.H., Pina Concas, M., Derringer, J., Furlotte, N.A., Galesloot, T.E., Girotto, G., Gupta, R, Hall, L.M., Harris, S.E., Hofer, E., Horikoshi, M., Huffman, J.E., Kaasik, K., Kalafati, I.P., Karlsson, R., Kong, A., Lahti, J., Lee, S.J. van der, deLeeuw, C., Lind, P.A., Lindgren, K.O., Liu, T., Mangino, M., Marten, J., Mihailov, E., Miller, M.B., Most, P.J. van der, Oldmeadow, C., Payton, A., Pervjakova, N., Peyrot, W.J., Qian, Y., Raitakari, O., Rueedi, R., Salvi, E., Schmidt, B., Schraut, K.E., Shi, J., Smith, A.V., Poot, R.A., Pourcain, B. St, Teumer, A., Thorleifsson, G., Verweij, N., Vuckovic, D., Wellmann, J., Westra, H.J., Yang, J., Zhao, W., Zhu, Z., Alizadeh, B.Z., Amin, N., Bakshi, A., Baumeister, S.E., Biino, G., Bonnelykke, K., Boyle, P.A., Campbell, H., Cappuccio, F.P., Davies, G., Neve, J.E. De, Deloukas, P., Demuth, I., Ding, J., Eibich, P., Eisele, L., Eklund, N., Evans, D.M., Faul, J.D., Feitosa, M.F., Forstner, A.J., Gandin, I., Gunnarsson, B., Halldorsson, B.V., Harris, T.B., Heath, A.C., Hocking, L.J., Holliday, E.G., Homuth, G., Horan, M.A., Franke, B., Kiemeney, L.A.L.M., et al., Okbay, A., Beauchamp, J.P., Fontana, M.A., Lee, J.J., Pers, T.H., Rietveld, C.A., Turley, P., Chen, G.B., Emilsson, V., Meddens, S.F., Oskarsson, S., Pickrell, J.K., Thom, K., Timshel, P., Vlaming, R. de, Abdellaoui, A., Ahluwalia, T.S., Bacelis, J., Baumbach, C., Bjornsdottir, G., Brandsma, J.H., Pina Concas, M., Derringer, J., Furlotte, N.A., Galesloot, T.E., Girotto, G., Gupta, R, Hall, L.M., Harris, S.E., Hofer, E., Horikoshi, M., Huffman, J.E., Kaasik, K., Kalafati, I.P., Karlsson, R., Kong, A., Lahti, J., Lee, S.J. van der, deLeeuw, C., Lind, P.A., Lindgren, K.O., Liu, T., Mangino, M., Marten, J., Mihailov, E., Miller, M.B., Most, P.J. van der, Oldmeadow, C., Payton, A., Pervjakova, N., Peyrot, W.J., Qian, Y., Raitakari, O., Rueedi, R., Salvi, E., Schmidt, B., Schraut, K.E., Shi, J., Smith, A.V., Poot, R.A., Pourcain, B. St, Teumer, A., Thorleifsson, G., Verweij, N., Vuckovic, D., Wellmann, J., Westra, H.J., Yang, J., Zhao, W., Zhu, Z., Alizadeh, B.Z., Amin, N., Bakshi, A., Baumeister, S.E., Biino, G., Bonnelykke, K., Boyle, P.A., Campbell, H., Cappuccio, F.P., Davies, G., Neve, J.E. De, Deloukas, P., Demuth, I., Ding, J., Eibich, P., Eisele, L., Eklund, N., Evans, D.M., Faul, J.D., Feitosa, M.F., Forstner, A.J., Gandin, I., Gunnarsson, B., Halldorsson, B.V., Harris, T.B., Heath, A.C., Hocking, L.J., Holliday, E.G., Homuth, G., Horan, M.A., Franke, B., Kiemeney, L.A.L.M., and et al.

Abstract

Contains fulltext : 167137.pdf (publisher's version ) (Closed access), Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

Published
2016

17. A Genome-Wide Association Meta-Analysis of Attention-Deficit/Hyperactivity Disorder Symptoms in Population-Based Pediatric Cohorts

Author

Middeldorp, C.M., Hammerschlag, A.R., Ouwens, K.G., Groen-Blokhuis, M.M., Pourcain, B. St, Greven, C.U., Pappa, I., Tiesler, C.M., Ang, W., Nolte, I.M., Vilor-Tejedor, N., Bacelis, J., Ebejer, J.L., Zhao, H., Davies, G.E., Ehli, E.A., Evans, D.M., Fedko, I.O., Guxens, M., Hottenga, J.J., Hudziak, J.J., Jugessur, A., Kemp, J.P., Krapohl, E., Martin, N.G., Murcia, M., Myhre, R., Ormel, J., Ring, S.M., Standl, M., Stergiakouli, E., Stoltenberg, C., Thiering, E., Timpson, N.J., Trzaskowski, M., Most, P.J. van der, Wang, C., Nyholt, D.R., Medland, S.E., Neale, B., Jacobsson, B., Sunyer, J., Hartman, C.A., Whitehouse, A.J.O., Pennell, C.E., Heinrich, J., Plomin, R., Smith, G., Tiemeier, H., Posthuma, D., Boomsma, D.I., Middeldorp, C.M., Hammerschlag, A.R., Ouwens, K.G., Groen-Blokhuis, M.M., Pourcain, B. St, Greven, C.U., Pappa, I., Tiesler, C.M., Ang, W., Nolte, I.M., Vilor-Tejedor, N., Bacelis, J., Ebejer, J.L., Zhao, H., Davies, G.E., Ehli, E.A., Evans, D.M., Fedko, I.O., Guxens, M., Hottenga, J.J., Hudziak, J.J., Jugessur, A., Kemp, J.P., Krapohl, E., Martin, N.G., Murcia, M., Myhre, R., Ormel, J., Ring, S.M., Standl, M., Stergiakouli, E., Stoltenberg, C., Thiering, E., Timpson, N.J., Trzaskowski, M., Most, P.J. van der, Wang, C., Nyholt, D.R., Medland, S.E., Neale, B., Jacobsson, B., Sunyer, J., Hartman, C.A., Whitehouse, A.J.O., Pennell, C.E., Heinrich, J., Plomin, R., Smith, G., Tiemeier, H., Posthuma, D., and Boomsma, D.I.

Abstract

Contains fulltext : 165989.pdf (publisher's version ) (Closed access), OBJECTIVE: The aims of this study were to elucidate the influence of common genetic variants on childhood attention-deficit/hyperactivity disorder (ADHD) symptoms, to identify genetic variants that explain its high heritability, and to investigate the genetic overlap of ADHD symptom scores with ADHD diagnosis. METHOD: Within the EArly Genetics and Lifecourse Epidemiology (EAGLE) consortium, genome-wide single nucleotide polymorphisms (SNPs) and ADHD symptom scores were available for 17,666 children (<13 years of age) from nine population-based cohorts. SNP-based heritability was estimated in data from the three largest cohorts. Meta-analysis based on genome-wide association (GWA) analyses with SNPs was followed by gene-based association tests, and the overlap in results with a meta-analysis in the Psychiatric Genomics Consortium (PGC) case-control ADHD study was investigated. RESULTS: SNP-based heritability ranged from 5% to 34%, indicating that variation in common genetic variants influences ADHD symptom scores. The meta-analysis did not detect genome-wide significant SNPs, but three genes, lying close to each other with SNPs in high linkage disequilibrium (LD), showed a gene-wide significant association (p values between 1.46 x 10(-6) and 2.66 x 10(-6)). One gene, WASL, is involved in neuronal development. Both SNP- and gene-based analyses indicated overlap with the PGC meta-analysis results with the genetic correlation estimated at 0.96. CONCLUSION: The SNP-based heritability for ADHD symptom scores indicates a polygenic architecture, and genes involved in neurite outgrowth are possibly involved. Continuous and dichotomous measures of ADHD appear to assess a genetically common phenotype. A next step is to combine data from population-based and case-control cohorts in genetic association studies to increase sample size and to improve statistical power for identifying genetic variants.

Published
2016

Catalog

Books, media, physical & digital resources
See catalog results