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1. The genetic architecture of the human cerebral cortex

Author

Grasby, KL, Jahanshad, N, Painter, JN, Colodro-Conde, L, Bralten, J, Hibar, DP, Lind, PA, Pizzagalli, F, Ching, CRK, McMahon, MAB, Shatokhina, N, Zsembik, LCP, Thomopoulos, SI, Zhu, AH, Strike, LT, Agartz, I, Alhusaini, S, Almeida, MAA, Alnaes, D, Amlien, IK, Andersson, M, Ard, T, Armstrong, NJ, Ashley-Koch, A, Atkins, JR, Bernard, M, Brouwer, RM, Buimer, EEL, Bulow, R, Burger, C, Cannon, DM, Chakravarty, M, Chen, Q, Cheung, JW, Couvy-Duchesne, B, Dale, AM, Dalvie, S, de Araujo, TK, de Zubicaray, GI, de Zwarte, SMC, den Braber, A, Nhat, TD, Dohm, K, Ehrlich, S, Engelbrecht, H-R, Erk, S, Fan, CC, Fedko, IO, Foley, SF, Ford, JM, Fukunaga, M, Garrett, ME, Ge, T, Giddaluru, S, Goldman, AL, Green, MJ, Groenewold, NA, Grotegerd, D, Gurholt, TP, Gutman, BA, Hansell, NK, Harris, MA, Harrison, MB, Haswell, CC, Hauser, M, Herms, S, Heslenfeld, DJ, Ho, NF, Hoehn, D, Hoffmann, P, Holleran, L, Hoogman, M, Hottenga, J-J, Ikeda, M, Janowitz, D, Jansen, IE, Jia, T, Jockwitz, C, Kanai, R, Karama, S, Kasperaviciute, D, Kaufmann, T, Kelly, S, Kikuchi, M, Klein, M, Knapp, M, Knodt, AR, Kramer, B, Lam, M, Lancaster, TM, Lee, PH, Lett, TA, Lewis, LB, Lopes-Cendes, I, Luciano, M, Macciardi, F, Marquand, AF, Mathias, SR, Melzer, TR, Milaneschi, Y, Mirza-Schreiber, N, Moreira, JCV, Muhleisen, TW, Mueller-Myhsok, B, Najt, P, Nakahara, S, Nho, K, Loohuis, LMO, Orfanos, DP, Pearson, JF, Pitcher, TL, Putz, B, Quide, Y, Ragothaman, A, Rashid, FM, Reay, WR, Redlich, R, Reinbold, CS, Repple, J, Richard, G, Riedel, BC, Risacher, SL, Rocha, CS, Mota, NR, Salminen, L, Saremi, A, Saykin, AJ, Schlag, F, Schmaal, L, Schofield, PR, Secolin, R, Shapland, CY, Shen, L, Shin, J, Shumskaya, E, Sonderby, IE, Sprooten, E, Tansey, KE, Teumer, A, Thalamuthu, A, Tordesillas-Gutierrez, D, Turner, JA, Uhlmann, A, Vallerga, CL, van der Meer, D, van Donkelaar, MMJ, van Eijk, L, van Erp, TGM, van Haren, NEM, van Rooij, D, van Tol, M-J, Veldink, JH, Verhoef, E, Walton, E, Wang, M, Wang, Y, Wardlaw, JM, Wen, W, Westlye, LT, Whelan, CD, Witt, SH, Wittfeld, K, Wolf, C, Wolfers, T, Wu, JQ, Yasuda, CL, Zaremba, D, Zhang, Z, Zwiers, MP, Artiges, E, Assareh, AA, Ayesa-Arriola, R, Belger, A, Brandt, CL, Brown, GG, Cichon, S, Curran, JE, Davies, GE, Degenhardt, F, Dennis, MF, Dietsche, B, Djurovic, S, Doherty, CP, Espiritu, R, Garijo, D, Gil, Y, Gowland, PA, Green, RC, Hausler, AN, Heindel, W, Ho, B-C, Hoffmann, WU, Holsboer, F, Homuth, G, Hosten, N, Jack, CR, Jang, M, Jansen, A, Kimbrel, NA, Kolskar, K, Koops, S, Krug, A, Lim, KO, Luykx, JJ, Mathalon, DH, Mather, KA, Mattay, VS, Matthews, S, Van Son, JM, McEwen, SC, Melle, I, Morris, DW, Mueller, BA, Nauck, M, Nordvik, JE, Noethen, MM, O'Leary, DS, Opel, N, Martinot, M-LP, Pike, GB, Preda, A, Quinlan, EB, Rasser, PE, Ratnakar, V, Reppermund, S, Steen, VM, Tooney, PA, Torres, FR, Veltman, DJ, Voyvodic, JT, Whelan, R, White, T, Yamamori, H, Adams, HHH, Bis, JC, Debette, S, Decarli, C, Fornage, M, Gudnason, V, Hofer, E, Ikram, MA, Launer, L, Longstreth, WT, Lopez, OL, Mazoyer, B, Mosley, TH, Roshchupkin, GV, Satizabal, CL, Schmidt, R, Seshadri, S, Yang, Q, Alvim, MKM, Ames, D, Anderson, TJ, Andreassen, OA, Arias-Vasquez, A, Bastin, ME, Baune, BT, Beckham, JC, Blangero, J, Boomsma, DI, Brodaty, H, Brunner, HG, Buckner, RL, Buitelaar, JK, Bustillo, JR, Cahn, W, Cairns, MJ, Calhoun, V, Carr, VJ, Caseras, X, Caspers, S, Cavalleri, GL, Cendes, F, Corvin, A, Crespo-Facorro, B, Dalrymple-Alford, JC, Dannlowski, U, de Geus, EJC, Deary, IJ, Delanty, N, Depondt, C, Desrivieres, S, Donohoe, G, Espeseth, T, Fernandez, G, Fisher, SE, Flor, H, Forstner, AJ, Francks, C, Franke, B, Glahn, DC, Gollub, RL, Grabe, HJ, Gruber, O, Haberg, AK, Hariri, AR, Hartman, CA, Hashimoto, R, Heinz, A, Henskens, FA, Hillegers, MHJ, Hoekstra, PJ, Holmes, AJ, Hong, LE, Hopkins, WD, Pol, HEH, Jernigan, TL, Jonsson, EG, Kahn, RS, Kennedy, MA, Kircher, TTJ, Kochunov, P, Kwok, JBJ, Le Hellard, S, Loughland, CM, Martin, NG, Martinot, J-L, McDonald, C, McMahon, KL, Meyer-Lindenberg, A, Michie, PT, Morey, RA, Mowry, B, Nyberg, L, Oosterlaan, J, Ophoff, RA, Pantelis, C, Paus, T, Pausova, Z, Penninx, BWJH, Polderman, TJC, Posthuma, D, Rietschel, M, Roffman, JL, Rowland, LM, Sachdev, PS, Samann, PG, Schall, U, Schumann, G, Scott, RJ, Sim, K, Sisodiya, SM, Smoller, JW, Sommer, IE, St Pourcain, B, Stein, DJ, Toga, AW, Trollor, JN, Van der Wee, NJA, van't Ent, D, Volzke, H, Walter, H, Weber, B, Weinberger, DR, Wright, MJ, Zhou, J, Stein, JL, Thompson, PM, Medland, SE, Grasby, KL, Jahanshad, N, Painter, JN, Colodro-Conde, L, Bralten, J, Hibar, DP, Lind, PA, Pizzagalli, F, Ching, CRK, McMahon, MAB, Shatokhina, N, Zsembik, LCP, Thomopoulos, SI, Zhu, AH, Strike, LT, Agartz, I, Alhusaini, S, Almeida, MAA, Alnaes, D, Amlien, IK, Andersson, M, Ard, T, Armstrong, NJ, Ashley-Koch, A, Atkins, JR, Bernard, M, Brouwer, RM, Buimer, EEL, Bulow, R, Burger, C, Cannon, DM, Chakravarty, M, Chen, Q, Cheung, JW, Couvy-Duchesne, B, Dale, AM, Dalvie, S, de Araujo, TK, de Zubicaray, GI, de Zwarte, SMC, den Braber, A, Nhat, TD, Dohm, K, Ehrlich, S, Engelbrecht, H-R, Erk, S, Fan, CC, Fedko, IO, Foley, SF, Ford, JM, Fukunaga, M, Garrett, ME, Ge, T, Giddaluru, S, Goldman, AL, Green, MJ, Groenewold, NA, Grotegerd, D, Gurholt, TP, Gutman, BA, Hansell, NK, Harris, MA, Harrison, MB, Haswell, CC, Hauser, M, Herms, S, Heslenfeld, DJ, Ho, NF, Hoehn, D, Hoffmann, P, Holleran, L, Hoogman, M, Hottenga, J-J, Ikeda, M, Janowitz, D, Jansen, IE, Jia, T, Jockwitz, C, Kanai, R, Karama, S, Kasperaviciute, D, Kaufmann, T, Kelly, S, Kikuchi, M, Klein, M, Knapp, M, Knodt, AR, Kramer, B, Lam, M, Lancaster, TM, Lee, PH, Lett, TA, Lewis, LB, Lopes-Cendes, I, Luciano, M, Macciardi, F, Marquand, AF, Mathias, SR, Melzer, TR, Milaneschi, Y, Mirza-Schreiber, N, Moreira, JCV, Muhleisen, TW, Mueller-Myhsok, B, Najt, P, Nakahara, S, Nho, K, Loohuis, LMO, Orfanos, DP, Pearson, JF, Pitcher, TL, Putz, B, Quide, Y, Ragothaman, A, Rashid, FM, Reay, WR, Redlich, R, Reinbold, CS, Repple, J, Richard, G, Riedel, BC, Risacher, SL, Rocha, CS, Mota, NR, Salminen, L, Saremi, A, Saykin, AJ, Schlag, F, Schmaal, L, Schofield, PR, Secolin, R, Shapland, CY, Shen, L, Shin, J, Shumskaya, E, Sonderby, IE, Sprooten, E, Tansey, KE, Teumer, A, Thalamuthu, A, Tordesillas-Gutierrez, D, Turner, JA, Uhlmann, A, Vallerga, CL, van der Meer, D, van Donkelaar, MMJ, van Eijk, L, van Erp, TGM, van Haren, NEM, van Rooij, D, van Tol, M-J, Veldink, JH, Verhoef, E, Walton, E, Wang, M, Wang, Y, Wardlaw, JM, Wen, W, Westlye, LT, Whelan, CD, Witt, SH, Wittfeld, K, Wolf, C, Wolfers, T, Wu, JQ, Yasuda, CL, Zaremba, D, Zhang, Z, Zwiers, MP, Artiges, E, Assareh, AA, Ayesa-Arriola, R, Belger, A, Brandt, CL, Brown, GG, Cichon, S, Curran, JE, Davies, GE, Degenhardt, F, Dennis, MF, Dietsche, B, Djurovic, S, Doherty, CP, Espiritu, R, Garijo, D, Gil, Y, Gowland, PA, Green, RC, Hausler, AN, Heindel, W, Ho, B-C, Hoffmann, WU, Holsboer, F, Homuth, G, Hosten, N, Jack, CR, Jang, M, Jansen, A, Kimbrel, NA, Kolskar, K, Koops, S, Krug, A, Lim, KO, Luykx, JJ, Mathalon, DH, Mather, KA, Mattay, VS, Matthews, S, Van Son, JM, McEwen, SC, Melle, I, Morris, DW, Mueller, BA, Nauck, M, Nordvik, JE, Noethen, MM, O'Leary, DS, Opel, N, Martinot, M-LP, Pike, GB, Preda, A, Quinlan, EB, Rasser, PE, Ratnakar, V, Reppermund, S, Steen, VM, Tooney, PA, Torres, FR, Veltman, DJ, Voyvodic, JT, Whelan, R, White, T, Yamamori, H, Adams, HHH, Bis, JC, Debette, S, Decarli, C, Fornage, M, Gudnason, V, Hofer, E, Ikram, MA, Launer, L, Longstreth, WT, Lopez, OL, Mazoyer, B, Mosley, TH, Roshchupkin, GV, Satizabal, CL, Schmidt, R, Seshadri, S, Yang, Q, Alvim, MKM, Ames, D, Anderson, TJ, Andreassen, OA, Arias-Vasquez, A, Bastin, ME, Baune, BT, Beckham, JC, Blangero, J, Boomsma, DI, Brodaty, H, Brunner, HG, Buckner, RL, Buitelaar, JK, Bustillo, JR, Cahn, W, Cairns, MJ, Calhoun, V, Carr, VJ, Caseras, X, Caspers, S, Cavalleri, GL, Cendes, F, Corvin, A, Crespo-Facorro, B, Dalrymple-Alford, JC, Dannlowski, U, de Geus, EJC, Deary, IJ, Delanty, N, Depondt, C, Desrivieres, S, Donohoe, G, Espeseth, T, Fernandez, G, Fisher, SE, Flor, H, Forstner, AJ, Francks, C, Franke, B, Glahn, DC, Gollub, RL, Grabe, HJ, Gruber, O, Haberg, AK, Hariri, AR, Hartman, CA, Hashimoto, R, Heinz, A, Henskens, FA, Hillegers, MHJ, Hoekstra, PJ, Holmes, AJ, Hong, LE, Hopkins, WD, Pol, HEH, Jernigan, TL, Jonsson, EG, Kahn, RS, Kennedy, MA, Kircher, TTJ, Kochunov, P, Kwok, JBJ, Le Hellard, S, Loughland, CM, Martin, NG, Martinot, J-L, McDonald, C, McMahon, KL, Meyer-Lindenberg, A, Michie, PT, Morey, RA, Mowry, B, Nyberg, L, Oosterlaan, J, Ophoff, RA, Pantelis, C, Paus, T, Pausova, Z, Penninx, BWJH, Polderman, TJC, Posthuma, D, Rietschel, M, Roffman, JL, Rowland, LM, Sachdev, PS, Samann, PG, Schall, U, Schumann, G, Scott, RJ, Sim, K, Sisodiya, SM, Smoller, JW, Sommer, IE, St Pourcain, B, Stein, DJ, Toga, AW, Trollor, JN, Van der Wee, NJA, van't Ent, D, Volzke, H, Walter, H, Weber, B, Weinberger, DR, Wright, MJ, Zhou, J, Stein, JL, Thompson, PM, and Medland, SE

Abstract

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.

Published
2020

2. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use

Author

Liu, M, Jiang, Y, Wedow, R, Li, Y, Brazel, DM, Chen, F, Datta, G, Davila-Velderrain, J, McGuire, D, Tian, C, Zhan, X, Team, 23Andme Research, Psychiatry, Hunt All-In, Choquet, H, Docherty, AR, Faul, JD, Foerster, JR, Fritsche, LG, Gabrielsen, ME, Gordon, SD, Haessler, J, Hottenga, J-J, Huang, H, Jang, S-K, Jansen, PR, Ling, Y, Mägi, R, Matoba, N, McMahon, G, Mulas, A, Orrù, V, Palviainen, T, Pandit, A, Reginsson, GW, Skogholt, AH, Smith, JA, Taylor, AE, Turman, C, Willemsen, G, Young, H, Young, KA, Zajac, GJM, Zhao, W, Zhou, W, Bjornsdottir, G, Boardman, JD, Boehnke, M, Boomsma, DI, Chen, C, Cucca, F, Davies, GE, Eaton, CB, Ehringer, MA, Esko, T, Fiorillo, E, Gillespie, NA, Gudbjartsson, DF, Haller, T, Harris, KM, Heath, AC, Hewitt, JK, Hickie, IB, Hokanson, JE, Hopfer, CJ, Hunter, DJ, Iacono, WG, Johnson, EO, Kamatani, Y, Kardia, SLR, Keller, MC, Kellis, M, Kooperberg, C, Kraft, P, Krauter, KS, Laakso, M, Lind, PA, Loukola, A, Lutz, SM, Madden, PAF, Martin, NG, McGue, M, McQueen, MB, Medland, SE, Metspalu, A, Mohlke, KL, Nielsen, JB, Okada, Y, Peters, U, Polderman, TJC, Posthuma, D, Reiner, AP, Rice, JP, Rimm, E, Rose, RJ, Runarsdottir, V, Stallings, MC, Stančáková, A, Stefansson, H, Thai, KK, Tindle, HA, Tyrfingsson, T, Wall, TL, Weir, DR, Weisner, C, Whitfield, JB, Winsvold, BS, Yin, J, Zuccolo, L, Bierut, LJ, Hveem, K, Lee, JJ, Munafò, MR, Saccone, NL, Willer, CJ, Cornelis, MC, David, SP, Hinds, DA, Jorgenson, E, Kaprio, J, Stitzel, JA, Stefansson, K, Thorgeirsson, TE, Abecasis, G, Liu, DJ, Vrieze, S, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, APH - Mental Health, APH - Methodology, Human genetics, Amsterdam Reproduction & Development (AR&D), APH - Aging & Later Life, and Human Genetics

Subjects
Male, Netherlands Twin Register (NTR), Smoking/genetics, ved/biology.organism_classification_rank.species, Alcohol, Genome-wide association study, Brain and Behaviour, chemistry.chemical_compound, 0302 clinical medicine, Tobacco Use Disorder/genetics, Tobacco/adverse effects, Genetics, 0303 health sciences, Smoking, Tobacco and Alcohol, public health, Tobacco Use Disorder, Middle Aged, 3. Good health, Phenotype, psychiatric disorders, Genetic Variation/genetics, Meta-analysis, Genome-Wide Association Study/methods, Female, Physical and Mental Health, Risk, Alcohol Drinking, psychology, Biology, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Tobacco, Humans, Model organism, Gene, 030304 developmental biology, Genetic association, ved/biology, Genetic Variation, Alcohol Drinking/genetics, Heritability, chemistry, genome-wide association studies, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6,7,8,9,10,11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures. © 2019. This is the authors’ accepted and refereed manuscript to the article.

Published
2019

3. The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia: design, results and future prospects

Author

Middeldorp, CM, Mahajan, A, Horikoshi, M, Robertson, NR, Beaumont, RN, Bradfield, JP, Bustamante, M, Cousminer, DL, Day, FR, De Silva, NM, Guxens, M, Mook-Kanamori, DO, St Pourcain, B, Warrington, NM, Adair, LS, Ahlqvist, E, Ahluwalia, TS, Almgren, P, Ang, W, Atalay, M, Auvinen, J, Bartels, M, Beckmann, JS, Bilbao, JR, Bond, T, Borja, JB, Cavadino, A, Charoen, P, Chen, Z, Coin, L, Cooper, C, Curtin, JA, Custovic, A, Das, S, Davies, GE, Dedoussis, GV, Duijts, L, Eastwood, PR, Eliasen, AU, Elliott, P, Eriksson, JG, Estivill, X, Fadista, J, Fedko, IO, Frayling, TM, Gaillard, R, Gauderman, WJ, Geller, F, Gilliland, F, Gilsanz, V, Granell, R, Grarup, N, Groop, L, Hadley, D, Hakonarson, H, Hansen, T, Hartman, CA, Hattersley, AT, Hayes, MG, Hebebrand, J, Heinrich, J, Helgeland, O, Henders, AK, Henderson, J, Henriksen, TB, Hirschhorn, JN, Hivert, M-F, Hocher, B, Holloway, JW, Holt, P, Hottenga, J-J, Hypponen, E, Iniguez, C, Johansson, S, Jugessur, A, Kahonen, M, Kalkwarf, HJ, Kaprio, J, Karhunen, V, Kemp, JP, Kerkhof, M, Koppelman, GH, Korner, A, Kotecha, S, Kreiner-Moller, E, Kulohoma, B, Kumar, A, Kutalik, Z, Lahti, J, Lappe, JM, Larsson, H, Lehtimaki, T, Lewin, AM, Li, J, Lichtenstein, P, Lindgren, CM, Lindi, V, Linneberg, A, Liu, X, Liu, J, Lowe, WL, Lundstrom, S, Lyytikainen, L-P, Ma, RCW, Mace, A, Magi, R, Magnus, P, Mamun, AA, Mannikko, M, Martin, NG, Mbarek, H, McCarthy, NS, Medland, SE, Melbye, M, Melen, E, Mohlke, KL, Monnereau, C, Morgen, CS, Morris, AP, Murray, JC, Myhre, R, Najman, JM, Nivard, MG, Nohr, EA, Nolte, IM, Ntalla, I, O'Reilly, P, Oberfield, SE, Oken, E, Oldehinkel, AJ, Pahkala, K, Palviainen, T, Panoutsopoulou, K, Pedersen, O, Pennell, CE, Pershagen, G, Pitkanen, N, Plomin, R, Power, C, Prasad, RB, Prokopenko, I, Pulkkinen, L, Raikkonen, K, Raitakari, OT, Reynolds, RM, Richmond, RC, Rivadeneira, F, Rodriguez, A, Rose, RJ, Salem, R, Santa-Marina, L, Saw, S-M, Schnurr, TM, Scott, JG, Selzam, S, Shepherd, JA, Simpson, A, Skotte, L, Sleiman, PMA, Snieder, H, Sorensen, TIA, Standl, M, Steegers, EAP, Strachan, DP, Straker, L, Strandberg, T, Taylor, M, Teo, Y-Y, Thiering, E, Torrent, M, Tyrrell, J, Uitterlinden, AG, van Beijsterveldt, T, van der Most, PJ, van Duijn, CM, Viikari, J, Vilor-Tejedor, N, Vogelezang, S, Vonk, JM, Vrijkotte, TGM, Vuoksimaa, E, Wang, CA, Watkins, WJ, Wichmann, H-E, Willemsen, G, Williams, GM, Wilson, JF, Wray, NR, Xu, S, Xu, C-J, Yaghootkar, H, Yi, L, Zafarmand, MH, Zeggini, E, Zemel, BS, Hinney, A, Lakka, TA, Whitehouse, AJO, Sunyer, J, Widen, EE, Feenstra, B, Sebert, S, Jacobsson, B, Njolstad, PR, Stoltenberg, C, Smith, GD, Lawlor, DA, Paternoster, L, Timpson, NJ, Ong, KK, Bisgaard, H, Bonnelykke, K, Jaddoe, VWV, Tiemeier, H, Jarvelin, M-R, Evans, DM, Perry, JRB, Grant, SFA, Boomsma, DI, Freathy, RM, McCarthy, MI, Felix, JF, Middeldorp, CM, Mahajan, A, Horikoshi, M, Robertson, NR, Beaumont, RN, Bradfield, JP, Bustamante, M, Cousminer, DL, Day, FR, De Silva, NM, Guxens, M, Mook-Kanamori, DO, St Pourcain, B, Warrington, NM, Adair, LS, Ahlqvist, E, Ahluwalia, TS, Almgren, P, Ang, W, Atalay, M, Auvinen, J, Bartels, M, Beckmann, JS, Bilbao, JR, Bond, T, Borja, JB, Cavadino, A, Charoen, P, Chen, Z, Coin, L, Cooper, C, Curtin, JA, Custovic, A, Das, S, Davies, GE, Dedoussis, GV, Duijts, L, Eastwood, PR, Eliasen, AU, Elliott, P, Eriksson, JG, Estivill, X, Fadista, J, Fedko, IO, Frayling, TM, Gaillard, R, Gauderman, WJ, Geller, F, Gilliland, F, Gilsanz, V, Granell, R, Grarup, N, Groop, L, Hadley, D, Hakonarson, H, Hansen, T, Hartman, CA, Hattersley, AT, Hayes, MG, Hebebrand, J, Heinrich, J, Helgeland, O, Henders, AK, Henderson, J, Henriksen, TB, Hirschhorn, JN, Hivert, M-F, Hocher, B, Holloway, JW, Holt, P, Hottenga, J-J, Hypponen, E, Iniguez, C, Johansson, S, Jugessur, A, Kahonen, M, Kalkwarf, HJ, Kaprio, J, Karhunen, V, Kemp, JP, Kerkhof, M, Koppelman, GH, Korner, A, Kotecha, S, Kreiner-Moller, E, Kulohoma, B, Kumar, A, Kutalik, Z, Lahti, J, Lappe, JM, Larsson, H, Lehtimaki, T, Lewin, AM, Li, J, Lichtenstein, P, Lindgren, CM, Lindi, V, Linneberg, A, Liu, X, Liu, J, Lowe, WL, Lundstrom, S, Lyytikainen, L-P, Ma, RCW, Mace, A, Magi, R, Magnus, P, Mamun, AA, Mannikko, M, Martin, NG, Mbarek, H, McCarthy, NS, Medland, SE, Melbye, M, Melen, E, Mohlke, KL, Monnereau, C, Morgen, CS, Morris, AP, Murray, JC, Myhre, R, Najman, JM, Nivard, MG, Nohr, EA, Nolte, IM, Ntalla, I, O'Reilly, P, Oberfield, SE, Oken, E, Oldehinkel, AJ, Pahkala, K, Palviainen, T, Panoutsopoulou, K, Pedersen, O, Pennell, CE, Pershagen, G, Pitkanen, N, Plomin, R, Power, C, Prasad, RB, Prokopenko, I, Pulkkinen, L, Raikkonen, K, Raitakari, OT, Reynolds, RM, Richmond, RC, Rivadeneira, F, Rodriguez, A, Rose, RJ, Salem, R, Santa-Marina, L, Saw, S-M, Schnurr, TM, Scott, JG, Selzam, S, Shepherd, JA, Simpson, A, Skotte, L, Sleiman, PMA, Snieder, H, Sorensen, TIA, Standl, M, Steegers, EAP, Strachan, DP, Straker, L, Strandberg, T, Taylor, M, Teo, Y-Y, Thiering, E, Torrent, M, Tyrrell, J, Uitterlinden, AG, van Beijsterveldt, T, van der Most, PJ, van Duijn, CM, Viikari, J, Vilor-Tejedor, N, Vogelezang, S, Vonk, JM, Vrijkotte, TGM, Vuoksimaa, E, Wang, CA, Watkins, WJ, Wichmann, H-E, Willemsen, G, Williams, GM, Wilson, JF, Wray, NR, Xu, S, Xu, C-J, Yaghootkar, H, Yi, L, Zafarmand, MH, Zeggini, E, Zemel, BS, Hinney, A, Lakka, TA, Whitehouse, AJO, Sunyer, J, Widen, EE, Feenstra, B, Sebert, S, Jacobsson, B, Njolstad, PR, Stoltenberg, C, Smith, GD, Lawlor, DA, Paternoster, L, Timpson, NJ, Ong, KK, Bisgaard, H, Bonnelykke, K, Jaddoe, VWV, Tiemeier, H, Jarvelin, M-R, Evans, DM, Perry, JRB, Grant, SFA, Boomsma, DI, Freathy, RM, McCarthy, MI, and Felix, JF

Abstract

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.

Published
2019

4. Novel genetic loci associated with hippocampal volume

Author

Hibar, DP, Adams, HHH, Jahanshad, N, Chauhan, G, Stein, JL, Hofer, E, Renteria, ME, Bis, JC, Arias-Vasquez, A, Ikram, MK, Desrivieres, S, Vernooij, MW, Abramovic, L, Alhusaini, S, Amin, N, Andersson, M, Arfanakis, K, Aribisala, BS, Armstrong, NJ, Athanasiu, L, Axelsson, T, Beecham, AH, Beiser, A, Bernard, M, Blanton, SH, Bohlken, MM, Boks, MP, Bralten, J, Brickman, AM, Carmichael, O, Chakravarty, MM, Chen, Q, Ching, CRK, Chouraki, V, Cuellar-Partida, G, Crivello, F, Den Braber, A, Nhat, TD, Ehrlich, S, Giddaluru, S, Goldman, AL, Gottesman, RF, Grimm, O, Griswold, ME, Guadalupe, T, Gutman, BA, Hass, J, Haukvik, UK, Hoehn, D, Holmes, AJ, Hoogman, M, Janowitz, D, Jia, T, Jorgensen, KN, Karbalai, N, Kasperaviciute, D, Kim, S, Klein, M, Kraemer, B, Lee, PH, Liewald, DCM, Lopez, LM, Luciano, M, Macare, C, Marquand, AF, Matarin, M, Mather, KA, Mattheisen, M, McKay, DR, Milaneschi, Y, Maniega, SM, Nho, K, Nugent, AC, Nyquist, P, Loohuis, LMO, Oosterlaan, J, Papmeyer, M, Pirpamer, L, Puetz, B, Ramasamy, A, Richards, JS, Risacher, SL, Roiz-Santianez, R, Rommelse, N, Ropele, S, Rose, EJ, Royle, NA, Rundek, T, Saemann, PG, Saremi, A, Satizabal, CL, Schmaal, L, Schork, AJ, Shen, L, Shin, J, Shumskaya, E, Smith, AV, Sprooten, E, Strike, LT, Teumer, A, Tordesillas-Gutierrez, D, Toro, R, Trabzuni, D, Trompet, S, Vaidya, D, Van der Grond, J, Van der Lee, SJ, Van der Meer, D, Van Donkelaar, MMJ, Van Eijk, KR, Van Erp, TGM, Van Rooij, D, Walton, E, Westlye, LT, Whelan, CD, Windham, BG, Winkler, AM, Wittfeld, K, Woldehawariat, G, Wolf, C, Wolfers, T, Yanek, LR, Yang, J, Zijdenbos, A, Zwiers, MP, Agartz, I, Almasy, L, Ames, D, Amouyel, P, Andreassen, OA, Arepalli, S, Assareh, AA, Barral, S, Bastin, ME, Becker, DM, Becker, JT, Bennett, DA, Blangero, J, van Bokhoven, H, Boomsma, DI, Brodaty, H, Brouwer, RM, Brunner, HG, Buckner, RL, Buitelaar, JK, Bulayeva, KB, Cahn, W, Calhoun, VD, Cannon, DM, Cavalleri, GL, Cheng, C-Y, Cichon, S, Cookson, MR, Corvin, A, Crespo-Facorro, B, Curran, JE, Czisch, M, Dale, AM, Davies, GE, De Craen, AJM, De Geus, EJC, De Jager, PL, De Zubicaray, GI, Deary, IJ, Debette, S, DeCarli, C, Delanty, N, Depondt, C, DeStefano, A, Dillman, A, Djurovic, S, Donohoe, G, Drevets, WC, Duggirala, R, Dyer, TD, Enzinger, C, Erk, S, Espeseth, T, Fedko, IO, Fernandez, G, Ferrucci, L, Fisher, SE, Fleischman, DA, Ford, I, Fornage, M, Foroud, TM, Fox, PT, Francks, C, Fukunaga, M, Gibbs, JR, Glahn, DC, Gollub, RL, Goring, HHH, Green, RC, Gruber, O, Gudnason, V, Guelfi, S, Haberg, AK, Hansell, NK, Hardy, J, Hartman, CA, Hashimoto, R, Hegenscheid, K, Heinz, A, Le Hellard, S, Hernandez, DG, Heslenfeld, DJ, Ho, B-C, Hoekstra, PJ, Hoffmann, W, Hofman, A, Holsboer, F, Homuth, G, Hosten, N, Hottenga, J-J, Huentelman, M, Pol, HEH, Ikeda, M, Jack, CR, Jenkinson, M, Johnson, R, Joensson, EG, Jukema, JW, Kahn, RS, Kanai, R, Kloszewska, I, Knopman, DS, Kochunov, P, Kwok, JB, Lawrie, SM, Lemaitre, H, Liu, X, Longo, DL, Lopez, OL, Lovestone, S, Martinez, O, Martinot, J-L, Mattay, VS, McDonald, C, McIntosh, AM, McMahon, FJ, McMahon, KL, Mecocci, P, Melle, I, Meyer-Lindenberg, A, Mohnke, S, Montgomery, GW, Morris, DW, Mosley, TH, Muhleisen, TW, Mueller-Myhsok, B, Nalls, MA, Nauck, M, Nichols, TE, Niessen, WJ, Nothen, MM, Nyberg, L, Ohi, K, Olvera, RL, Ophoff, RA, Pandolfo, M, Paus, T, Pausova, Z, Penninx, BWJH, Pike, GB, Potkin, SG, Psaty, BM, Reppermund, S, Rietschel, M, Roffman, JL, Romanczuk-Seiferth, N, Rotter, JI, Ryten, M, Sacco, RL, Sachdev, PS, Saykin, AJ, Schmidt, R, Schmidt, H, Schofield, PR, Sigursson, S, Simmons, A, Singleton, A, Sisodiya, SM, Smith, C, Smoller, JW, Soininen, H, Steen, VM, Stott, DJ, Sussmann, JE, Thalamuthu, A, Toga, AW, Traynor, BJ, Troncoso, J, Tsolaki, M, Tzourio, C, Uitterlinden, AG, Hernandez, MCV, Van der Brug, M, van der Lugt, A, van der Wee, NJA, Van Haren, NEM, van't Ent, D, Van Tol, M-J, Vardarajan, BN, Vellas, B, Veltman, DJ, Voelzke, H, Walter, H, Wardlaw, JM, Wassink, TH, Weale, ME, Weinberger, DR, Weiner, MW, Wen, W, Westman, E, White, T, Wong, TY, Wright, CB, Zielke, RH, Zonderman, AB, Martin, NG, Van Duijn, CM, Wright, MJ, Longstreth, WT, Schumann, G, Grabe, HJ, Franke, B, Launer, LJ, Medland, SE, Seshadri, S, Thompson, PM, Ikram, MA, Hibar, DP, Adams, HHH, Jahanshad, N, Chauhan, G, Stein, JL, Hofer, E, Renteria, ME, Bis, JC, Arias-Vasquez, A, Ikram, MK, Desrivieres, S, Vernooij, MW, Abramovic, L, Alhusaini, S, Amin, N, Andersson, M, Arfanakis, K, Aribisala, BS, Armstrong, NJ, Athanasiu, L, Axelsson, T, Beecham, AH, Beiser, A, Bernard, M, Blanton, SH, Bohlken, MM, Boks, MP, Bralten, J, Brickman, AM, Carmichael, O, Chakravarty, MM, Chen, Q, Ching, CRK, Chouraki, V, Cuellar-Partida, G, Crivello, F, Den Braber, A, Nhat, TD, Ehrlich, S, Giddaluru, S, Goldman, AL, Gottesman, RF, Grimm, O, Griswold, ME, Guadalupe, T, Gutman, BA, Hass, J, Haukvik, UK, Hoehn, D, Holmes, AJ, Hoogman, M, Janowitz, D, Jia, T, Jorgensen, KN, Karbalai, N, Kasperaviciute, D, Kim, S, Klein, M, Kraemer, B, Lee, PH, Liewald, DCM, Lopez, LM, Luciano, M, Macare, C, Marquand, AF, Matarin, M, Mather, KA, Mattheisen, M, McKay, DR, Milaneschi, Y, Maniega, SM, Nho, K, Nugent, AC, Nyquist, P, Loohuis, LMO, Oosterlaan, J, Papmeyer, M, Pirpamer, L, Puetz, B, Ramasamy, A, Richards, JS, Risacher, SL, Roiz-Santianez, R, Rommelse, N, Ropele, S, Rose, EJ, Royle, NA, Rundek, T, Saemann, PG, Saremi, A, Satizabal, CL, Schmaal, L, Schork, AJ, Shen, L, Shin, J, Shumskaya, E, Smith, AV, Sprooten, E, Strike, LT, Teumer, A, Tordesillas-Gutierrez, D, Toro, R, Trabzuni, D, Trompet, S, Vaidya, D, Van der Grond, J, Van der Lee, SJ, Van der Meer, D, Van Donkelaar, MMJ, Van Eijk, KR, Van Erp, TGM, Van Rooij, D, Walton, E, Westlye, LT, Whelan, CD, Windham, BG, Winkler, AM, Wittfeld, K, Woldehawariat, G, Wolf, C, Wolfers, T, Yanek, LR, Yang, J, Zijdenbos, A, Zwiers, MP, Agartz, I, Almasy, L, Ames, D, Amouyel, P, Andreassen, OA, Arepalli, S, Assareh, AA, Barral, S, Bastin, ME, Becker, DM, Becker, JT, Bennett, DA, Blangero, J, van Bokhoven, H, Boomsma, DI, Brodaty, H, Brouwer, RM, Brunner, HG, Buckner, RL, Buitelaar, JK, Bulayeva, KB, Cahn, W, Calhoun, VD, Cannon, DM, Cavalleri, GL, Cheng, C-Y, Cichon, S, Cookson, MR, Corvin, A, Crespo-Facorro, B, Curran, JE, Czisch, M, Dale, AM, Davies, GE, De Craen, AJM, De Geus, EJC, De Jager, PL, De Zubicaray, GI, Deary, IJ, Debette, S, DeCarli, C, Delanty, N, Depondt, C, DeStefano, A, Dillman, A, Djurovic, S, Donohoe, G, Drevets, WC, Duggirala, R, Dyer, TD, Enzinger, C, Erk, S, Espeseth, T, Fedko, IO, Fernandez, G, Ferrucci, L, Fisher, SE, Fleischman, DA, Ford, I, Fornage, M, Foroud, TM, Fox, PT, Francks, C, Fukunaga, M, Gibbs, JR, Glahn, DC, Gollub, RL, Goring, HHH, Green, RC, Gruber, O, Gudnason, V, Guelfi, S, Haberg, AK, Hansell, NK, Hardy, J, Hartman, CA, Hashimoto, R, Hegenscheid, K, Heinz, A, Le Hellard, S, Hernandez, DG, Heslenfeld, DJ, Ho, B-C, Hoekstra, PJ, Hoffmann, W, Hofman, A, Holsboer, F, Homuth, G, Hosten, N, Hottenga, J-J, Huentelman, M, Pol, HEH, Ikeda, M, Jack, CR, Jenkinson, M, Johnson, R, Joensson, EG, Jukema, JW, Kahn, RS, Kanai, R, Kloszewska, I, Knopman, DS, Kochunov, P, Kwok, JB, Lawrie, SM, Lemaitre, H, Liu, X, Longo, DL, Lopez, OL, Lovestone, S, Martinez, O, Martinot, J-L, Mattay, VS, McDonald, C, McIntosh, AM, McMahon, FJ, McMahon, KL, Mecocci, P, Melle, I, Meyer-Lindenberg, A, Mohnke, S, Montgomery, GW, Morris, DW, Mosley, TH, Muhleisen, TW, Mueller-Myhsok, B, Nalls, MA, Nauck, M, Nichols, TE, Niessen, WJ, Nothen, MM, Nyberg, L, Ohi, K, Olvera, RL, Ophoff, RA, Pandolfo, M, Paus, T, Pausova, Z, Penninx, BWJH, Pike, GB, Potkin, SG, Psaty, BM, Reppermund, S, Rietschel, M, Roffman, JL, Romanczuk-Seiferth, N, Rotter, JI, Ryten, M, Sacco, RL, Sachdev, PS, Saykin, AJ, Schmidt, R, Schmidt, H, Schofield, PR, Sigursson, S, Simmons, A, Singleton, A, Sisodiya, SM, Smith, C, Smoller, JW, Soininen, H, Steen, VM, Stott, DJ, Sussmann, JE, Thalamuthu, A, Toga, AW, Traynor, BJ, Troncoso, J, Tsolaki, M, Tzourio, C, Uitterlinden, AG, Hernandez, MCV, Van der Brug, M, van der Lugt, A, van der Wee, NJA, Van Haren, NEM, van't Ent, D, Van Tol, M-J, Vardarajan, BN, Vellas, B, Veltman, DJ, Voelzke, H, Walter, H, Wardlaw, JM, Wassink, TH, Weale, ME, Weinberger, DR, Weiner, MW, Wen, W, Westman, E, White, T, Wong, TY, Wright, CB, Zielke, RH, Zonderman, AB, Martin, NG, Van Duijn, CM, Wright, MJ, Longstreth, WT, Schumann, G, Grabe, HJ, Franke, B, Launer, LJ, Medland, SE, Seshadri, S, Thompson, PM, and Ikram, MA

Abstract

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.

Published
2017

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

Author

Middeldorp CM, Hammerschlag AR, Ouwens KG, Groen-Blokhuis MM, St Pourcain B, Greven CU, Pappa I, Tiesler CM, Ang W, Nolte IM, Vilor-Tejedor N, Bacelis J, Ebejer JL, Zhao H, Davies GE, Ehli EA, Evans DM, Fedko IO, Guxens M, Hottenga JJ, Hudziak JJ, Jugessur A, Kemp JP, Krapohl E, Martin NG, Murcia M, Myhre R, Ormel J, Ring SM, Standl M, Stergiakouli E, Stoltenberg C, Thiering E, Timpson NJ, Trzaskowski M, van der Most PJ, Wang C, EArly Genetics and Lifecourse Epidemiology (EAGLE) Consortium P, Nyholt DR, Medland SE, Neale B, Jacobsson B, Sunyer J, Hartman CA, Whitehouse AJ, Pennell CE, Heinrich J, Plomin R, Davey Smith G, Tiemeier H, Posthuma D, and Boomsma DI

Abstract

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 (

Published
2016

6. Genetic and environmental influences interact with age and sex in shaping the human methylome

Author

Dongen, J, Nivard, MG, Willemsen, G, Hottenga, JJ, Helmer, Q, Dolan, CV, Ehli, EA, Davies, GE, van Iterson, M, Breeze, C E, Beck, S, Suchiman, H E, Jansen, R, van Meurs, Joyce, Heijmans, BT, Slagboom, PE (Eline), Boomsma, DI, Dongen, J, Nivard, MG, Willemsen, G, Hottenga, JJ, Helmer, Q, Dolan, CV, Ehli, EA, Davies, GE, van Iterson, M, Breeze, C E, Beck, S, Suchiman, H E, Jansen, R, van Meurs, Joyce, Heijmans, BT, Slagboom, PE (Eline), and Boomsma, DI

Published
2016

7. Estimation of Genetic Relationships Between Individuals Across Cohorts and Platforms: Application to Childhood Height

Author

Fedko, IO, Hottenga, JJ, Medina Gomez, Maria, Pappa, Irene, Beijsterveld, CEM, Ehli, EA, Davies, GE, Rivadeneira, Fernando, Tiemeier, Henning, Swertz, MA, Middeldorp, CM, Bartels, M, Boomsma, DI, Fedko, IO, Hottenga, JJ, Medina Gomez, Maria, Pappa, Irene, Beijsterveld, CEM, Ehli, EA, Davies, GE, Rivadeneira, Fernando, Tiemeier, Henning, Swertz, MA, Middeldorp, CM, Bartels, M, and Boomsma, DI

Abstract

Combining genotype data across cohorts increases power to estimate the heritability due to common single nucleotide polymorphisms (SNPs), based on analyzing a Genetic Relationship Matrix (GRM). However, the combination of SNP data across multiple cohorts may lead to stratification, when for example, different genotyping platforms are used. In the current study, we address issues of combining SNP data from different cohorts, the Netherlands Twin Register (NTR) and the Generation R (GENR) study. Both cohorts include children of Northern European Dutch background (N = 3102 + 2826, respectively) who were genotyped on different platforms. We explore imputation and phasing as a tool and compare three GRM-building strategies, when data from two cohorts are (1) just combined, (2) pre-combined and cross-platform imputed and (3) cross-platform imputed and post-combined. We test these three strategies with data on childhood height for unrelated individuals (N = 3124, average age 6.7 years) to explore their effect on SNP-heritability estimates and compare results to those obtained from the independent studies. All combination strategies result in SNP-heritability estimates with a standard error smaller than those of the independent studies. We did not observe significant difference in estimates of SNP-heritability based on various cross-platform imputed GRMs. SNP-heritability of childhood height was on average estimated as 0.50 (SE = 0.10). Introducing cohort as a covariate resulted in a parts per thousand 2 % drop. Principal components (PCs) adjustment resulted in SNP-heritability estimates of about 0.39 (SE = 0.11). Strikingly, we did not find significant difference between cross-platform imputed and combined GRMs. All estimates were significant regardless the use of PCs adjustment. Based on these analyses we conclude that imputation with a reference set helps to increase power to estimate SNP-heritability by combining cohorts of the same ethnicity genotyped on different plat

Published
2015

8. Abstract PD2-5: Low carbohydrate dietary intervention improves insulin, hormonal levels and inflammatory markers in early stage, postmenopausal breast cancer survivors

Author

Krie, AK, primary, Bohlen, KN, additional, Hu, Y, additional, Ageton, C, additional, Demuth, H, additional, Norfolk, D, additional, Kittelsrud, J, additional, Thomes, R, additional, Fahrendorf, A, additional, Muth, J, additional, Rojas-Espaillat, LA, additional, and Davies, GE, additional

Published
2013
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9. Abstract P4-09-04: Weight loss and lipid-lowering efficacy of a low carbohydrate, calorie restricted diet intervention on postmenopausal breast cancer patients

Author

Krie, AK, primary, Bohlen, KN, additional, Demuth, H, additional, Ageton, C, additional, Norfolk, D, additional, Kittelsrud, J, additional, Thomes, R, additional, Fahrendorf, A, additional, Muth, J, additional, Rojas-Espaillat, LA, additional, Davies, GE, additional, and Hu, Y, additional

Published
2013
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16. Berberine inhibits adipogenesis in high-fat diet-induced obesity mice.

Author

Hu Y and Davies GE

Abstract

Our previous studies illustrated that berberine inhibited adipogenesis in murine-derived 3T3-L1 preadipocytes and human white preadipocytes. In this study, the effects of berberine on the adipogenesis of high-fat diet-induced obesity (FD) or normal diet (ND) mice and possible transcriptional impact are investigated. The results demonstrated that in FD mice, berberine reduced mouse weight gain and food intake and serum glucose, triglyceride, and total cholesterol levels accompanied with a down-regulation of PPARgamma expression and an up-regulation of GATA-3 expression. Berberine had no adverse effects on ND mice. These encouraging findings suggest that berberine has excellent pharmacological potential to prevent obesity. [ABSTRACT FROM AUTHOR]

Published
2010
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18. Use of a Diimidoester Cross-Linking Reagent to Examine the Submit Structure of Rabbit Muscle Pyruvate Kinase

Author

Davies Ge and Kaplan Jg

Subjects
Chemical Phenomena, Macromolecular Substances, Protein subunit, Pyruvate Kinase, Imides, Oligomer, chemistry.chemical_compound, Tetramer, Nitriles, Animals, Sodium dodecyl sulfate, Polyacrylamide gel electrophoresis, Carbon Isotopes, Muscles, Pimelic Acids, Sodium Dodecyl Sulfate, General Medicine, Electrophoresis, Disc, Chemistry, Dimethyl pimelimidate, chemistry, Biochemistry, Isotope Labeling, Reagent, Rabbits, Pyruvate kinase
Abstract

Rabbit muscle pyruvate kinase, a tetramer of highly similar or identical subunits, is known to dissociate in urea via a dimeric intermediate. To provide additional evidence regarding the structure of the native oligomer, we have treated pyruvate kinase with dimethyl pimelimidate and examined the yields of cross-linked species resolved by polyacrylamide gel electrophoresis in the presence of sodium dodecyl sulfate. Of four products resolved, predominating species are dimers and tetramers of the pyruvate kinase subunit, while monomers and trimers are present in lesser amounts. These relative yields are consistent with a dimeric structure of the tetramer.In a typical cross-linking reaction, about 86 of the 148 primary amino groups in the pyruvate kinase tetramer are amidinated. Of 53 moles of cross-linking reagent incorporated per mole of tetramer, 38% have reacted monofunctionally, with hydrolysis of the second imidoester group, and 62% have reacted bifunctionally to form intra- and intersubunit cross-links.

Published
1972

19. Prospects for Animal Tests in Experimental Sensitization to Drugs

Author

Davies Ge

Subjects
03 medical and health sciences, 0302 clinical medicine, medicine.anatomical_structure, business.industry, medicine, 030212 general & internal medicine, 030223 otorhinolaryngology, business, Data science, Sensitization
Published
1962

20. Platelets contain proteins immunologically related to red cell spectrin and protein 4.1

Author

Davies, GE and Cohen, CM

Abstract

Human platelets were tested for the presence of proteins immunologically cross-reactive with red cell spectrin and protein 4.1. As assessed by indirect immunofluorescence microscopy, platelets were specifically reactive with affinity-purified rabbit antisera against red cell spectrin and protein 4.1. The immunoreactive platelet constituents were further analyzed by sodium dodecyl sulfate- polyacrylamide gel electrophoresis, followed by electrophoretic transfer to nitrocellulose paper and immunoperoxidase staining. We found that whole platelets, membranes, and cytoskeletal preparations isolated by Triton X-100 extraction contain small amounts of proteins reacting with anti-spectrin or anti-protein 4.1 antiserum. The immunoreactive spectrin-like platelet protein has an apparent molecular weight of 240,000 and comigrates with the alpha-subunit of red cell spectrin. The major immunoreactive protein 4.1-like constituent has an apparent molecular weight of 78,000, which is slightly less than that of red cell protein 4.1. We conclude that platelets contain a spectrin- like protein which, by analogy with red cell spectrin, may have a role in membrane-cytoskeletal attachment. The properties and function of the platelet protein 4.1-like constituent are not yet known.

Published
1985
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21. Platelet protein organization: analysis by treatment with membrane- permeable cross-linking reagents

Author

Davies, GE and Palek, J

Abstract

We have examined platelet protein organization by treatment of intact resting or thrombin-activated platelets with two cross-linking reagents, diamide or dithiobis(succinimidyl propionate) (DTSP). Cross- linked complexes were separated by polyacrylamide gel electrophoresis in the absence of reducing agent and their composition determined after reductive cleavage and analysis in a second-dimensional gel. The most prominent cross-linked species produced by diamide treatment of of resting platelets are (A) cytoskeletal protein homopolymers, such as myosin heavy chain dimer and actin oligomers, and (B) high molecular weight material consisting of homo- or heteropolymers of cytoskeletal proteins and 230,000, 170,000, 100,000, 55,000, and 52,000 dalton proteins. DTSP treatment forms similar complexes and also cross-links membrane glycoproteins IIb and III into high molecular weight material. Thrombin activation of platelets before treatment with diamide or DTSP results in increased cross-linking of myosin and increased incorporation of several proteins, particularly myosin and glycoproteins IIb and III, into high molecular weight material. The results provide evidence for reorganization of cytoskeletal and membrane proteins during platelet function.

Published
1982
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29. Books

Author

McVeigh, Brita, Davies, Geoff, and Garrett, Simon

Published
2000

36. COMT Val158Met genotype as a risk factor for problem behaviors in youth.

Author

Albaugh MD, Harder VS, Althoff RR, Rettew DC, Ehli EA, Lengyel-Nelson T, Davies GE, Ayer L, Sulman J, Stanger C, Hudziak JJ, Albaugh, Matthew D, Harder, Valerie S, Althoff, Robert R, Rettew, David C, Ehli, Erik A, Lengyel-Nelson, Timea, Davies, Gareth E, Ayer, Lynsay, and Sulman, Julie

Abstract

Objective: To test the association between the catechol-O-methyltransferase (COMT) Val158Met polymorphism and both aggressive behavior and attention problems in youth. We hypothesized that youth carrying a Met allele would have greater average aggressive behavior scores, and that youth exhibiting Val-homozygosity would have greater average attention problems scores.Method: Complete data on maternally rated Child Behavior Checklist (CBCL) measures of aggressive behavior (AGG) and attention problems (AP), COMT polymorphism data, demographics, and maternal parenting quality were available for 149 youth (6 to 18 years old). Multivariable linear regression models were used to test the degree to which youth COMT Val158Met genotype was associated with AGG and AP while statistically controlling for age, gender, parental socioeconomic status (SES), and maternal parenting quality from the Alabama Parenting Questionnaire.Results: Mothers of Met-carriers rated their children higher on average AGG scores when compared with mothers of Val-homozygotes (p = .016). Further analyses revealed that this association was even more robust for maternal ratings of direct aggression (p = .007). The hypothesized association between Val-homozygosity and higher average AP scores relative to average AP scores of Met-carriers did not quite reach statistical significance (p = .062).Conclusions: After controlling for demographics, SES, and maternal parenting quality as confounders, there remains a strong association between youth carrying a Met allele and higher average AGG scores relative to Val-homozygotes. [ABSTRACT FROM AUTHOR]

Published
2010
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37. Inhibitory effect and transcriptional impact of berberine and evodiamine on human white preadipocyte differentiation.

Author

Hu Y, Fahmy H, Zjawiony JK, and Davies GE

Abstract

It has been reported that the botanical alkaloids, berberine and evodiamine inhibit mouse preadipocyte 3T3-L1 differentiation. The aim of this study was to investigate the effect and transcriptional impact of berberine and evodiamine individually and in combination on human white preadipocyte (HWP) differentiation. We have shown that treatment with 8 microM berberine or 4 microM evodiamine resulted in a major inhibition of HWP differentiation accompanied by up-regulation of both GATA binding protein 2 and 3 (GATA-2 and GATA-3) mRNA and protein expression, suggesting that both compounds may have excellent potential as agents to prevent obesity. (c) 2009 Elsevier B.V. All rights reserved. [ABSTRACT FROM AUTHOR]

Published
2010
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38. A Lateral-Flow Device for the Rapid Detection of Scedosporium Species.

Author

Davies GE and Thornton CR

Abstract

Scedosporium species are human pathogenic fungi, responsible for chronic, localised, and life-threatening disseminated infections in both immunocompetent and immunocompromised individuals. The diagnosis of Scedosporium infections currently relies on non-specific CT, lengthy and insensitive culture from invasive biopsy, and the time-consuming histopathology of tissue samples. At present, there are no rapid antigen tests that detect Scedosporium -specific biomarkers. Here, we report the development of a rapid (30 min) and sensitive (pmol/L sensitivity) lateral-flow device (LFD) test, incorporating a Scedosporium -specific IgG1 monoclonal antibody (mAb), HG12, which binds to extracellular polysaccharide (EPS) antigens between ~15 kDa and 250 kDa secreted during the hyphal growth of the pathogens. The test is compatible with human serum and allows for the detection of the Scedosporium species most frequently reported as agents of human disease ( Scedosporium apiospermum , Scedosporium aurantiacum , and Scedosporium boydii ), with limits of detection (LODs) of the EPS biomarkers in human serum of ~0.81 ng/mL ( S. apiospermum ), ~0.94 ng/mL ( S. aurantiacum ), and ~1.95 ng/mL ( S. boydii ). The Scedosporium -specific LFD ( Sced LFD) test therefore provides a potential novel opportunity for the detection of infections caused by different Scedosporium species.

Published
2024
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39. Targeting CD20-expressing malignant melanoma cells augments BRAF inhibitor killing.

Author

Mukhtar AB, Morgan HJ, Gibbs A, Davies GE, Lovatt C, and Patel GK

Subjects
Humans, Proto-Oncogene Proteins B-raf genetics, Neoplasm Recurrence, Local, Protein Kinase Inhibitors pharmacology, Mutation, Cell Line, Tumor, Melanoma pathology
Abstract

Background: Mutant BRAF targeted therapies remain a standard of care for the treatment of metastatic malignant melanoma (MM); however, high initial response rates are tempered by the persistence of residual MM cells that eventually lead to disease recurrence and mortality. As MM recurrence during targeted therapy can present with the simultaneous occurrence of multiple tumour nodules at the original body sites, we hypothesized the presence of an intrinsically resistant MM cell subpopulation., Objectives: To identify an MM cell subpopulation that is intrinsically resistant to targeted therapy and possibly responsible for MM recurrence., Methods: Using melanoma cell lines, we defined culture conditions for the reproducible three-dimensional growth of melanospheres to investigate putative cancer stem cell populations. We undertook RNA sequencing and bioinformatic analysis to characterize cell populations between adherent and nonadherent culture, and cells expressing or not expressing CD20. Furthermore, we defined an in vitro assay to evaluate the killing of melanoma cancer stem cells as a therapeutic test using combination therapies targeting driver mutation and CD20., Results: We described the culture conditions that promote MM cells to form melanospheres with a reproducible colony-forming efficiency rate of 0.3-1.3%. RNA sequencing of melanosphere vs. conventional MM cell cultures (n = 6), irrespective of the BRAF mutation status, showed that melanosphere formation was associated with growth and differentiation transcriptional signatures resembling MM tumours. Importantly, melanosphere formation also led to the emergence of a CD20+ MM cell subpopulation, similar to that observed in primary human MM tumours. CD20+ MM cells were resistant to BRAF inhibitor therapy and, consistent with this finding, demonstrated a Forkhead box protein M1 transcriptomic profile (n = 6). Combining BRAF inhibitor and anti-CD20 antibody treatment led to the additional killing of previously resistant CD20+  BRAF mutant MM cells., Conclusions: In patients with MM that harbour a CD20+ subpopulation, combined therapy with BRAF inhibitor and anti-CD20 antibody could potentially kill residual MM cells and prevent disease recurrence., Competing Interests: Conflicts of interest The authors declare no conflicts of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of British Association of Dermatologists. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Published
2024
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40. Development of a monoclonal antibody and a lateral-flow device for the rapid detection of a Mucorales-specific biomarker.

Author

Thornton CR, Davies GE, and Dougherty L

Subjects
Humans, Antibodies, Monoclonal, Aspergillus, Biomarkers, Mucorales, Fusarium
Abstract

Mucoromycosis is a highly aggressive angio-invasive disease of humans caused by fungi in the zygomycete order, Mucorales. While Rhizopus arrhizus is the principal agent of mucoromycosis, other Mucorales fungi including Apophysomyces , Cunninghamella , Lichtheimia , Mucor , Rhizomucor and Syncephalastrum are able to cause life-threatening rhino-orbital-cerebral, pulmonary, gastro-intestinal and necrotising cutaneous infections in humans. Diagnosis of the disease currently relies on non-specific CT, lengthy and insensitive culture from invasive biopsy, and time-consuming histopathology of tissue samples. At present, there are no rapid antigen tests that detect Mucorales-specific biomarkers of infection, and which allow point-of-care diagnosis of mucoromycosis. Here, we report the development of an IgG2b monoclonal antibody (mAb), TG11, which binds to extracellular polysaccharide (EPS) antigens of between 20 kDa and 250 kDa secreted during hyphal growth of Mucorales fungi. The mAb is Mucorales-specific and does not cross-react with other yeasts and molds of clinical importance including Aspergillus , Candida , Cryptococcus , Fusarium , Lomentospora and Scedosporium species. Using the mAb, we have developed a Competitive lateral-flow device that allows rapid (30 min) detection of the EPS biomarker in human serum and bronchoalveolar lavage (BAL), with a limit of detection (LOD) in human serum of ~100 ng/mL serum (~224.7 pmol/L serum). The LFD therefore provides a potential novel opportunity for detection of mucoromycosis caused by different Mucorales species., Competing Interests: CRT is a Director of ISCA Diagnostics Ltd. GED is an employee of ISCA Diagnostics Ltd. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Thornton, Davies and Dougherty.)

Published
2023
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41. A spatial human thymus cell atlas mapped to a continuous tissue axis.

Author

Yayon N, Kedlian VR, Boehme L, Suo C, Wachter B, Beuschel RT, Amsalem O, Polanski K, Koplev S, Tuck E, Dann E, Van Hulle J, Perera S, Putteman T, Predeus AV, Dabrowska M, Richardson L, Tudor C, Kreins AY, Engelbert J, Stephenson E, Kleshchevnikov V, De Rita F, Crossland D, Bosticardo M, Pala F, Prigmore E, Chipampe NJ, Prete M, Fei L, To K, Barker RA, He X, Van Nieuwerburgh F, Bayraktar O, Patel M, Davies GE, Haniffa MA, Uhlmann V, Notarangelo LD, Germain RN, Radtke AJ, Marioni JC, Taghon T, and Teichmann SA

Abstract

T cells develop from circulating precursors, which enter the thymus and migrate throughout specialised sub-compartments to support maturation and selection. This process starts already in early fetal development and is highly active until the involution of the thymus in adolescence. To map the micro-anatomical underpinnings of this process in pre- vs. post-natal states, we undertook a spatially resolved analysis and established a new quantitative morphological framework for the thymus, the Cortico-Medullary Axis. Using this axis in conjunction with the curation of a multimodal single-cell, spatial transcriptomics and high-resolution multiplex imaging atlas, we show that canonical thymocyte trajectories and thymic epithelial cells are highly organised and fully established by post-conception week 12, pinpoint TEC progenitor states, find that TEC subsets and peripheral tissue genes are associated with Hassall's Corpuscles and uncover divergence in the pace and drivers of medullary entry between CD4 vs. CD8 T cell lineages. These findings are complemented with a holistic toolkit for spatial analysis and annotation, providing a basis for a detailed understanding of T lymphocyte development., Competing Interests: Conflict of interest J.C.M has been an employee of Genentech, Inc. since September 2022. In the past three years, S.A.T. has consulted for or been a member of scientific advisory boards at Qiagen, Sanofi, GlaxoSmithKline, and ForeSite Labs. She is a consultant and equity holder for TransitionBio and EnsoCell. The remaining authors declare no competing interests.

Published
2023
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42. Clinical utility of pharmacogenetics in a psychiatric and primary care population.

Author

Bohlen KN, Kittelsrud JM, Nelson ME, Weisser LK, Matthiesen NJ, Fieldsend JA, Buschette NB, Cooper LL, Davies GE, and Ehli EA

Subjects
Humans, Primary Health Care, Pharmacogenetics, Quality of Life
Abstract

This study evaluated the timing, use, and clinical outcomes of the GeneFolio® Pharmacogenomic Panel in a healthcare setting with patients managed by primary care providers or by psychiatrists. Participants were randomized to receive a pharmacogenetics report at four weeks or 12 weeks. After DNA collection and genetic analysis, pharmacists produced a recommendation report which was given to providers at the randomization week. The four-week group decreased depression severity (PHQ-9 and BDI) faster than the 12-week group (p = 0.0196), and psychiatrists' patients decreased their depression severity faster than primary care patients (PHQ-9 p = 0.0005, BDI p = 0.0218). Mean mental quality of life increased over time (p < 0.0001), but it increased slower for patients taking drugs in the Significant drug-drug-gene interaction category (p = 0.0012). Mental quality of life, depression severity, and clinical outcomes were improved by GeneFolio® pharmacogenomic testing regardless of provider type, with earlier testing improving outcomes sooner., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Published
2023
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43. CD200 ectodomain shedding into the tumor microenvironment leads to NK cell dysfunction and apoptosis.

Author

Morgan HJ, Rees E, Lanfredini S, Powell KA, Gore J, Gibbs A, Lovatt C, Davies GE, Olivero C, Shorning BY, Tornillo G, Tonks A, Darley R, Wang EC, and Patel GK

Subjects
Humans, Tumor Microenvironment, PPAR gamma, Killer Cells, Natural, fas Receptor, Apoptosis, Carcinoma, Squamous Cell genetics, Carcinoma, Basal Cell
Abstract

The basis of immune evasion, a hallmark of cancer, can differ even when cancers arise from one cell type such as in the human skin keratinocyte carcinomas: basal and squamous cell carcinoma. Here we showed that the basal cell carcinoma tumor-initiating cell surface protein CD200, through ectodomain shedding, was responsible for the near absence of NK cells within the basal cell carcinoma tumor microenvironment. In situ, CD200 underwent ectodomain shedding by metalloproteinases MMP3 and MMP11, which released biologically active soluble CD200 into the basal cell carcinoma microenvironment. CD200 bound its cognate receptor on NK cells to suppress MAPK pathway signaling that in turn blocked indirect (IFN-γ release) and direct cell killing. In addition, reduced ERK phosphorylation relinquished negative regulation of PPARγ-regulated gene transcription and led to membrane accumulation of the Fas/FADD death receptor and its ligand, FasL, which resulted in activation-induced apoptosis. Blocking CD200 inhibition of MAPK or PPARγ signaling restored NK cell survival and tumor cell killing, with relevance to many cancer types. Our results thus uncover a paradigm for CD200 as a potentially novel and targetable NK cell-specific immune checkpoint, which is responsible for NK cell-associated poor outcomes in many cancers.

Published
2022
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44. A genome-wide association study of total child psychiatric problems scores.

Author

Neumann A, Nolte IM, Pappa I, Ahluwalia TS, Pettersson E, Rodriguez A, Whitehouse A, van Beijsterveldt CEM, Benyamin B, Hammerschlag AR, Helmer Q, Karhunen V, Krapohl E, Lu Y, van der Most PJ, Palviainen T, St Pourcain B, Seppälä I, Suarez A, Vilor-Tejedor N, Tiesler CMT, Wang C, Wills A, Zhou A, Alemany S, Bisgaard H, Bønnelykke K, Davies GE, Hakulinen C, Henders AK, Hyppönen E, Stokholm J, Bartels M, Hottenga JJ, Heinrich J, Hewitt J, Keltikangas-Järvinen L, Korhonen T, Kaprio J, Lahti J, Lahti-Pulkkinen M, Lehtimäki T, Middeldorp CM, Najman JM, Pennell C, Power C, Oldehinkel AJ, Plomin R, Räikkönen K, Raitakari OT, Rimfeld K, Sass L, Snieder H, Standl M, Sunyer J, Williams GM, Bakermans-Kranenburg MJ, Boomsma DI, van IJzendoorn MH, Hartman CA, and Tiemeier H

Subjects
Genetic Predisposition to Disease, Genome-Wide Association Study methods, Humans, Polymorphism, Single Nucleotide, Attention Deficit Disorder with Hyperactivity genetics, Attention Deficit Disorder with Hyperactivity psychology, Bipolar Disorder genetics
Abstract

Substantial genetic correlations have been reported across psychiatric disorders and numerous cross-disorder genetic variants have been detected. To identify the genetic variants underlying general psychopathology in childhood, we performed a genome-wide association study using a total psychiatric problem score. We analyzed 6,844,199 common SNPs in 38,418 school-aged children from 20 population-based cohorts participating in the EAGLE consortium. The SNP heritability of total psychiatric problems was 5.4% (SE = 0.01) and two loci reached genome-wide significance: rs10767094 and rs202005905. We also observed an association of SBF2, a gene associated with neuroticism in previous GWAS, with total psychiatric problems. The genetic effects underlying the total score were shared with common psychiatric disorders only (attention-deficit/hyperactivity disorder, anxiety, depression, insomnia) (rG > 0.49), but not with autism or the less common adult disorders (schizophrenia, bipolar disorder, or eating disorders) (rG < 0.01). Importantly, the total psychiatric problem score also showed at least a moderate genetic correlation with intelligence, educational attainment, wellbeing, smoking, and body fat (rG > 0.29). The results suggest that many common genetic variants are associated with childhood psychiatric symptoms and related phenotypes in general instead of with specific symptoms. Further research is needed to establish causality and pleiotropic mechanisms between related traits., Competing Interests: The authors have declared that no competing interests exist.

Published
2022
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45. Development of a Monoclonal Antibody and a Serodiagnostic Lateral-Flow Device Specific to Rhizopus arrhizus (Syn. R. oryzae ), the Principal Global Agent of Mucormycosis in Humans.

Author

Davies GE and Thornton CR

Abstract

Mucormycosis is a highly aggressive angio-invasive disease of humans caused by fungi in the zygomycete order, Mucorales. Though a number of different species can cause mucormycosis, the principal agent of the disease worldwide is Rhizopus arrhizus , which accounts for the majority of rhino-orbital-cerebral, pulmonary, and disseminated infections in immunocompromised individuals. It is also the main cause of life-threatening infections in patients with poorly controlled diabetes mellitus, and in corticosteroid-treated patients with SARS-CoV-2 infection, where it causes the newly described disease, COVID-19-associated mucormycosis (CAM). Diagnosis currently relies on non-specific CT, a lengthy and insensitive culture from invasive biopsy, and a time-consuming histopathology of tissue samples. At present, there are no rapid antigen tests for the disease that detect biomarkers of infection, and which allow point-of-care diagnosis. Here, we report the development of an IgG1 monoclonal antibody (mAb), KC9, which is specific to Rhizopus arrhizus var. arrhizus (syn. Rhizopus oryzae ) and Rhizopus arrhizus var. delemar ( Rhizopus delemar ), and which binds to a 15 kDa extracellular polysaccharide (EPS) antigen secreted during hyphal growth of the pathogen. Using the mAb, we have developed a competitive lateral-flow device (LFD) that allows rapid (30 min) and sensitive (~50 ng/mL running buffer) detection of the EPS biomarker, and which is compatible with human serum (limit of detection of ~500 ng/mL) and bronchoalveolar lavage fluid (limit of detection of ~100 ng/mL). The LFD, therefore, provides a potential novel opportunity for the non-invasive detection of mucormycosis caused by Rhizopus arrhizus .

Published
2022
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46. Insights into the Antibacterial Mechanism of Action of Chelating Agents by Selective Deprivation of Iron, Manganese, and Zinc.

Author

Paterson JR, Beecroft MS, Mulla RS, Osman D, Reeder NL, Caserta JA, Young TR, Pettigrew CA, Davies GE, Williams JAG, and Sharples GJ

Subjects
Anti-Bacterial Agents pharmacology, Chelating Agents chemistry, Chelating Agents pharmacology, Humans, Ions, Iron metabolism, Iron Chelating Agents pharmacology, Manganese metabolism, Zinc metabolism, Zinc pharmacology
Abstract

Bacterial growth and proliferation can be restricted by limiting the availability of metal ions in their environment. Humans sequester iron, manganese, and zinc to help prevent infection by pathogens, a system termed nutritional immunity. Commercially used chelants have high binding affinities with a variety of metal ions, which may lead to antibacterial properties that mimic these innate immune processes. However, the modes of action of many of these chelating agents in bacterial growth inhibition and their selectivity in metal deprivation in cellulo remain ill-defined. We address this shortcoming by examining the effect of 11 chelators on Escherichia coli growth and their impact on the cellular concentration of five metals. The following four distinct effects were uncovered: (i) no apparent alteration in metal composition, (ii) depletion of manganese alongside reductions in iron and zinc levels, (iii) reduced zinc levels with a modest reduction in manganese, and (iv) reduced iron levels coupled with elevated manganese. These effects do not correlate with the absolute known chelant metal ion affinities in solution; however, for at least five chelators for which key data are available, they can be explained by differences in the relative affinity of chelants for each metal ion. The results reveal significant insights into the mechanism of growth inhibition by chelants, highlighting their potential as antibacterials and as tools to probe how bacteria tolerate selective metal deprivation. IMPORTANCE Chelating agents are widely used in industry and consumer goods to control metal availability, with bacterial growth restriction as a secondary benefit for preservation. However, the antibacterial mechanism of action of chelants is largely unknown, particularly with respect to the impact on cellular metal concentrations. The work presented here uncovers distinct metal starvation effects imposed by different chelants on the model Gram-negative bacterium Escherichia coli. The chelators were studied both individually and in pairs, with the majority producing synergistic effects in combinations that maximize antibacterial hostility. The judicious selection of chelants based on contrasting cellular effects should enable reductions in the quantities of chelant required in numerous commercial products and presents opportunities to replace problematic chemistries with biodegradable alternatives.

Published
2022
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47. Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation.

Author

Min JL, Hemani G, Hannon E, Dekkers KF, Castillo-Fernandez J, Luijk R, Carnero-Montoro E, Lawson DJ, Burrows K, Suderman M, Bretherick AD, Richardson TG, Klughammer J, Iotchkova V, Sharp G, Al Khleifat A, Shatunov A, Iacoangeli A, McArdle WL, Ho KM, Kumar A, Söderhäll C, Soriano-Tárraga C, Giralt-Steinhauer E, Kazmi N, Mason D, McRae AF, Corcoran DL, Sugden K, Kasela S, Cardona A, Day FR, Cugliari G, Viberti C, Guarrera S, Lerro M, Gupta R, Bollepalli S, Mandaviya P, Zeng Y, Clarke TK, Walker RM, Schmoll V, Czamara D, Ruiz-Arenas C, Rezwan FI, Marioni RE, Lin T, Awaloff Y, Germain M, Aïssi D, Zwamborn R, van Eijk K, Dekker A, van Dongen J, Hottenga JJ, Willemsen G, Xu CJ, Barturen G, Català-Moll F, Kerick M, Wang C, Melton P, Elliott HR, Shin J, Bernard M, Yet I, Smart M, Gorrie-Stone T, Shaw C, Al Chalabi A, Ring SM, Pershagen G, Melén E, Jiménez-Conde J, Roquer J, Lawlor DA, Wright J, Martin NG, Montgomery GW, Moffitt TE, Poulton R, Esko T, Milani L, Metspalu A, Perry JRB, Ong KK, Wareham NJ, Matullo G, Sacerdote C, Panico S, Caspi A, Arseneault L, Gagnon F, Ollikainen M, Kaprio J, Felix JF, Rivadeneira F, Tiemeier H, van IJzendoorn MH, Uitterlinden AG, Jaddoe VWV, Haley C, McIntosh AM, Evans KL, Murray A, Räikkönen K, Lahti J, Nohr EA, Sørensen TIA, Hansen T, Morgen CS, Binder EB, Lucae S, Gonzalez JR, Bustamante M, Sunyer J, Holloway JW, Karmaus W, Zhang H, Deary IJ, Wray NR, Starr JM, Beekman M, van Heemst D, Slagboom PE, Morange PE, Trégouët DA, Veldink JH, Davies GE, de Geus EJC, Boomsma DI, Vonk JM, Brunekreef B, Koppelman GH, Alarcón-Riquelme ME, Huang RC, Pennell CE, van Meurs J, Ikram MA, Hughes AD, Tillin T, Chaturvedi N, Pausova Z, Paus T, Spector TD, Kumari M, Schalkwyk LC, Visscher PM, Davey Smith G, Bock C, Gaunt TR, Bell JT, Heijmans BT, Mill J, and Relton CL

Subjects
Chromosome Mapping, Epigenesis, Genetic genetics, Genome-Wide Association Study, Humans, Multifactorial Inheritance genetics, Polymorphism, Single Nucleotide genetics, Quantitative Trait, Heritable, Transcriptome genetics, DNA metabolism, DNA Methylation genetics, Gene Expression Regulation genetics, Genetic Predisposition to Disease genetics, Quantitative Trait Loci genetics
Abstract

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Published
2021
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48. Genetic association study of childhood aggression across raters, instruments, and age.

Author

Ip HF, van der Laan CM, Krapohl EML, Brikell I, Sánchez-Mora C, Nolte IM, St Pourcain B, Bolhuis K, Palviainen T, Zafarmand H, Colodro-Conde L, Gordon S, Zayats T, Aliev F, Jiang C, Wang CA, Saunders G, Karhunen V, Hammerschlag AR, Adkins DE, Border R, Peterson RE, Prinz JA, Thiering E, Seppälä I, Vilor-Tejedor N, Ahluwalia TS, Day FR, Hottenga JJ, Allegrini AG, Rimfeld K, Chen Q, Lu Y, Martin J, Soler Artigas M, Rovira P, Bosch R, Español G, Ramos Quiroga JA, Neumann A, Ensink J, Grasby K, Morosoli JJ, Tong X, Marrington S, Middeldorp C, Scott JG, Vinkhuyzen A, Shabalin AA, Corley R, Evans LM, Sugden K, Alemany S, Sass L, Vinding R, Ruth K, Tyrrell J, Davies GE, Ehli EA, Hagenbeek FA, De Zeeuw E, Van Beijsterveldt TCEM, Larsson H, Snieder H, Verhulst FC, Amin N, Whipp AM, Korhonen T, Vuoksimaa E, Rose RJ, Uitterlinden AG, Heath AC, Madden P, Haavik J, Harris JR, Helgeland Ø, Johansson S, Knudsen GPS, Njolstad PR, Lu Q, Rodriguez A, Henders AK, Mamun A, Najman JM, Brown S, Hopfer C, Krauter K, Reynolds C, Smolen A, Stallings M, Wadsworth S, Wall TL, Silberg JL, Miller A, Keltikangas-Järvinen L, Hakulinen C, Pulkki-Råback L, Havdahl A, Magnus P, Raitakari OT, Perry JRB, Llop S, Lopez-Espinosa MJ, Bønnelykke K, Bisgaard H, Sunyer J, Lehtimäki T, Arseneault L, Standl M, Heinrich J, Boden J, Pearson J, Horwood LJ, Kennedy M, Poulton R, Eaves LJ, Maes HH, Hewitt J, Copeland WE, Costello EJ, Williams GM, Wray N, Järvelin MR, McGue M, Iacono W, Caspi A, Moffitt TE, Whitehouse A, Pennell CE, Klump KL, Burt SA, Dick DM, Reichborn-Kjennerud T, Martin NG, Medland SE, Vrijkotte T, Kaprio J, Tiemeier H, Davey Smith G, Hartman CA, Oldehinkel AJ, Casas M, Ribasés M, Lichtenstein P, Lundström S, Plomin R, Bartels M, Nivard MG, and Boomsma DI

Subjects
Adolescent, Child, Child, Preschool, Female, Genetic Association Studies, Genome-Wide Association Study, Humans, Infant, Retrospective Studies, Aggression, Mental Disorders
Abstract

Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGG overall ) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGG overall . The gene-based analysis returned three significant genes: ST3GAL3 (P = 1.6E-06), PCDH7 (P = 2.0E-06), and IPO13 (P = 2.5E-06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (r g ) among rater-specific assessment of AGG ranged from r g  = 0.46 between self- and teacher-assessment to r g  = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong r g s with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range [Formula: see text]: 0.19-1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (r g  = ~-0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range [Formula: see text]: 0.46-0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG., (© 2021. The Author(s).)

Published
2021
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49. DNA methylation signatures of aggression and closely related constructs: A meta-analysis of epigenome-wide studies across the lifespan.

Author

van Dongen J, Hagenbeek FA, Suderman M, Roetman PJ, Sugden K, Chiocchetti AG, Ismail K, Mulder RH, Hafferty JD, Adams MJ, Walker RM, Morris SW, Lahti J, Küpers LK, Escaramis G, Alemany S, Jan Bonder M, Meijer M, Ip HF, Jansen R, Baselmans BML, Parmar P, Lowry E, Streit F, Sirignano L, Send TS, Frank J, Jylhävä J, Wang Y, Mishra PP, Colins OF, Corcoran DL, Poulton R, Mill J, Hannon E, Arseneault L, Korhonen T, Vuoksimaa E, Felix JF, Bakermans-Kranenburg MJ, Campbell A, Czamara D, Binder E, Corpeleijn E, Gonzalez JR, Grazuleviciene R, Gutzkow KB, Evandt J, Vafeiadi M, Klein M, van der Meer D, Ligthart L, Kluft C, Davies GE, Hakulinen C, Keltikangas-Järvinen L, Franke B, Freitag CM, Konrad K, Hervas A, Fernández-Rivas A, Vetro A, Raitakari O, Lehtimäki T, Vermeiren R, Strandberg T, Räikkönen K, Snieder H, Witt SH, Deuschle M, Pedersen NL, Hägg S, Sunyer J, Franke L, Kaprio J, Ollikainen M, Moffitt TE, Tiemeier H, van IJzendoorn MH, Relton C, Vrijheid M, Sebert S, Jarvelin MR, Caspi A, Evans KL, McIntosh AM, Bartels M, and Boomsma DI

Subjects
Adolescent, Adult, Aged, Aggression, Child, Child, Preschool, CpG Islands genetics, Epigenesis, Genetic genetics, Genome-Wide Association Study, Humans, Longevity, Middle Aged, Young Adult, DNA Methylation genetics, Epigenome
Abstract

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 × 10 -7 ; Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits., (© 2021. The Author(s).)

Published
2021
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50. Large-scale association analyses identify host factors influencing human gut microbiome composition.

Author

Kurilshikov A, Medina-Gomez C, Bacigalupe R, Radjabzadeh D, Wang J, Demirkan A, Le Roy CI, Raygoza Garay JA, Finnicum CT, Liu X, Zhernakova DV, Bonder MJ, Hansen TH, Frost F, Rühlemann MC, Turpin W, Moon JY, Kim HN, Lüll K, Barkan E, Shah SA, Fornage M, Szopinska-Tokov J, Wallen ZD, Borisevich D, Agreus L, Andreasson A, Bang C, Bedrani L, Bell JT, Bisgaard H, Boehnke M, Boomsma DI, Burk RD, Claringbould A, Croitoru K, Davies GE, van Duijn CM, Duijts L, Falony G, Fu J, van der Graaf A, Hansen T, Homuth G, Hughes DA, Ijzerman RG, Jackson MA, Jaddoe VWV, Joossens M, Jørgensen T, Keszthelyi D, Knight R, Laakso M, Laudes M, Launer LJ, Lieb W, Lusis AJ, Masclee AAM, Moll HA, Mujagic Z, Qibin Q, Rothschild D, Shin H, Sørensen SJ, Steves CJ, Thorsen J, Timpson NJ, Tito RY, Vieira-Silva S, Völker U, Völzke H, Võsa U, Wade KH, Walter S, Watanabe K, Weiss S, Weiss FU, Weissbrod O, Westra HJ, Willemsen G, Payami H, Jonkers DMAE, Arias Vasquez A, de Geus EJC, Meyer KA, Stokholm J, Segal E, Org E, Wijmenga C, Kim HL, Kaplan RC, Spector TD, Uitterlinden AG, Rivadeneira F, Franke A, Lerch MM, Franke L, Sanna S, D'Amato M, Pedersen O, Paterson AD, Kraaij R, Raes J, and Zhernakova A

Subjects
Adolescent, Adult, Bifidobacterium genetics, Child, Child, Preschool, Cohort Studies, Female, Gastrointestinal Microbiome genetics, Genome-Wide Association Study, Humans, Lactase genetics, Linkage Disequilibrium, Male, Mendelian Randomization Analysis, Metabolism genetics, RNA, Ribosomal, 16S, Gastrointestinal Microbiome physiology, Genetic Variation, Quantitative Trait Loci
Abstract

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P < 5 × 10 -8 ) threshold. One locus, the lactase (LCT) gene locus, reached study-wide significance (genome-wide association study signal: P = 1.28 × 10 -20 ), and it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.95 × 10 -10  < P < 5 × 10 -8 ) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization identified enrichment of microbiome trait loci in the metabolic, nutrition and environment domains and suggested the microbiome might have causal effects in ulcerative colitis and rheumatoid arthritis.

Published
2021
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