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1. 598 - Defining the capacity of the lumbosacral network for neuromodulation in humans with spinal cord injury

Author: Krenn, MJ, Gordineer, EA, Tansey, KE, and Stokic, DS
Published: 2024
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2. The Relationship Between Polygenic Risk Scores and Cognition in Schizophrenia

Author: Richards, AL, Pardinas, A.F., Frizzati, A., Tansey, KE, Lynham, A.J., Holmans, P.A. (Peter), Walters, T.R., Richards, AL, Pardinas, A.F., Frizzati, A., Tansey, KE, Lynham, A.J., Holmans, P.A. (Peter), and Walters, T.R.
Abstract: Background: Cognitive impairment is a clinically important feature of schizophrenia. Polygenic risk score (PRS) methods have demonstrated genetic overlap between schizophrenia, bipolar disorder (BD), major depressive disorder (MDD), educational attainment (EA), and IQ, but very few studies have examined associations between these PRS and cognitive phenotypes within schizophrenia cases. Methods: We combined genetic and cognitive data in 3034 schizophrenia cases from 11 samples using the general intelligence factor g as the primary measure of cognition. We used linear regression to examine the association between cognition and PRS for EA, IQ, schizophrenia, BD, and MDD. The results were then meta-analyzed across all samples. A genome-wide association studies (GWAS) of cognition was conducted in schizophrenia cases. Results: PRS for both population IQ (P = 4.39 × 10–28) and EA (P = 1.27 × 10–26) were positively correlated with cognition in those with schizophrenia. In contrast, there was no association between cognition in schizophrenia cases and PRS for schizophrenia (P = .39), BD (P = .51), or MDD (P = .49). No individual variant approached genome-wide significance in the GWAS. Conclusions: Cognition in schizophrenia cases is more strongly associated with PRS that index cognitive traits in the general population than PRS for neuropsychiatric disorders. This suggests the mechanisms of cognitive variation within schizophrenia are at least partly independent from those that pre
Published: 2020
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3. Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression

Author: Glanville, KP, Coleman, JR, Hanscombe, KB, Euesden, J, Choi, SW, Purves, KL, Breen, G, Air, TM, Andlauer, TFM, Baune, BT, Binder, EB, Blackwood, DHR, Boomsma, D, Buttenschon, HN, Colodro-Conde, L, Dannlowski, U, Direk, N, Dunn, EC, Forstner, AJ, de Geus, EJC, Grabe, HJ, Hamilton, SP, Jones, I, Jones, LA, Knowles, JA, Kutalik, Z, Levinson, DF, Lewis, G, Lind, PA, Lucae, S, Magnusson, PK, McGuffin, P, McIntosh, AM, Milaneschi, Y, Mors, O, Mostafavi, S, Mueller-Myhsok, B, Pedersen, NL, Penninx, BWJH, Potash, JB, Preisig, M, Ripke, S, Shi, J, Shyn, S, Smoller, JW, Streit, F, Sullivan, PF, Tiemeier, H, Uher, R, Van der Auwera, S, Weissman, MM, O'Reilly, PF, Lewis, CM, Wray, NR, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Bryois, J, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Dolan, C, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Howard, DM, Ising, M, Jansen, R, Jorgenson, E, Kohane, IS, Kraft, J, Kretzschmar, WW, Li, Y, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milani, L, Mondimore, FM, Montgomery, GW, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Berger, K, Cichon, S, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Li, QS, Madden, PAF, Martin, NG, Metspalu, A, Mortensen, PB, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Perlis, RH, Porteous, DJ, Rietschel, M, Schaefer, C, Schulze, TG, Stefansson, K, Voelzke, H, Werge, T, Borglum, AD, Glanville, KP, Coleman, JR, Hanscombe, KB, Euesden, J, Choi, SW, Purves, KL, Breen, G, Air, TM, Andlauer, TFM, Baune, BT, Binder, EB, Blackwood, DHR, Boomsma, D, Buttenschon, HN, Colodro-Conde, L, Dannlowski, U, Direk, N, Dunn, EC, Forstner, AJ, de Geus, EJC, Grabe, HJ, Hamilton, SP, Jones, I, Jones, LA, Knowles, JA, Kutalik, Z, Levinson, DF, Lewis, G, Lind, PA, Lucae, S, Magnusson, PK, McGuffin, P, McIntosh, AM, Milaneschi, Y, Mors, O, Mostafavi, S, Mueller-Myhsok, B, Pedersen, NL, Penninx, BWJH, Potash, JB, Preisig, M, Ripke, S, Shi, J, Shyn, S, Smoller, JW, Streit, F, Sullivan, PF, Tiemeier, H, Uher, R, Van der Auwera, S, Weissman, MM, O'Reilly, PF, Lewis, CM, Wray, NR, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Bryois, J, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Dolan, C, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Howard, DM, Ising, M, Jansen, R, Jorgenson, E, Kohane, IS, Kraft, J, Kretzschmar, WW, Li, Y, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milani, L, Mondimore, FM, Montgomery, GW, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Berger, K, Cichon, S, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Li, QS, Madden, PAF, Martin, NG, Metspalu, A, Mortensen, PB, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Perlis, RH, Porteous, DJ, Rietschel, M, Schaefer, C, Schulze, TG, Stefansson, K, Voelzke, H, Werge, T, and Borglum, AD
Abstract: BACKGROUND: The prevalence of depression is higher in individuals with autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Shared genetic etiology is a plausible explanation for the overlap, and in this study we tested whether genetic variation in the major histocompatibility complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression. METHODS: We fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 human leukocyte antigen (HLA) alleles and 4 complement component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium Major Depressive Disorder Working Group and the UK Biobank. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants, applying both a region-wide significance threshold (3.9 × 10-6) and a candidate threshold (1.6 × 10-4). RESULTS: No HLA alleles or C4 haplotypes were associated with depression at the region-wide threshold. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold for testing in HLA genes in the meta-analysis (odds ratio = 0.98, 95% confidence interval = 0.97-0.99). CONCLUSIONS: We found no evidence that an increased risk for depression was conferred by HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia. These results suggest that any HLA or C4 variants associated with depression either are rare or have very modest effect sizes.
Published: 2020

4. 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

5. Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank

Author: Coleman, JRI, Peyrot, WJ, Purves, KL, Davis, KAS, Rayner, C, Choi, SW, Hubel, C, Gaspar, HA, Kan, C, Van der Auwera, S, Adams, MJ, Lyall, DM, Choi, KW, Dunn, EC, Vassos, E, Danese, A, Maughan, B, Grabe, HJ, Lewis, CM, O'Reilly, PF, McIntosh, AM, Smith, DJ, Wray, NR, Hotopf, M, Eley, TC, Breen, G, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Forstner, AJ, Frank, J, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Howard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, SI, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, DI, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Volzke, H, Weissman, MM, Werge, T, Levinson, DF, Borglum, AD, Sullivan, PF, Coleman, JRI, Peyrot, WJ, Purves, KL, Davis, KAS, Rayner, C, Choi, SW, Hubel, C, Gaspar, HA, Kan, C, Van der Auwera, S, Adams, MJ, Lyall, DM, Choi, KW, Dunn, EC, Vassos, E, Danese, A, Maughan, B, Grabe, HJ, Lewis, CM, O'Reilly, PF, McIntosh, AM, Smith, DJ, Wray, NR, Hotopf, M, Eley, TC, Breen, G, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Forstner, AJ, Frank, J, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Howard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, SI, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, DI, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Volzke, H, Weissman, MM, Werge, T, Levinson, DF, Borglum, AD, and Sullivan, PF
Abstract: Depression is more frequent among individuals exposed to traumatic events. Both trauma exposure and depression are heritable. However, the relationship between these traits, including the role of genetic risk factors, is complex and poorly understood. When modelling trauma exposure as an environmental influence on depression, both gene-environment correlations and gene-environment interactions have been observed. The UK Biobank concurrently assessed Major Depressive Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 genotyped individuals of European ancestry. We contrasted genetic influences on MDD stratified by reported trauma exposure (final sample size range: 24,094-92,957). The SNP-based heritability of MDD with reported trauma exposure (24%) was greater than MDD without reported trauma exposure (12%). Simulations showed that this is not confounded by the strong, positive genetic correlation observed between MDD and reported trauma exposure. We also observed that the genetic correlation between MDD and waist circumference was only significant in individuals reporting trauma exposure (rg = 0.24, p = 1.8 × 10-7 versus rg = -0.05, p = 0.39 in individuals not reporting trauma exposure, difference p = 2.3 × 10-4). Our results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.
Published: 2020

6. Evidence for increased genetic risk load for major depression in patients assigned to electroconvulsive therapy

Author: Foo, JC, Streit, F, Frank, J, Witt, SH, Treutlein, J, Baune, BT, Moebus, S, Joeckel, K-H, Forstner, AJ, Noethen, MM, Rietschel, M, Sartorius, A, Kranaster, L, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JRI, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, O'Reilly, PF, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, SI, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Berger, K, Boomsma, DI, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, AD, Sullivan, PF, Foo, JC, Streit, F, Frank, J, Witt, SH, Treutlein, J, Baune, BT, Moebus, S, Joeckel, K-H, Forstner, AJ, Noethen, MM, Rietschel, M, Sartorius, A, Kranaster, L, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JRI, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, O'Reilly, PF, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, SI, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Berger, K, Boomsma, DI, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, AD, and Sullivan, PF
Abstract: Electroconvulsive therapy (ECT) is the treatment of choice for severe and treatment-resistant depression; disorder severity and unfavorable treatment outcomes are shown to be influenced by an increased genetic burden for major depression (MD). Here, we tested whether ECT assignment and response/nonresponse are associated with an increased genetic burden for major depression (MD) using polygenic risk score (PRS), which summarize the contribution of disease-related common risk variants. Fifty-one psychiatric inpatients suffering from a major depressive episode underwent ECT. MD-PRS were calculated for these inpatients and a separate population-based sample (n = 3,547 healthy; n = 426 self-reported depression) based on summary statistics from the Psychiatric Genomics Consortium MDD-working group (Cases: n = 59,851; Controls: n = 113,154). MD-PRS explained a significant proportion of disease status between ECT patients and healthy controls (p = .022, R2 = 1.173%); patients showed higher MD-PRS. MD-PRS in population-based depression self-reporters were intermediate between ECT patients and controls (n.s.). Significant associations between MD-PRS and ECT response (50% reduction in Hamilton depression rating scale scores) were not observed. Our findings indicate that ECT cohorts show an increased genetic burden for MD and are consistent with the hypothesis that treatment-resistant MD patients represent a subgroup with an increased genetic risk for MD. Larger samples are needed to better substantiate these findings.
Published: 2019

7. Genome-wide by environment interaction studies of depressive symptoms and psychosocial stress in UK Biobank and Generation Scotland

Author: Arnau-Soler, A, Macdonald-Dunlop, E, Adams, MJ, Clarke, T-K, MacIntyre, DJ, Milburn, K, Navrady, L, Hayward, C, McIntosh, AM, Thomson, PA, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenscon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Rawford, GEC, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, Macintyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, O'Reilly, PF, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, ASD, Sullivan, PF, Arnau-Soler, A, Macdonald-Dunlop, E, Adams, MJ, Clarke, T-K, MacIntyre, DJ, Milburn, K, Navrady, L, Hayward, C, McIntosh, AM, Thomson, PA, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenscon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Rawford, GEC, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, Macintyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, O'Reilly, PF, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, ASD, and Sullivan, PF
Abstract: Stress is associated with poorer physical and mental health. To improve our understanding of this link, we performed genome-wide association studies (GWAS) of depressive symptoms and genome-wide by environment interaction studies (GWEIS) of depressive symptoms and stressful life events (SLE) in two UK population-based cohorts (Generation Scotland and UK Biobank). No SNP was individually significant in either GWAS, but gene-based tests identified six genes associated with depressive symptoms in UK Biobank (DCC, ACSS3, DRD2, STAG1, FOXP2 and KYNU; p < 2.77 × 10-6). Two SNPs with genome-wide significant GxE effects were identified by GWEIS in Generation Scotland: rs12789145 (53-kb downstream PIWIL4; p = 4.95 × 10-9; total SLE) and rs17070072 (intronic to ZCCHC2; p = 1.46 × 10-8; dependent SLE). A third locus upstream CYLC2 (rs12000047 and rs12005200, p < 2.00 × 10-8; dependent SLE) when the joint effect of the SNP main and GxE effects was considered. GWEIS gene-based tests identified: MTNR1B with GxE effect with dependent SLE in Generation Scotland; and PHF2 with the joint effect in UK Biobank (p < 2.77 × 10-6). Polygenic risk scores (PRSs) analyses incorporating GxE effects improved the prediction of depressive symptom scores, when using weights derived from either the UK Biobank GWAS of depressive symptoms (p = 0.01) or the PGC GWAS of major depressive disorder (p = 5.91 × 10-3). Using an independent sample, PRS derived using GWEIS GxE effects provided evidence of shared aetiologies between depressive symptoms and schizotypal personality, heart disease and COPD. Further such studies are required and may result in improved treatments for depression and other stress-related conditions.
Published: 2019

8. Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

Author: Czamara, D, Eraslan, G, Page, CM, Lahti, J, Lahti-Pulkkinen, M, Hamalainen, E, Kajantie, E, Laivuori, H, Villa, PM, Reynolds, RM, Nystad, W, Haberg, SE, London, SJ, O'Donnell, KJ, Garg, E, Meaney, MJ, Entringer, S, Wadhwa, PD, Buss, C, Jones, MJ, Lin, DTS, MacIsaac, JL, Kobor, MS, Koen, N, Zar, HJ, Koenen, KC, Dalvie, S, Stein, DJ, Kondofersky, I, Mueller, NS, Theis, FJ, Raikkonen, K, Binder, EB, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, O'Reilly, PF, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, AD, Sullivan, PF, Czamara, D, Eraslan, G, Page, CM, Lahti, J, Lahti-Pulkkinen, M, Hamalainen, E, Kajantie, E, Laivuori, H, Villa, PM, Reynolds, RM, Nystad, W, Haberg, SE, London, SJ, O'Donnell, KJ, Garg, E, Meaney, MJ, Entringer, S, Wadhwa, PD, Buss, C, Jones, MJ, Lin, DTS, MacIsaac, JL, Kobor, MS, Koen, N, Zar, HJ, Koenen, KC, Dalvie, S, Stein, DJ, Kondofersky, I, Mueller, NS, Theis, FJ, Raikkonen, K, Binder, EB, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, McGuffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, O'Reilly, PF, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, AD, and Sullivan, PF
Abstract: Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike's information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk.
Published: 2019

9. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity (vol 50, pg 26, 2018)

Author: Turcot, V, Lu, Y, Highland, HM, Schurmann, C, Justice, AE, Fine, RS, Bradfield, JP, Esko, T, Giri, A, Graff, M, Guo, X, Hendricks, AE, Karaderi, T, Lempradl, A, Locke, AE, Mahajan, A, Marouli, E, Sivapalaratnam, S, Young, KL, Alfred, T, Feitosa, MF, Masca, NGD, Manning, AK, Medina-Gomez, C, Mudgal, P, Ng, MCY, Reiner, AP, Vedantam, S, Willems, SM, Winkler, TW, Abecasis, G, Aben, KK, Alam, DS, Alharthi, SE, Allison, M, Amouyel, P, Asselbergs, FW, Auer, PL, Balkau, B, Bang, LE, Barroso, I, Bastarache, L, Benn, M, Bergmann, S, Bielak, LF, Bluher, M, Boehnke, M, Boeing, H, Boerwinkle, E, Boger, CA, Bork-Jensen, J, Bots, ML, Bottinger, EP, Bowden, DW, Brandslund, I, Breen, G, Brilliant, MH, Broer, L, Brumat, M, Burt, AA, Butterworth, AS, Campbell, PT, Cappellani, S, Carey, DJ, Catamo, E, Caulfield, MJ, Chambers, JC, Chasman, DI, Chen, Y-DI, Chowdhury, R, Christensen, C, Chu, AY, Cocca, M, Collins, FS, Cook, JP, Corley, J, Galbany, JC, Cox, AJ, Crosslin, DS, Cuellar-Partida, G, D'Eustacchio, A, Danesh, J, Davies, G, Bakker, PIW, Groot, MCH, Mutsert, R, Deary, IJ, Dedoussis, G, Demerath, EW, Heijer, M, Hollander, AI, Ruijter, HM, Dennis, JG, Denny, JC, Di Angelantonio, E, Drenos, F, Du, M, Dube, M-P, Dunning, AM, Easton, DF, Edwards, TL, Ellinghaus, D, Ellinor, PT, Elliott, P, Evangelou, E, Farmaki, A-E, Farooqi, IS, Faul, JD, Fauser, S, Feng, S, Ferrannini, E, Ferrieres, J, Florez, JC, Ford, I, Fornage, M, Franco, OH, Franke, A, Franks, PW, Friedrich, N, Frikke-Schmidt, R, Galesloot, TE, Gan, W, Gandin, I, Gasparini, P, Gibson, J, Giedraitis, V, Gjesing, AP, Gordon-Larsen, P, Gorski, M, Grabe, H-J, Grant, SFA, Grarup, N, Griffiths, HL, Grove, ML, Gudnason, V, Gustafsson, S, Haessler, J, Hakonarson, H, Hammerschlag, AR, Hansen, T, Harris, KM, Harris, TB, Hattersley, AT, Have, CT, Hayward, C, He, L, Heard-Costa, NL, Heath, AC, Heid, IM, Helgeland, O, Hernesniemi, J, Hewitt, AW, Holmen, OL, Hovingh, GK, Howson, JMM, Hu, Y, Huang, PL, Huffman, JE, Ikram, MA, Ingelsson, E, Jackson, AU, Jansson, J-H, Jarvik, GP, Jensen, GB, Jia, Y, Johansson, S, Jorgensen, ME, Jorgensen, T, Jukema, JW, Kahali, B, Kahn, RS, Kahonen, M, Kamstrup, PR, Kanoni, S, Kaprio, J, Karaleftheri, M, Kardia, SLR, Karpe, F, Kathiresan, S, Kee, F, Kiemeney, LA, Kim, E, Kitajima, H, Komulainen, P, Kooner, JS, Kooperberg, C, Korhonen, T, Kovacs, P, Kuivaniemi, H, Kutalik, Z, Kuulasmaa, K, Kuusisto, J, Laakso, M, Lakka, TA, Lamparter, D, Lange, EM, Lange, LA, Langenberg, C, Larson, EB, Lee, NR, Lehtimaki, T, Lewis, CE, Li, H, Li, J, Li-Gao, R, Lin, H, Lin, K-H, Lin, L-A, Lin, X, Lind, L, Lindstrom, J, Linneberg, A, Liu, C-T, Liu, DJ, Liu, Y, Lo, KS, Lophatananon, A, Lotery, AJ, Loukola, A, Luan, J, Lubitz, SA, Lyytikainen, L-P, Mannisto, S, Marenne, G, Mazul, AL, McCarthy, MI, McKean-Cowdin, R, Medland, SE, Meidtner, K, Milani, L, Mistry, V, Mitchell, P, Mohlke, KL, Moilanen, L, Moitry, M, Montgomery, GW, Mook-Kanamori, DO, Moore, C, Mori, TA, Morris, AD, Morris, AP, Mueller-Nurasyid, M, Munroe, PB, Nalls, MA, Narisu, N, Nelson, CP, Neville, M, Nielsen, SF, Nikus, K, Njolstad, PR, Nordestgaard, BG, Nyholt, DR, O'Connel, JR, O'Donoghue, ML, Loohuis, LMO, Ophoff, RA, Owen, KR, Packard, CJ, Padmanabhan, S, Palmer, CNA, Palmer, ND, Pasterkamp, G, Patel, AP, Pattie, A, Pedersen, O, Peissig, PL, Peloso, GM, Pennell, CE, Perola, M, Perry, JA, Perry, JRB, Pers, TH, Person, TN, Peters, A, Petersen, ERB, Peyser, PA, Pirie, A, Polasek, O, Polderman, TJ, Puolijoki, H, Raitakari, OT, Rasheed, A, Rauramaa, R, Reilly, DF, Renstrom, F, Rheinberger, M, Ridker, PM, Rioux, JD, Rivas, MA, Roberts, DJ, Robertson, NR, Robino, A, Rolandsson, O, Rudan, I, Ruth, KS, Saleheen, D, Salomaa, V, Samani, NJ, Sapkota, Y, Sattar, N, Schoen, RE, Schreiner, PJ, Schulze, MB, Scott, RA, Segura-Lepe, MP, Shah, SH, Sheu, WH-H, Sim, X, Slater, AJ, Small, KS, Smith, AV, Southam, L, Spector, TD, Speliotes, EK, Starr, JM, Stefansson, K, Steinthorsdottir, V, Stirrups, KE, Strauch, K, Stringham, HM, Stumvoll, M, Sun, L, Surendran, P, Swift, AJ, Tada, H, Tansey, KE, Tardif, J-C, Taylor, KD, Teumer, A, Thompson, DJ, Thorleifsson, G, Thorsteinsdottir, U, Thuesen, BH, Tonjes, A, Tromp, G, Trompet, S, Tsafantakis, E, Tuomilehto, J, Tybjaerg-Hansen, A, Tyrer, JP, Uher, R, Uitterlinden, AG, Uusitupa, M, Laan, SW, Duijn, CM, Leeuwen, N, van Setten, J, Vanhala, M, Varbo, A, Varga, TV, Varma, R, Edwards, DRV, Vermeulen, SH, Veronesi, G, Vestergaard, H, Vitart, V, Vogt, TF, Volker, U, Vuckovic, D, Wagenknecht, LE, Walker, M, Wallentin, L, Wang, F, Wang, CA, Wang, S, Wang, Y, Ware, EB, Wareham, NJ, Warren, HR, Waterworth, DM, Wessel, J, White, HD, Willer, CJ, Wilson, JG, Witte, DR, Wood, AR, Wu, Y, Yaghootkar, H, Yao, J, Yao, P, Yerges-Armstrong, LM, Young, R, Zeggini, E, Zhan, X, Zhang, W, Zhao, JH, Zhao, W, Zhou, W, Zondervan, KT, Consortium, GG, Rotter, JI, Pospisilik, JA, Rivadeneira, F, Borecki, IB, Deloukas, P, Frayling, TM, Lettre, G, North, KE, Lindgren, CM, Hirschhorn, JN, Loos, RJF, Vascular Medicine, ACS - Atherosclerosis & ischemic syndromes, and Amsterdam Cardiovascular Sciences
Published: 2018

10. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity (vol 50, pg 765, 2017)

Author: Turcot, V, Lu, Y, Highland, HM, Schurmann, C, Justice, AE, Fine, RS, Bradfield, JP, Esko, T, Giri, A, Graff, M, Guo, X, Hendricks, AE, Karaderi, T, Lempradl, A, Locke, AE, Mahajan, A, Marouli, E, Sivapalaratnam, S, Young, KL, Alfred, T, Feitosa, MF, Masca, NGD, Manning, AK, Medina-Gomez, C, Mudgal, P, Ng, MCY, Reiner, AP, Vedantam, S, Willems, SM, Winkler, TW, Abecasis, G, Aben, KK, Alam, DS, Alharthi, SE, Allison, M, Amouyel, P, Asselbergs, FW, Auer, PL, Balkau, B, Bang, LE, Barroso, I, Bastarache, L, Benn, M, Bergmann, S, Bielak, LF, Bluher, M, Boehnke, M, Boeing, H, Boerwinkle, E, Boger, CA, Bork-Jensen, J, Bots, ML, Bottinger, EP, Bowden, DW, Brandslund, I, Breen, G, Brilliant, MH, Broer, L, Brumat, M, Burt, AA, Butterworth, AS, Campbell, PT, Cappellani, S, Carey, DJ, Catamo, E, Caulfield, MJ, Chambers, JC, Chasman, DI, Chen, Y-DI, Chowdhury, R, Christensen, C, Chu, AY, Cocca, M, Collins, FS, Cook, JP, Corley, J, Galbany, JC, Cox, AJ, Crosslin, DS, Cuellar-Partida, G, D'Eustacchio, A, Danesh, J, Davies, G, Bakker, PIW, Groot, MCH, Mutsert, R, Deary, IJ, Dedoussis, G, Demerath, EW, Heijer, M, Hollander, AI, Ruijter, HM, Dennis, JG, Denny, JC, Angelantonio, E, Drenos, F, Du, M, Dube, M-P, Dunning, AM, Easton, DF, Edwards, TL, Ellinghaus, D, Ellinor, PT, Elliott, P, Evangelou, E, Farmaki, A-E, Farooqi, IS, Faul, JD, Fauser, S, Feng, S, Ferrannini, E, Ferrieres, J, Florez, JC, Ford, I, Fornage, M, Franco, OH, Franke, A, Franks, PW, Friedrich, N, Frikke-Schmidt, R, Galesloot, TE, Gan, W, Gandin, I, Gasparini, P, Gibson, J, Giedraitis, V, Gjesing, AP, Gordon-Larsen, P, Gorski, M, Grabe, H-J, Grant, SFA, Grarup, N, Griffiths, HL, Grove, ML, Gudnason, V, Gustafsson, S, Haessler, J, Hakonarson, H, Hammerschlag, AR, Hansen, T, Harris, KM, Harris, TB, Hattersley, AT, Have, CT, Hayward, C, He, L, Heard-Costa, NL, Heath, AC, Heid, IM, Helgeland, O, Hernesniemi, J, Hewitt, AW, Holmen, OL, Hovingh, GK, Howson, JMM, Hu, Y, Huang, PL, Huffman, JE, Ikram, MA, Ingelsson, E, Jackson, AU, Jansson, J-H, Jarvik, GP, Jensen, GB, Jia, Y, Johansson, S, Jorgensen, ME, Jorgensen, T, Jukema, JW, Kahali, B, Kahn, RS, Kahonen, M, Kamstrup, PR, Kanoni, S, Kaprio, J, Karaleftheri, M, Kardia, SLR, Karpe, F, Kathiresan, S, Kee, F, Kiemeney, LA, Kim, E, Kitajima, H, Komulainen, P, Kooner, JS, Kooperberg, C, Korhonen, T, Kovacs, P, Kuivaniemi, H, Kutalik, Z, Kuulasmaa, K, Kuusisto, J, Laakso, M, Lakka, TA, Lamparter, D, Lange, EM, Lange, LA, Langenberg, C, Larson, EB, Lee, NR, Lehtimaki, T, Lewis, CE, Li, H, Li, J, Li-Gao, R, Lin, H, Lin, K-H, Lin, L-A, Lin, X, Lind, L, Lindstrom, J, Linneberg, A, Liu, C-T, Liu, DJ, Liu, Y, Lo, KS, Lophatananon, A, Lotery, AJ, Loukola, A, Luan, J, Lubitz, SA, Lyytikainen, L-P, Mannisto, S, Marenne, G, Mazul, AL, McCarthy, MI, McKean-Cowdin, R, Medland, SE, Meidtner, K, Milani, L, Mistry, V, Mitchell, P, Mohlke, KL, Moilanen, L, Moitry, M, Montgomery, GW, Mook-Kanamori, DO, Moore, C, Mori, TA, Morris, AD, Morris, AP, Mueller-Nurasyid, M, Munroe, PB, Nalls, MA, Narisu, N, Nelson, CP, Neville, M, Nielsen, SF, Nikus, K, Njolstad, PR, Nordestgaard, BG, Nyholt, DR, O'Connel, JR, O'Donoghue, ML, Loohuis, LMO, Ophoff, RA, Owen, KR, Packard, CJ, Padmanabhan, S, Palmer, CNA, Palmer, ND, Pasterkamp, G, Patel, AP, Pattie, A, Pedersen, O, Peissig, PL, Peloso, GM, Pennell, CE, Perola, M, Perry, JA, Perry, JRB, Pers, TH, Person, TN, Peters, A, Petersen, ERB, Peyser, PA, Pirie, A, Polasek, O, Polderman, TJ, Puolijoki, H, Raitakari, OT, Rasheed, A, Rauramaa, R, Reilly, DF, Renstrom, F, Rheinberger, M, Ridker, PM, Rioux, JD, Rivas, MA, Roberts, DJ, Robertson, NR, Robino, A, Rolandsson, O, Rudan, I, Ruth, KS, Saleheen, D, Salomaa, V, Samani, NJ, Sapkota, Y, Sattar, N, Schoen, RE, Schreiner, PJ, Schulze, MB, Scott, RA, Segura-Lepe, MP, Shah, SH, Sheu, WH-H, Sim, X, Slater, AJ, Small, KS, Smith, AV, Southam, L, Spector, TD, Speliotes, EK, Starr, JM, Stefansson, K, Steinthorsdottir, V, Stirrups, KE, Strauch, K, Stringham, HM, Stumvoll, M, Sun, L, Surendran, P, Swift, AJ, Tada, H, Tansey, KE, Tardif, J-C, Taylor, KD, Teumer, A, Thompson, DJ, Thorleifsson, G, Thorsteinsdottir, U, Thuesen, BH, Tonjes, A, Tromp, G, Trompet, S, Tsafantakis, E, Tuomilehto, J, Tybjaerg-Hansen, A, Tyrer, JP, Uher, R, Uitterlinden, AG, Uusitupa, M, Laan, SW, Duijn, CM, Leeuwen, N, van Setten, J, Vanhala, M, Varbo, A, Varga, TV, Varma, R, Edwards, DRV, Vermeulen, SH, Veronesi, G, Vestergaard, H, Vitart, V, Vogt, TF, Volker, U, Vuckovic, D, Wagenknecht, LE, Walker, M, Wallentin, L, Wang, F, Wang, CA, Wang, S, Wang, Y, Ware, EB, Wareham, NJ, Warren, HR, Waterworth, DM, Wessel, J, White, HD, Willer, CJ, Wilson, JG, Witte, DR, Wood, AR, Wu, Y, Yaghootkar, H, Yao, J, Yao, P, Yerges-Armstrong, LM, Young, R, Zeggini, E, Zhan, X, Zhang, W, Zhao, JH, Zhao, W, Zhou, W, Zondervan, KT, Rotter, JI, Pospisilik, JA, Rivadeneira, F, Borecki, IB, Deloukas, P, Frayling, TM, Lettre, G, North, KE, Lindgren, CM, Hirschhorn, JN, Loos, RJF, Graduate School, Vascular Medicine, ACS - Atherosclerosis & ischemic syndromes, and Amsterdam Cardiovascular Sciences
Published: 2018

11. Genome-wide interaction study of a proxy for stress-sensitivity and its prediction of major depressive disorder

Author: Arnau-Soler, A., Adams, M. J., Hayward, C. (Caroline), Thomson, PA, Porteous, D, Campbell, A. (Archie), Smith, B.H. (Blair), Black, C., Padmanabhan, S. (Sandosh), Mcintosh, A.M. (Andrew), Wray, N.R. (Naomi), Ripke, S. (Stephan), Mattheisen, M. (Manuel), Trzaskowski, M., Byrne, E.M. (Enda), Abdellaoui, A. (Abdel), Agerbo, E, Air, T.M., Andlauer, T.F.M., Bacanu, SA, Bækvad-Hansen, M., Beekman, A.T.F. (Aartjan), Bigdeli, TB, Binder, E.B. (Elisabeth), Blackwood, D.H.R. (Douglas), Bryois, J., Buttenschøn, H.N., Bybjerg-Grauholm, J., Cai, N., Castelao, E, Christensen, J.H., Clarke, T.-K., Coleman, J.R.I., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N.J. (Nick), Crawford, G.E., Davies, G. (Gail), Deary, I.J. (Ian), Degenhardt, F., Derks, E.M. (Eske), Direk, N., Dolan, C.V. (Conor), Dunn, EC, Eley, T.C. (T.), Escott-Price, V, Kiadeh, F.F.H., Finucane, HK, Forstner, A.J. (Andreas), Frank, J. (Josef), Gaspar, H.A., Gill, M. (Michael), Goes, F.S., Gordon, S.D., Grove, J. (Jakob), Hall, L.S., Hansen, C.S., Hansen, T.F. (Thomas F), Herms, S. (Stefan), Hickie, I.B. (Ian), Hoffmann, P. (Per), Homuth, G. (Georg), Horn, C., Hottenga, JJ, Hougaard, D.M. (David), Ising, M. (Marcus), Jansen, R, Jorgenson, E, Knowles, J.A. (James A), Kohane, IS, Kraft, J., Kretzschmar, W.W., Krogh, J., Kutalik, Z. (Zoltán), Li, Y. (Yuwen), Lind, P.A. (Penelope), Macintyre, D.J. (Donald J), MacKinnon, D.F., Maier, R.M., Maier, W. (Wolfgang), Marchini, J. (Jonathan), Mbarek, H, McGrath, P., Mcguffin, P. (Peter), Medland, S.E., Mehta, D, Middeldorp, CM, Mihailov, E. (Evelin), Milaneschi, Y. (Yuri), Milani, L. (Lili), Mondimore, F.M., Montgomery, G.W. (Grant), Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M.G., Nyholt, D.R. (Dale), O'Reilly, P.F. (Paul), Oskarsson, H. (Hogni), Owen, M.J., Painter, JN, Pedersen, CB, Pedersen, M.G., Peterson, R.E., Pettersson, E, Peyrot, W.J. (Wouter ), Pistis, G. (Giorgio), Posthuma, D., Quiroz, J.A., Qvist, P., Rice, J.P. (John), Riley, B.P. (Brien), Rivera, M., Mirza, S.S., Schoevers, R. (Robert), Schulte, E.C., Shen, L. (Li), Shi, J. (Julia), Shyn, S.I. (Stanley I), Sigurdsson, E. (Engilbert), Sinnamon, G.C.B., Smit, J.H.M., Smith, D.J. (Derek James), Stefansson, H. (Hreinn), Steinberg, S. (Stacy), Streit, F., Strohmaier, J., Tansey, KE, Teismann, H., Teumer, A. (Alexander), Thompson, W., Thorgeirsson, T.E. (Thorgeir), Traylor, M. (Matthew), Treutlein, J. (Jens), Trubetskoy, V., Uitterlinden, A.G. (André), Umbricht, D., Van der Auwera, S., van Hemert, A.M., Viktorin, A, Visscher, P.M. (Peter), Wang, Y. (Yijing), Webb, BT, Weinsheimer, S.M., Wellmann, J. (Jürgen), Willemsen, G.A.H.M. (Gonneke), Witt, S.H. (Stephanie H), Wu, Y., Xi, HS, Yang, J., Zhang, F. (Feng), Arolt, V, Baune, BT, Berger, K. (Klaus), Boomsma, D.I. (Dorret), Cichon, S. (Sven), Dannlowski, U., de Geus, EJCN, DePaulo, J.R., Domenici, E, Domschke, K., Esko, T. (Tõnu), Grabe, H.J. (Hans Jörgen), Hamilton, S.P. (Steven P), Heath, A.C. (Andrew), Kendler, K. (K.), Kloiber, S, Lewis, G, Li, Q.S., Lucae, S. (Susanne), Madden, P.A. (Pamela), Magnusson, P.K. (Patrik), Martin, N.G. (Nicholas), Metspalu, A. (Andres), Mors, O., Mortensen, P.B., Müller-Myhsok, B., Nordentoft, M, Nöthen, M.M. (Markus), O'Donovan, M. (Michael), Paciga, S.A., Pedersen, N.L. (Nancy), Penninx, B.W.J.H. (Brenda), Perlis, R.H. (Roy H), Porteous, D.J. (David J.), Potash, J.B. (James B), Preisig, M. (Martin), Rietschel, M., Schaefer, C. (Catherine), Schulze, T.G. (Thomas), Smoller, J.W., Zwart, J-A. (John-Anker), Tiemeier, H.W. (Henning), Uher, R, Völzke, H. (Henry), Weissman, M.M. (Myrna M), Werge, T.M. (Thomas), Lewis, C.M. (Cathryn), Levinson, D.F. (Douglas), Breen, G. (Gerome), Børglum, A.D., Sullivan, P.F. (Patrick), Arnau-Soler, A., Adams, M. J., Hayward, C. (Caroline), Thomson, PA, Porteous, D, Campbell, A. (Archie), Smith, B.H. (Blair), Black, C., Padmanabhan, S. (Sandosh), Mcintosh, A.M. (Andrew), Wray, N.R. (Naomi), Ripke, S. (Stephan), Mattheisen, M. (Manuel), Trzaskowski, M., Byrne, E.M. (Enda), Abdellaoui, A. (Abdel), Agerbo, E, Air, T.M., Andlauer, T.F.M., Bacanu, SA, Bækvad-Hansen, M., Beekman, A.T.F. (Aartjan), Bigdeli, TB, Binder, E.B. (Elisabeth), Blackwood, D.H.R. (Douglas), Bryois, J., Buttenschøn, H.N., Bybjerg-Grauholm, J., Cai, N., Castelao, E, Christensen, J.H., Clarke, T.-K., Coleman, J.R.I., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N.J. (Nick), Crawford, G.E., Davies, G. (Gail), Deary, I.J. (Ian), Degenhardt, F., Derks, E.M. (Eske), Direk, N., Dolan, C.V. (Conor), Dunn, EC, Eley, T.C. (T.), Escott-Price, V, Kiadeh, F.F.H., Finucane, HK, Forstner, A.J. (Andreas), Frank, J. (Josef), Gaspar, H.A., Gill, M. (Michael), Goes, F.S., Gordon, S.D., Grove, J. (Jakob), Hall, L.S., Hansen, C.S., Hansen, T.F. (Thomas F), Herms, S. (Stefan), Hickie, I.B. (Ian), Hoffmann, P. (Per), Homuth, G. (Georg), Horn, C., Hottenga, JJ, Hougaard, D.M. (David), Ising, M. (Marcus), Jansen, R, Jorgenson, E, Knowles, J.A. (James A), Kohane, IS, Kraft, J., Kretzschmar, W.W., Krogh, J., Kutalik, Z. (Zoltán), Li, Y. (Yuwen), Lind, P.A. (Penelope), Macintyre, D.J. (Donald J), MacKinnon, D.F., Maier, R.M., Maier, W. (Wolfgang), Marchini, J. (Jonathan), Mbarek, H, McGrath, P., Mcguffin, P. (Peter), Medland, S.E., Mehta, D, Middeldorp, CM, Mihailov, E. (Evelin), Milaneschi, Y. (Yuri), Milani, L. (Lili), Mondimore, F.M., Montgomery, G.W. (Grant), Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M.G., Nyholt, D.R. (Dale), O'Reilly, P.F. (Paul), Oskarsson, H. (Hogni), Owen, M.J., Painter, JN, Pedersen, CB, Pedersen, M.G., Peterson, R.E., Pettersson, E, Peyrot, W.J. (Wouter ), Pistis, G. (Giorgio), Posthuma, D., Quiroz, J.A., Qvist, P., Rice, J.P. (John), Riley, B.P. (Brien), Rivera, M., Mirza, S.S., Schoevers, R. (Robert), Schulte, E.C., Shen, L. (Li), Shi, J. (Julia), Shyn, S.I. (Stanley I), Sigurdsson, E. (Engilbert), Sinnamon, G.C.B., Smit, J.H.M., Smith, D.J. (Derek James), Stefansson, H. (Hreinn), Steinberg, S. (Stacy), Streit, F., Strohmaier, J., Tansey, KE, Teismann, H., Teumer, A. (Alexander), Thompson, W., Thorgeirsson, T.E. (Thorgeir), Traylor, M. (Matthew), Treutlein, J. (Jens), Trubetskoy, V., Uitterlinden, A.G. (André), Umbricht, D., Van der Auwera, S., van Hemert, A.M., Viktorin, A, Visscher, P.M. (Peter), Wang, Y. (Yijing), Webb, BT, Weinsheimer, S.M., Wellmann, J. (Jürgen), Willemsen, G.A.H.M. (Gonneke), Witt, S.H. (Stephanie H), Wu, Y., Xi, HS, Yang, J., Zhang, F. (Feng), Arolt, V, Baune, BT, Berger, K. (Klaus), Boomsma, D.I. (Dorret), Cichon, S. (Sven), Dannlowski, U., de Geus, EJCN, DePaulo, J.R., Domenici, E, Domschke, K., Esko, T. (Tõnu), Grabe, H.J. (Hans Jörgen), Hamilton, S.P. (Steven P), Heath, A.C. (Andrew), Kendler, K. (K.), Kloiber, S, Lewis, G, Li, Q.S., Lucae, S. (Susanne), Madden, P.A. (Pamela), Magnusson, P.K. (Patrik), Martin, N.G. (Nicholas), Metspalu, A. (Andres), Mors, O., Mortensen, P.B., Müller-Myhsok, B., Nordentoft, M, Nöthen, M.M. (Markus), O'Donovan, M. (Michael), Paciga, S.A., Pedersen, N.L. (Nancy), Penninx, B.W.J.H. (Brenda), Perlis, R.H. (Roy H), Porteous, D.J. (David J.), Potash, J.B. (James B), Preisig, M. (Martin), Rietschel, M., Schaefer, C. (Catherine), Schulze, T.G. (Thomas), Smoller, J.W., Zwart, J-A. (John-Anker), Tiemeier, H.W. (Henning), Uher, R, Völzke, H. (Henry), Weissman, M.M. (Myrna M), Werge, T.M. (Thomas), Lewis, C.M. (Cathryn), Levinson, D.F. (Douglas), Breen, G. (Gerome), Børglum, A.D., and Sullivan, P.F. (Patrick)
Abstract: Individual response to stress is correlated with neuroticism and is an important predictor of both neuroticism and the onset of major depressive disorder (MDD). Identification of the genetics underpinning individual differences in response to negative events (stress-sensitivity) may improve our understanding of the molecular pathways involved, and its association with stress-related illnesses. We sought to generate a proxy for stress-sensitivity through modelling the interaction between SNP allele and MDD status on neuroticism score in order to identify genetic variants that contribute to the higher neuroticism seen in individuals with a lifetime diagnosis of d
Published: 2018
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12. Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder

Author: de Jong, S, Abdalla Diniz, MJ, Saloma, A, Gadelha, A, Santoro, ML, Ota, VK, Noto, C, Curtis, C, Newhouse, SJ, Patel, H, Hall, LS, O'Reilly, PF, Belangero, S, Bressan, RA, Breen, G, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, Mcgrath, P, Mcguffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Borglum, AD, Sullivan, PF, Meier, S, Strauss, J, Xu, W, Vincent, JB, Matthews, K, Ferreira, M, O'Dushlaine, C, Purcell, S, Raychaudhuri, S, Ruderfer, DM, Sklar, P, Scott, LJ, Flickinger, M, Burmeister, M, Li, J, Guan, W, Absher, D, Thompson, RC, Meng, FG, Schatzberg, AF, Bunney, WE, Barchas, JD, Watson, SJ, Myers, RM, Akil, H, Boehnke, M, Chambert, K, Moran, J, Scolnick, E, Djurovic, S, Melle, I, Morken, G, Corvin, A, Anjorin, A, Kandaswamy, R, Lawrence, J, McLean, AW, Pickard, BS, Bergen, SE, Nimgaonkar, V, Landen, M, Schalling, M, Osby, U, Backlund, L, Frisen, L, Langstrom, N, Stahl, E, Dobbyn, A, Jamain, S, Etain, B, Bellivier, F, Leber, M, Maaser, A, Fischer, SB, Reinbold, CS, Kittel-Schneider, S, Fullerton, JM, Oruc, L, Para, JG, Mayoral, F, Rivas, F, Czerski, PM, Kammerer-Ciernioch, J, Vedder, H, Borrmann-Hassenbach, M, Pfennig, A, Brennan, P, McKay, JD, Kogevinas, M, Schwarz, M, Schofield, PR, Muehleisen, TW, Schumacher, J, Bauer, M, Wright, A, Mitchell, PB, Hautzinger, M, Kelsoe, JR, Greenwood, TA, Nievergelt, CM, Shilling, PD, Smith, EN, Bloss, CS, Edenberg, HJ, Koller, DL, Gershon, ES, Liu, C, Badner, JA, Scheftner, WA, Lawson, WB, Nwulia, EA, Hipolito, M, Coryell, W, Rice, J, Byerley, W, McMahon, FJ, Lohoff, FW, Zandi, PP, Mahon, PB, McInnis, MG, Zollner, S, Zhang, P, Szelinger, S, St Clair, D, Caesar, S, Gordon-Smith, K, Fraser, C, Green, EK, Grozeva, D, Hamshere, ML, Kirov, G, Nikolov, I, Collier, DA, Elkin, A, Williamson, R, Young, AH, Ferrier, IN, Milanova, V, Alda, M, Cervantes, P, Cruceanu, C, Rouleau, GA, Turecki, G, Paciga, S, Winslow, AR, Grigoroiu-Serbanescu, M, Ophoff, R, Adolfsson, R, Adolfsson, AN, Del-Favero, J, Pato, C, Biernacka, JM, Frye, MA, Morris, D, Schork, NJ, Reif, A, Lissowska, J, Hauser, J, Szeszenia-Dabrowska, N, McGhee, K, Quinn, E, Moskvina, V, Holmans, PA, Farmer, A, Kennedy, JL, Andreassen, OA, Mattingsdal, M, Bass, NJ, Gurling, H, McQuillin, A, Breuer, R, Hultman, C, Lichtenstein, P, Huckins, LM, Leboyer, M, Lathrop, M, Nurnberger, J, Steffens, M, Foroud, TM, Berrettini, WH, Craig, DW, Shi, J, de Jong, S, Abdalla Diniz, MJ, Saloma, A, Gadelha, A, Santoro, ML, Ota, VK, Noto, C, Curtis, C, Newhouse, SJ, Patel, H, Hall, LS, O'Reilly, PF, Belangero, S, Bressan, RA, Breen, G, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, Mcgrath, P, Mcguffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Borglum, AD, Sullivan, PF, Meier, S, Strauss, J, Xu, W, Vincent, JB, Matthews, K, Ferreira, M, O'Dushlaine, C, Purcell, S, Raychaudhuri, S, Ruderfer, DM, Sklar, P, Scott, LJ, Flickinger, M, Burmeister, M, Li, J, Guan, W, Absher, D, Thompson, RC, Meng, FG, Schatzberg, AF, Bunney, WE, Barchas, JD, Watson, SJ, Myers, RM, Akil, H, Boehnke, M, Chambert, K, Moran, J, Scolnick, E, Djurovic, S, Melle, I, Morken, G, Corvin, A, Anjorin, A, Kandaswamy, R, Lawrence, J, McLean, AW, Pickard, BS, Bergen, SE, Nimgaonkar, V, Landen, M, Schalling, M, Osby, U, Backlund, L, Frisen, L, Langstrom, N, Stahl, E, Dobbyn, A, Jamain, S, Etain, B, Bellivier, F, Leber, M, Maaser, A, Fischer, SB, Reinbold, CS, Kittel-Schneider, S, Fullerton, JM, Oruc, L, Para, JG, Mayoral, F, Rivas, F, Czerski, PM, Kammerer-Ciernioch, J, Vedder, H, Borrmann-Hassenbach, M, Pfennig, A, Brennan, P, McKay, JD, Kogevinas, M, Schwarz, M, Schofield, PR, Muehleisen, TW, Schumacher, J, Bauer, M, Wright, A, Mitchell, PB, Hautzinger, M, Kelsoe, JR, Greenwood, TA, Nievergelt, CM, Shilling, PD, Smith, EN, Bloss, CS, Edenberg, HJ, Koller, DL, Gershon, ES, Liu, C, Badner, JA, Scheftner, WA, Lawson, WB, Nwulia, EA, Hipolito, M, Coryell, W, Rice, J, Byerley, W, McMahon, FJ, Lohoff, FW, Zandi, PP, Mahon, PB, McInnis, MG, Zollner, S, Zhang, P, Szelinger, S, St Clair, D, Caesar, S, Gordon-Smith, K, Fraser, C, Green, EK, Grozeva, D, Hamshere, ML, Kirov, G, Nikolov, I, Collier, DA, Elkin, A, Williamson, R, Young, AH, Ferrier, IN, Milanova, V, Alda, M, Cervantes, P, Cruceanu, C, Rouleau, GA, Turecki, G, Paciga, S, Winslow, AR, Grigoroiu-Serbanescu, M, Ophoff, R, Adolfsson, R, Adolfsson, AN, Del-Favero, J, Pato, C, Biernacka, JM, Frye, MA, Morris, D, Schork, NJ, Reif, A, Lissowska, J, Hauser, J, Szeszenia-Dabrowska, N, McGhee, K, Quinn, E, Moskvina, V, Holmans, PA, Farmer, A, Kennedy, JL, Andreassen, OA, Mattingsdal, M, Bass, NJ, Gurling, H, McQuillin, A, Breuer, R, Hultman, C, Lichtenstein, P, Huckins, LM, Leboyer, M, Lathrop, M, Nurnberger, J, Steffens, M, Foroud, TM, Berrettini, WH, Craig, DW, and Shi, J
Abstract: Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree (n ~ 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generations. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity increases over the generations of a family. Joint analyses of rare and common variation may be a powerful way to understand the familial genetics of psychiatric disorders.
Published: 2018

13. Defining the capacity of the lumbosacral network for neuromodulation in humans with spinal cord injury

Author: Krenn, MJ, Gordineer, EA, Tansey, KE, and Stokic, DS
Published: 2024
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14. Testing the principles of Mendelian randomization: Opportunities and complications on a genomewide scale

Author: Taylor, M, primary, Tansey, KE, additional, Lawlor, DA, additional, Bowden, J, additional, Evans, DM, additional, Davey, Smith G, additional, and Timpson, NJ, additional
Published: 2017
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15. A mega-analysis of genome-wide association studies for major depressive disorder

Author: Ripke, S, Wray, NR, Lewis, CM, Hamilton, SP, Weissman, MM, Breen, G, Byrne, EM, Blackwood, DHR, Boomsma, DI, Cichon, S, Heath, AC, Holsboer, F, Lucae, S, Madden, PA, Martin, NG, McGuffin, P, Muglia, P, Noethen, MM, Penninx, BP, Pergadia, ML, Potash, JB, Rietschel, M, Lin, DY, Muller-Myhsok, B, Shi, J, Steinberg, S, Grabe, HJ, Lichtenstein, P, Magnusson, P, Perlis, RH, Preisig, M, Smoller, JW, Stefansson, K, Uher, R, Kutalik, Z, Tansey, KE, Teumer, A, Viktorin, A, Barnes, MR, Bettecken, T, Binder, EB, Breuer, R, Castro, VM, Churchill, SE, Coryell, WH, Craddock, N, Craig, IW, Czamara, D, de Geus, EJC, Degenhardt, F, Farmer, AE, Fava, M, Frank, J, Gainer, VS, Gallagher, PJ, Gordon, SD, Goryachev, S, Gross, M, Guipponi, M, Henders, AK, Herms, S, Hickie, IB, Hoefels, S, Hoogendijk, Witte, Hottenga, JJ (Jouke Jan), Iosifescu, DV, Ising, M, Jones, I, Jones, L, Jung-Ying, T, Knowles, JA, Kohane, IS, Kohli, MA, Korszun, A, Landen, M, Lawson, WB, Lewis, G, MacIntyre, DJ, Maier, W, Mattheisen, M, McGrath, PJ, McIntosh, A, McLean, AW, Middeldorp, CM (Christel), Middleton, L, Montgomery, GM, Murphy, SN, Nauck, M, Nolen, WA, Nyholt, DR, O' Donovan, M, Oskarsson, H, Pedersen, N, Scheftner, WA, Schulz, TG, Shyn, SI, Sigurdsson, E, Slager, SL, Smit, JH, Stefansson, H, Steffens, M, Thorgeirsson, T, Tozzi, F, Treutlein, J, Uhr, M, van den Oord, EJCG (Edwin), Van Grootheest, G, Volzke, H, Weilburg, JB, Willemsen, G, Zitman, FG, Neale, BM, Daly, M, Levinson, DF, Sullivan, PF, Psychiatry, Epidemiology, and Child and Adolescent Psychiatry / Psychology
Published: 2013

16. Common genetic variation and antidepressant efficacy in major depressive disorder : a meta-analysis of three genome-wide pharmacogenetic studies

Author: Uher, R, Tansey, KE, Rietschel, M, Henigsberg, N, Maier, W, Mors, Ole, Hauser, J, Placentino, A, Souery, D, Farmer, A, Aitchinson, KJ, Craig, I, McGuffin, P, Lewis, CM, Ising, M, Lucae, S, Binder, EB, Kloiber, S, Holsboer, F, Müller-Myhsok, B, Ripke, S, Hamilton, SP, Laje, G, McMahon, FJ, Fava, M, Rush, AJ, and Perlis, RH
Subjects: Oncology, Adult, Male, medicine.medical_specialty, MEDLINE, Genome-wide association study, Citalopram, Polymorphism, Single Nucleotide, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Genetic variation, medicine, Humans, Psychiatry, antidepressive agents, genome, genetics, major depressive disorder, pharmacogenetics, mars, Psychiatric Status Rating Scales, Depressive Disorder, Major, Remission Induction, Genetic Variation, Middle Aged, medicine.disease, 3. Good health, 030227 psychiatry, Europe, Psychiatry and Mental health, Treatment Outcome, Pharmacogenetics, Meta-analysis, Major depressive disorder, Antidepressant, Antidepressive Agents, Second-Generation, Chromosomes, Human, Pair 5, Female, Psychology, 030217 neurology & neurosurgery, Imputation (genetics), Genome-Wide Association Study
Abstract: Objective Indirect evidence suggests that common genetic variation contributes to individual differences in antidepressant efficacy among individuals with major depressive disorder, but previous studies may have been underpowered to detect these effects. Method A meta-analysis was performed on data from three genome-wide pharmacogenetic studies (the Genome-Based Therapeutic Drugs for Depression [GENDEP] project, the Munich Antidepressant Response Signature [MARS] project, and the Sequenced Treatment Alternatives to Relieve Depression [STAR*D] study), which included 2, 256 individuals of Northern European descent with major depressive disorder, and antidepressant treatment outcomes were prospectively collected. After imputation, 1.2 million single-nucleotide polymorphisms were tested, capturing common variation for association with symptomatic improvement and remission after up to 12 weeks of antidepressant treatment. Results No individual association met a genome-wide threshold for statistical significance in the primary analyses. A polygenic score derived from a meta-analysis of GENDEP and MARS participants accounted for up to approximately 1.2% of the variance in outcomes in STAR*D, suggesting a weakly concordant signal distributed over many polymorphisms. An analysis restricted to 1, 354 individuals treated with citalopram (STAR*D) or escitalopram (GENDEP) identified an intergenic region on chromosome 5 associated with early improvement after 2 weeks of treatment. Conclusions Despite increased statistical power accorded by meta-analysis, the authors identified no reliable predictors of antidepressant treatment outcome, although they did identify modest, direct evidence that common genetic variation contributes to individual differences in antidepressant response.
Published: 2013

17. Genetic predictors of response to serotonergic and noradrenergic antidepressants in major depressive disorder: a genome-wide analysis of individual-level data and a meta-analysis.

Author: Hay, PJ, Tansey, KE, Guipponi, M, Perroud, N, Bondolfi, G, Domenici, E, Evans, D, Hall, SK, Hauser, J, Henigsberg, N, Hu, X, Jerman, B, Maier, W, Mors, O, O'Donovan, M, Peters, TJ, Placentino, A, Rietschel, M, Souery, D, Aitchison, KJ, Craig, I, Farmer, A, Wendland, JR, Malafosse, A, Holmans, P, Lewis, G, Lewis, CM, Stensbøl, TB, Kapur, S, McGuffin, P, Uher, R, Hay, PJ, Tansey, KE, Guipponi, M, Perroud, N, Bondolfi, G, Domenici, E, Evans, D, Hall, SK, Hauser, J, Henigsberg, N, Hu, X, Jerman, B, Maier, W, Mors, O, O'Donovan, M, Peters, TJ, Placentino, A, Rietschel, M, Souery, D, Aitchison, KJ, Craig, I, Farmer, A, Wendland, JR, Malafosse, A, Holmans, P, Lewis, G, Lewis, CM, Stensbøl, TB, Kapur, S, McGuffin, P, and Uher, R
Abstract: BACKGROUND: It has been suggested that outcomes of antidepressant treatment for major depressive disorder could be significantly improved if treatment choice is informed by genetic data. This study aims to test the hypothesis that common genetic variants can predict response to antidepressants in a clinically meaningful way. METHODS AND FINDINGS: The NEWMEDS consortium, an academia-industry partnership, assembled a database of over 2,000 European-ancestry individuals with major depressive disorder, prospectively measured treatment outcomes with serotonin reuptake inhibiting or noradrenaline reuptake inhibiting antidepressants and available genetic samples from five studies (three randomized controlled trials, one part-randomized controlled trial, and one treatment cohort study). After quality control, a dataset of 1,790 individuals with high-quality genome-wide genotyping provided adequate power to test the hypotheses that antidepressant response or a clinically significant differential response to the two classes of antidepressants could be predicted from a single common genetic polymorphism. None of the more than half million genetic markers significantly predicted response to antidepressants overall, serotonin reuptake inhibitors, or noradrenaline reuptake inhibitors, or differential response to the two types of antidepressants (genome-wide significance p<5×10(-8)). No biological pathways were significantly overrepresented in the results. No significant associations (genome-wide significance p<5×10(-8)) were detected in a meta-analysis of NEWMEDS and another large sample (STAR*D), with 2,897 individuals in total. Polygenic scoring found no convergence among multiple associations in NEWMEDS and STAR*D. CONCLUSIONS: No single common genetic variant was associated with antidepressant response at a clinically relevant level in a European-ancestry cohort. Effects specific to particular antidepressant drugs could not be investigated in the current study. Please see lat
Published: 2012

18. Synchronous stimulation and monitoring of soleus H reflex during robotic body weight-supported ambulation in subjects with spinal cord injury.

Author: Querry RG, Pacheco F, Annaswamy T, Goetz L, Winchester PK, and Tansey KE
Published: 2008
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19. Genetic predictors of response to serotonergic and noradrenergic antidepressants in major depressive disorder: a genome-wide analysis of individual-level data and a meta-analysis.

Author: Tansey KE, Guipponi M, Perroud N, Bondolfi G, Domenici E, Evans D, Hall SK, Hauser J, Henigsberg N, Hu X, Jerman B, Maier W, Mors O, O'Donovan M, Peters TJ, Placentino A, Rietschel M, Souery D, Aitchison KJ, and Craig I
Abstract: Background: It has been suggested that outcomes of antidepressant treatment for major depressive disorder could be significantly improved if treatment choice is informed by genetic data. This study aims to test the hypothesis that common genetic variants can predict response to antidepressants in a clinically meaningful way.Methods and Findings: The NEWMEDS consortium, an academia-industry partnership, assembled a database of over 2,000 European-ancestry individuals with major depressive disorder, prospectively measured treatment outcomes with serotonin reuptake inhibiting or noradrenaline reuptake inhibiting antidepressants and available genetic samples from five studies (three randomized controlled trials, one part-randomized controlled trial, and one treatment cohort study). After quality control, a dataset of 1,790 individuals with high-quality genome-wide genotyping provided adequate power to test the hypotheses that antidepressant response or a clinically significant differential response to the two classes of antidepressants could be predicted from a single common genetic polymorphism. None of the more than half million genetic markers significantly predicted response to antidepressants overall, serotonin reuptake inhibitors, or noradrenaline reuptake inhibitors, or differential response to the two types of antidepressants (genome-wide significance p<5×10(-8)). No biological pathways were significantly overrepresented in the results. No significant associations (genome-wide significance p<5×10(-8)) were detected in a meta-analysis of NEWMEDS and another large sample (STAR*D), with 2,897 individuals in total. Polygenic scoring found no convergence among multiple associations in NEWMEDS and STAR*D.Conclusions: No single common genetic variant was associated with antidepressant response at a clinically relevant level in a European-ancestry cohort. Effects specific to particular antidepressant drugs could not be investigated in the current study. Please see later in the article for the Editors' Summary. [ABSTRACT FROM AUTHOR]
Published: 2012
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20. Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk.

Author: Dimitriadis SI, Perry G, Lancaster TM, Tansey KE, Singh KD, Holmans P, Pocklington A, Davey Smith G, Zammit S, Hall J, O'Donovan MC, Owen MJ, Jones DK, and Linden DE
Subjects: Young Adult, Humans, Genetic Predisposition to Disease genetics, Brain diagnostic imaging, Risk Factors, Genotype, Schizophrenia diagnostic imaging, Schizophrenia genetics
Abstract: Research studies based on tractography have revealed a prominent reduction of asymmetry in some key white-matter tracts in schizophrenia (SCZ). However, we know little about the influence of common genetic risk factors for SCZ on the efficiency of routing on structural brain networks (SBNs). Here, we use a novel recall-by-genotype approach, where we sample young adults from a population-based cohort (ALSPAC:N genotyped = 8,365) based on their burden of common SCZ risk alleles as defined by polygenic risk score (PRS). We compared 181 individuals at extremes of low (N = 91) or high (N = 90) SCZ-PRS under a robust diffusion MRI-based graph theoretical SBN framework. We applied a semi-metric analysis revealing higher SMR values for the high SCZ-PRS group compared with the low SCZ-PRS group in the left hemisphere. Furthermore, a hemispheric asymmetry index showed a higher leftward preponderance of indirect connections for the high SCZ-PRS group compared with the low SCZ-PRS group (PFDR < 0.05). These findings might indicate less efficient structural connectivity in the higher genetic risk group. This is the first study in a population-based sample that reveals differences in the efficiency of SBNs associated with common genetic risk variants for SCZ., (© The Author(s) 2022. Published by Oxford University Press.)
Published: 2023
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21. Neuromodulation with transcutaneous spinal stimulation reveals different groups of motor profiles during robot-guided stepping in humans with incomplete spinal cord injury.

Author: Krenn MJ, White JM, Stokic DS, and Tansey KE
Subjects: Male, Humans, Walking physiology, Electromyography, Muscle, Skeletal physiology, Spinal Cord physiology, Robotics, Spinal Cord Injuries, Spinal Cord Stimulation
Abstract: Neuromodulation via spinal stimulation has been investigated for improving motor function and reducing spasticity after spinal cord injury (SCI) in humans. Despite the reported heterogeneity of outcomes, few investigations have attempted to discern commonalities among individual responses to neuromodulation, especially the impact of stimulation frequencies. Here, we examined how exposure to continuous lumbosacral transcutaneous spinal stimulation (TSS) across a range of frequencies affects robotic torques and EMG patterns during stepping in a robotic gait orthosis on a motorized treadmill. We studied nine chronic motor-incomplete SCI individuals (8/1 AIS-C/D, 8 men) during robot-guided stepping with body-weight support without and with TSS applied at random frequencies between 1 and up to 100 Hz at a constant, individually selected stimulation intensity below the common motor threshold for posterior root reflexes. The hip and knee robotic torques needed to maintain the predefined stepping trajectory and EMG in eight bilateral leg muscles were recorded. We calculated the standardized mean difference between the stimulation conditions grouped into frequency bins and the no stimulation condition to determine changes in the normalized torques and the average EMG envelopes. We found heterogeneous changes in robotic torques across individuals. Agglomerative clustering of robotic torques identified four groups wherein the patterns of changes differed in magnitude and direction depending mainly on the stimulation frequency and stance/swing phase. On one end of the spectrum, the changes in robotic torques were greater with increasing stimulation frequencies (four participants), which coincided with a decrease in EMG, mainly due to the reduction of clonogenic motor output in the lower leg muscles. On the other end, we found an inverted u-shape change in torque over the mid-frequency range along with an increase in EMG, reflecting the augmentation of gait-related physiological (two participants) or pathophysiological (one participant) output. We conclude that TSS during robot-guided stepping reveals different frequency-dependent motor profiles among individuals with chronic motor incomplete SCI. This suggests the need for a better understanding and characterization of motor control profiles in SCI when applying TSS as a therapeutic intervention for improving gait., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
Published: 2023
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22. Soleus H and Lower Limb Posterior Root Muscle Reflexes During Stepping After Incomplete SCI.

Author: Tansey KE, Farrell BJ, Bruce JA, and McKay WB
Abstract: The goal of this study was to examine and compare the step cycle related modulation of the soleus H and posterior root muscle (PRM) reflexes in subjects with and without spinal cord injury. Ten subjects without neurological injury and fifteen subjects with spinal cord injury (SCI) underwent soleus H reflex and lower limb PRM reflex testing while standing and stepping in a robotic gait orthosis. Reflex amplitudes were evaluated during standing, mid stance and mid swing to determine if speed and/or injury altered step cycle related neuromodulation. H and PRM reflexes in the soleus underwent step cycle related modulation in injured and uninjured subjects though the degree of modulation differed between the two reflexes with the H reflex showing more step cycle related modulation. We found in the SCI group that both the soleus H and soleus PRM reflex amplitudes were higher relative to the non-injured group and modulated less during the step cycle. We also found that modulation of the soleus H reflex, but not soleus PRM reflex, correlated to the lower extremity motor scores in individuals with SCI. Our evidence suggests that the inability to provide appropriate step cycle related reflex modulation may be due to decreased supra-spinal regulation of motoneuron and spinal excitability and could be an indicator of the severity of injury as it relates to clinically measured lower extremity motor scores., Competing Interests: The authors declare 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 © 2022 Tansey, Farrell, Bruce and McKay.)
Published: 2022
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23. Global Brain Flexibility During Working Memory Is Reduced in a High-Genetic-Risk Group for Schizophrenia.

Author: Dimitriadis SI, Lancaster TM, Perry G, Tansey KE, Jones DK, Singh KD, Zammit S, Smith GD, Hall J, O'Donovan MC, Owen MJ, and Linden DE
Subjects: Brain, Female, Genetic Predisposition to Disease, Humans, Longitudinal Studies, Male, Memory, Short-Term physiology, Schizophrenia
Abstract: Background: Altered functional brain connectivity has been proposed as an intermediate phenotype between genetic risk loci and clinical expression of schizophrenia. Genetic high-risk groups of healthy subjects are particularly suited for the investigation of this proposition because they can be tested in the absence of medication or other secondary effects of schizophrenia., Methods: Here, we applied dynamic functional connectivity analysis to functional magnetic resonance imaging data to reveal the reconfiguration of brain networks during a cognitive task. We recruited healthy carriers of common risk variants using the recall-by-genotype design. We assessed 197 individuals: 99 individuals (52 female, 47 male) with low polygenic risk scores (schizophrenia risk profile scores [SCZ-PRSs]) and 98 individuals (52 female, 46 male) with high SCZ-PRSs from both tails of the SCZ-PRS distribution from a genotyped population cohort, the Avon Longitudinal Study of Parents and Children (N = 8169). We compared groups both on conventional brain activation profiles, using the general linear model of the experiment, and on the neural flexibility index, which quantifies how frequent a brain region's community affiliation changes over experimental time., Results: Behavioral performance and standard brain activation profiles did not differ significantly between groups. High SCZ-PRS was associated with reduced flexibility index and network modularity across n-back levels. The whole-brain flexibility index and that of the frontoparietal working memory network was associated with n-back performance. We identified a dynamic network phenotype related to high SCZ-PRS., Conclusions: Such neurophysiological markers can become important for the elucidation of biological mechanisms of schizophrenia and, particularly, the associated cognitive deficit., (Copyright © 2021. Published by Elsevier Inc.)
Published: 2021
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24. Genetic risk for schizophrenia is associated with altered visually-induced gamma band activity: evidence from a population sample stratified polygenic risk.

Author: Dimitriadis SI, Perry G, Foley SF, Tansey KE, Jones DK, Holmans P, Zammit S, Hall J, O'Donovan MC, Owen MJ, Singh KD, and Linden DE
Subjects: Birth Cohort, Gamma Rhythm, Humans, Magnetoencephalography, Risk Factors, Schizophrenia genetics
Abstract: Gamma oscillations (30-90 Hz) have been proposed as a signature of cortical visual information processing, particularly the balance between excitation and inhibition, and as a biomarker of neuropsychiatric diseases. Magnetoencephalography (MEG) provides highly reliable visual-induced gamma oscillation estimates, both at sensor and source level. Recent studies have reported a deficit of visual gamma activity in schizophrenia patients, in medication naive subjects, and high-risk clinical participants, but the genetic contribution to such a deficit has remained unresolved. Here, for the first time, we use a genetic risk score approach to assess the relationship between genetic risk for schizophrenia and visual gamma activity in a population-based sample drawn from a birth cohort. We compared visual gamma activity in a group (N = 104) with a high genetic risk profile score for schizophrenia (SCZ-PRS) to a group with low SCZ-PRS (N = 99). Source-reconstructed V1 activity was extracted using beamformer analysis applied to MEG recordings using individual MRI scans. No group differences were found in the induced gamma peak amplitude or peak frequency. However, a non-parametric statistical contrast of the response spectrum revealed more robust group differences in the amplitude of high-beta/gamma power across the frequency range, suggesting that overall spectral shape carries important biological information beyond the individual frequency peak. Our findings show that changes in gamma band activity correlate with liability to schizophrenia and suggest that the index changes to synaptic function and neuronal firing patterns that are of pathophysiological relevance rather than consequences of the disorder., (© 2021. The Author(s).)
Published: 2021
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25. Deleterious effects of whole-body vibration on the spine: A review of in vivo, ex vivo, and in vitro models.

Author: Patterson F, Miralami R, Tansey KE, Prabhu RK, and Priddy LB
Subjects: Humans, Spine, Vibration adverse effects, Low Back Pain etiology, Occupational Exposure adverse effects, Spinal Diseases
Abstract: Occupational exposure to whole-body vibration is associated with the development of musculoskeletal, neurological, and other ailments. Low back pain and other spine disorders are prevalent among those exposed to whole-body vibration in occupational and military settings. Although standards for limiting exposure to whole-body vibration have been in place for decades, there is a lack of understanding of whole-body vibration-associated risks among safety and healthcare professionals. Consequently, disorders associated with whole-body vibration exposure remain prevalent in the workforce and military. The relationship between whole-body vibration and low back pain in humans has been established largely through cohort studies, for which vibration inputs that lead to symptoms are rarely, if ever, quantified. This gap in knowledge highlights the need for the development of relevant in vivo, ex vivo, and in vitro models to study such pathologies. The parameters of vibrational stimuli (eg, frequency and direction) play critical roles in such pathologies, but the specific cause-and-effect relationships between whole-body vibration and spinal pathologies remain mostly unknown. This paper provides a summary of whole-body vibration parameters; reviews in vivo, ex vivo, and in vitro models for spinal pathologies resulting from whole-body vibration; and offers suggestions to address the gaps in translating injury biomechanics data to inform clinical practice., (© 2021 The Authors. Animal Models and Experimental Medicine published by John Wiley & Sons Australia, Ltd on behalf of The Chinese Association for Laboratory Animal Sciences.)
Published: 2021
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26. The Expedited International Standards for Neurological Classification of Spinal Cord Injury (E-ISNCSCI).

Author: Burns SP and Tansey KE
Subjects: Clinical Protocols, Humans, Neurologic Examination standards, Practice Guidelines as Topic standards, Spinal Cord Injuries classification, Spinal Cord Injuries diagnosis
Published: 2020
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27. 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, Alnæs D, Amlien IK, Andersson M, Ard T, Armstrong NJ, Ashley-Koch A, Atkins JR, Bernard M, Brouwer RM, Buimer EEL, Bülow R, Bürger 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, Doan NT, Dohm K, Ehrlich S, Engelbrecht HR, 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 JJ, 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, Krämer 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, Mühleisen TW, Müller-Myhsok B, Najt P, Nakahara S, Nho K, Olde Loohuis LM, Orfanos DP, Pearson JF, Pitcher TL, Pütz B, Quidé 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, Sønderby IE, Sprooten E, Tansey KE, Teumer A, Thalamuthu A, Tordesillas-Gutiérrez 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 MJ, 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, Häusler AN, Heindel W, Ho BC, Hoffmann WU, Holsboer F, Homuth G, Hosten N, Jack CR Jr, Jang M, Jansen A, Kimbrel NA, Kolskår K, Koops S, Krug A, Lim KO, Luykx JJ, Mathalon DH, Mather KA, Mattay VS, Matthews S, Mayoral Van Son J, McEwen SC, Melle I, Morris DW, Mueller BA, Nauck M, Nordvik JE, Nöthen MM, O'Leary DS, Opel N, Martinot MP, 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, Desrivières S, Donohoe G, Espeseth T, Fernández G, Fisher SE, Flor H, Forstner AJ, Francks C, Franke B, Glahn DC, Gollub RL, Grabe HJ, Gruber O, Håberg AK, Hariri AR, Hartman CA, Hashimoto R, Heinz A, Henskens FA, Hillegers MHJ, Hoekstra PJ, Holmes AJ, Hong LE, Hopkins WD, Hulshoff Pol HE, Jernigan TL, Jönsson EG, Kahn RS, Kennedy MA, Kircher TTJ, Kochunov P, Kwok JBJ, Le Hellard S, Loughland CM, Martin NG, Martinot JL, 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, Sämann 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, Völzke H, Walter H, Weber B, Weinberger DR, Wright MJ, Zhou J, Stein JL, Thompson PM, and Medland SE
Subjects: Attention Deficit Disorder with Hyperactivity genetics, Brain Mapping, Cognition, Genetic Loci, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Organ Size genetics, Parkinson Disease genetics, Cerebral Cortex anatomy & histology, Genetic Variation
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., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)
Published: 2020
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28. The Relationship Between Polygenic Risk Scores and Cognition in Schizophrenia.

Author: Richards AL, Pardiñas AF, Frizzati A, Tansey KE, Lynham AJ, Holmans P, Legge SE, Savage JE, Agartz I, Andreassen OA, Blokland GAM, Corvin A, Cosgrove D, Degenhardt F, Djurovic S, Espeseth T, Ferraro L, Gayer-Anderson C, Giegling I, van Haren NE, Hartmann AM, Hubert JJ, Jönsson EG, Konte B, Lennertz L, Olde Loohuis LM, Melle I, Morgan C, Morris DW, Murray RM, Nyman H, Ophoff RA, van Os J, Petryshen TL, Quattrone D, Rietschel M, Rujescu D, Rutten BPF, Streit F, Strohmaier J, Sullivan PF, Sundet K, Wagner M, Escott-Price V, Owen MJ, Donohoe G, O'Donovan MC, and Walters JTR
Subjects: Datasets as Topic, Humans, Multifactorial Inheritance, Bipolar Disorder genetics, Depressive Disorder, Major genetics, Educational Status, Genome-Wide Association Study, Intelligence genetics, Psychotic Disorders genetics, Schizophrenia genetics
Abstract: Background: Cognitive impairment is a clinically important feature of schizophrenia. Polygenic risk score (PRS) methods have demonstrated genetic overlap between schizophrenia, bipolar disorder (BD), major depressive disorder (MDD), educational attainment (EA), and IQ, but very few studies have examined associations between these PRS and cognitive phenotypes within schizophrenia cases., Methods: We combined genetic and cognitive data in 3034 schizophrenia cases from 11 samples using the general intelligence factor g as the primary measure of cognition. We used linear regression to examine the association between cognition and PRS for EA, IQ, schizophrenia, BD, and MDD. The results were then meta-analyzed across all samples. A genome-wide association studies (GWAS) of cognition was conducted in schizophrenia cases., Results: PRS for both population IQ (P = 4.39 × 10-28) and EA (P = 1.27 × 10-26) were positively correlated with cognition in those with schizophrenia. In contrast, there was no association between cognition in schizophrenia cases and PRS for schizophrenia (P = .39), BD (P = .51), or MDD (P = .49). No individual variant approached genome-wide significance in the GWAS., Conclusions: Cognition in schizophrenia cases is more strongly associated with PRS that index cognitive traits in the general population than PRS for neuropsychiatric disorders. This suggests the mechanisms of cognitive variation within schizophrenia are at least partly independent from those that predispose to schizophrenia diagnosis itself. Our findings indicate that this cognitive variation arises at least in part due to genetic factors shared with cognitive performance in populations and is not solely due to illness or treatment-related factors, although our findings are consistent with important contributions from these factors., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.)
Published: 2020
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29. Differential cardiovascular responses to cutaneous afferent subtypes in a nociceptive intersegmental spinal reflex.

Author: Lee HJ, White JM, Chung J, Malone P, DeWeerth SP, and Tansey KE
Subjects: Animals, Blood Pressure physiology, Electric Stimulation, Female, Heart Rate physiology, Muscles physiology, Nerve Fibers, Myelinated physiology, Rats, Long-Evans, Cardiovascular System metabolism, Nociception physiology, Reflex physiology, Skin innervation, Spinal Cord physiology
Abstract: Electrical stimulation to segmental dorsal cutaneous nerves (DCNs) activates a nociceptive sensorimotor reflex and the same afferent stimulation also evokes blood pressure (BP) and heart rate (HR) responses in rats. To investigate the relationship between those cardiovascular responses and the activation of nociceptive afferents, we analyzed BP and HR responses to electrical stimulations at each DCN from T6 to L1 at 0.5 mA to activate A-fiber alone or 5 mA to activate both A- and C-fibers at different frequencies. Evoked cardiovascular responses showed a decrease and then an increase in BP and an increase and then a plateau in HR. Segmentally, both cardiovascular responses tended to be larger when evoked from the more rostral DCNs. Stimulation frequency had a larger effect on cardiovascular responses than the rostrocaudal level of the DCN input. Stimulation strength showed a large effect on BP changes dependent on C-fibers whereas HR changes were dependent on A-fibers. Additional A-fiber activation by stimulating up to 4 adjacent DCNs concurrently, but only at 0.5 mA, affected HR but not BP. These data support that cutaneous nociceptive afferent subtypes preferentially contribute to different cardiovascular responses, A-fibers to HR and C-fibers to BP, with temporal (stimulation frequency) and spatial (rostrocaudal level) dynamics.
Published: 2019
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30. Central Plasticity of Cutaneous Afferents Is Associated with Nociceptive Hyperreflexia after Spinal Cord Injury in Rats.

Author: Lee HJ, Malone PS, Chung J, White JM, Wilson N, Tidwell J, and Tansey KE
Subjects: Animals, Electric Stimulation methods, Female, Rats, Long-Evans, Skin physiopathology, Spinal Cord physiopathology, Muscle, Skeletal physiopathology, Reflex physiology, Reflex, Abnormal physiology, Spinal Cord Injuries physiopathology
Abstract: Electrical stimulations of dorsal cutaneous nerves (DCNs) at each lumbothoracic spinal level produce the bilateral cutaneus trunci muscle (CTM) reflex responses which consist of two temporal components: an early and late responses purportedly mediated by A δ and C fibers, respectively. We have previously reported central projections of DCN A and C fibers and demonstrated that different projection patterns of those afferent types contributed to the somatotopic organization of CTM reflex responses. Unilateral hemisection spinal cord injury (SCI) was made at T10 spinal segments to investigate the plasticity of early and late CTM responses 6 weeks after injury. Both early and late responses were drastically increased in response to both ipsi- and contralateral DCN stimulations both above (T6 and T8) and below (T12 and L1) the levels of injury demonstrating that nociceptive hyperreflexia developed at 6 weeks following hemisection SCI. We also found that DCN A and C fibers centrally sprouted, expanded their projection areas, and increased synaptic terminations in both T7 and T13, which correlated with the size of hemisection injury. These data demonstrate that central sprouting of cutaneous afferents away from the site of injury is closely associated with enhanced responses of intraspinal signal processing potentially contributing to nociceptive hyperreflexia following SCI., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2019 Hyun Joon Lee et al.)
Published: 2019
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31. Application of electrophysiological measures in spinal cord injury clinical trials: a narrative review.

Author: Hubli M, Kramer JLK, Jutzeler CR, Rosner J, Furlan JC, Tansey KE, and Schubert M
Subjects: Clinical Trials as Topic methods, Electrophysiological Phenomena physiology, Humans, Patient Selection, Recovery of Function physiology, Reflex physiology, Spinal Cord Injuries therapy, Evoked Potentials, Motor physiology, Evoked Potentials, Somatosensory physiology, Spinal Cord Injuries diagnosis, Spinal Cord Injuries physiopathology
Abstract: Study Design: Narrative review., Objectives: To discuss how electrophysiology may contribute to future clinical trials in spinal cord injury (SCI) in terms of: (1) improvement of SCI diagnosis, patient stratification and determination of exclusion criteria; (2) the assessment of adverse events; and (3) detection of therapeutic effects following an intervention., Methods: An international expert panel for electrophysiological measures in SCI searched and discussed the literature focused on the topic., Results: Electrophysiology represents a valid method to detect, track, and quantify readouts of nerve functions including signal conduction, e.g., evoked potentials testing long spinal tracts, and neural processing, e.g., reflex testing. Furthermore, electrophysiological measures can predict functional outcomes and thereby guide rehabilitation programs and therapeutic interventions for clinical studies., Conclusion: Objective and quantitative measures of sensory, motor, and autonomic function based on electrophysiological techniques are promising tools to inform and improve future SCI trials. Complementing clinical outcome measures, electrophysiological recordings can improve the SCI diagnosis and patient stratification, as well as the detection of both beneficial and adverse events. Specifically composed electrophysiological measures can be used to characterize the topography and completeness of SCI and reveal neuronal integrity below the lesion, a prerequisite for the success of any interventional trial. Further validation of electrophysiological tools with regard to their validity, reliability, and sensitivity are needed in order to become routinely applied in clinical SCI trials.
Published: 2019
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32. Convergent Evidence That ZNF804A Is a Regulator of Pre-messenger RNA Processing and Gene Expression.

Author: Chapman RM, Tinsley CL, Hill MJ, Forrest MP, Tansey KE, Pardiñas AF, Rees E, Doyle AM, Wilkinson LS, Owen MJ, O'Donovan MC, and Blake DJ
Subjects: Autism Spectrum Disorder genetics, Bipolar Disorder genetics, CELF Proteins metabolism, Cell Line, Tumor, Gene Knockdown Techniques, Humans, Kruppel-Like Transcription Factors metabolism, Muscle Proteins metabolism, RNA Splicing Factors metabolism, RNA-Binding Proteins metabolism, Gene Expression Regulation genetics, Kruppel-Like Transcription Factors genetics, RNA Precursors metabolism, RNA Splicing genetics, RNA, Messenger metabolism, Schizophrenia genetics
Abstract: Genome-wide association studies have linked common variation in ZNF804A with an increased risk of schizophrenia. However, little is known about the biology of ZNF804A and its role in schizophrenia. Here, we investigate the function of ZNF804A using a variety of complementary molecular techniques. We show that ZNF804A is a nuclear protein that interacts with neuronal RNA splicing factors and RNA-binding proteins including RBFOX1, which is also associated with schizophrenia, CELF3/4, components of the ubiquitin-proteasome system and the ZNF804A paralog, GPATCH8. GPATCH8 also interacts with splicing factors and is localized to nuclear speckles indicative of a role in pre-messenger RNA (mRNA) processing. Sequence analysis showed that GPATCH8 contains ultraconserved, alternatively spliced poison exons that are also regulated by RBFOX proteins. ZNF804A knockdown in SH-SY5Y cells resulted in robust changes in gene expression and pre-mRNA splicing converging on pathways associated with nervous system development, synaptic contact, and cell adhesion. We observed enrichment (P = 1.66 × 10-9) for differentially spliced genes in ZNF804A-depleted cells among genes that contain RBFOX-dependent alternatively spliced exons. Differentially spliced genes in ZNF804A-depleted cells were also enriched for genes harboring de novo loss of function mutations in autism spectrum disorder (P = 6.25 × 10-7, enrichment 2.16) and common variant alleles associated with schizophrenia (P = .014), bipolar disorder and schizophrenia (P = .003), and autism spectrum disorder (P = .005). These data suggest that ZNF804A and its paralogs may interact with neuronal-splicing factors and RNA-binding proteins to regulate the expression of a subset of synaptic and neurodevelopmental genes., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.)
Published: 2019
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33. Temporal and spatial dynamics of spinal sensorimotor processing in an intersegmental cutaneous nociceptive reflex.

Author: White JM, Lee HJ, Malone P, DeWeerth SP, and Tansey KE
Subjects: Animals, Electric Stimulation, Female, Rats, Rats, Long-Evans, Back Muscles physiology, Evoked Potentials physiology, Habituation, Psychophysiologic physiology, Nerve Fibers, Myelinated physiology, Nerve Fibers, Unmyelinated physiology, Nociception physiology, Reflex physiology, Spinal Cord physiology
Abstract: The cutaneus trunci muscle (CTM) reflex produces a skin "shrug" in response to pinch on a rat's back through a three-part neural circuit: 1 ) A-fiber and C-fiber afferents in segmental dorsal cutaneous nerves (DCNs) from lumbar to cervical levels, 2 ) ascending propriospinal interneurons, and 3 ) the CTM motoneuron pool located at the cervicothoracic junction. We recorded neurograms from a CTM nerve branch in response to electrical stimulation. The pulse trains were delivered at multiple DCNs (T 6 -L 1 ), on both sides of the midline, at two stimulus strengths (0.5 or 5 mA, to activate Aδ fibers or Aδ and C fibers, respectively) and four stimulation frequencies (1, 2, 5, or 10 Hz) for 20 s. We quantified both the temporal dynamics (i.e., latency, sensitization, habituation, and frequency dependence) and the spatial dynamics (spinal level) of the reflex. The evoked responses were time-windowed into Early, Mid, Late, and Ongoing phases, of which the Mid phase, between the Early (Aδ fiber mediated) and Late (C fiber mediated) phases, has not been previously identified. All phases of the response varied with stimulus strength, frequency, history, and DCN level/side stimulated. In addition, we observed nociceptive characteristics like C fiber-mediated sensitization (wind-up) and habituation. Finally, the range of latencies in the ipsilateral responses were not very large rostrocaudally, suggesting a myelinated neural path within the ipsilateral spinal cord for at least the A fiber-mediated Early-phase response. Overall, these results demonstrate that the CTM reflex shares the temporal dynamics in other nociceptive reflexes and exhibits spatial (segmental and lateral) dynamics not seen in those reflexes. NEW & NOTEWORTHY We have physiologically studied an intersegmental reflex exploring detailed temporal, stimulus strength-based, stimulation history-dependent, lateral and segmental quantification of the reflex responses to cutaneous nociceptive stimulations. We found several physiological features in this reflex pathway, e.g., wind-up, latency changes, and somatotopic differences. These physiological observations allow us to understand how the anatomy of this reflex may be organized. We have also identified a new phase of this reflex, termed the "mid" response.
Published: 2019
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34. Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Author: Turcot V, Lu Y, Highland HM, Schurmann C, Justice AE, Fine RS, Bradfield JP, Esko T, Giri A, Graff M, Guo X, Hendricks AE, Karaderi T, Lempradl A, Locke AE, Mahajan A, Marouli E, Sivapalaratnam S, Young KL, Alfred T, Feitosa MF, Masca NGD, Manning AK, Medina-Gomez C, Mudgal P, Ng MCY, Reiner AP, Vedantam S, Willems SM, Winkler TW, Abecasis G, Aben KK, Alam DS, Alharthi SE, Allison M, Amouyel P, Asselbergs FW, Auer PL, Balkau B, Bang LE, Barroso I, Bastarache L, Benn M, Bergmann S, Bielak LF, Blüher M, Boehnke M, Boeing H, Boerwinkle E, Böger CA, Bork-Jensen J, Bots ML, Bottinger EP, Bowden DW, Brandslund I, Breen G, Brilliant MH, Broer L, Brumat M, Burt AA, Butterworth AS, Campbell PT, Cappellani S, Carey DJ, Catamo E, Caulfield MJ, Chambers JC, Chasman DI, Chen YI, Chowdhury R, Christensen C, Chu AY, Cocca M, Collins FS, Cook JP, Corley J, Galbany JC, Cox AJ, Crosslin DS, Cuellar-Partida G, D'Eustacchio A, Danesh J, Davies G, Bakker PIW, Groot MCH, Mutsert R, Deary IJ, Dedoussis G, Demerath EW, Heijer M, Hollander AI, Ruijter HM, Dennis JG, Denny JC, Di Angelantonio E, Drenos F, Du M, Dubé MP, Dunning AM, Easton DF, Edwards TL, Ellinghaus D, Ellinor PT, Elliott P, Evangelou E, Farmaki AE, Farooqi IS, Faul JD, Fauser S, Feng S, Ferrannini E, Ferrieres J, Florez JC, Ford I, Fornage M, Franco OH, Franke A, Franks PW, Friedrich N, Frikke-Schmidt R, Galesloot TE, Gan W, Gandin I, Gasparini P, Gibson J, Giedraitis V, Gjesing AP, Gordon-Larsen P, Gorski M, Grabe HJ, Grant SFA, Grarup N, Griffiths HL, Grove ML, Gudnason V, Gustafsson S, Haessler J, Hakonarson H, Hammerschlag AR, Hansen T, Harris KM, Harris TB, Hattersley AT, Have CT, Hayward C, He L, Heard-Costa NL, Heath AC, Heid IM, Helgeland Ø, Hernesniemi J, Hewitt AW, Holmen OL, Hovingh GK, Howson JMM, Hu Y, Huang PL, Huffman JE, Ikram MA, Ingelsson E, Jackson AU, Jansson JH, Jarvik GP, Jensen GB, Jia Y, Johansson S, Jørgensen ME, Jørgensen T, Jukema JW, Kahali B, Kahn RS, Kähönen M, Kamstrup PR, Kanoni S, Kaprio J, Karaleftheri M, Kardia SLR, Karpe F, Kathiresan S, Kee F, Kiemeney LA, Kim E, Kitajima H, Komulainen P, Kooner JS, Kooperberg C, Korhonen T, Kovacs P, Kuivaniemi H, Kutalik Z, Kuulasmaa K, Kuusisto J, Laakso M, Lakka TA, Lamparter D, Lange EM, Lange LA, Langenberg C, Larson EB, Lee NR, Lehtimäki T, Lewis CE, Li H, Li J, Li-Gao R, Lin H, Lin KH, Lin LA, Lin X, Lind L, Lindström J, Linneberg A, Liu CT, Liu DJ, Liu Y, Lo KS, Lophatananon A, Lotery AJ, Loukola A, Luan J, Lubitz SA, Lyytikäinen LP, Männistö S, Marenne G, Mazul AL, McCarthy MI, McKean-Cowdin R, Medland SE, Meidtner K, Milani L, Mistry V, Mitchell P, Mohlke KL, Moilanen L, Moitry M, Montgomery GW, Mook-Kanamori DO, Moore C, Mori TA, Morris AD, Morris AP, Müller-Nurasyid M, Munroe PB, Nalls MA, Narisu N, Nelson CP, Neville M, Nielsen SF, Nikus K, Njølstad PR, Nordestgaard BG, Nyholt DR, O'Connel JR, O'Donoghue ML, Loohuis LMO, Ophoff RA, Owen KR, Packard CJ, Padmanabhan S, Palmer CNA, Palmer ND, Pasterkamp G, Patel AP, Pattie A, Pedersen O, Peissig PL, Peloso GM, Pennell CE, Perola M, Perry JA, Perry JRB, Pers TH, Person TN, Peters A, Petersen ERB, Peyser PA, Pirie A, Polasek O, Polderman TJ, Puolijoki H, Raitakari OT, Rasheed A, Rauramaa R, Reilly DF, Renström F, Rheinberger M, Ridker PM, Rioux JD, Rivas MA, Roberts DJ, Robertson NR, Robino A, Rolandsson O, Rudan I, Ruth KS, Saleheen D, Salomaa V, Samani NJ, Sapkota Y, Sattar N, Schoen RE, Schreiner PJ, Schulze MB, Scott RA, Segura-Lepe MP, Shah SH, Sheu WH, Sim X, Slater AJ, Small KS, Smith AV, Southam L, Spector TD, Speliotes EK, Starr JM, Stefansson K, Steinthorsdottir V, Stirrups KE, Strauch K, Stringham HM, Stumvoll M, Sun L, Surendran P, Swift AJ, Tada H, Tansey KE, Tardif JC, Taylor KD, Teumer A, Thompson DJ, Thorleifsson G, Thorsteinsdottir U, Thuesen BH, Tönjes A, Tromp G, Trompet S, Tsafantakis E, Tuomilehto J, Tybjaerg-Hansen A, Tyrer JP, Uher R, Uitterlinden AG, Uusitupa M, Laan SW, Duijn CM, Leeuwen N, van Setten J, Vanhala M, Varbo A, Varga TV, Varma R, Edwards DRV, Vermeulen SH, Veronesi G, Vestergaard H, Vitart V, Vogt TF, Völker U, Vuckovic D, Wagenknecht LE, Walker M, Wallentin L, Wang F, Wang CA, Wang S, Wang Y, Ware EB, Wareham NJ, Warren HR, Waterworth DM, Wessel J, White HD, Willer CJ, Wilson JG, Witte DR, Wood AR, Wu Y, Yaghootkar H, Yao J, Yao P, Yerges-Armstrong LM, Young R, Zeggini E, Zhan X, Zhang W, Zhao JH, Zhao W, Zhao W, Zhou W, Zondervan KT, Rotter JI, Pospisilik JA, Rivadeneira F, Borecki IB, Deloukas P, Frayling TM, Lettre G, North KE, Lindgren CM, Hirschhorn JN, and Loos RJF
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2019
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35. Comparison of peak oxygen consumption response to aquatic and robotic therapy in individuals with chronic motor incomplete spinal cord injury: a randomized controlled trial.

Author: Gorman PH, Scott W, VanHiel L, Tansey KE, Sweatman WM, and Geigle PR
Subjects: Adult, Female, Humans, Male, Middle Aged, Prospective Studies, Rehabilitation Centers, Spinal Cord Injuries diagnosis, Spinal Cord Injuries metabolism, Exercise Test methods, Exercise Therapy methods, Oxygen Consumption physiology, Robotics methods, Spinal Cord Injuries rehabilitation, Water Sports physiology
Abstract: Study Design: Randomized dual center controlled clinical trial., Objective: To determine and compare the cardiorespiratory impact of 3 months of aquatic and robotic therapy for individuals with chronic motor incomplete spinal cord injury (CMISCI)., Settings: Two rehabilitation specialty hospitals., Methods: Thirty-one individuals with CMISCI with neurological level between C2-T12 at least 1 year post injury were randomized to either aquatic or robotic treadmill therapy for 36 sessions. Customized sessions lasted 40-45 min at 65-75% heart rate reserve intensity with peak oxygen consumption (peak VO 2 ) measured during arm ergometry at baseline and post intervention. Additional peak robotic treadmill VO 2 assessments were obtained before and after training for participants randomized to robotic intervention., Results: Peak VO 2 measured with arm ergometry was not significantly different with either aquatic intervention (8.1%, p = 0.14, n = 15) or robotic intervention (-0.7%, p = 0.31, n = 17). Peak VO 2 measured with robotic treadmill ergometry demonstrated a statistical improvement (14.7%, p = 0.03, n = 17, two-tailed t-test) across the robotic intervention. Comparison between the two interventions demonstrated a trend favoring aquatic therapy for improving arm ergometry peak VO 2 (ANOVA, p = 0.063)., Conclusions: Neither 3-month exercise interventions statistically improved arm cycle ergometry peak VO 2 , our cardiorespiratory surrogate marker, although percent improvement was greater in the aquatic exercise condition. Robotic ergometry peak VO 2 did improve for the robotic intervention, confirming previous work. These results suggest that either intervention may hold utility in improving cardiorespiratory fitness in CMISCI, but peak VO 2 measurement technique appears critical in detecting effects., Sponsorship: DOD CDMRP SCI Research Program Clinical Trial Award SC090147, FY 2009. This study is registered under ClinicalTrials.gov Identifier: NCT01407354.
Published: 2019
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36. Oscillatory hyperactivity and hyperconnectivity in young APOE -ɛ4 carriers and hypoconnectivity in Alzheimer's disease.

Author: Koelewijn L, Lancaster TM, Linden D, Dima DC, Routley BC, Magazzini L, Barawi K, Brindley L, Adams R, Tansey KE, Bompas A, Tales A, Bayer A, and Singh K
Subjects: Adult, Aged, Aged, 80 and over, Alzheimer Disease diagnostic imaging, Alzheimer Disease pathology, Brain diagnostic imaging, Brain Mapping methods, Female, Genotype, Heterozygote, Humans, Image Processing, Computer-Assisted, Machine Learning, Magnetic Resonance Imaging, Magnetoencephalography methods, Male, Parietal Lobe, Sensitivity and Specificity, Young Adult, Alzheimer Disease genetics, Alzheimer Disease metabolism, Apolipoprotein E4 genetics, Apolipoprotein E4 metabolism, Genetic Predisposition to Disease
Abstract: We studied resting-state oscillatory connectivity using magnetoencephalography in healthy young humans (N = 183) genotyped for APOE-ɛ4, the greatest genetic risk for Alzheimer's disease (AD). Connectivity across frequencies, but most prevalent in alpha/beta, was increased in APOE-ɛ4 in a set of mostly right-hemisphere connections, including lateral parietal and precuneus regions of the Default Mode Network. Similar regions also demonstrated hyperactivity, but only in gamma (40-160 Hz). In a separate study of AD patients, hypoconnectivity was seen in an extended bilateral network that partially overlapped with the hyperconnected regions seen in young APOE-ɛ4 carriers. Using machine-learning, AD patients could be distinguished from elderly controls with reasonable sensitivity and specificity, while young APOE-e4 carriers could also be distinguished from their controls with above chance performance. These results support theories of initial hyperconnectivity driving eventual profound disconnection in AD and suggest that this is present decades before the onset of AD symptomology., Competing Interests: LK, TL, DL, DD, BR, LM, KB, LB, RA, KT, AB, AT, AB, KS No competing interests declared, (© 2019, Koelewijn et al.)
Published: 2019
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37. Structural and Functional Neuroimaging of Polygenic Risk for Schizophrenia: A Recall-by-Genotype-Based Approach.

Author: Lancaster TM, Dimitriadis SL, Tansey KE, Perry G, Ihssen N, Jones DK, Singh KD, Holmans P, Pocklington A, Davey Smith G, Zammit S, Hall J, O'Donovan MC, Owen MJ, and Linden DE
Subjects: Adult, Cohort Studies, Female, Functional Neuroimaging methods, Humans, Magnetic Resonance Imaging, Male, Reward, Risk, Young Adult, Brain diagnostic imaging, Brain pathology, Brain physiopathology, Genetic Predisposition to Disease genetics, Genotype, Neuroimaging methods, Reversal Learning physiology, Schizophrenia genetics, Schizophrenia pathology, Schizophrenia physiopathology, Ventral Striatum diagnostic imaging, Ventral Striatum pathology, Ventral Striatum physiopathology
Abstract: Risk profile scores (RPS) derived from genome-wide association studies (GWAS) explain a considerable amount of susceptibility for schizophrenia (SCZ). However, little is known about how common genetic risk factors for SCZ influence the structure and function of the human brain, largely due to the constraints of imaging sample sizes. In the current study, we use a novel recall-by-genotype (RbG) methodological approach, where we sample young adults from a population cohort (Avon Longitudinal Study of Parents and Children: N genotyped = 8365) based on their SCZ-RPS. We compared 197 healthy individuals at extremes of low (N = 99) or high (N = 98) SCZ-RPS with behavioral tests, and structural and functional magnetic resonance imaging (fMRI). We first provide methodological details that will inform the design of future RbG studies for common SCZ genetic risk. We further provide an between group analysis of the RbG individuals (low vs high SCZ-RPS) who underwent structural neuroimaging data (T1-weighted scans) and fMRI data during a reversal learning task. While we found little evidence for morphometric differences between the low and high SCZ-RPS groups, we observed an impact of SCZ-RPS on blood oxygen level-dependent (BOLD) signal during reward processing in the ventral striatum (PFWE-VS-CORRECTED = .037), a previously investigated broader reward-related network (PFWE-ROIS-CORRECTED = .008), and across the whole brain (PFWE-WHOLE-BRAIN-CORRECTED = .013). We also describe the study strategy and discuss specific challenges of RbG for SCZ risk (such as SCZ-RPS related homoscedasticity). This study will help to elucidate the behavioral and imaging phenotypes that are associated with SCZ genetic risk., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.)
Published: 2019
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38. Polygenic impact of common genetic risk loci for Alzheimer's disease on cerebral blood flow in young individuals.

Author: Chandler HL, Wise RG, Murphy K, Tansey KE, Linden DEJ, and Lancaster TM
Subjects: Alzheimer Disease diagnosis, Apolipoprotein E4 genetics, Biomarkers, Female, Genetic Association Studies, Gray Matter diagnostic imaging, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Alzheimer Disease genetics, Alzheimer Disease physiopathology, Cerebrovascular Circulation genetics, Genetic Predisposition to Disease, Multifactorial Inheritance, Quantitative Trait Loci
Abstract: Genome-wide association studies (GWAS) show that many common alleles confer risk for developing Alzheimer's disease (AD). These risk loci may contribute to MRI alterations in young individuals, preceding the clinical manifestations of AD. Prior evidence identifies vascular dysregulation as the earliest marker of disease progression. However, it remains unclear whether cerebrovascular function (measured via grey-matter cerebral blood flow (gmCBF)) is altered in young individuals with increased AD genetic risk. We establish relationships between gmCBF with APOE and AD polygenic risk score in a young cohort (N = 75; aged: 19-32). Genetic risk was assessed via a) possessing at least one copy of the APOE ɛ4 allele and b) a polygenic risk score (AD-PRS) estimated from AD-GWAS. We observed a reduction in gmCBF in APOE ɛ4 carriers and a negative relationship between AD-PRS and gmCBF. We further found regional reductions in gmCBF in individuals with higher AD-PRS across the frontal cortex (P FWE < 0.05). Our findings suggest that a larger burden of AD common genetic risk alleles is associated with attenuated cerebrovascular function, during young adulthood. These results suggest that cerebral vasculature is a mechanism by which AD risk alleles confer susceptibility.
Published: 2019
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39. Fractional anisotropy of the uncinate fasciculus and cingulum in bipolar disorder type I, type II, unaffected siblings and healthy controls.

Author: Foley SF, Bracher-Smith M, Tansey KE, Harrison JR, Parker GD, and Caseras X
Subjects: Adult, Anisotropy, Bipolar Disorder classification, Case-Control Studies, Female, Humans, Linear Models, Male, Middle Aged, Nucleus Accumbens pathology, Prefrontal Cortex pathology, Psychiatric Status Rating Scales, Siblings, White Matter pathology, Bipolar Disorder physiopathology, Brain pathology, Diffusion Tensor Imaging
Abstract: Background: Fractional anisotropy in the uncinate fasciculus and the cingulum may be biomarkers for bipolar disorder and may even be distinctly affected in different subtypes of bipolar disorder, an area in need of further research.AimsThis study aims to establish if fractional anisotropy in the uncinate fasciculus and cingulum shows differences between healthy controls, patients with bipolar disorder type I (BD-I) and type II (BD-II), and their unaffected siblings., Method: Fractional anisotropy measures from the uncinate fasciculus, cingulum body and parahippocampal cingulum were compared with tractography methods in 40 healthy controls, 32 patients with BD-I, 34 patients with BD-II, 17 siblings of patients with BD-I and 14 siblings of patients with BD-II., Results: The main effects were found in both the right and left uncinate fasciculus, with patients with BD-I showing significantly lower fractional anisotropy than both patients with BD-II and healthy controls. Participants with BD-II did not differ from healthy controls. Siblings showed similar effects in the left uncinate fasciculus. In a subsequent complementary analysis, we investigated the association between fractional anisotropy in the uncinate fasciculus and polygenic risk for bipolar disorder and psychosis in a large cohort (n = 570) of healthy participants. However, we found no significant association., Conclusions: Fractional anisotropy in the uncinate fasciculus differs significantly between patients with BD-I and patients with BD-II and healthy controls. This supports the hypothesis of differences in the physiological sub-tract between bipolar disorder subtypes. Similar results were found in unaffected siblings, suggesting the potential for this biomarker to represent an endophenotype for BD-I. However, fractional anisotropy in the uncinate fasciculus seems unrelated to polygenic risk for bipolar disorder or psychosis.Declaration of interestNone.
Published: 2018
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40. The Psychiatric Risk Gene Transcription Factor 4 (TCF4) Regulates Neurodevelopmental Pathways Associated With Schizophrenia, Autism, and Intellectual Disability.

Author: Forrest MP, Hill MJ, Kavanagh DH, Tansey KE, Waite AJ, and Blake DJ
Subjects: Chromatin Immunoprecipitation, High-Throughput Nucleotide Sequencing, Humans, Autism Spectrum Disorder genetics, Gene Expression genetics, Gene Expression Regulation, Developmental genetics, Genetic Predisposition to Disease genetics, Intellectual Disability genetics, Schizophrenia genetics, Transcription Factor 4 genetics
Abstract: Background: Common genetic variants in and around the gene encoding transcription factor 4 (TCF4) are associated with an increased risk of schizophrenia. Conversely, rare damaging TCF4 mutations cause Pitt-Hopkins syndrome and have also been found in individuals with intellectual disability (ID) and autism spectrum disorder (ASD)., Methods: Chromatin immunoprecipitation and next generation sequencing were used to identify the genomic targets of TCF4. These data were integrated with expression, epigenetic and disease gene sets using a range of computational tools., Results: We identify 10604 TCF4 binding sites in the genome that were assigned to 5437 genes. De novo motif enrichment found that most TCF4 binding sites contained at least one E-box (5'-CAtcTG). Approximately 77% of TCF4 binding sites overlapped with the H3K27ac histone modification for active enhancers. Enrichment analysis on the set of TCF4 targets identified numerous, highly significant functional clusters for pathways including nervous system development, ion transport and signal transduction, and co-expression modules for genes associated with synaptic function and brain development. Importantly, we found that genes harboring de novo mutations in schizophrenia (P = 5.3 × 10-7), ASD (P = 2.5 × 10-4), and ID (P = 7.6 × 10-3) were also enriched among TCF4 targets. TCF4 binding sites were also found at other schizophrenia risk loci including the nicotinic acetylcholine receptor cluster, CHRNA5/CHRNA3/CHRNB4 and SETD1A., Conclusions: These data demonstrate that TCF4 binding sites are found in a large number of neuronal genes that include many genetic risk factors for common neurodevelopmental disorders.
Published: 2018
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41. Effect of cytochrome CYP2C19 metabolizing activity on antidepressant response and side effects: Meta-analysis of data from genome-wide association studies.

Author: Fabbri C, Tansey KE, Perlis RH, Hauser J, Henigsberg N, Maier W, Mors O, Placentino A, Rietschel M, Souery D, Breen G, Curtis C, Lee SH, Newhouse S, Patel H, O'Donovan M, Lewis G, Jenkins G, Weinshilboum RM, Farmer A, Aitchison KJ, Craig I, McGuffin P, Schruers K, Biernacka JM, Uher R, and Lewis CM
Subjects: Citalopram adverse effects, Citalopram therapeutic use, Depressive Disorder, Major drug therapy, Depressive Disorder, Major genetics, Depressive Disorder, Major metabolism, Humans, Antidepressive Agents adverse effects, Antidepressive Agents therapeutic use, Cytochrome P-450 CYP2C19 genetics, Cytochrome P-450 CYP2C19 metabolism, Pharmacogenomic Variants
Abstract: Cytochrome (CYP) P450 enzymes have a primary role in antidepressant metabolism and variants in these polymorphic genes are targets for pharmacogenetic investigation. This is the first meta-analysis to investigate how CYP2C19 polymorphisms predict citalopram/escitalopram efficacy and side effects. CYP2C19 metabolic phenotypes comprise poor metabolizers (PM), intermediate and intermediate+ metabolizers (IM; IM+), extensive and extensive+ metabolizers (EM [wild type]; EM+) and ultra-rapid metabolizers (UM) defined by the two most common CYP2C19 functional polymorphisms (rs4244285 and rs12248560) in Caucasians. These polymorphisms were genotyped or imputed from genome-wide data in four samples treated with citalopram or escitalopram (GENDEP, STAR*D, GenPod, PGRN-AMPS). Treatment efficacy was assessed by standardized percentage symptom improvement and by remission. Side effect data were available at weeks 2-4, 6 and 9 in three samples. A fixed-effects meta-analysis was performed using EM as the reference group. Analysis of 2558 patients for efficacy and 2037 patients for side effects showed that PMs had higher symptom improvement (SMD = 0.43, CI = 0.19-0.66) and higher remission rates (OR = 1.55, CI = 1.23-1.96) compared to EMs. At weeks 2-4, PMs showed higher risk of gastro-intestinal (OR = 1.26, CI = 1.08-1.47), neurological (OR = 1.28, CI = 1.07-1.53) and sexual side effects (OR = 1.52, CI = 1.23-1.87; week 6 values were similar). No difference was seen at week 9 or in total side effect burden. PMs did not have higher risk of dropout at week 4 compared to EMs. Antidepressant dose was not different among CYP2C19 groups. CYP2C19 polymorphisms may provide helpful information for guiding citalopram/escitalopram treatment, despite PMs being relatively rare among Caucasians (∼2%)., (Copyright © 2018 Elsevier B.V. and ECNP. All rights reserved.)
Published: 2018
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42. Lower extremity outcome measures: considerations for clinical trials in spinal cord injury.

Author: Bolliger M, Blight AR, Field-Fote EC, Musselman K, Rossignol S, Barthélemy D, Bouyer L, Popovic MR, Schwab JM, Boninger ML, Tansey KE, Scivoletto G, Kleitman N, Jones LAT, Gagnon DH, Nadeau S, Haupt D, Awai L, Easthope CS, Zörner B, Rupp R, Lammertse D, Curt A, and Steeves J
Subjects: Humans, Spinal Cord Injuries pathology, Clinical Trials as Topic methods, Lower Extremity physiopathology, Outcome Assessment, Health Care, Spinal Cord Injuries therapy
Abstract: Study Design: This is a focused review article., Objectives: To identify important concepts in lower extremity (LE) assessment with a focus on locomotor outcomes and provide guidance on how existing outcome measurement tools may be best used to assess experimental therapies in spinal cord injury (SCI). The emphasis lies on LE outcomes in individuals with complete and incomplete SCI in Phase II-III trials., Methods: This review includes a summary of topics discussed during a workshop focusing on LE function in SCI, conceptual discussion of corresponding outcome measures and additional focused literature review., Results: There are a number of sensitive, accurate, and responsive outcome tools measuring both quantitative and qualitative aspects of LE function. However, in trials with individuals with very acute injuries, a baseline assessment of the primary (or secondary) LE outcome measure is often not feasible., Conclusion: There is no single outcome measure to assess all individuals with SCI that can be used to monitor changes in LE function regardless of severity and level of injury. Surrogate markers have to be used to assess LE function in individuals with severe SCI. However, it is generally agreed that a direct measurement of the performance for an appropriate functional activity supersedes any surrogate marker. LE assessments have to be refined so they can be used across all time points after SCI, regardless of the level or severity of spinal injury., Sponsors: Craig H. Neilsen Foundation, Spinal Cord Outcomes Partnership Endeavor.
Published: 2018
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43. Examining cognition across the bipolar/schizophrenia diagnostic spectrum.

Author: Lynham AJ, Hubbard L, Tansey KE, Hamshere ML, Legge SE, Owen MJ, Jones IR, and Walters JTR
Subjects: Adult, Bipolar Disorder complications, Bipolar Disorder diagnosis, Case-Control Studies, Cognition Disorders complications, Cognition Disorders diagnosis, Female, Humans, Male, Middle Aged, Neuropsychological Tests, Psychiatric Status Rating Scales, Psychotic Disorders complications, Psychotic Disorders diagnosis, Schizophrenia complications, Schizophrenia diagnosis, Bipolar Disorder psychology, Cognition Disorders psychology, Psychotic Disorders psychology, Schizophrenic Psychology
Abstract: Background: Cognitive impairments are well-established features of schizophrenia, but there is ongoing debate about the nature and degree of cognitive impairment in patients with schizoaffective disorder and bipolar disorder. We hypothesized that there is a spectrum of increasing impairment from bipolar disorder to schizoaffective disorder bipolar type, to schizoaffective disorder depressive type and schizophrenia., Methods: We compared performance on the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery between participants with schizophrenia ( n = 558), schizoaffective disorder depressive type ( n = 112), schizoaffective disorder type ( n = 76), bipolar disorder ( n = 78) and healthy participants ( n = 103) using analysis of covariance with post hoc comparisons. We conducted an ordinal logistic regression to examine whether cognitive impairments followed the hypothesized spectrum from bipolar disorder (least severe) to schizophrenia (most severe). In addition to categorical diagnoses, we addressed the influence of symptom domains, examining the association between cognition and mania, depression and psychosis., Results: Cognitive impairments increased in severity from bipolar disorder to schizoaffective disorder bipolar type, to schizophrenia and schizoaffective disorder depressive type. Participants with schizophrenia and schizoaffective disorder depressive type showed equivalent performance ( d = 0.07, p = 0.90). The results of the ordinal logistic regression were consistent with a spectrum of deficits from bipolar disorder to schizoaffective disorder bipolar type, to schizophrenia/schizoaffective disorder depressive type (odds ratio = 1.98, p < 0.001). In analyses of the associations between symptom dimensions and cognition, higher scores on the psychosis dimension were associated with poorer performance (B = 0.015, standard error = 0.002, p < 0.001)., Limitations: There were fewer participants with schizoaffective disorder and bipolar disorder than schizophrenia. Despite this, our analyses were robust to differences in group sizes, and we were able to detect differences between groups., Conclusion: Cognitive impairments represent a symptom dimension that cuts across traditional diagnostic boundaries.
Published: 2018

44. A "Snapshot" of the Advances in SCI Therapeutics.

Author: Cortes M, Alias GG, and Tansey KE
Subjects: Humans, Spinal Cord Injuries therapy
Published: 2018
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45. New insights into the pharmacogenomics of antidepressant response from the GENDEP and STAR*D studies: rare variant analysis and high-density imputation.

Author: Fabbri C, Tansey KE, Perlis RH, Hauser J, Henigsberg N, Maier W, Mors O, Placentino A, Rietschel M, Souery D, Breen G, Curtis C, Sang-Hyuk L, Newhouse S, Patel H, Guipponi M, Perroud N, Bondolfi G, O'Donovan M, Lewis G, Biernacka JM, Weinshilboum RM, Farmer A, Aitchison KJ, Craig I, McGuffin P, Uher R, and Lewis CM
Subjects: Antidepressive Agents therapeutic use, Depressive Disorder, Major genetics, Depressive Disorder, Major pathology, Genetic Variation, Genotype, Humans, Integrins genetics, Nerve Tissue Proteins genetics, Polymorphism, Single Nucleotide, Treatment Outcome, Antidepressive Agents adverse effects, Depressive Disorder, Major drug therapy, Genome-Wide Association Study, Pharmacogenetics trends
Abstract: Genome-wide association studies have generally failed to identify polymorphisms associated with antidepressant response. Possible reasons include limited coverage of genetic variants that this study tried to address by exome genotyping and dense imputation. A meta-analysis of Genome-Based Therapeutic Drugs for Depression (GENDEP) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D) studies was performed at the single-nucleotide polymorphism (SNP), gene and pathway levels. Coverage of genetic variants was increased compared with previous studies by adding exome genotypes to previously available genome-wide data and using the Haplotype Reference Consortium panel for imputation. Standard quality control was applied. Phenotypes were symptom improvement and remission after 12 weeks of antidepressant treatment. Significant findings were investigated in NEWMEDS consortium samples and Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) for replication. A total of 7062 950 SNPs were analyzed in GENDEP (n=738) and STAR*D (n=1409). rs116692768 (P=1.80e-08, ITGA9 (integrin α9)) and rs76191705 (P=2.59e-08, NRXN3 (neurexin 3)) were significantly associated with symptom improvement during citalopram/escitalopram treatment. At the gene level, no consistent effect was found. At the pathway level, the Gene Ontology (GO) terms GO: 0005694 (chromosome) and GO: 0044427 (chromosomal part) were associated with improvement (corrected P=0.007 and 0.045, respectively). The association between rs116692768 and symptom improvement was replicated in PGRN-AMPS (P=0.047), whereas rs76191705 was not. The two SNPs did not replicate in NEWMEDS. ITGA9 codes for a membrane receptor for neurotrophins and NRXN3 is a transmembrane neuronal adhesion receptor involved in synaptic differentiation. Despite their meaningful biological rationale for being involved in antidepressant effect, replication was partial. Further studies may help in clarifying their role.
Published: 2018
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46. Considerations and recommendations for selection and utilization of upper extremity clinical outcome assessments in human spinal cord injury trials.

Author: Jones LAT, Bryden A, Wheeler TL, Tansey KE, Anderson KD, Beattie MS, Blight A, Curt A, Field-Fote E, Guest JD, Hseih J, Jakeman LB, Kalsi-Ryan S, Krisa L, Lammertse DP, Leiby B, Marino R, Schwab JM, Scivoletto G, Tulsky DS, Wirth E, Zariffa J, Kleitman N, Mulcahey MJ, and Steeves JD
Subjects: Humans, Clinical Trials as Topic methods, Outcome Assessment, Health Care methods, Spinal Cord Injuries diagnosis, Spinal Cord Injuries therapy
Abstract: Study Design: This is a focused review article., Objectives: This review presents important features of clinical outcomes assessments (COAs) in human spinal cord injury research. Considerations for COAs by trial phase and International Classification of Functioning, Disability and Health are presented as well as strengths and recommendations for upper extremity COAs for research. Clinical trial tools and designs to address recruitment challenges are identified., Methods: The methods include a summary of topics discussed during a two-day workshop, conceptual discussion of upper extremity COAs and additional focused literature review., Results: COAs must be appropriate to trial phase and particularly in mid-late-phase trials, should reflect recovery vs. compensation, as well as being clinically meaningful. The impact and extent of upper vs. lower motoneuron disease should be considered, as this may affect how an individual may respond to a given therapeutic. For trials with broad inclusion criteria, the content of COAs should cover all severities and levels of SCI. Specific measures to assess upper extremity function as well as more comprehensive COAs are under development. In addition to appropriate use of COAs, methods to increase recruitment, such as adaptive trial designs and prognostic modeling to prospectively stratify heterogeneous populations into appropriate cohorts should be considered., Conclusions: With an increasing number of clinical trials focusing on improving upper extremity function, it is essential to consider a range of factors when choosing a COA., Sponsors: Craig H. Neilsen Foundation, Spinal Cord Outcomes Partnership Endeavor.
Published: 2018
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47. Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Author: Turcot V, Lu Y, Highland HM, Schurmann C, Justice AE, Fine RS, Bradfield JP, Esko T, Giri A, Graff M, Guo X, Hendricks AE, Karaderi T, Lempradl A, Locke AE, Mahajan A, Marouli E, Sivapalaratnam S, Young KL, Alfred T, Feitosa MF, Masca NGD, Manning AK, Medina-Gomez C, Mudgal P, Ng MCY, Reiner AP, Vedantam S, Willems SM, Winkler TW, Abecasis G, Aben KK, Alam DS, Alharthi SE, Allison M, Amouyel P, Asselbergs FW, Auer PL, Balkau B, Bang LE, Barroso I, Bastarache L, Benn M, Bergmann S, Bielak LF, Blüher M, Boehnke M, Boeing H, Boerwinkle E, Böger CA, Bork-Jensen J, Bots ML, Bottinger EP, Bowden DW, Brandslund I, Breen G, Brilliant MH, Broer L, Brumat M, Burt AA, Butterworth AS, Campbell PT, Cappellani S, Carey DJ, Catamo E, Caulfield MJ, Chambers JC, Chasman DI, Chen YI, Chowdhury R, Christensen C, Chu AY, Cocca M, Collins FS, Cook JP, Corley J, Corominas Galbany J, Cox AJ, Crosslin DS, Cuellar-Partida G, D'Eustacchio A, Danesh J, Davies G, Bakker PIW, Groot MCH, Mutsert R, Deary IJ, Dedoussis G, Demerath EW, Heijer M, Hollander AI, Ruijter HM, Dennis JG, Denny JC, Angelantonio E, Drenos F, Du M, Dubé MP, Dunning AM, Easton DF, Edwards TL, Ellinghaus D, Ellinor PT, Elliott P, Evangelou E, Farmaki AE, Farooqi IS, Faul JD, Fauser S, Feng S, Ferrannini E, Ferrieres J, Florez JC, Ford I, Fornage M, Franco OH, Franke A, Franks PW, Friedrich N, Frikke-Schmidt R, Galesloot TE, Gan W, Gandin I, Gasparini P, Gibson J, Giedraitis V, Gjesing AP, Gordon-Larsen P, Gorski M, Grabe HJ, Grant SFA, Grarup N, Griffiths HL, Grove ML, Gudnason V, Gustafsson S, Haessler J, Hakonarson H, Hammerschlag AR, Hansen T, Harris KM, Harris TB, Hattersley AT, Have CT, Hayward C, He L, Heard-Costa NL, Heath AC, Heid IM, Helgeland Ø, Hernesniemi J, Hewitt AW, Holmen OL, Hovingh GK, Howson JMM, Hu Y, Huang PL, Huffman JE, Ikram MA, Ingelsson E, Jackson AU, Jansson JH, Jarvik GP, Jensen GB, Jia Y, Johansson S, Jørgensen ME, Jørgensen T, Jukema JW, Kahali B, Kahn RS, Kähönen M, Kamstrup PR, Kanoni S, Kaprio J, Karaleftheri M, Kardia SLR, Karpe F, Kathiresan S, Kee F, Kiemeney LA, Kim E, Kitajima H, Komulainen P, Kooner JS, Kooperberg C, Korhonen T, Kovacs P, Kuivaniemi H, Kutalik Z, Kuulasmaa K, Kuusisto J, Laakso M, Lakka TA, Lamparter D, Lange EM, Lange LA, Langenberg C, Larson EB, Lee NR, Lehtimäki T, Lewis CE, Li H, Li J, Li-Gao R, Lin H, Lin KH, Lin LA, Lin X, Lind L, Lindström J, Linneberg A, Liu CT, Liu DJ, Liu Y, Lo KS, Lophatananon A, Lotery AJ, Loukola A, Luan J, Lubitz SA, Lyytikäinen LP, Männistö S, Marenne G, Mazul AL, McCarthy MI, McKean-Cowdin R, Medland SE, Meidtner K, Milani L, Mistry V, Mitchell P, Mohlke KL, Moilanen L, Moitry M, Montgomery GW, Mook-Kanamori DO, Moore C, Mori TA, Morris AD, Morris AP, Müller-Nurasyid M, Munroe PB, Nalls MA, Narisu N, Nelson CP, Neville M, Nielsen SF, Nikus K, Njølstad PR, Nordestgaard BG, Nyholt DR, O'Connel JR, O'Donoghue ML, Olde Loohuis LM, Ophoff RA, Owen KR, Packard CJ, Padmanabhan S, Palmer CNA, Palmer ND, Pasterkamp G, Patel AP, Pattie A, Pedersen O, Peissig PL, Peloso GM, Pennell CE, Perola M, Perry JA, Perry JRB, Pers TH, Person TN, Peters A, Petersen ERB, Peyser PA, Pirie A, Polasek O, Polderman TJ, Puolijoki H, Raitakari OT, Rasheed A, Rauramaa R, Reilly DF, Renström F, Rheinberger M, Ridker PM, Rioux JD, Rivas MA, Roberts DJ, Robertson NR, Robino A, Rolandsson O, Rudan I, Ruth KS, Saleheen D, Salomaa V, Samani NJ, Sapkota Y, Sattar N, Schoen RE, Schreiner PJ, Schulze MB, Scott RA, Segura-Lepe MP, Shah SH, Sheu WH, Sim X, Slater AJ, Small KS, Smith AV, Southam L, Spector TD, Speliotes EK, Starr JM, Stefansson K, Steinthorsdottir V, Stirrups KE, Strauch K, Stringham HM, Stumvoll M, Sun L, Surendran P, Swift AJ, Tada H, Tansey KE, Tardif JC, Taylor KD, Teumer A, Thompson DJ, Thorleifsson G, Thorsteinsdottir U, Thuesen BH, Tönjes A, Tromp G, Trompet S, Tsafantakis E, Tuomilehto J, Tybjaerg-Hansen A, Tyrer JP, Uher R, Uitterlinden AG, Uusitupa M, Laan SW, Duijn CM, Leeuwen N, van Setten J, Vanhala M, Varbo A, Varga TV, Varma R, Velez Edwards DR, Vermeulen SH, Veronesi G, Vestergaard H, Vitart V, Vogt TF, Völker U, Vuckovic D, Wagenknecht LE, Walker M, Wallentin L, Wang F, Wang CA, Wang S, Wang Y, Ware EB, Wareham NJ, Warren HR, Waterworth DM, Wessel J, White HD, Willer CJ, Wilson JG, Witte DR, Wood AR, Wu Y, Yaghootkar H, Yao J, Yao P, Yerges-Armstrong LM, Young R, Zeggini E, Zhan X, Zhang W, Zhao JH, Zhao W, Zhou W, Zondervan KT, Rotter JI, Pospisilik JA, Rivadeneira F, Borecki IB, Deloukas P, Frayling TM, Lettre G, North KE, Lindgren CM, Hirschhorn JN, and Loos RJF
Abstract: In the published version of this paper, the name of author Emanuele Di Angelantonio was misspelled. This error has now been corrected in the HTML and PDF versions of the article.
Published: 2018
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48. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression.

Author: Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, Adams MJ, Agerbo E, Air TM, Andlauer TMF, Bacanu SA, Bækvad-Hansen M, Beekman AFT, Bigdeli TB, Binder EB, Blackwood DRH, Bryois J, Buttenschøn HN, Bybjerg-Grauholm J, Cai N, Castelao E, Christensen JH, Clarke TK, Coleman JIR, Colodro-Conde L, Couvy-Duchesne B, Craddock N, Crawford GE, Crowley CA, Dashti HS, Davies G, Deary IJ, Degenhardt F, Derks EM, Direk N, Dolan CV, Dunn EC, Eley TC, Eriksson N, Escott-Price V, Kiadeh FHF, Finucane HK, Forstner AJ, Frank J, Gaspar HA, Gill M, Giusti-Rodríguez P, Goes FS, Gordon SD, Grove J, Hall LS, Hannon E, Hansen CS, Hansen TF, Herms S, Hickie IB, Hoffmann P, Homuth G, Horn C, Hottenga JJ, Hougaard DM, Hu M, Hyde CL, Ising M, Jansen R, Jin F, Jorgenson E, Knowles JA, Kohane IS, Kraft J, Kretzschmar WW, Krogh J, Kutalik Z, Lane JM, Li Y, Li Y, Lind PA, Liu X, Lu L, MacIntyre DJ, MacKinnon DF, Maier RM, Maier W, Marchini J, Mbarek H, McGrath P, McGuffin P, Medland SE, Mehta D, Middeldorp CM, Mihailov E, Milaneschi Y, Milani L, Mill J, Mondimore FM, Montgomery GW, Mostafavi S, Mullins N, Nauck M, Ng B, Nivard MG, Nyholt DR, O'Reilly PF, Oskarsson H, Owen MJ, Painter JN, Pedersen CB, Pedersen MG, Peterson RE, Pettersson E, Peyrot WJ, Pistis G, Posthuma D, Purcell SM, Quiroz JA, Qvist P, Rice JP, Riley BP, Rivera M, Saeed Mirza S, Saxena R, Schoevers R, Schulte EC, Shen L, Shi J, Shyn SI, Sigurdsson E, Sinnamon GBC, Smit JH, Smith DJ, Stefansson H, Steinberg S, Stockmeier CA, Streit F, Strohmaier J, Tansey KE, Teismann H, Teumer A, Thompson W, Thomson PA, Thorgeirsson TE, Tian C, Traylor M, Treutlein J, Trubetskoy V, Uitterlinden AG, Umbricht D, Van der Auwera S, van Hemert AM, Viktorin A, Visscher PM, Wang Y, Webb BT, Weinsheimer SM, Wellmann J, Willemsen G, Witt SH, Wu Y, Xi HS, Yang J, Zhang F, Arolt V, Baune BT, Berger K, Boomsma DI, Cichon S, Dannlowski U, de Geus ECJ, DePaulo JR, Domenici E, Domschke K, Esko T, Grabe HJ, Hamilton SP, Hayward C, Heath AC, Hinds DA, Kendler KS, Kloiber S, Lewis G, Li QS, Lucae S, Madden PFA, Magnusson PK, Martin NG, McIntosh AM, Metspalu A, Mors O, Mortensen PB, Müller-Myhsok B, Nordentoft M, Nöthen MM, O'Donovan MC, Paciga SA, Pedersen NL, Penninx BWJH, Perlis RH, Porteous DJ, Potash JB, Preisig M, Rietschel M, Schaefer C, Schulze TG, Smoller JW, Stefansson K, Tiemeier H, Uher R, Völzke H, Weissman MM, Werge T, Winslow AR, Lewis CM, Levinson DF, Breen G, Børglum AD, and Sullivan PF
Subjects: Case-Control Studies, Female, Genetic Predisposition to Disease, Genome-Wide Association Study methods, Humans, Male, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, Schizophrenia genetics, Depressive Disorder, Major genetics, Multifactorial Inheritance
Abstract: Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.
Published: 2018
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49. Genetic risk for Alzheimer's disease is concentrated in specific macrophage and microglial transcriptional networks.

Author: Tansey KE, Cameron D, and Hill MJ
Subjects: Chromatin metabolism, Deoxyribonucleases metabolism, Humans, Inheritance Patterns genetics, Macrophages metabolism, Microglia metabolism, Monocytes metabolism, Nucleotide Motifs genetics, Organ Specificity genetics, Polymorphism, Single Nucleotide genetics, Risk Factors, Transcription Factors metabolism, Alzheimer Disease genetics, Gene Regulatory Networks, Genetic Predisposition to Disease, Macrophages pathology, Microglia pathology, Transcription, Genetic
Abstract: Background: Genome-wide association studies of Alzheimer's disease (AD) have identified a number of significant risk loci, the majority of which lie in non-coding regions of the genome. The lack of causal alleles and considerable polygenicity remains a significant barrier to translation into mechanistic understanding. This includes identifying causal variants and the cell/tissue types in which they operate. A fuller understanding of the cell types and transcriptional networks involved in AD genetic risk mechanisms will provide important insights into pathogenesis., Methods: We assessed the significance of the overlap between genome-wide significant AD risk variants and sites of open chromatin from data sets representing diverse tissue types. We then focussed on macrophages and microglia to investigate the role of open chromatin sites containing motifs for specific transcription factors. Partitioned heritability using LDscore regression was used to investigate the contribution of specific macrophage and microglia transcription factor motif-containing open chromatin sites to the heritability of AD., Results: AD risk single nucleotide polymorphisms (SNPs) are preferentially located at sites of open chromatin in immune cells, particularly monocytes (z score = 4.43; corrected P = 5.88 × 10 - 3 ). Similar enrichments are observed for macrophages (z score = 4.10; corrected P < 2.40 × 10 - 3 ) and microglia (z score = 4.34, corrected P = 0.011). In both macrophages and microglia, AD risk variants are enriched at a subset of open chromatin sites that contain DNA binding motifs for specific transcription factors, e.g. SPI1 and MEF2. Genetic variation at many of these motif-containing sites also mediate a substantial proportion of AD heritability, with SPI1-containing sites capturing the majority of the common variant SNP-chip heritability (microglia enrichment = 16.28, corrected enrichment P = 0.0044)., Conclusions: AD risk alleles plausibly operate in immune cells, including microglia, and are concentrated in specific transcriptional networks. Combined with primary genetic association results, the SPI1 and MEF2 transcriptional networks appear central to AD risk mechanisms. Investigation of transcription factors targeting AD risk SNP associated regulatory elements could provide powerful insights into the molecular processes affected by AD polygenic risk. More broadly, our findings support a model of polygenic disease risk that arises from variants located in specific transcriptional networks.
Published: 2018
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50. Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference.

Author: Corbin LJ, Tan VY, Hughes DA, Wade KH, Paul DS, Tansey KE, Butcher F, Dudbridge F, Howson JM, Jallow MW, John C, Kingston N, Lindgren CM, O'Donavan M, O'Rahilly S, Owen MJ, Palmer CNA, Pearson ER, Scott RA, van Heel DA, Whittaker J, Frayling T, Tobin MD, Wain LV, Smith GD, Evans DM, Karpe F, McCarthy MI, Danesh J, Franks PW, and Timpson NJ
Subjects: Causality, Genetic Variation, Humans, Molecular Epidemiology, Risk Factors, United Kingdom, Genome-Wide Association Study methods, Genome-Wide Association Study statistics & numerical data, Genome-Wide Association Study trends, Genotype, Phenotype
Abstract: Detailed phenotyping is required to deepen our understanding of the biological mechanisms behind genetic associations. In addition, the impact of potentially modifiable risk factors on disease requires analytical frameworks that allow causal inference. Here, we discuss the characteristics of Recall-by-Genotype (RbG) as a study design aimed at addressing both these needs. We describe two broad scenarios for the application of RbG: studies using single variants and those using multiple variants. We consider the efficacy and practicality of the RbG approach, provide a catalogue of UK-based resources for such studies and present an online RbG study planner.
Published: 2018
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