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2. On the trajectory of discrimination: A meta-analysis and forecasting survey capturing 44 years of field experiments on gender and hiring decisions

Author

Schaerer, M, Plessis, C, Nguyen, M, Aert, R, Tiokhin, L, Lakens, D, Clemente, E, Pfeiffer, T, Dreber, A, Johannesson, M, Clark, C, Uhlmann, E, Abraham, A, Adamus, M, Akinci, C, Alberti, F, Alsharawy, A, Alzahawi, S, Anseel, F, Arndt, F, Balkan, B, Baskin, E, Bearden, C, Benotsch, E, Bernritter, S, Black, S, Bleidorn, W, Boysen, A, Brienza, J, Brown, M, Brown, S, Brown, J, Buckley, J, Buttliere, B, Byrd, N, Cigler, H, Capitan, T, Cherubini, P, Chong, S, Ciftci, E, Conrad, C, Conway, P, Costa, E, Cox, J, Cox, D, Cruz, F, Dawson, I, Demiral, E, Derrick, J, Doshi, S, Dunleavy, D, Durham, J, Elbaek, C, Ellis, D, Ert, E, Espinoza, M, Fullbrunn, S, Fath, S, Furrer, R, Fiala, L, Fillon, A, Forsgren, M, Fytraki, A, Galarza, F, Gandhi, L, Garrison, S, Geraldes, D, Ghasemi, O, Gjoneska, B, Gothilander, J, Gruhn, D, Grieder, M, Hafenbradl, S, Halkias, G, Hancock, R, Hantula, D, Harton, H, Hoffmann, C, Holzmeister, F, Horak, F, Hosch, A, Imada, H, Ioannidis, K, Jaeger, B, Janas, M, Janik, B, Kc, R, Keel, P, Keeley, J, Keller, L, Kenrick, D, Kiely, K, Knutsson, M, Kovacheva, A, Kovera, M, Krivoshchekov, V, Krumrei-Mancuso, E, Kulibert, D, Lacko, D, Lemay, E, Leung, D, Li, F, Lin, H, Lorenzo, K, Lorenzo-Luaces, L, Lou, N, Lovakov, A, Luzardo, A, Macaulay, S, Madan, C, Mahmoud, O, Makel, M, Mari, S, Fages, D, Marsh, A, Mccarthy, R, Mercier, B, Milfont, T, Mittlaender, S, Montoya, A, Moyer, A, Myrseth, K, Navarro-Martinez, D, Nelson, A, Neyse, L, Minghui, N, Niszczota, P, Obrecht, N, Otterbring, T, Panlilio, Z, Park, L, Pauer, S, Pavlov, Y, Pentek, I, Pereyra, J, Perkowski, P, Pew, E, Peynircioglu, Z, Pezzo, M, Pirrone, A, Plonsky, O, Porfirio, J, Pownall, M, Prochnicki, M, Protzko, J, Roer, J, Rahnev, D, Reis, H, Rios, K, Rodrigues, D, Rodriguez, P, Roth, Y, Ruffle, B, Samahita, M, Schmidt, A, Schoemann, M, Schoenegger, P, Schwebel, D, Segovia, A, Sherman, J, Siegenthaler, S, Siem, B, Sirota, M, Smith, E, Stamatogiannakis, A, Stewart-Williams, S, Storage, D, Su, Y, Talbert, E, Todd, A, Tonin, M, Trautmann, S, Travaglino, G, Tsang, J, Veldhuizen, R, Varnum, M, Walf, A, Wallrich, L, Wang, K, Ward, D, Waugh, C, Wingen, T, Woike, J, Wollbrant, C, Wu, S, Wylie, K, Xiao, Q, Xue, S, Yakobi, O, Zayas, V, Zheng, J, Zhong, Y, Zogmaister, C, Zolopa, C, Lisa, N, Chin Wen, O, Dmitry, G, Schaerer M., Plessis C. D., Nguyen M. H. B., Aert R. C. M. V., Tiokhin L., Lakens D., Clemente E. G., Pfeiffer T., Dreber A., Johannesson M., Clark C. J., Uhlmann E. L., Abraham A. T., Adamus M., Akinci C., Alberti F., Alsharawy A. M., Alzahawi S., Anseel F., Arndt F., Balkan B., Baskin E., Bearden C. E., Benotsch E. G., Bernritter S., Black S. R., Bleidorn W., Boysen A. P., Brienza J. P., Brown M., Brown S. E. V., Brown J. W., Buckley J., Buttliere B., Byrd N., Cigler H., Capitan T., Cherubini P., Chong S. Y., Ciftci E. E., Conrad C. D., Conway P., Costa E., Cox J. A., Cox D. J., Cruz F., Dawson I. G. J., Demiral E. E., Derrick J. L., Doshi S., Dunleavy D. J., Durham J. D., Elbaek C. T., Ellis D. A., Ert E., Espinoza M. P., Fullbrunn S. C., Fath S., Furrer R., Fiala L., Fillon A. A., Forsgren M., Fytraki A. T., Galarza F. B., Gandhi L., Garrison S. M., Geraldes D., Ghasemi O., Gjoneska B., Gothilander J., Gruhn D., Grieder M., Hafenbradl S., Halkias G., Hancock R., Hantula D. A., Harton H. C., Hoffmann C. P., Holzmeister F., Horak F., Hosch A. -K., Imada H., Ioannidis K., Jaeger B., Janas M., Janik B., Kc R. P., Keel P. K., Keeley J. W., Keller L., Kenrick D. T., Kiely K. M., Knutsson M., Kovacheva A., Kovera M. B., Krivoshchekov V., Krumrei-Mancuso E. J., Kulibert D., Lacko D., Lemay E. P., Leung D. W., Li F., Lin H., Lorenzo K. E., Lorenzo-Luaces L., Lou N. M., Lovakov A., Luzardo A., MacAulay S. C., Madan C. R., Mahmoud O., Makel M. C., Mari S., Fages D. M., Marsh A. A., McCarthy R. J., Mercier B., Milfont T. L., Mittlaender S., Montoya A. K., Moyer A., Myrseth K. O. R., Navarro-Martinez D., Nelson A. J., Neyse L., Minghui N., Niszczota P., Obrecht N. A., Otterbring T., Panlilio Z. A., Park L. E., Pauer S., Pavlov Y. G., Pentek I., Pereyra J. S., Perkowski P., Pew E., Peynircioglu Z. F., Pezzo M. V., Pirrone A., Plonsky O., Porfirio J. C. C., Pownall M., Prochnicki M. M., Protzko J., Roer J. P., Rahnev D., Reis H. T., Rios K., Rodrigues D. L., Rodriguez P., Roth Y., Ruffle B. J., Samahita M., Schmidt A., Schoemann M., Schoenegger P., Schwebel D. C., Segovia A. M., Sherman J. W., Siegenthaler S., Siem B., Sirota M., Smith E. R., Stamatogiannakis A., Stewart-Williams S., Storage D., Su Y., Talbert E. J., Todd A. R., Tonin M., Trautmann S. T., Travaglino G. A., Tsang J. -A., Veldhuizen R. V., Varnum M. E. W., Walf A. A., Wallrich L., Wang K., Ward D. E., Waugh C. E., Wingen T., Woike J. K., Wollbrant C. E., Wu S., Wylie K., Xiao Q., Xue S. Y., Yakobi O., Zayas V., Zheng J., Zhong Y., Zogmaister C., Zolopa C. S., Lisa N., Chin Wen O., Dmitry G., Schaerer, M, Plessis, C, Nguyen, M, Aert, R, Tiokhin, L, Lakens, D, Clemente, E, Pfeiffer, T, Dreber, A, Johannesson, M, Clark, C, Uhlmann, E, Abraham, A, Adamus, M, Akinci, C, Alberti, F, Alsharawy, A, Alzahawi, S, Anseel, F, Arndt, F, Balkan, B, Baskin, E, Bearden, C, Benotsch, E, Bernritter, S, Black, S, Bleidorn, W, Boysen, A, Brienza, J, Brown, M, Brown, S, Brown, J, Buckley, J, Buttliere, B, Byrd, N, Cigler, H, Capitan, T, Cherubini, P, Chong, S, Ciftci, E, Conrad, C, Conway, P, Costa, E, Cox, J, Cox, D, Cruz, F, Dawson, I, Demiral, E, Derrick, J, Doshi, S, Dunleavy, D, Durham, J, Elbaek, C, Ellis, D, Ert, E, Espinoza, M, Fullbrunn, S, Fath, S, Furrer, R, Fiala, L, Fillon, A, Forsgren, M, Fytraki, A, Galarza, F, Gandhi, L, Garrison, S, Geraldes, D, Ghasemi, O, Gjoneska, B, Gothilander, J, Gruhn, D, Grieder, M, Hafenbradl, S, Halkias, G, Hancock, R, Hantula, D, Harton, H, Hoffmann, C, Holzmeister, F, Horak, F, Hosch, A, Imada, H, Ioannidis, K, Jaeger, B, Janas, M, Janik, B, Kc, R, Keel, P, Keeley, J, Keller, L, Kenrick, D, Kiely, K, Knutsson, M, Kovacheva, A, Kovera, M, Krivoshchekov, V, Krumrei-Mancuso, E, Kulibert, D, Lacko, D, Lemay, E, Leung, D, Li, F, Lin, H, Lorenzo, K, Lorenzo-Luaces, L, Lou, N, Lovakov, A, Luzardo, A, Macaulay, S, Madan, C, Mahmoud, O, Makel, M, Mari, S, Fages, D, Marsh, A, Mccarthy, R, Mercier, B, Milfont, T, Mittlaender, S, Montoya, A, Moyer, A, Myrseth, K, Navarro-Martinez, D, Nelson, A, Neyse, L, Minghui, N, Niszczota, P, Obrecht, N, Otterbring, T, Panlilio, Z, Park, L, Pauer, S, Pavlov, Y, Pentek, I, Pereyra, J, Perkowski, P, Pew, E, Peynircioglu, Z, Pezzo, M, Pirrone, A, Plonsky, O, Porfirio, J, Pownall, M, Prochnicki, M, Protzko, J, Roer, J, Rahnev, D, Reis, H, Rios, K, Rodrigues, D, Rodriguez, P, Roth, Y, Ruffle, B, Samahita, M, Schmidt, A, Schoemann, M, Schoenegger, P, Schwebel, D, Segovia, A, Sherman, J, Siegenthaler, S, Siem, B, Sirota, M, Smith, E, Stamatogiannakis, A, Stewart-Williams, S, Storage, D, Su, Y, Talbert, E, Todd, A, Tonin, M, Trautmann, S, Travaglino, G, Tsang, J, Veldhuizen, R, Varnum, M, Walf, A, Wallrich, L, Wang, K, Ward, D, Waugh, C, Wingen, T, Woike, J, Wollbrant, C, Wu, S, Wylie, K, Xiao, Q, Xue, S, Yakobi, O, Zayas, V, Zheng, J, Zhong, Y, Zogmaister, C, Zolopa, C, Lisa, N, Chin Wen, O, Dmitry, G, Schaerer M., Plessis C. D., Nguyen M. H. B., Aert R. C. M. V., Tiokhin L., Lakens D., Clemente E. G., Pfeiffer T., Dreber A., Johannesson M., Clark C. J., Uhlmann E. L., Abraham A. T., Adamus M., Akinci C., Alberti F., Alsharawy A. M., Alzahawi S., Anseel F., Arndt F., Balkan B., Baskin E., Bearden C. E., Benotsch E. G., Bernritter S., Black S. R., Bleidorn W., Boysen A. P., Brienza J. P., Brown M., Brown S. E. V., Brown J. W., Buckley J., Buttliere B., Byrd N., Cigler H., Capitan T., Cherubini P., Chong S. Y., Ciftci E. E., Conrad C. D., Conway P., Costa E., Cox J. A., Cox D. J., Cruz F., Dawson I. G. J., Demiral E. E., Derrick J. L., Doshi S., Dunleavy D. J., Durham J. D., Elbaek C. T., Ellis D. A., Ert E., Espinoza M. P., Fullbrunn S. C., Fath S., Furrer R., Fiala L., Fillon A. A., Forsgren M., Fytraki A. T., Galarza F. B., Gandhi L., Garrison S. M., Geraldes D., Ghasemi O., Gjoneska B., Gothilander J., Gruhn D., Grieder M., Hafenbradl S., Halkias G., Hancock R., Hantula D. A., Harton H. C., Hoffmann C. P., Holzmeister F., Horak F., Hosch A. -K., Imada H., Ioannidis K., Jaeger B., Janas M., Janik B., Kc R. P., Keel P. K., Keeley J. W., Keller L., Kenrick D. T., Kiely K. M., Knutsson M., Kovacheva A., Kovera M. B., Krivoshchekov V., Krumrei-Mancuso E. J., Kulibert D., Lacko D., Lemay E. P., Leung D. W., Li F., Lin H., Lorenzo K. E., Lorenzo-Luaces L., Lou N. M., Lovakov A., Luzardo A., MacAulay S. C., Madan C. R., Mahmoud O., Makel M. C., Mari S., Fages D. M., Marsh A. A., McCarthy R. J., Mercier B., Milfont T. L., Mittlaender S., Montoya A. K., Moyer A., Myrseth K. O. R., Navarro-Martinez D., Nelson A. J., Neyse L., Minghui N., Niszczota P., Obrecht N. A., Otterbring T., Panlilio Z. A., Park L. E., Pauer S., Pavlov Y. G., Pentek I., Pereyra J. S., Perkowski P., Pew E., Peynircioglu Z. F., Pezzo M. V., Pirrone A., Plonsky O., Porfirio J. C. C., Pownall M., Prochnicki M. M., Protzko J., Roer J. P., Rahnev D., Reis H. T., Rios K., Rodrigues D. L., Rodriguez P., Roth Y., Ruffle B. J., Samahita M., Schmidt A., Schoemann M., Schoenegger P., Schwebel D. C., Segovia A. M., Sherman J. W., Siegenthaler S., Siem B., Sirota M., Smith E. R., Stamatogiannakis A., Stewart-Williams S., Storage D., Su Y., Talbert E. J., Todd A. R., Tonin M., Trautmann S. T., Travaglino G. A., Tsang J. -A., Veldhuizen R. V., Varnum M. E. W., Walf A. A., Wallrich L., Wang K., Ward D. E., Waugh C. E., Wingen T., Woike J. K., Wollbrant C. E., Wu S., Wylie K., Xiao Q., Xue S. Y., Yakobi O., Zayas V., Zheng J., Zhong Y., Zogmaister C., Zolopa C. S., Lisa N., Chin Wen O., and Dmitry G.

Abstract

A preregistered meta-analysis, including 244 effect sizes from 85 field audits and 361,645 individual job applications, tested for gender bias in hiring practices in female-stereotypical and gender-balanced as well as male-stereotypical jobs from 1976 to 2020. A “red team” of independent experts was recruited to increase the rigor and robustness of our meta-analytic approach. A forecasting survey further examined whether laypeople (n = 499 nationally representative adults) and scientists (n = 312) could predict the results. Forecasters correctly anticipated reductions in discrimination against female candidates over time. However, both scientists and laypeople overestimated the continuation of bias against female candidates. Instead, selection bias in favor of male over female candidates was eliminated and, if anything, slightly reversed in sign starting in 2009 for mixed-gender and male-stereotypical jobs in our sample. Forecasters further failed to anticipate that discrimination against male candidates for stereotypically female jobs would remain stable across the decades.

Published
2023

4. High educational performance is a distinctive feature of bipolar disorder: a study on cognition in bipolar disorder, schizophrenia patients, relatives and controls

Author

Vreeker, A., Boks, M. P. M., Abramovic, L., Verkooijen, S., van Bergen, A. H., Hillegers, M. H. J., Spijker, A. T., Hoencamp, E., Regeer, E. J., Riemersma-Van der Lek, R. F., Stevens, A. W. M. M., Schulte, P. F. J., Vonk, R., Hoekstra, R., van Beveren, N. J. M., Kupka, R. W., Brouwer, R. M., Bearden, C. E., MacCabe, J. H., and Ophoff, R. A.

Published
2016
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7. Effects of eight neuropsychiatric copy number variants on human brain structure

Author

Modenato, C., Kumar, K., Moreau, C., Martin-Brevet, S., Huguet, G., Schramm, C., Jean-Louis, M., Martin, C. -O., Younis, N., Tamer, P., Douard, E., Thebault-Dagher, F., Cote, V., Charlebois, A. -R., Deguire, F., Maillard, A. M., Rodriguez-Herreros, B., Pain, A., Richetin, S., Addor, M. -C., Andrieux, J., Arveiler, B., Baujat, G., Sloan-Bena, F., Belfiore, M., Bonneau, D., Bouquillon, S., Boute, O., Brusco, A., Busa, T., Caberg, J. -H., Campion, D., Colombert, V., Cordier, M. -P., David, A., Debray, F. -G., Delrue, M. -A., Doco-Fenzy, M., Dunkhase-Heinl, U., Edery, P., Fagerberg, C., Faivre, L., Forzano, F., Genevieve, D., Gerard, M., Giachino, D., Guichet, A., Guillin, O., Heron, D., Isidor, B., Jacquette, A., Jaillard, S., Journel, H., Keren, B., Lacombe, D., Lebon, S., Le Caignec, C., Lemaitre, M. -P., Lespinasse, J., Mathieu-Dramart, M., Mercier, S., Mignot, C., Missirian, C., Petit, F., Pilekaer Sorensen, K., Pinson, L., Plessis, G., Prieur, F., Raymond, A., Rooryck-Thambo, C., Rossi, M., Sanlaville, D., Schlott Kristiansen, B., Schluth-Bolard, C., Till, M., Van Haelst, M., Van Maldergem, L., Alupay, H., Aaronson, B., Ackerman, S., Ankenman, K., Anwar, A., Atwell, C., Bowe, A., Beaudet, A. L., Benedetti, M., Berg, J., Berman, J., Berry, L. N., Bibb, A. L., Blaskey, L., Brennan, J., Brewton, C. M., Buckner, R., Bukshpun, P., Burko, J., Cali, P., Cerban, B., Chang, Y., Cheong, M., Chow, V., Chu, Z., Chudnovskaya, D., Cornew, L., Dale, C., Dell, J., Dempsey, A. G., Deschamps, T., Earl, R., Edgar, J., Elgin, J., Olson, J. E., Evans, Y. L., Findlay, A., Fischbach, G. D., Fisk, C., Fregeau, B., Gaetz, B., Gaetz, L., Garza, S., Gerdts, J., Glenn, O., Gobuty, S. E., Golembski, R., Greenup, M., Heiken, K., Hines, K., Hinkley, L., Jackson, F. I., Jenkins, J., Jeremy, R. J., Johnson, K., Kanne, S. M., Kessler, S., Khan, S. Y., Ku, M., Kuschner, E., Laakman, A. L., Lam, P., Lasala, M. W., Lee, H., Laguerre, K., Levy, S., Cavanagh, A. L., Llorens, A. V., Campe, K. L., Luks, T. L., Marco, E. J., Martin, S., Martin, A. J., Marzano, G., Masson, C., Mcgovern, K. E., Keehn, R. M. N., Miller, D. T., Miller, F. K., Moss, T. J., Murray, R., Nagarajan, S. S., Nowell, K. P., Owen, J., Paal, A. M., Packer, A., Page, P. Z., Paul, B. M., Peters, A., Peterson, D., Poduri, A., Pojman, N. J., Porche, K., Proud, M. B., Qasmieh, S., Ramocki, M. B., Reilly, B., Roberts, T. P. L., Shaw, D., Sinha, T., Smith-Packard, B., Gallagher, A. S., Swarnakar, V., Thieu, T., Triantafallou, C., Vaughan, R., Wakahiro, M., Wallace, A., Ward, T., Wenegrat, J., Wolken, A., Melie-Garcia, L., Kushan, L., Silva, A. I., van den Bree, M. B. M., Linden, D. E. J., Owen, M. J., Hall, J., Lippe, S., Chakravarty, M., Bzdok, D., Bearden, C. E., Draganski, B., Jacquemont, S., Human genetics, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Reproduction & Development (AR&D), 16p11.2 European Consortium, Simons Searchlight Consortium, Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, School for Mental Health & Neuroscience, RS: MHeNs - R3 - Neuroscience, Addor, M.C., Andrieux, J., Arveiler, B., Baujat, G., Sloan-Béna, F., Belfiore, M., Bonneau, D., Bouquillon, S., Boute, O., Brusco, A., Busa, T., Caberg, J.H., Campion, D., Colombert, V., Cordier, M.P., David, A., Debray, F.G., Delrue, M.A., Doco-Fenzy, M., Dunkhase-Heinl, U., Edery, P., Fagerberg, C., Faivre, L., Forzano, F., Genevieve, D., Gérard, M., Giachino, D., Guichet, A., Guillin, O., Héron, D., Isidor, B., Jacquette, A., Jaillard, S., Journel, H., Keren, B., Lacombe, D., Lebon, S., Le Caignec, C., Lemaître, M.P., Lespinasse, J., Mathieu-Dramart, M., Mercier, S., Mignot, C., Missirian, C., Petit, F., Pilekær Sørensen, K., Pinson, L., Plessis, G., Prieur, F., Raymond, A., Rooryck-Thambo, C., Rossi, M., Sanlaville, D., Schlott Kristiansen, B., Schluth-Bolard, C., Till, M., Van Haelst, M., Van Maldergem, L., Alupay, H., Aaronson, B., Ackerman, S., Ankenman, K., Anwar, A., Atwell, C., Bowe, A., Beaudet, A.L., Benedetti, M., Berg, J., Berman, J., Berry, L.N., Bibb, A.L., Blaskey, L., Brennan, J., Brewton, C.M., Buckner, R., Bukshpun, P., Burko, J., Cali, P., Cerban, B., Chang, Y., Cheong, M., Chow, V., Chu, Z., Chudnovskaya, D., Cornew, L., Dale, C., Dell, J., Dempsey, A.G., Deschamps, T., Earl, R., Edgar, J., Elgin, J., Olson, J.E., Evans, Y.L., Findlay, A., Fischbach, G.D., Fisk, C., Fregeau, B., Gaetz, B., Gaetz, L., Garza, S., Gerdts, J., Glenn, O., Gobuty, S.E., Golembski, R., Greenup, M., Heiken, K., Hines, K., Hinkley, L., Jackson, F.I., Jenkins, J., Jeremy, R.J., Johnson, K., Kanne, S.M., Kessler, S., Khan, S.Y., Ku, M., Kuschner, E., Laakman, A.L., Lam, P., Lasala, M.W., Lee, H., LaGuerre, K., Levy, S., Cavanagh, A.L., Llorens, A.V., Campe, K.L., Luks, T.L., Marco, E.J., Martin, S., Martin, A.J., Marzano, G., Masson, C., McGovern, K.E., Keehn, R.M., Miller, D.T., Miller, F.K., Moss, T.J., Murray, R., Nagarajan, S.S., Nowell, K.P., Owen, J., Paal, A.M., Packer, A., Page, P.Z., Paul, B.M., Peters, A., Peterson, D., Poduri, A., Pojman, N.J., Porche, K., Proud, M.B., Qasmieh, S., Ramocki, M.B., Reilly, B., Roberts, TPL, Shaw, D., Sinha, T., Smith-Packard, B., Gallagher, A.S., Swarnakar, V., Thieu, T., Triantafallou, C., Vaughan, R., Wakahiro, M., Wallace, A., Ward, T., Wenegrat, J., and Wolken, A.

Subjects
0301 basic medicine, Simons Searchlight Consortium, Autism, 0302 clinical medicine, Gyrus, Gene duplication, 2.1 Biological and endogenous factors, Psychology, Copy-number variation, Aetiology, Genetics, Brain, Human brain, Magnetic Resonance Imaging, Psychiatry and Mental health, Mental Health, medicine.anatomical_structure, Schizophrenia, Neurological, Public Health and Health Services, RC321-571, DNA Copy Number Variations, Intellectual and Developmental Disabilities (IDD), Clinical Sciences, 16p11.2 European Consortium, Neurosciences. Biological psychiatry. Neuropsychiatry, Neuroimaging, Biology, Basic Behavioral and Social Science, Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, Clinical Research, Behavioral and Social Science, mental disorders, medicine, Humans, 22Q11.2 DELETION SYNDROME, Clinical genetics, AUTISM, COMMON, Biological Psychiatry, Prevention, Human Genome, Brain morphometry, Neurosciences, medicine.disease, DUPLICATION, Brain Disorders, 030104 developmental biology, 030217 neurology & neurosurgery, Neuroscience
Abstract

Many copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing that CNVs have large effects on brain anatomy. Here, we aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. We analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers (deletion/duplication) at the 1q21.1 (n = 39/28), 16p11.2 (n = 87/78), 22q11.2 (n = 75/30), and 15q11.2 (n = 72/76) loci as well as 1296 non-carriers (controls). Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy, with deletions and duplications showing mirror effects at the global and regional levels. Although CNVs mainly showed distinct brain patterns, principal component analysis (PCA) loaded subsets of CNVs on two latent brain dimensions, which explained 32 and 29% of the variance of the 8 Cohen’s d maps. The cingulate gyrus, insula, supplementary motor cortex, and cerebellum were identified by PCA and multi-view pattern learning as top regions contributing to latent dimension shared across subsets of CNVs. The large proportion of distinct CNV effects on brain morphology may explain the small neuroimaging effect sizes reported in polygenic psychiatric conditions. Nevertheless, latent gene brain morphology dimensions will help subgroup the rapidly expanding landscape of neuropsychiatric variants and dissect the heterogeneity of idiopathic conditions.

Published
2021
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9. Using common genetic variation to examine phenotypic expression and risk prediction in 22q11.2 deletion syndrome

Author

Davies, R. W., Fiksinski, A. M., Breetvelt, E. J., Williams, N. M., Hooper, S. R., Monfeuga, T., Bassett, A. S., Owen, M. J., Gur, R. E., Morrow, B. E., McDonald-McGinn, D. M., Swillen, A., Chow, E. W. C., van den Bree, M., Emanuel, B. S., Vermeesch, J. R., van Amelsvoort, T., Arango, C., Armando, M., Campbell, L. E., Cubells, J. F., Eliez, S., Garcia-Minaur, S., Gothelf, D., Kates, W. R., Murphy, K. C., Murphy, C. M., Murphy, D. G., Philip, N., Repetto, G. M., Shashi, V., Simon, T. J., Suner, D. H., Vicari, Stefano, Scherer, S. W., Epstein, M. P., Warren, S. T., Morrison, S., Chawner, S., Vingerhoets, C., Breckpot, J., Vergaelen, E., Vogels, A., Monks, S., Prasad, S. E., Sandini, C., Schneider, M., Maeder, J., Fraguas, D., Evers, R., Tassone, F., Morey-Canyelles, J., Ousley, O. Y., Antshel, K. M., Fremont, W., Fritsch, R., Ornstein, C., Daly, E. M., Costain, G. A., Boot, E., Heung, T., Crowley, T. B., Zackai, E. H., Calkins, M. E., Gur, R. C., Mccabe, K. L., Busa, T., Schoch, K., Pontillo, M., Duijff, S. N., Kahn, R. S., Houben, Mariasofia, Kushan, L., Jalbrzikowski, M., Carmel, M., Mekori-Domachevsky, E., Michaelovsky, E., Weinberger, R., Bearden, C. E., Vorstman, J. A. S., Marseille medical genetics - Centre de génétique médicale de Marseille (MMG), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Département de génétique médicale [Hôpital de la Timone - APHM], Institut National de la Santé et de la Recherche Médicale (INSERM)- Hôpital de la Timone [CHU - APHM] (TIMONE)-Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU), RS: MHeNs - R2 - Mental Health, Psychiatrie & Neuropsychologie, and MUMC+: MA Med Staf Spec Psychiatrie (9)

Subjects
0301 basic medicine, Male, Multifactorial Inheritance, [SDV]Life Sciences [q-bio], INTELLIGENCE, Medical and Health Sciences, Cohort Studies, ddc:616.89, 0302 clinical medicine, Borderline intellectual functioning, Risk Factors, Intellectual disability, 2.1 Biological and endogenous factors, PREMORBID IQ, Cognitive decline, Aetiology, Child, ComputingMilieux_MISCELLANEOUS, Intelligence quotient, ABNORMALITIES, General Medicine, Middle Aged, Serious Mental Illness, Mental Health, Phenotype, Schizophrenia, 030220 oncology & carcinogenesis, Child, Preschool, Cohort, Female, Clinical psychology, Adult, Psychosis, Adolescent, Immunology, behavioral disciplines and activities, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, Young Adult, Settore MED/39 - NEUROPSICHIATRIA INFANTILE, PSYCHOSIS, Clinical Research, Intellectual Disability, Genetic variation, Behavioral and Social Science, mental disorders, medicine, Genetics, DiGeorge Syndrome, Humans, Cognitive Dysfunction, Preschool, METAANALYSIS, International 22q11.2 Brain and Behavior Consortium, Aged, DECLINE, reliability, business.industry, Prevention, cognitive-development, Genetic Variation, PERFORMANCE, medicine.disease, Brain Disorders, schizophrenia, 030104 developmental biology, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, business
Abstract

The 22q11.2 deletion syndrome (22q11DS) is associated with a 20-25% risk of schizophrenia. In a cohort of 962 individuals with 22q11DS, we examined the shared genetic basis between schizophrenia and schizophrenia-related early trajectory phenotypes: sub-threshold symptoms of psychosis, low baseline intellectual functioning and cognitive decline. We studied the association of these phenotypes with two polygenic scores, derived for schizophrenia and intelligence, and evaluated their use for individual risk prediction in 22q11DS. Polygenic scores were not only associated with schizophrenia and baseline intelligence quotient (IQ), respectively, but schizophrenia polygenic score was also significantly associated with cognitive (verbal IQ) decline and nominally associated with sub-threshold psychosis. Furthermore, in comparing the tail-end deciles of the schizophrenia and IQ polygenic score distributions, 33% versus 9% of individuals with 22q11DS had schizophrenia, and 63% versus 24% of individuals had intellectual disability. Collectively, these data show a shared genetic basis for schizophrenia and schizophrenia-related phenotypes and also highlight the future potential of polygenic scores for risk stratification among individuals with highly, but incompletely, penetrant genetic variants.Polygenic risk scores are nearing a level of differentiation required for their clinical utility in risk prediction in populations with high-risk rare pathogenic genetic variants.

Published
2020
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13. Genetic contributors to risk of schizophrenia in the presence of a 22q11.2 deletion

Author

Cleynen, I., Engchuan, W., Hestand, M. S., Heung, T., Holleman, A. M., Johnston, H. R., Monfeuga, T., McDonald-McGinn, D. M., Gur, R. E., Morrow, B. E., Swillen, A., Vorstman, J. A. S., Bearden, C. E., Chow, E. W. C., van den Bree, M., Emanuel, B. S., Vermeesch, J. R., Warren, S. T., Owen, M. J., Chopra, P., Cutler, D. J., Duncan, R., Kotlar, A. V., Mulle, J. G., Voss, A. J., Zwick, M. E., Diacou, A., Golden, A., Guo, T., Lin, J. -R., Wang, T., Zhang, Z., Zhao, Yu Yang, Marshall, C., Merico, D., Jin, A., Lilley, B., Salmons, H. I., Tran, O., Holmans, P., Pardinas, A., Walters, J. T. R., Demaerel, W., Boot, E., Butcher, N. J., Costain, G. A., Lowther, C., Evers, R., van Amelsvoort, T. A. M. J., van Duin, E., Vingerhoets, C., Breckpot, J., Devriendt, K., Vergaelen, E., Vogels, A., Crowley, T. B., Mcginn, D. E., Moss, E. M., Sharkus, R. J., Unolt, M., Zackai, E. H., Calkins, M. E., Gallagher, R. S., Gur, R. C., Tang, S. X., Fritsch, R., Ornstein, C., Repetto, G. M., Breetvelt, E., Duijff, S. N., Fiksinski, A., Moss, H., Niarchou, M., Murphy, K. C., Prasad, S. E., Daly, E. M., Gudbrandsen, M., Murphy, C. M., Murphy, D. G., Buzzanca, A., Fabio, F. D., Digilio, M. C., Pontillo, M., Marino, B., Vicari, Stefano, Coleman, K., Cubells, J. F., Ousley, O. Y., Carmel, M., Gothelf, D., Mekori-Domachevsky, E., Michaelovsky, E., Weinberger, R., Weizman, A., Kushan, L., Jalbrzikowski, M., Armando, M., Eliez, S., Sandini, C., Schneider, M., Bena, F. S., Antshel, K. M., Fremont, W., Kates, W. R., Belzeaux, R., Busa, T., Philip, N., Campbell, L. E., Mccabe, K. L., Hooper, S. R., Schoch, K., Shashi, V., Simon, T. J., Tassone, F., Arango, C., Fraguas, D., Garcia-Minaur, S., Morey-Canyelles, J., Rosell, J., Suner, D. H., Raventos-Simic, J., Epstein, M. P., Williams, N. M., Bassett, A. S., Zhao Y., Vicari S. (ORCID:0000-0002-5395-2262), Cleynen, I., Engchuan, W., Hestand, M. S., Heung, T., Holleman, A. M., Johnston, H. R., Monfeuga, T., McDonald-McGinn, D. M., Gur, R. E., Morrow, B. E., Swillen, A., Vorstman, J. A. S., Bearden, C. E., Chow, E. W. C., van den Bree, M., Emanuel, B. S., Vermeesch, J. R., Warren, S. T., Owen, M. J., Chopra, P., Cutler, D. J., Duncan, R., Kotlar, A. V., Mulle, J. G., Voss, A. J., Zwick, M. E., Diacou, A., Golden, A., Guo, T., Lin, J. -R., Wang, T., Zhang, Z., Zhao, Yu Yang, Marshall, C., Merico, D., Jin, A., Lilley, B., Salmons, H. I., Tran, O., Holmans, P., Pardinas, A., Walters, J. T. R., Demaerel, W., Boot, E., Butcher, N. J., Costain, G. A., Lowther, C., Evers, R., van Amelsvoort, T. A. M. J., van Duin, E., Vingerhoets, C., Breckpot, J., Devriendt, K., Vergaelen, E., Vogels, A., Crowley, T. B., Mcginn, D. E., Moss, E. M., Sharkus, R. J., Unolt, M., Zackai, E. H., Calkins, M. E., Gallagher, R. S., Gur, R. C., Tang, S. X., Fritsch, R., Ornstein, C., Repetto, G. M., Breetvelt, E., Duijff, S. N., Fiksinski, A., Moss, H., Niarchou, M., Murphy, K. C., Prasad, S. E., Daly, E. M., Gudbrandsen, M., Murphy, C. M., Murphy, D. G., Buzzanca, A., Fabio, F. D., Digilio, M. C., Pontillo, M., Marino, B., Vicari, Stefano, Coleman, K., Cubells, J. F., Ousley, O. Y., Carmel, M., Gothelf, D., Mekori-Domachevsky, E., Michaelovsky, E., Weinberger, R., Weizman, A., Kushan, L., Jalbrzikowski, M., Armando, M., Eliez, S., Sandini, C., Schneider, M., Bena, F. S., Antshel, K. M., Fremont, W., Kates, W. R., Belzeaux, R., Busa, T., Philip, N., Campbell, L. E., Mccabe, K. L., Hooper, S. R., Schoch, K., Shashi, V., Simon, T. J., Tassone, F., Arango, C., Fraguas, D., Garcia-Minaur, S., Morey-Canyelles, J., Rosell, J., Suner, D. H., Raventos-Simic, J., Epstein, M. P., Williams, N. M., Bassett, A. S., Zhao Y., and Vicari S. (ORCID:0000-0002-5395-2262)

Abstract

Schizophrenia occurs in about one in four individuals with 22q11.2 deletion syndrome (22q11.2DS). The aim of this International Brain and Behavior 22q11.2DS Consortium (IBBC) study was to identify genetic factors that contribute to schizophrenia, in addition to the ~20-fold increased risk conveyed by the 22q11.2 deletion. Using whole-genome sequencing data from 519 unrelated individuals with 22q11.2DS, we conducted genome-wide comparisons of common and rare variants between those with schizophrenia and those with no psychotic disorder at age ≥25 years. Available microarray data enabled direct comparison of polygenic risk for schizophrenia between 22q11.2DS and independent population samples with no 22q11.2 deletion, with and without schizophrenia (total n = 35,182). Polygenic risk for schizophrenia within 22q11.2DS was significantly greater for those with schizophrenia (padj = 6.73 × 10−6). Novel reciprocal case–control comparisons between the 22q11.2DS and population-based cohorts showed that polygenic risk score was significantly greater in individuals with psychotic illness, regardless of the presence of the 22q11.2 deletion. Within the 22q11.2DS cohort, results of gene-set analyses showed some support for rare variants affecting synaptic genes. No common or rare variants within the 22q11.2 deletion region were significantly associated with schizophrenia. These findings suggest that in addition to the deletion conferring a greatly increased risk to schizophrenia, the risk is higher when the 22q11.2 deletion and common polygenic risk factors that contribute to schizophrenia in the general population are both present.

Published
2020

15. The Association between familial risk and brain abnormalities Is disease specific: an ENIGMA-relatives study of schizophrenia and bipolar disorder

Author

Zwarte, S. M. C., Brouwer, R. M., Agartz, I., Alda, M., Aleman, A., Alpert, K. I., Bearden, C. E., Bertolino, A., Bois, C., Bonvino, A., Bramon, E., Buimer, E., Cahn, W., Cannon, D. M., Cannon, T. D., Caseras, X., Castro-Fornieles, J., Chen, Q., Serna, E., Giorgio, A. D., Doucet, G., Eker, M. C., Erk, S., Fears, S., Foley, S., Frangou, S., Frankland, A., Fullerton, J., Glahn, D., Goghari, V., Goldman, A., Gonul, A., Gruber, O., Haan, L., Hajek, T., Hawkins, E., Heinz, A., Hillegers, M., Pol, H., Hultman, C., Ingvar, M., Johansson, V., Jönsson, E., Kane, K., Kempton, M., Koenis, M., Kopecek, M., Krabbendam, L., Krämer, B., Lawrie, S., Lenroot, R., Marcelis, M., Marsman, J-B, Mattay, V., McDonald, C., Meyer-Lindenberg, A., Michielse, S., Mitchell, P., Moreno, D., Murray, R., Mwangi, B., Najt, P., Neilson, E., Newport, J., Os, J., Overs, B., Özerdem, A., Picchioni, M., Richter, A., Roberts, G., Aydoğan, A. S., Schofield, P., Şimşek, F., Soares, J., Sugranyes, G., Toulopoulou, Timothea, Tronchin, G., Walter, H., Wang, L., Weinberger, D., Whalley, H., Yalın, N., Andreassen, O., Ching, C., Erp, T., Turner, J., Jahanshad, N., Thompson, P., Kahn, R., Haren, N., and Toulopoulou, Timothea

Subjects
Meta-analysis, Familial riskImaging, Bipolar disorder, Neurodevelopment, Schizophrenia
Abstract

Background Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects. Methods We performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects. Results FDRs-BD had significantly larger ICV (d = +0.16, q < .05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = −0.12, q < .05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d < −0.09, q < .05 corrected); and third ventricle was larger (d = +0.15, q < .05 corrected). The findings were not explained by psychopathology in the relatives or control subjects. Conclusions Despite shared genetic liability, FDRs-SZ and FDRs-BD show a differential pattern of structural brain abnormalities, specifically a divergent effect in ICV. This may imply that the neurodevelopmental trajectories leading to brain anomalies in schizophrenia or bipolar disorder are distinct.

Published
2019

16. Childhood trauma and cognitive functioning in individuals at clinical high risk (CHR) for psychosis

Author

Velikonja, T., primary, Velthorst, E., additional, Zinberg, J., additional, Cannon, T. D., additional, Cornblatt, B. A., additional, Perkins, D. O., additional, Cadenhead, K. S., additional, Tsuang, M. T., additional, Addington, J., additional, Woods, S. W., additional, McGlashan, T., additional, Mathalon, D. H., additional, Stone, W., additional, Keshavan, M., additional, Seidman, L., additional, and Bearden, C. E., additional

Published
2020
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17. Childhood trauma and cognitive functioning in individuals at clinical high risk (CHR) for psychosis.

Author

Velikonja, T., Velthorst, E., Zinberg, J., Cannon, T. D., Cornblatt, B. A., Perkins, D. O., Cadenhead, K. S., Tsuang, M. T., Addington, J., Woods, S. W., McGlashan, T., Mathalon, D. H., Stone, W., Keshavan, M., Seidman, L., and Bearden, C. E.

Subjects
COGNITIVE ability, PSYCHOSES, BULLYING, SEX crimes, SOCIAL perception, COGNITION
Abstract

Evidence suggests that early trauma may have a negative effect on cognitive functioning in individuals with psychosis, yet the relationship between childhood trauma and cognition among those at clinical high risk (CHR) for psychosis remains unexplored. Our sample consisted of 626 CHR children and 279 healthy controls who were recruited as part of the North American Prodrome Longitudinal Study 2. Childhood trauma up to the age of 16 (psychological, physical, and sexual abuse, emotional neglect, and bullying) was assessed by using the Childhood Trauma and Abuse Scale. Multiple domains of cognition were measured at baseline and at the time of psychosis conversion, using standardized assessments. In the CHR group, there was a trend for better performance in individuals who reported a history of multiple types of childhood trauma compared with those with no/one type of trauma (Cohen d = 0.16). A history of multiple trauma types was not associated with greater cognitive change in CHR converters over time. Our findings tentatively suggest there may be different mechanisms that lead to CHR states. Individuals who are at clinical high risk who have experienced multiple types of childhood trauma may have more typically developing premorbid cognitive functioning than those who reported minimal trauma do. Further research is needed to unravel the complexity of factors underlying the development of at-risk states. [ABSTRACT FROM AUTHOR]

Published
2021
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20. Subcortical volumetric abnormalities in bipolar disorder

Author

Hibar, D. P., Westlye, L. T., Van Erp, T. G M, Rasmussen, J., Leonardo, C. D., Faskowitz, J., Haukvik, U. K., Hartberg, C. B., Doan, N. T., Agartz, I., Dale, A. M., Gruber, O., Krämer, B., Trost, S., Liberg, B., Abé, C., Ekman, C. J., Ingvar, M., Landén, M., Fears, S. C., Freimer, N. B., Bearden, C. E., Sprooten, E., Glahn, D. C., Pearlson, G. D., Emsell, L., Kenney, J., Scanlon, C., McDonald, C., Cannon, D. M., Almeida, J., Versace, A., Caseras, X., Lawrence, N. S., Phillips, M. L., Dima, D., Delvecchio, G., Frangou, S., Satterthwaite, T. D., Wolf, D., Houenou, J., Henry, C., Malt, U. F., BØen, E., Elvs'shagen, T., Young, A. H., Lloyd, A. J., Goodwin, G. M., Mackay, C. E., Bourne, C., Bilderbeck, A., Abramovic, L., Boks, M. P., Van Haren, N. E M, Ophoff, R. A., Kahn, R. S., Bauer, M., Pfennig, A., Alda, M., Hajek, T., Mwangi, B., Soares, J. C., Nickson, T., Dimitrova, R., Sussmann, J. E., Hagenaars, S., Whalley, H. C., McIntosh, A. M., Thompson, P. M., Andreassen, O. A., Hibar, D. P., Westlye, L. T., Van Erp, T. G M, Rasmussen, J., Leonardo, C. D., Faskowitz, J., Haukvik, U. K., Hartberg, C. B., Doan, N. T., Agartz, I., Dale, A. M., Gruber, O., Krämer, B., Trost, S., Liberg, B., Abé, C., Ekman, C. J., Ingvar, M., Landén, M., Fears, S. C., Freimer, N. B., Bearden, C. E., Sprooten, E., Glahn, D. C., Pearlson, G. D., Emsell, L., Kenney, J., Scanlon, C., McDonald, C., Cannon, D. M., Almeida, J., Versace, A., Caseras, X., Lawrence, N. S., Phillips, M. L., Dima, D., Delvecchio, G., Frangou, S., Satterthwaite, T. D., Wolf, D., Houenou, J., Henry, C., Malt, U. F., BØen, E., Elvs'shagen, T., Young, A. H., Lloyd, A. J., Goodwin, G. M., Mackay, C. E., Bourne, C., Bilderbeck, A., Abramovic, L., Boks, M. P., Van Haren, N. E M, Ophoff, R. A., Kahn, R. S., Bauer, M., Pfennig, A., Alda, M., Hajek, T., Mwangi, B., Soares, J. C., Nickson, T., Dimitrova, R., Sussmann, J. E., Hagenaars, S., Whalley, H. C., McIntosh, A. M., Thompson, P. M., and Andreassen, O. A.

Published
2016

21. Subcortical volumetric abnormalities in bipolar disorder

Author

Brain, Onderzoeksgroep 4, Onderzoeksgroep 2, Onderzoek, Circulatory Health, Hibar, D. P., Westlye, L. T., Van Erp, T. G M, Rasmussen, J., Leonardo, C. D., Faskowitz, J., Haukvik, U. K., Hartberg, C. B., Doan, N. T., Agartz, I., Dale, A. M., Gruber, O., Krämer, B., Trost, S., Liberg, B., Abé, C., Ekman, C. J., Ingvar, M., Landén, M., Fears, S. C., Freimer, N. B., Bearden, C. E., Sprooten, E., Glahn, D. C., Pearlson, G. D., Emsell, L., Kenney, J., Scanlon, C., McDonald, C., Cannon, D. M., Almeida, J., Versace, A., Caseras, X., Lawrence, N. S., Phillips, M. L., Dima, D., Delvecchio, G., Frangou, S., Satterthwaite, T. D., Wolf, D., Houenou, J., Henry, C., Malt, U. F., BØen, E., Elvs'shagen, T., Young, A. H., Lloyd, A. J., Goodwin, G. M., Mackay, C. E., Bourne, C., Bilderbeck, A., Abramovic, L., Boks, M. P., Van Haren, N. E M, Ophoff, R. A., Kahn, R. S., Bauer, M., Pfennig, A., Alda, M., Hajek, T., Mwangi, B., Soares, J. C., Nickson, T., Dimitrova, R., Sussmann, J. E., Hagenaars, S., Whalley, H. C., McIntosh, A. M., Thompson, P. M., Andreassen, O. A., Brain, Onderzoeksgroep 4, Onderzoeksgroep 2, Onderzoek, Circulatory Health, Hibar, D. P., Westlye, L. T., Van Erp, T. G M, Rasmussen, J., Leonardo, C. D., Faskowitz, J., Haukvik, U. K., Hartberg, C. B., Doan, N. T., Agartz, I., Dale, A. M., Gruber, O., Krämer, B., Trost, S., Liberg, B., Abé, C., Ekman, C. J., Ingvar, M., Landén, M., Fears, S. C., Freimer, N. B., Bearden, C. E., Sprooten, E., Glahn, D. C., Pearlson, G. D., Emsell, L., Kenney, J., Scanlon, C., McDonald, C., Cannon, D. M., Almeida, J., Versace, A., Caseras, X., Lawrence, N. S., Phillips, M. L., Dima, D., Delvecchio, G., Frangou, S., Satterthwaite, T. D., Wolf, D., Houenou, J., Henry, C., Malt, U. F., BØen, E., Elvs'shagen, T., Young, A. H., Lloyd, A. J., Goodwin, G. M., Mackay, C. E., Bourne, C., Bilderbeck, A., Abramovic, L., Boks, M. P., Van Haren, N. E M, Ophoff, R. A., Kahn, R. S., Bauer, M., Pfennig, A., Alda, M., Hajek, T., Mwangi, B., Soares, J. C., Nickson, T., Dimitrova, R., Sussmann, J. E., Hagenaars, S., Whalley, H. C., McIntosh, A. M., Thompson, P. M., and Andreassen, O. A.

Published
2016

22. High educational performance is a distinctive feature of bipolar disorder: A study on cognition in bipolar disorder, schizophrenia patients, relatives and controls

Author

Onderzoek, Onderzoeksgroep 2, Brain, Risico & Preventie Ond., AIOS Psychiatrie, Onderzoeksgroep 3, Onderzoeksgroep 1, Circulatory Health, Vreeker, A., Boks, M. P M, Abramovic, L., Verkooijen, S., Van Bergen, A. H., Hillegers, M. H J, Spijker, A. T., Hoencamp, E., Regeer, E. J., Riemersma-Van Der Lek, R. F., Stevens, A. W M M, Schulte, P. F J, Vonk, R., Hoekstra, R., Van Beveren, N. J M, Kupka, R. W., Brouwer, R. M., Bearden, C. E., MacCabe, J. H., Ophoff, R. A., Onderzoek, Onderzoeksgroep 2, Brain, Risico & Preventie Ond., AIOS Psychiatrie, Onderzoeksgroep 3, Onderzoeksgroep 1, Circulatory Health, Vreeker, A., Boks, M. P M, Abramovic, L., Verkooijen, S., Van Bergen, A. H., Hillegers, M. H J, Spijker, A. T., Hoencamp, E., Regeer, E. J., Riemersma-Van Der Lek, R. F., Stevens, A. W M M, Schulte, P. F J, Vonk, R., Hoekstra, R., Van Beveren, N. J M, Kupka, R. W., Brouwer, R. M., Bearden, C. E., MacCabe, J. H., and Ophoff, R. A.

Published
2016

23. Insights into psychosis risk from leukocyte microRNA expression

Author

Jeffries, C D, primary, Perkins, D O, additional, Chandler, S D, additional, Stark, T, additional, Yeo, E, additional, Addington, J, additional, Bearden, C E, additional, Cadenhead, K S, additional, Cannon, T D, additional, Cornblatt, B A, additional, Mathalon, D H, additional, McGlashan, T H, additional, Seidman, L J, additional, Walker, E F, additional, Woods, S W, additional, Glatt, S J, additional, and Tsuang, M, additional

Published
2016
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24. Cognitive decline preceding the onset of psychosis in patients with 22q11.2 deletion syndrome

Author

Vorstman, J. A. S., Breetvelt, E. J., Duijff, S. N., Eliez, S., Schneider, M., Jalbrzikowski, M., Armando, M., Vicari, S., Shashi, V., Hooper, S. R., Chow, E. W. C., Fung, W. L. A., Butcher, N. J., Young, D. A., McDonald-McGinn, D. M., Vogels, A., Van Amelsvoort, T., Gothelf, D., Weinberger, R., Weizman, A., Klaassen, P. W. J., Koops, S., Kates, W. R., Antshel, K. M., Simon, T. J., Ousley, O. Y., Swillen, A., Gur, R. E., Bearden, C. E., Kahn, R. S., Bassett, A. S., Emanuel, B. S., Zackai, E. H., Kushan, L., Fremont, W., Schoch, K., Stoddard, J., Cubells, J., Fu, F., Campbell, L. E., Fritsch, R., Vergaelen, E., Neeleman, M., Boot, E., Debbane, M., Philip, N., Green, T., Van DenBree, M. B. M., Murphy, D., Canyelles, J. M., Arango, C., Murphy, K. C., Pontillo, M., Vicari S. (ORCID:0000-0002-5395-2262), Vorstman, J. A. S., Breetvelt, E. J., Duijff, S. N., Eliez, S., Schneider, M., Jalbrzikowski, M., Armando, M., Vicari, S., Shashi, V., Hooper, S. R., Chow, E. W. C., Fung, W. L. A., Butcher, N. J., Young, D. A., McDonald-McGinn, D. M., Vogels, A., Van Amelsvoort, T., Gothelf, D., Weinberger, R., Weizman, A., Klaassen, P. W. J., Koops, S., Kates, W. R., Antshel, K. M., Simon, T. J., Ousley, O. Y., Swillen, A., Gur, R. E., Bearden, C. E., Kahn, R. S., Bassett, A. S., Emanuel, B. S., Zackai, E. H., Kushan, L., Fremont, W., Schoch, K., Stoddard, J., Cubells, J., Fu, F., Campbell, L. E., Fritsch, R., Vergaelen, E., Neeleman, M., Boot, E., Debbane, M., Philip, N., Green, T., Van DenBree, M. B. M., Murphy, D., Canyelles, J. M., Arango, C., Murphy, K. C., Pontillo, M., and Vicari S. (ORCID:0000-0002-5395-2262)

Abstract

Importance: Patients with 22q11.2 deletion syndrome (22q11DS) have an elevated (25%) risk of developing schizophrenia. Recent reports have suggested that a subgroup of children with 22q11DS display a substantial decline in cognitive abilities starting at a young age.Objective: To determine whether early cognitive decline is associated with risk of psychotic disorder in 22q11DS.Design, Setting, And Participants: Prospective longitudinal cohort study. As part of an international research consortium initiative, we used the largest data set of intelligence (IQ) measurements in patients with 22q11DS reported to date to investigate longitudinal IQ trajectories and the risk of subsequent psychotic illness. A total of 829 patients with a confirmed hemizygous 22q11.2 deletion, recruited through 12 international clinical research sites, were included. Both psychiatric assessments and longitudinal IQ measurements were available for a subset of 411 patients (388 with≥1 assessment at age 8-24 years).Main Outcomes And Measures: Diagnosis of a psychotic disorder, initial IQ, longitudinal IQ trajectory, and timing of the last psychiatric assessment with respect to the last IQ test.Results: Among 411 patients with 22q11DS, 55 (13.4%) were diagnosed as having a psychotic disorder. The mean (SD) age at the most recent psychiatric assessment was 16.1 (6.2) years. The mean (SD) full-scale IQ at first cognitive assessment was lower in patients who developed a psychotic disorder (65.5 [12.0]) compared with those without a psychotic disorder (74.0 [14.0]). On average, children with 22q11DS showed a mild decline in IQ (full-scale IQ, 7.04 points) with increasing age, particularly in the domain of verbal IQ (9.02 points). In those who developed psychotic illness, this decline was significantly steeper (P < .001). Those with a negative deviation from the average cognitive trajectory observed in 22q11DS were at significantly increased risk for the development of a psychotic disorder (odds r

Published
2015

25. Alcohol confounds relationship between cannabis misuse and psychosis conversion in a high-risk sample

Author

Auther, A. M., primary, Cadenhead, K. S., additional, Carrión, R. E., additional, Addington, J., additional, Bearden, C. E., additional, Cannon, T. D., additional, McGlashan, T. H., additional, Perkins, D. O., additional, Seidman, L., additional, Tsuang, M., additional, Walker, E. F., additional, Woods, S. W., additional, and Cornblatt, B. A., additional

Published
2015
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26. Psychiatric disorders from childhood to adulthood in 22q11.2 deletion syndrome: Results from the international consortium on brain and behavior in 22q11.2 deletion syndrome

Author

Schneider, M., Debbane, M., Bassett, A. S., Chow, E. W. C., Fung, W. L. A., Van Den Bree, M. B. M., Owen, M., Murphy, K. C., Niarchou, M., Kates, W. R., Antshel, K. M., Fremont, W., McDonald-McGinn, D. M., Gur, R. E., Zackai, E. H., Vorstman, J., Duijff, S. N., Klaassen, P. W. J., Swillen, A., Gothelf, D., Green, T., Weizman, A., Van Amelsvoort, T., Evers, L., Boot, E., Shashi, V., Hooper, S. R., Bearden, C. E., Jalbrzikowski, M., Armando, M., Vicari, Stefano, Murphy, D. G., Ousley, O., Campbell, L. E., Simon, T. J., Eliez, S., Vicari S. (ORCID:0000-0002-5395-2262), Schneider, M., Debbane, M., Bassett, A. S., Chow, E. W. C., Fung, W. L. A., Van Den Bree, M. B. M., Owen, M., Murphy, K. C., Niarchou, M., Kates, W. R., Antshel, K. M., Fremont, W., McDonald-McGinn, D. M., Gur, R. E., Zackai, E. H., Vorstman, J., Duijff, S. N., Klaassen, P. W. J., Swillen, A., Gothelf, D., Green, T., Weizman, A., Van Amelsvoort, T., Evers, L., Boot, E., Shashi, V., Hooper, S. R., Bearden, C. E., Jalbrzikowski, M., Armando, M., Vicari, Stefano, Murphy, D. G., Ousley, O., Campbell, L. E., Simon, T. J., Eliez, S., and Vicari S. (ORCID:0000-0002-5395-2262)

Abstract

Objective: Chromosome 22q11.2 deletion syndrome is a neurogenetic disorder associated with high rates of schizophrenia and other psychiatric conditions. The authors report what is to their knowledge the first large-scale collaborative study of rates and sex distributions of psychiatric disorders from childhood to adulthood in 22q11.2 deletion syndrome. The associations among psychopathology, intellect, and functioning were examined in a subgroup of participants. Method: The 1,402 participants with 22q11.2 deletion syndrome, ages 6-68 years, were assessed for psychiatric disorders with validated diagnostic instruments. Data on intelligence and adaptive functioning were available for 183 participants ages 6 to 24 years. Results: Attention deficit hyperactivity disorder (ADHD) was the most frequent disorder in children (37.10%) and was overrepresented in males. Anxiety disorders were more prevalent than mood disorders at all ages, but especially in children and adolescents. Anxiety and unipolar mood disorders were over-represented in females. Psychotic disorders were present in 41% of adults over age 25. Males did not predominate in psychotic or autism spectrum disorders. Hierarchical regressions in the subgroup revealed that daily living skills were predicted by the presence of anxiety disorders. Psychopathology was not associated with communication or socialization skills. Conclusions: To the authors' knowledge, this is the largest study of psychiatric morbidity in 22q11.2 deletion syndrome. It validates previous findings that this condition is one of the strongest risk factors for psychosis. Anxiety and developmental disorders were also prevalent. These results highlight the need to monitor and reduce the long-term burden of psychopathology in 22q11.2 deletion syndrome.

Published
2014

27. Cortical abnormalities in bipolar disorder: an MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group

Author

Hibar, D P, Westlye, L T, Doan, N T, Jahanshad, N, Cheung, J W, Ching, C R K, Versace, A, Bilderbeck, A C, Uhlmann, A, Mwangi, B, Krämer, B, Overs, B, Hartberg, C B, Abé, C, Dima, D, Grotegerd, D, Sprooten, E, Bøen, E, Jimenez, E, Howells, F M, Delvecchio, G, Temmingh, H, Starke, J, Almeida, J R C, Goikolea, J M, Houenou, J, Beard, L M, Rauer, L, Abramovic, L, Bonnin, M, Ponteduro, M F, Keil, M, Rive, M M, Yao, N, Yalin, N, Najt, P, Rosa, P G, Redlich, R, Trost, S, Hagenaars, S, Fears, S C, Alonso-Lana, S, van Erp, T G M, Nickson, T, Chaim-Avancini, T M, Meier, T B, Elvsåshagen, T, Haukvik, U K, Lee, W H, Schene, A H, Lloyd, A J, Young, A H, Nugent, A, Dale, A M, Pfennig, A, McIntosh, A M, Lafer, B, Baune, B T, Ekman, C J, Zarate, C A, Bearden, C E, Henry, C, Simhandl, C, McDonald, C, Bourne, C, Stein, D J, Wolf, D H, Cannon, D M, Glahn, D C, Veltman, D J, Pomarol-Clotet, E, Vieta, E, Canales-Rodriguez, E J, Nery, F G, Duran, F L S, Busatto, G F, Roberts, G, Pearlson, G D, Goodwin, G M, Kugel, H, Whalley, H C, Ruhe, H G, Soares, J C, Fullerton, J M, Rybakowski, J K, Savitz, J, Chaim, K T, Fatjó-Vilas, M, Soeiro-de-Souza, M G, Boks, M P, Zanetti, M V, Otaduy, M C G, Schaufelberger, M S, Alda, M, Ingvar, M, Phillips, M L, Kempton, M J, Bauer, M, Landén, M, Lawrence, N S, van Haren, N E M, Horn, N R, Freimer, N B, Gruber, O, Schofield, P R, Mitchell, P B, Kahn, R S, Lenroot, R, Machado-Vieira, R, Ophoff, R A, Sarró, S, Frangou, S, Satterthwaite, T D, Hajek, T, Dannlowski, U, Malt, U F, Arolt, V, Gattaz, W F, Drevets, W C, Caseras, X, Agartz, I, Thompson, P M, and Andreassen, O A

Abstract

Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen’s d=-0.293; P=1.71 × 10-21), left fusiform gyrus (d=-0.288; P=8.25 × 10-21) and left rostral middle frontal cortex (d=-0.276; P=2.99 × 10-19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.

Published
2018
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32. Subcortical volumetric abnormalities in bipolar disorder

Author

Hibar, D P, Westlye, L T, van Erp, T G M, Rasmussen, J, Leonardo, C D, Faskowitz, J, Haukvik, U K, Hartberg, C B, Doan, N T, Agartz, I, Dale, A M, Gruber, O, Krämer, B, Trost, S, Liberg, B, Abé, C, Ekman, C J, Ingvar, M, Landén, M, Fears, S C, Freimer, N B, Bearden, C E, Sprooten, E, Glahn, D C, Pearlson, G D, Emsell, L, Kenney, J, Scanlon, C, McDonald, C, Cannon, D M, Almeida, J, Versace, A, Caseras, X, Lawrence, N S, Phillips, M L, Dima, D, Delvecchio, G, Frangou, S, Satterthwaite, T D, Wolf, D, Houenou, J, Henry, C, Malt, U F, Bøen, E, Elvsåshagen, T, Young, A H, Lloyd, A J, Goodwin, G M, Mackay, C E, Bourne, C, Bilderbeck, A, Abramovic, L, Boks, M P, van Haren, N E M, Ophoff, R A, Kahn, R S, Bauer, M, Pfennig, A, Alda, M, Hajek, T, Mwangi, B, Soares, J C, Nickson, T, Dimitrova, R, Sussmann, J E, Hagenaars, S, Whalley, H C, McIntosh, A M, Thompson, P M, and Andreassen, O A

Abstract

Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case–control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen’s d=−0.232; P=3.50 × 10−7) and thalamus (d=−0.148; P=4.27 × 10−3) and enlarged lateral ventricles (d=−0.260; P=3.93 × 10−5) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons.

Published
2016
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38. Insights into psychosis risk from leukocyte microRNA expression

Author

Jeffries, C D, Perkins, D O, Chandler, S D, Stark, T, Yeo, E, Addington, J, Bearden, C E, Cadenhead, K S, Cannon, T D, Cornblatt, B A, Mathalon, D H, McGlashan, T H, Seidman, L J, Walker, E F, Woods, S W, Glatt, S J, and Tsuang, M

Abstract

Dysregulation of immune system functions has been implicated in schizophrenia, suggesting that immune cells may be involved in the development of the disorder. With the goal of a biomarker assay for psychosis risk, we performed small RNA sequencing on RNA isolated from circulating immune cells. We compared baseline microRNA (miRNA) expression for persons who were unaffected (n=27) or who, over a subsequent 2-year period, were at clinical high risk but did not progress to psychosis (n=37), or were at high risk and did progress to psychosis (n=30). A greedy algorithm process led to selection of five miRNAs that when summed with +1 weights distinguished progressed from nonprogressed subjects with an area under the receiver operating characteristic curve of 0.86. Of the five, miR-941 is human-specific with incompletely understood functions, but the other four are prominent in multiple immune system pathways. Three of those four are downregulated in progressed vs. nonprogressed subjects (with weight -1 in a classifier function that increases with risk); all three have also been independently reported as downregulated in monocytes from schizophrenia patients vs. unaffected subjects. Importantly, these findings passed stringent randomization tests that minimized the risk of conclusions arising by chance. Regarding miRNA–miRNA correlations over the three groups, progressed subjects were found to have much weaker miRNA orchestration than nonprogressed or unaffected subjects. If independently verified, the leukocytic miRNA biomarker assay might improve accuracy of psychosis high-risk assessments and eventually help rationalize preventative intervention decisions.

Published
2016
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42. What we learn about bipolar disorder from large-scale neuroimaging

Author

Christian K. Tamnes, Bartholomeus C M Haarman, Jair C. Soares, Ole A. Andreassen, Viola Oertel, Theodore D. Satterthwaite, G. Tronchin, Michael Stäblein, Bradley J. MacIntosh, Melissa Pauling, Christopher R.K. Ching, Daniel H. Wolf, Dick J. Veltman, Ingrid Agartz, Bernhard T. Baune, Salvador Sarró, Mon-Ju Wu, Scott C Fears, Eduard Vieta, Melissa J. Green, Neeltje E.M. van Haren, Yann Quidé, Erlend Bøen, Yash Patel, Igor Nenadic, Martin Alda, Lisa T. Eyler, Arnaud Pouchon, Danai Dima, Tomáš Paus, Irene Bollettini, Torbjørn Elvsåshagen, Rachel M. Brouwer, Lakshmi N. Yatham, Michael Bauer, Caterina del Mar Bonnín, C. McDonald, Udo Dannlowski, Bronwyn Overs, Edith Pomarol-Clotet, Cristian Vargas Upegui, Oliver Gruber, Henricus G. Ruhé, Márcio Gerhardt Soeiro-de-Souza, Edouard Duchesnay, Hilary P. Blumberg, Tilo Kircher, Miho Ota, Michael Berk, Christoph Abé, Andreas Jansen, Kang Sim, Heather C. Whalley, Derrek P. Hibar, Roel A. Ophoff, Georgios V Thomaidis, Henrik Walter, Sophia Frangou, Michèle Wessa, Dara M. Cannon, Cara M. Altimus, Allison C. Nugent, Rodrigo Machado-Vieira, Orwa Dandash, Marcella Bellani, Unn K. Haukvik, Philip B. Mitchell, Ling-Li Zeng, Christian Knöchel, Jose Manuel Goikolea, Sonja M C de Zwarte, Francesco Benedetti, Sara Poletti, Janice M. Fullerton, Carlos A. Zarate, Aart H. Schene, Dan J. Stein, Chantal Henry, Tristram A. Lett, Mikael Landén, Daniel L Pham, Paolo Brambilla, Silvia Alonso-Lana, Sophia I. Thomopoulos, Carlos López-Jaramillo, Tomas Hajek, Bernd Kramer, G. Delvecchio, Maria M. Rive, Lars T. Westlye, Erick J. Canales-Rodríguez, Victoria L. Ives-Deliperi, Dominik Grotegerd, Beny Lafer, Abraham Nunes, Carrie E. Bearden, Raymond Salvador, Joaquim Radua, Amy C Bilderbeck, Xavier Caseras, Paul M. Thompson, Jorge R. C. Almeida, Pauline Favre, Gloria Roberts, David C. Glahn, Dag Alnæs, Julian A Pineda-Zapata, Tiril P. Gurholt, Mircea Polosan, Josselin Houenou, Fabiano G. Nery, Leila Nabulsi, Mary L. Phillips, Fleur M. Howells, Ana M. Díaz-Zuluaga, Elisa M T Melloni, Ching, C. R. K., Hibar, D. P., Gurholt, T. P., Nunes, A., Thomopoulos, S. I., Abe, C., Agartz, I., Brouwer, R. M., Cannon, D. M., de Zwarte, S. M. C., Eyler, L. T., Favre, P., Hajek, T., Haukvik, U. K., Houenou, J., Landen, M., Lett, T. A., Mcdonald, C., Nabulsi, L., Patel, Y., Pauling, M. E., Paus, T., Radua, J., Soeiro-de-Souza, M. G., Tronchin, G., van Haren, N. E. M., Vieta, E., Walter, H., Zeng, L. -L., Alda, M., Almeida, J., Alnaes, D., Alonso-Lana, S., Altimus, C., Bauer, M., Baune, B. T., Bearden, C. E., Bellani, M., Benedetti, F., Berk, M., Bilderbeck, A. C., Blumberg, H. P., Boen, E., Bollettini, I., del Mar Bonnin, C., Brambilla, P., Canales-Rodriguez, E. J., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Diaz-Zuluaga, A. M., Dima, D., Duchesnay, E., Elvsashagen, T., Fears, S. C., Frangou, S., Fullerton, J. M., Glahn, D. C., Goikolea, J. M., Green, M. J., Grotegerd, D., Gruber, O., Haarman, B. C. M., Henry, C., Howells, F. M., Ives-Deliperi, V., Jansen, A., Kircher, T. T. J., Knochel, C., Kramer, B., Lafer, B., Lopez-Jaramillo, C., Machado-Vieira, R., Macintosh, B. J., Melloni, E. M. T., Mitchell, P. B., Nenadic, I., Nery, F., Nugent, A. C., Oertel, V., Ophoff, R. A., Ota, M., Overs, B. J., Pham, D. L., Phillips, M. L., Pineda-Zapata, J. A., Poletti, S., Polosan, M., Pomarol-Clotet, E., Pouchon, A., Quide, Y., Rive, M. M., Roberts, G., Ruhe, H. G., Salvador, R., Sarro, S., Satterthwaite, T. D., Schene, A. H., Sim, K., Soares, J. C., Stablein, M., Stein, D. J., Tamnes, C. K., Thomaidis, G. V., Upegui, C. V., Veltman, D. J., Wessa, M., Westlye, L. T., Whalley, H. C., Wolf, D. H., Wu, M. -J., Yatham, L. N., Zarate, C. A., Thompson, P. M., and Andreassen, O. A.

Subjects
mega-analysis, Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], cortical surface area, Review Article, 0302 clinical medicine, Manic-depressive illness, Multicenter Studies as Topic, Spectrum disorder, Review Articles, bipolar disorder, Cerebral Cortex, Trastorn bipolar, neuroimaging, Radiological and Ultrasound Technology, 05 social sciences, ENIGMA, HUMAN BRAIN, Magnetic Resonance Imaging, psychiatry, 3. Good health, Neurology, Meta-analysis, Scale (social sciences), Anatomy, Psychology, Clinical risk factor, Clinical psychology, MRI, MAJOR PSYCHIATRIC-DISORDERS, Schizoaffective disorder, 050105 experimental psychology, 03 medical and health sciences, Magnetic resonance imaging, Neuroimaging, Meta-Analysis as Topic, SDG 3 - Good Health and Well-being, Imatges per ressonància magnètica, medicine, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Bipolar disorder, HIPPOCAMPAL VOLUMES, mega‐analysis, GRAY-MATTER VOLUME, SPECTRUM DISORDER, volume, DIABETES-MELLITUS, cortical thickness, COGNITIVE IMPAIRMENT, medicine.disease, Mental illness, meta-analysis, meta‐analysis, RC0321, Neurology (clinical), SCHIZOAFFECTIVE DISORDER, PSYCHOTIC FEATURES, 030217 neurology & neurosurgery
Abstract

MRI‐derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta‐Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis‐driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large‐scale meta‐ and mega‐analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large‐scale, collaborative studies of mental illness., This review discusses the major challenges facing neuroimaging research of bipolar disorder and highlights the major accomplishments, ongoing challenges and future goals of the ENIGMA Bipolar Disorder Working Group.

Published
2022
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43. Longitudinal changes in social cognition in individuals at clinical high risk for psychosis: An outcome based analysis.

Author

Shakeel, M K, Lu, L, Cannon, T D, Cadenhead, K S, Cornblatt, B A, McGlashan, T H, Perkins, D O, Seidman, L J, Tsuang, M T, Woods, S W, Walker, E F, Mathalon, D H, Bearden, C E, and Addington, J

Abstract

Social cognition deficits have been observed in individuals at clinical high risk (CHR) for psychosis. Longitudinal change in social cognition were analyzed in CHR individuals from the North American Prodrome Longitudinal Study (NAPLS2) based on outcome at 24 months. Individuals (n = 359) were classified into remission, symptomatic, prodromal progression and transition to psychosis (CHR-T) groups. Social cognition was assessed using theory of mind, emotion perception, and social perception tasks. There were no differences at baseline or 24 months between the groups on social cognition. Non-transition groups improved significantly over time on social cognition, but CHR-T did not show this effect. [ABSTRACT FROM AUTHOR]

Published
2018
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44. Occasional cannabis use is associated with higher premorbid functioning and IQ in youth at clinical high-risk (CHR) for psychosis: Parallel findings to psychosis cohorts.

Author

Kennedy L, Ku BS, Addington J, Amir CM, Bearden CE, Cannon TD, Carrión R, Cornblatt B, Keshavan M, Perkins D, Mathalon D, Stone W, Walker E, Woods S, and Cadenhead KS

Subjects
Humans, Male, Female, Adolescent, Young Adult, Child, Longitudinal Studies, Adult, Marijuana Use epidemiology, Risk, Cognitive Dysfunction etiology, Cognitive Dysfunction physiopathology, Neuropsychological Tests, Psychotic Disorders physiopathology, Prodromal Symptoms, Intelligence physiology
Abstract

Background: Neurocognitive deficits have been widely reported in clinical high-risk for psychosis (CHR) populations. Additionally, rates of cannabis use are high among CHR youth and are associated with greater symptom severity. Cannabis use has been sometimes shown to be associated with better neurocognition in more progressed psychosis cohorts, therefore in this study we aimed to determine whether a similar pattern was present in CHR., Methods: CHR participants ages 12-30 from the North American Prodromal Longitudinal Study (NAPLS-3) (N = 698) were grouped according to: "minimal to no cannabis use" (n = 406), "occasional use" (n = 127), or "frequent use" (n = 165). At baseline, cannabis use groups were compared on neurocognitive tests, clinical, and functional measures. Follow-up analyses were used to model relationships between cannabis use frequency, neurocognition, premorbid, and social functioning., Results: Occasional cannabis users performed significantly better than other use-groups on measures of IQ, with similar trend-level patterns observed across neurocognitive domains. Occasional cannabis users demonstrated better social, global, and premorbid functioning compared to the other use-groups and less severe symptoms compared to the frequent use group. Follow-up structural equation modeling/path analyses found significant positive associations between premorbid functioning, social functioning, and IQ, which in turn was associated with occasional cannabis use frequency., Discussion: Better premorbid functioning positively predicts both better social functioning and higher IQ which in turn is associated with a moderate cannabis use pattern in CHR, similar to reports in first-episode and chronic psychosis samples. Better premorbid functioning likely represents a protective factor in the CHR population and predicts a better functional outcome., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Published
2024
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45. Synaptic-dependent developmental dysconnectivity in 22q11.2 deletion syndrome.

Author

Alvino FG, Gini S, Minetti A, Pagani M, Sastre-Yagüe D, Barsotti N, De Guzman E, Schleifer C, Stuefer A, Kushan L, Montani C, Galbusera A, Papaleo F, Lombardo MV, Pasqualetti M, Bearden CE, and Gozzi A

Abstract

Chromosome 22q11.2 deletion is among the strongest known genetic risk factors for neuropsychiatric disorders, including autism and schizophrenia. Brain imaging studies have reported disrupted large-scale functional connectivity in people with 22q11 deletion syndrome (22q11DS). However, the significance and biological determinants of these functional alterations remain unclear. Here, we use a cross-species design to investigate the developmental trajectory and neural underpinnings of brain dysconnectivity in 22q11DS. We find that LgDel mice, an established mouse model of 22q11DS, exhibit age-specific patterns of functional MRI (fMRI) dysconnectivity, with widespread fMRI hyper-connectivity in juvenile mice reverting to focal hippocampal hypoconnectivity over puberty. These fMRI connectivity alterations are mirrored by co-occurring developmental alterations in dendritic spine density, and are both transiently normalized by developmental GSK3β inhibition, suggesting a synaptic origin for this phenomenon. Notably, analogous hyper- to hypoconnectivity reconfiguration occurs also in human 22q11DS, where it affects hippocampal and cortical regions spatially enriched for synaptic genes that interact with GSK3β, and autism-relevant transcripts. Functional dysconnectivity in somatomotor components of this network is predictive of age-dependent social alterations in 22q11.2 deletion carriers. Taken together, these findings suggest that synaptic-related mechanisms underlie developmentally mediated functional dysconnectivity in 22q11DS.

Published
2024
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46. Heterotopia in Individuals with 22q11.2 Deletion Syndrome.

Author

Neuhaus E, Hattingen E, Breuer S, Steidl E, Polomac N, Rosenow F, Rüber T, Herrmann E, Ecker C, Kushan L, Lin A, Vajdi A, Bearden CE, and Jurcoane A

Subjects
Brain diagnostic imaging, Female, Humans, Magnetic Resonance Imaging, Middle Aged, Retrospective Studies, DiGeorge Syndrome complications, DiGeorge Syndrome diagnostic imaging, DiGeorge Syndrome genetics, Periventricular Nodular Heterotopia diagnostic imaging, Periventricular Nodular Heterotopia genetics
Abstract

Background and Purpose: MR imaging studies and neuropathologic findings in individuals with 22q11.2 deletion syndrome show anomalous early brain development. We aimed to retrospectively evaluate cerebral abnormalities, focusing on gray matter heterotopia, and to correlate these with subjects' neuropsychiatric impairments., Materials and Methods: Three raters assessed gray matter heterotopia and other morphologic brain abnormalities on 3D T1WI and T2*WI in 75 individuals with 22q11.2 deletion syndrome (27 females, 15.5 [SD, 7.4] years of age) and 53 controls (24 females, 12.6 [SD, 4.7] years of age). We examined the association among the groups' most frequent morphologic findings, general cognitive performance, and comorbid neuropsychiatric conditions., Results: Heterotopia in the white matter were the most frequent finding in individuals with 22q11.2 deletion syndrome ( n = 29; controls, n = 0; between-group difference, P < .001), followed by cavum septi pellucidi and/or vergae ( n = 20; controls, n = 0; P < .001), periventricular cysts ( n = 10; controls, n = 0; P = .007), periventricular nodular heterotopia ( n = 10; controls, n = 0; P = .007), and polymicrogyria ( n = 3; controls, n = 0; P = .3). However, individuals with these morphologic brain abnormalities did not differ significantly from those without them in terms of general cognitive functioning and psychiatric comorbidities., Conclusions: Taken together, our findings, periventricular nodular heterotopia or heterotopia in the white matter (possibly related to interrupted Arc cells migration), persistent cavum septi pellucidi and/or vergae, and formation of periventricular cysts, give clues to the brain development disorder induced by the 22q11.2 deletion syndrome. There was no evidence that these morphologic findings were associated with differences in psychiatric or cognitive presentation of the 22q11.2 deletion syndrome., (© 2021 by American Journal of Neuroradiology.)

Published
2021
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47. Persistent negative symptoms in youth at clinical high risk for psychosis: A longitudinal study.

Author

Devoe DJ, Lu L, Cannon TD, Cadenhead KS, Cornblatt BA, McGlashan TH, Perkins DO, Seidman LJ, Tsuang MT, Woods SW, Walker EF, Mathalon DH, Bearden CE, and Addington J

Subjects
Adolescent, Humans, Longitudinal Studies, Prodromal Symptoms, Cognition Disorders, Psychotic Disorders complications, Psychotic Disorders epidemiology, Schizophrenia complications, Schizophrenia epidemiology
Abstract

Background: Severity of negative symptoms has been associated with poor functioning, cognitive deficits, and defeatist beliefs in schizophrenia patients. However, one area that remains understudied is persistent negative symptoms (PNS). Negative symptoms, including PNS, have been observed in those at clinical high-risk (CHR) for psychosis. The aim of this study was to determine if PNS were associated with functioning, neurocognition, and defeatist beliefs in a CHR sample., Method: CHR participants (n = 764) were recruited for the North American Prodrome Longitudinal Study. Negative symptoms were rated on the Scale of Psychosis-risk Symptoms. Generalized linear mixed models for repeated measures were used to examine changes over time between and within groups (PNS vs non-PNS)., Results: The PNS group (n = 67) had significant deficits in functioning at baseline, 6, 12, 18, and 24-months compared to the non-PNS group (n = 673). Functioning improved over time in the non-PNS group, while functioning in the PNS group remained relatively stable and poor over a two-year period. A consistent trend emerged demonstrating higher defeatist beliefs in the PNS group; however, this result was lost when controlling for persistent depressive symptoms. There were no significant differences between the groups on neurocognition, social cognition, and transition to psychosis., Conclusions: PNS exist in youth at CHR for psychosis, resulting in significant and persistent functional impairment, which remains when controlling for persistent depressive symptoms. PNS remain even in CHR youth who do not transition to psychosis. Thus, PNS may represent an unmet therapeutic need in CHR populations for which there are currently no effective treatments., Competing Interests: Declaration of competing interest The authors have declared that there are no conflicts of interest in relation to the subject of this study. Dr. Cannon and Dr. Mathalon report that they are consultants to Boerhinger Ingelheim Pharmaceuticals. Dr. Cannon reports that he is a consultant to Lundbeck A/S., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Published
2021
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48. The Neuroanatomy of Autism Spectrum Disorder Symptomatology in 22q11.2 Deletion Syndrome.

Author

Gudbrandsen M, Daly E, Murphy CM, Wichers RH, Stoencheva V, Perry E, Andrews D, Blackmore CE, Rogdaki M, Kushan L, Bearden CE, Murphy DGM, Craig MC, and Ecker C

Subjects
Adolescent, Adult, Autism Spectrum Disorder etiology, Autism Spectrum Disorder pathology, Autism Spectrum Disorder psychology, Brain pathology, Case-Control Studies, Child, DiGeorge Syndrome complications, DiGeorge Syndrome pathology, DiGeorge Syndrome psychology, Entorhinal Cortex diagnostic imaging, Entorhinal Cortex pathology, Female, Gyrus Cinguli diagnostic imaging, Gyrus Cinguli pathology, Humans, Male, Organ Size, Parietal Lobe diagnostic imaging, Parietal Lobe pathology, Prefrontal Cortex diagnostic imaging, Prefrontal Cortex pathology, Temporal Lobe diagnostic imaging, Temporal Lobe pathology, Young Adult, Autism Spectrum Disorder diagnostic imaging, Brain diagnostic imaging, DiGeorge Syndrome diagnostic imaging
Abstract

22q11.2 Deletion Syndrome (22q11.2DS) is a genetic condition associated with a high prevalence of neuropsychiatric conditions that include autism spectrum disorder (ASD). While evidence suggests that clinical phenotypes represent distinct neurodevelopmental outcomes, it remains unknown whether this translates to the level of neurobiology. To fractionate the 22q11.2DS phenotype on the level of neuroanatomy, we examined differences in vertex-wise estimates of cortical volume, surface area, and cortical thickness between 1) individuals with 22q11.2DS (n = 62) and neurotypical controls (n = 57) and 2) 22q11.2DS individuals with ASD symptomatology (n = 30) and those without (n = 25). We firstly observed significant differences in surface anatomy between 22q11.2DS individuals and controls for all 3 neuroanatomical features, predominantly in parietotemporal regions, cingulate and dorsolateral prefrontal cortices. We also established that 22q11.2DS individuals with ASD symptomatology were neuroanatomically distinct from 22q11.2DS individuals without ASD symptoms, particularly in brain regions that have previously been linked to ASD (e.g., dorsolateral prefrontal cortices and the entorhinal cortex). Our findings indicate that different clinical 22q11.2DS phenotypes, including those with ASD symptomatology, may represent different neurobiological subgroups. The spatially distributed patterns of neuroanatomical differences associated with ASD symptomatology in 22q11.2DS may thus provide useful information for patient stratification and the prediction of clinical outcomes., (© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Published
2019
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49. The Early Psychosis Screener for Internet (EPSI)-SR: Predicting 12 month psychotic conversion using machine learning.

Author

Brodey BB, Girgis RR, Favorov OV, Bearden CE, Woods SW, Addington J, Perkins DO, Walker EF, Cornblatt BA, Brucato G, Purcell SE, Brodey IS, and Cadenhead KS

Subjects
Early Diagnosis, Humans, Predictive Value of Tests, Psychotic Disorders psychology, Risk Assessment, Support Vector Machine, Diagnosis, Computer-Assisted, Internet, Machine Learning, Psychotic Disorders diagnosis
Abstract

Introduction: A faster and more accurate self-report screener for early psychosis is needed to promote early identification and intervention., Methods: Self-report Likert-scale survey items were administered to individuals being screened with the Structured Interview for Psychosis-risk Syndromes (SIPS) and followed at eight early psychosis clinics. An a priori analytic plan included Spectral Clustering Analysis to reduce the item pool, followed by development of Support Vector Machine (SVM) classifiers., Results: The cross-validated positive predictive value (PPV) of the EPSI at the default cut-off (76.5%) exceeded that of the clinician-administered SIPS (68.5%) at separating individuals who would not convert to psychosis within 12 months from those who either would convert within 12 months or who had already experienced a first episode psychosis (FEP). When used in tandem with the SIPS on clinical high risk participants, the EPSI increased the combined PPV to 86.6%. The SVM classified as FEP/converters only 1% of individuals in non-clinical and 4% of clinical low risk populations. Sensitivity of the EPSI, however, was 51% at the default cut-off., Discussion: The EPSI identifies, comparably to the SIPS but in less time and with fewer resources, individuals who are either at very high risk to develop a psychotic disorder within 12 months or who are already psychotic. At its default cut-off, EPSI misses 49% of current or future psychotic cases. The cut-off can, however, be adjusted based on purpose. The EPSI is the first validated assessment to predict 12-month psychotic conversion. An online screening system, www.eps.telesage.org, is under development., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

Published
2019
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50. The Early Psychosis Screener (EPS): Quantitative validation against the SIPS using machine learning.

Author

Brodey BB, Girgis RR, Favorov OV, Addington J, Perkins DO, Bearden CE, Woods SW, Walker EF, Cornblatt BA, Brucato G, Walsh B, Elkin KA, and Brodey IS

Subjects
Adolescent, Adult, Female, Humans, Interview, Psychological, Longitudinal Studies, Male, Risk, Young Adult, Machine Learning, Prodromal Symptoms, Psychiatric Status Rating Scales standards, Psychotic Disorders diagnosis, Schizophrenia diagnosis, Self Report standards
Abstract

Machine learning techniques were used to identify highly informative early psychosis self-report items and to validate an early psychosis screener (EPS) against the Structured Interview for Psychosis-risk Syndromes (SIPS). The Prodromal Questionnaire-Brief Version (PQ-B) and 148 additional items were administered to 229 individuals being screened with the SIPS at 7 North American Prodrome Longitudinal Study sites and at Columbia University. Fifty individuals were found to have SIPS scores of 0, 1, or 2, making them clinically low risk (CLR) controls; 144 were classified as clinically high risk (CHR) (SIPS 3-5) and 35 were found to have first episode psychosis (FEP) (SIPS 6). Spectral clustering analysis, performed on 124 of the items, yielded two cohesive item groups, the first mostly related to psychosis and mania, the second mostly related to depression, anxiety, and social and general work/school functioning. Items within each group were sorted according to their usefulness in distinguishing between CLR and CHR individuals using the Minimum Redundancy Maximum Relevance procedure. A receiver operating characteristic area under the curve (AUC) analysis indicated that maximal differentiation of CLR and CHR participants was achieved with a 26-item solution (AUC=0.899±0.001). The EPS-26 outperformed the PQ-B (AUC=0.834±0.001). For screening purposes, the self-report EPS-26 appeared to differentiate individuals who are either CLR or CHR approximately as well as the clinician-administered SIPS. The EPS-26 may prove useful as a self-report screener and may lead to a decrease in the duration of untreated psychosis. A validation of the EPS-26 against actual conversion is underway., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Published
2018
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