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51. Clinical and genetic determinants of serum brain-derived neurotrophic factor (BDNF) levels in psychotic patients: A longitudinal prospective study

Author

Manchia, M., primary, Deriu, L., additional, Tusconi, M., additional, Primavera, D., additional, Caboni, E., additional, Iaselli, N., additional, Sundas, D., additional, Collu, R., additional, Scherma, M., additional, Congiu, D., additional, Squassina, A., additional, Fratta, W., additional, Fadda, P., additional, and Carpiniello, B., additional

Published
2019
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52. Analysis of the influence of microRNAs in lithium response in bipolar disorder

Author

Reinbold, CS, Forstner, AJ, Hecker, J, Fullerton, JM, Hoffmann, P, Hou, L, Heilbronner, U, Degenhardt, F, Adli, M, Akiyama, K, Akula, N, Ardau, R, Arias, B, Backlund, L, Benabarre, A, Bengesser, S, Bhattacharjee, AK, Biernacka, JM, Birner, A, Marie-Claire, C, Cervantes, P, Chen, GB, Chen, HC, Chillotti, C, Clark, SR, Colom, F, Cousins, DA, Cruceanu, C, Czerski, PM, Dayer, A, Étain, B, Falkai, P, Frisén, L, Gard, S, Garnham, JS, Goes, FS, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Herms, S, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kittel-Schneider, S, Kliwicki, S, König, B, Kusumi, I, Lackner, N, Laje, G, Landén, M, Lavebratt, C, Leboyer, M, Leckband, SG, Jaramillo, CAL, MacQueen, G, Manchia, M, Martinsson, L, Mattheisen, M, McCarthy, MJ, McElroy, SL, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Ösby, U, Ozaki, N, Perlis, RH, Pfennig, A, Reich-Erkelenz, D, Rouleau, GA, Schofield, PR, Schubert, KO, Schweizer, BW, Seemüller, F, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Smoller, JW, Squassina, A, Stamm, TJ, Stopkova, P, Tighe, SK, Tortorella, A, Turecki, G, Volkert, J, Witt, SH, Wright, AJ, Trevor Young, L, Zandi, PP, Potash, JB, DePaulo, JR, Bauer, M, Reininghaus, E, Novák, T, Aubry, JM, Reinbold, CS, Forstner, AJ, Hecker, J, Fullerton, JM, Hoffmann, P, Hou, L, Heilbronner, U, Degenhardt, F, Adli, M, Akiyama, K, Akula, N, Ardau, R, Arias, B, Backlund, L, Benabarre, A, Bengesser, S, Bhattacharjee, AK, Biernacka, JM, Birner, A, Marie-Claire, C, Cervantes, P, Chen, GB, Chen, HC, Chillotti, C, Clark, SR, Colom, F, Cousins, DA, Cruceanu, C, Czerski, PM, Dayer, A, Étain, B, Falkai, P, Frisén, L, Gard, S, Garnham, JS, Goes, FS, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Herms, S, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kittel-Schneider, S, Kliwicki, S, König, B, Kusumi, I, Lackner, N, Laje, G, Landén, M, Lavebratt, C, Leboyer, M, Leckband, SG, Jaramillo, CAL, MacQueen, G, Manchia, M, Martinsson, L, Mattheisen, M, McCarthy, MJ, McElroy, SL, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Ösby, U, Ozaki, N, Perlis, RH, Pfennig, A, Reich-Erkelenz, D, Rouleau, GA, Schofield, PR, Schubert, KO, Schweizer, BW, Seemüller, F, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Smoller, JW, Squassina, A, Stamm, TJ, Stopkova, P, Tighe, SK, Tortorella, A, Turecki, G, Volkert, J, Witt, SH, Wright, AJ, Trevor Young, L, Zandi, PP, Potash, JB, DePaulo, JR, Bauer, M, Reininghaus, E, Novák, T, and Aubry, JM

Abstract

Bipolar disorder (BD) is a common, highly heritable neuropsychiatric disease characterized by recurrent episodes of mania and depression. Lithium is the best-established long-term treatment for BD, even though individual response is highly variable. Evidence suggests that some of this variability has a genetic basis. This is supported by the largest genome-wide association study (GWAS) of lithium response to date conducted by the International Consortium on Lithium Genetics (ConLiGen). Recently, we performed the first genome-wide analysis of the involvement of miRNAs in BD and identified nine BD-associated miRNAs. However, it is unknown whether these miRNAs are also associated with lithium response in BD. In the present study, we therefore tested whether common variants at these nine candidate miRNAs contribute to the variance in lithium response in BD. Furthermore, we systematically analyzed whether any other miRNA in the genome is implicated in the response to lithium. For this purpose, we performed gene-based tests for all known miRNA coding genes in the ConLiGen GWAS dataset (n = 2,563 patients) using a set-based testing approach adapted from the versatile gene-based test for GWAS (VEGAS2). In the candidate approach, miR-499a showed a nominally significant association with lithium response, providing some evidence for involvement in both development and treatment of BD. In the genome-wide miRNA analysis, 71 miRNAs showed nominally significant associations with the dichotomous phenotype and 106 with the continuous trait for treatment response. A total of 15 miRNAs revealed nominal significance in both phenotypes with miR-633 showing the strongest association with the continuous trait (p = 9.80E-04) and miR-607 with the dichotomous phenotype (p = 5.79E-04). No association between miRNAs and treatment response to lithium in BD in either of the tested conditions withstood multiple testing correction. Given the limited power of our study, the investigation of miRNAs

Published
2018

53. Association of polygenic score for schizophrenia and HLA antigen and inflammation genes with response to lithium in bipolar affective disorder: A genome-wide association study

Author

Amare, AT, Schubert, KO, Hou, L, Clark, SR, Papiol, S, Heilbronner, U, Degenhardt, F, Tekola-Ayele, F, Hsu, YH, Shekhtman, T, Adli, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, JM, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Cervantes, P, Chen, HC, Chillotti, C, Cichon, S, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Del Zompo, M, DePaulo, JR, Étain, B, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Hofmann, A, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kuo, PH, Kato, T, Kelsoe, J, Kittel-Schneider, S, Kliwicki, S, König, B, Kusumi, I, Laje, G, Landén, M, Lavebratt, C, Leboyer, M, Leckband, SG, Tortorella, A, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, S, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nöthen, MM, Novák, T, O'Donovan, C, Ozaki, N, Ösby, U, Pfennig, A, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Maj, M, Turecki, G, Amare, AT, Schubert, KO, Hou, L, Clark, SR, Papiol, S, Heilbronner, U, Degenhardt, F, Tekola-Ayele, F, Hsu, YH, Shekhtman, T, Adli, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, JM, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Cervantes, P, Chen, HC, Chillotti, C, Cichon, S, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Del Zompo, M, DePaulo, JR, Étain, B, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Hofmann, A, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kuo, PH, Kato, T, Kelsoe, J, Kittel-Schneider, S, Kliwicki, S, König, B, Kusumi, I, Laje, G, Landén, M, Lavebratt, C, Leboyer, M, Leckband, SG, Tortorella, A, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, S, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nöthen, MM, Novák, T, O'Donovan, C, Ozaki, N, Ösby, U, Pfennig, A, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Maj, M, and Turecki, G

Abstract

IMPORTANCE Lithium is a first-line mood stabilizer for the treatment of bipolar affective disorder (BPAD). However, the efficacy of lithium varies widely, with a nonresponse rate of up to 30%. Biological response markers are lacking. Genetic factors are thought to mediate treatment response to lithium, and there is a previously reported genetic overlap between BPAD and schizophrenia (SCZ). OBJECTIVES To test whether a polygenic score for SCZ is associated with treatment response to lithium in BPAD and to explore the potential molecular underpinnings of this association. DESIGN, SETTING, AND PARTICIPANTS A total of 2586 patients with BPAD who had undergone lithium treatment were genotyped and assessed for long-term response to treatment between 2008 and 2013.Weighted SCZ polygenic scores were computed at different P value thresholds using summary statistics from an international multicenter genome-wide association study (GWAS) of 36 989 individuals with SCZ and genotype data from patients with BPAD from the Consortium on Lithium Genetics. For functional exploration, a cross-trait meta-GWAS and pathway analysis was performed, combining GWAS summary statistics on SCZ and response to treatment with lithium. Data analysis was performed from September 2016 to February 2017. MAIN OUTCOMES AND MEASURES Treatment response to lithiumwas defined on both the categorical and continuous scales using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. The effect measures include odds ratios and the proportion of variance explained. RESULTS Of the 2586 patients in the study (mean [SD] age, 47.2 [13.9] years), 1478 were women and 1108 were men. The polygenic score for SCZ was inversely associated with lithium treatment response in the categorical outcome, at a threshold P < 5 ? 10-2. Patients with BPAD who had a low polygenic load for SCZ responded better to lithium, with odds ratios for lithium response ranging from 3.46 (95%

Published
2018

54. Solar insolation in springtime influences age of onset of bipolar I disorder

Author

Bauer, M. Glenn, T. Alda, M. Aleksandrovich, M.A. Andreassen, O.A. Angelopoulos, E. Ardau, R. Ayhan, Y. Baethge, C. Bharathram, S.R. Bauer, R. Baune, B.T. Becerra-Palars, C. Bellivier, F. Belmaker, R.H. Berk, M. Bersudsky, Y. Bicakci, Ş. Birabwa-Oketcho, H. Bjella, T.D. Bossini, L. Cabrera, J. Cheung, E.Y.W. Del Zompo, M. Dodd, S. Donix, M. Etain, B. Fagiolini, A. Fountoulakis, K.N. Frye, M.A. Gonzalez-Pinto, A. Gottlieb, J.F. Grof, P. Harima, H. Henry, C. Isometsä, E.T. Janno, S. Kapczinski, F. Kardell, M. Khaldi, S. Kliwicki, S. König, B. Kot, T.L. Krogh, R. Kunz, M. Lafer, B. Landén, M. Larsen, E.R. Lewitzka, U. Licht, R.W. Lopez-Jaramillo, C. MacQueen, G. Manchia, M. Marsh, W. Martinez-Cengotitabengoa, M. Melle, I. Meza-Urzúa, F. Yee Ming, M. Monteith, S. Morken, G. Mosca, E. Munoz, R. Mythri, S.V. Nacef, F. Nadella, R.K. Nery, F.G. Nielsen, R.E. O'Donovan, C. Omrani, A. Osher, Y. Østermark Sørensen, H. Ouali, U. Pica Ruiz, Y. Pilhatsch, M. Pinna, M. da Ponte, F.D.R. Quiroz, D. Ramesar, R. Rasgon, N. Reddy, M.S. Reif, A. Ritter, P. Rybakowski, J.K. Sagduyu, K. Scippa, Â.M. Severus, E. Simhandl, C. Stein, D.J. Strejilevich, S. Subramaniam, M. Sulaiman, A.H. Suominen, K. Tagata, H. Tatebayashi, Y. Tondo, L. Torrent, C. Vaaler, A.E. Veeh, J. Vieta, E. Viswanath, B. Yoldi-Negrete, M. Zetin, M. Zgueb, Y. Whybrow, P.C.

Abstract

Objective: To confirm prior findings that the larger the maximum monthly increase in solar insolation in springtime, the younger the age of onset of bipolar disorder. Method: Data were collected from 5536 patients at 50 sites in 32 countries on six continents. Onset occurred at 456 locations in 57 countries. Variables included solar insolation, birth-cohort, family history, polarity of first episode and country physician density. Results: There was a significant, inverse association between the maximum monthly increase in solar insolation at the onset location, and the age of onset. This effect was reduced in those without a family history of mood disorders and with a first episode of mania rather than depression. The maximum monthly increase occurred in springtime. The youngest birth-cohort had the youngest age of onset. All prior relationships were confirmed using both the entire sample, and only the youngest birth-cohort (all estimated coefficients P < 0.001). Conclusion: A large increase in springtime solar insolation may impact the onset of bipolar disorder, especially with a family history of mood disorders. Recent societal changes that affect light exposure (LED lighting, mobile devices backlit with LEDs) may influence adaptability to a springtime circadian challenge. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd

Published
2017

55. Can network analysis shed light on predictors of lithium response in bipolar I disorder?

Author

Scott, J., Bellivier, F., Manchia, M., Schulze, T., Alda, M., Etain, B., Cervantes, Pablo, Garnham, Julie, Nunes, Abraham, O'Donovan, Claire, Slaney, Claire, Bauer, Michael, Pfennig, Andrea, Reif, Andreas, Kittel‐Schneider, Sarah, Veeh, Julia, Zompo, Maria del, Ardau, Raffaella, Chillotti, Caterina, and Severino, Giovanni

Subjects
BIPOLAR disorder, THERAPEUTIC use of lithium, OBSESSIVE-compulsive disorder, PANIC disorders, ANXIETY disorders
Abstract

Objective: To undertake a large‐scale clinical study of predictors of lithium (Li) response in bipolar I disorder (BD‐I) and apply contemporary multivariate approaches to account for inter‐relationships between putative predictors. Methods: We used network analysis to estimate the number and strength of connections between potential predictors of good Li response (measured by a new scoring algorithm for the Retrospective Assessment of Response to Lithium Scale) in 900 individuals with BD‐I recruited to the Consortium of Lithium Genetics. Results: After accounting for co‐associations between potential predictors, the most important factors associated with the good Li response phenotype were panic disorder, manic predominant polarity, manic first episode, age at onset between 15–32 years and family history of BD. Factors most strongly linked to poor outcome were comorbid obsessive–compulsive disorder, alcohol and/or substance misuse, and/or psychosis (symptoms or syndromes). Conclusions: Network analysis can offer important additional insights to prospective studies of predictors of Li treatment outcomes. It appears to especially help in further clarifying the role of family history of BD (i.e. its direct and indirect associations) and highlighting the positive and negative associations of different subtypes of anxiety disorders with Li response, particularly the little‐known negative association between Li response and obsessive–compulsive disorder. [ABSTRACT FROM AUTHOR]

Published
2020
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56. Prediction of lithium response using clinical data.

Author

Nunes, A., Ardau, R., Berghöfer, A., Bocchetta, A., Chillotti, C., Deiana, V., Garnham, J., Grof, E., Hajek, T., Manchia, M., Müller‐Oerlinghausen, B., Pinna, M., Pisanu, C., O'Donovan, C., Severino, G., Slaney, C., Suwalska, A., Zvolsky, P., Cervantes, P., and Zompo, M.

Subjects
MACHINE learning, RECEIVER operating characteristic curves, THERAPEUTIC use of lithium, BIOMARKERS
Abstract

Objective: Promptly establishing maintenance therapy could reduce morbidity and mortality in patients with bipolar disorder. Using a machine learning approach, we sought to evaluate whether lithium responsiveness (LR) is predictable using clinical markers. Method: Our data are the largest existing sample of direct interview‐based clinical data from lithium‐treated patients (n = 1266, 34.7% responders), collected across seven sites, internationally. We trained a random forest model to classify LR—as defined by the previously validated Alda scale—against 180 clinical predictors. Results: Under appropriate cross‐validation procedures, LR was predictable in the pooled sample with an area under the receiver operating characteristic curve of 0.80 (95% CI 0.78–0.82) and a Cohen kappa of 0.46 (0.4–0.51). The model demonstrated a particularly low false‐positive rate (specificity 0.91 [0.88–0.92]). Features related to clinical course and the absence of rapid cycling appeared consistently informative. Conclusion: Clinical data can inform out‐of‐sample LR prediction to a potentially clinically relevant degree. Despite the relevance of clinical course and the absence of rapid cycling, there was substantial between‐site heterogeneity with respect to feature importance. Future work must focus on improving classification of true positives, better characterizing between‐ and within‐site heterogeneity, and further testing such models on new external datasets. [ABSTRACT FROM AUTHOR]

Published
2020
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57. Solar insolation in springtime influences age of onset of bipolar I disorder

Author

Bauer, M, Glenn, T, Alda, M, Aleksandrovich, MA, Andreassen, OA, Angelopoulos, E, Ardau, R, Ayhan, Y, Baethge, C, Bharathram, SR, Bauer, R, Baune, BT, Becerra-Palars, C, Bellivier, F, Belmaker, RH, Berk, M, Bersudsky, Y, Bicakci, S, Birabwa-Oketcho, H, Bjella, TD, Bossini, L, Cabrera, J, Cheung, EYW, Del Zompo, M, Dodd, S, Donix, M, Etain, B, Fagiolini, A, Fountoulakis, KN, Frye, MA, Gonzalez-Pinto, A, Gottlieb, JF, Grof, P, Harima, H, Henry, C, Isometsae, ET, Janno, S, Kapczinski, F, Kardell, M, Khaldi, S, Kliwicki, S, Koenig, B, Kot, TL, Krogh, R, Kunz, M, Lafer, B, Landen, M, Larsen, ER, Lewitzka, U, Licht, RW, Lopez-Jaramillo, C, MacQueen, G, Manchia, M, Marsh, W, Martinez-Cengotitabengoa, M, Melle, I, Meza-Urzua, F, Yee Ming, M, Monteith, S, Morken, G, Mosca, E, Munoz, R, Mythri, SV, Nacef, F, Nadella, RK, Nery, FG, Nielsen, RE, O'Donovan, C, Omrani, A, Osher, Y, Ostermark Sorensen, H, Ouali, U, Pica Ruiz, Y, Pilhatsch, M, Pinna, M, da Ponte, FDR, Quiroz, D, Ramesar, R, Rasgon, N, Reddy, MS, Reif, A, Ritter, P, Rybakowski, JK, Sagduyu, K, Scippa, AM, Severus, E, Simhandl, C, Stein, DJ, Strejilevich, S, Subramaniam, M, Sulaiman, AH, Suominen, K, Tagata, H, Tatebayashi, Y, Tondo, L, Torrent, C, Vaaler, AE, Veeh, J, Vieta, E, Viswanath, B, Yoldi-Negrete, M, Zetin, M, Zgueb, Y, Whybrow, PC, Bauer, M, Glenn, T, Alda, M, Aleksandrovich, MA, Andreassen, OA, Angelopoulos, E, Ardau, R, Ayhan, Y, Baethge, C, Bharathram, SR, Bauer, R, Baune, BT, Becerra-Palars, C, Bellivier, F, Belmaker, RH, Berk, M, Bersudsky, Y, Bicakci, S, Birabwa-Oketcho, H, Bjella, TD, Bossini, L, Cabrera, J, Cheung, EYW, Del Zompo, M, Dodd, S, Donix, M, Etain, B, Fagiolini, A, Fountoulakis, KN, Frye, MA, Gonzalez-Pinto, A, Gottlieb, JF, Grof, P, Harima, H, Henry, C, Isometsae, ET, Janno, S, Kapczinski, F, Kardell, M, Khaldi, S, Kliwicki, S, Koenig, B, Kot, TL, Krogh, R, Kunz, M, Lafer, B, Landen, M, Larsen, ER, Lewitzka, U, Licht, RW, Lopez-Jaramillo, C, MacQueen, G, Manchia, M, Marsh, W, Martinez-Cengotitabengoa, M, Melle, I, Meza-Urzua, F, Yee Ming, M, Monteith, S, Morken, G, Mosca, E, Munoz, R, Mythri, SV, Nacef, F, Nadella, RK, Nery, FG, Nielsen, RE, O'Donovan, C, Omrani, A, Osher, Y, Ostermark Sorensen, H, Ouali, U, Pica Ruiz, Y, Pilhatsch, M, Pinna, M, da Ponte, FDR, Quiroz, D, Ramesar, R, Rasgon, N, Reddy, MS, Reif, A, Ritter, P, Rybakowski, JK, Sagduyu, K, Scippa, AM, Severus, E, Simhandl, C, Stein, DJ, Strejilevich, S, Subramaniam, M, Sulaiman, AH, Suominen, K, Tagata, H, Tatebayashi, Y, Tondo, L, Torrent, C, Vaaler, AE, Veeh, J, Vieta, E, Viswanath, B, Yoldi-Negrete, M, Zetin, M, Zgueb, Y, and Whybrow, PC

Abstract

OBJECTIVE: To confirm prior findings that the larger the maximum monthly increase in solar insolation in springtime, the younger the age of onset of bipolar disorder. METHOD: Data were collected from 5536 patients at 50 sites in 32 countries on six continents. Onset occurred at 456 locations in 57 countries. Variables included solar insolation, birth-cohort, family history, polarity of first episode and country physician density. RESULTS: There was a significant, inverse association between the maximum monthly increase in solar insolation at the onset location, and the age of onset. This effect was reduced in those without a family history of mood disorders and with a first episode of mania rather than depression. The maximum monthly increase occurred in springtime. The youngest birth-cohort had the youngest age of onset. All prior relationships were confirmed using both the entire sample, and only the youngest birth-cohort (all estimated coefficients P < 0.001). CONCLUSION: A large increase in springtime solar insolation may impact the onset of bipolar disorder, especially with a family history of mood disorders. Recent societal changes that affect light exposure (LED lighting, mobile devices backlit with LEDs) may influence adaptability to a springtime circadian challenge.

Published
2017

58. Impact of sunlight on the age of onset of bipolar disorder

Author

Bauer, M., Glenn, T., Alda, M., Andreassen, O., Ardau, R., Bellivier, F., Berk, M., Bjella, T. D., Bossini, L., Del Zompo, M., Dodd, S., Fagiolini, Andrea, Frye, M. A., Gonzalez Pinto, A., Henry, C., Kapczinski, F., Kliwicki, S., König, B., Kunz, M., Lafer, B., Lopez Jaramillo, C., Manchia, M., Marsh, W., Martinez Cengotitabengoa, M., Melle, I., Morken, G., Munoz, R., Nery, F. G., O'Donovan, C., Pfennig, A., Quiroz, D., Rasgon, N., Reif, A., Rybakowski, J., Sagduyu, K., Simhandl, C., Torrent, C., Vieta, E., Zetin, M., Whybrow, P. C., Farmacologie en Toxicologie, and RS: CARIM School for Cardiovascular Diseases

Subjects
Adult, Aged, 80 and over, Male, bipolar disorder, Adolescent, Photoperiod, Middle Aged, Age of onset, Bipolar disorder, Solar insolation, Sunlight, Article, solar insolation, age of onset, Solar Energy, Humans, Female, Seasons, sunlight, Geography, Medical, Aged, Retrospective Studies
Abstract

Although bipolar disorder has high heritability, the onset occurs during several decades of life, suggesting that social and environmental factors may have considerable influence on disease onset. This study examined the association between the age of onset and sunlight at the location of onset.Data were obtained from 2414 patients with a diagnosis of bipolar I disorder, according to DSM-IV criteria. Data were collected at 24 sites in 13 countries spanning latitudes 6.3 to 63.4 degrees from the equator, including data from both hemispheres. The age of onset and location of onset were obtained retrospectively, from patient records and/or direct interviews. Solar insolation data, or the amount of electromagnetic energy striking the surface of the earth, were obtained from the NASA Surface Meteorology and Solar Energy (SSE) database for each location of onset.The larger the maximum monthly increase in solar insolation at the location of onset, the younger the age of onset (coefficient= -4.724, 95% CI: -8.124 to -1.323, p=0.006), controlling for each country's median age. The maximum monthly increase in solar insolation occurred in springtime. No relationships were found between the age of onset and latitude, yearly total solar insolation, and the maximum monthly decrease in solar insolation. The largest maximum monthly increases in solar insolation occurred in diverse environments, including Norway, arid areas in California, and Chile.The large maximum monthly increase in sunlight in springtime may have an important influence on the onset of bipolar disorder.? 2012 John Wiley and Sons A/S.

Published
2012
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61. Influence of birth cohort on age of onset cluster analysis in bipolar I disorder

Author

Bauer, M. Glenn, T. Alda, M. Andreassen, O. A. and Angelopoulos, E. Ardau, R. Baethge, C. Bauer, R. and Bellivier, F. Belmaker, R. H. Berk, M. Bjella, T. D. and Bossini, L. Bersudsky, Y. Cheung, E. Y. W. Conell, J. and Del Zompo, M. Dodd, S. Etain, B. Fagiolini, A. Frye, M. A. Fountoulakis, K. N. Garneau-Fournier, J. Gonzalez-Pinto, A. Harima, H. Hassel, S. Henry, C. Iacovides, A. and Isometsa, E. T. Kapczinski, F. Kliwicki, S. Koenig, B. and Krogh, R. Kunz, M. Lafer, B. Larsen, E. R. Lewitzka, U. and Lopez-Jaramillo, C. MacQueen, G. Manchia, M. Marsh, W. and Martinez-Cengotitabengoa, M. Melle, I. Monteith, S. and Morken, G. Munoz, R. Nery, F. G. O'Donovan, C. Osher, Y. and Pfennig, A. Quiroz, D. Ramesar, R. Rasgon, N. Reif, A. Ritter, P. Rybakowski, J. K. Sagduyu, K. Scippa, A. M. Severus, E. Simhandl, C. Stein, D. J. Strejilevich, S. Sulaiman, A. Hatim Suominen, K. Tagata, H. and Tatebayashi, Y. Torrent, C. Vieta, E. Viswanath, B. and Wanchoo, M. J. Zetin, M. Whybrow, P. C.

Abstract

Purpose: Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database. Methods: The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared. Results: There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups. Conclusion: These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research. (C) 2014 Elsevier Masson SAS. All rights reserved.

Published
2015

62. Genetic variants associated with response to lithium treatment in bipolar disorder: A genome-wide association study

Author

Hou, L, Heilbronner, U, Degenhardt, F, Adli, M, Akiyama, K, Akula, N, Ardau, R, Arias, B, Backlund, L, Banzato, CEM, Benabarre, A, Bengesser, S, Bhattacharjee, AK, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Bui, ET, Cervantes, P, Chen, GB, Chen, HC, Chillotti, C, Cichon, S, Clark, SR, Colom, F, Cousins, DA, Cruceanu, C, Czerski, PM, Dantas, CR, Dayer, A, Étain, B, Falkai, P, Forstner, AJ, Frisén, L, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Hofmann, A, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kittel-Schneider, S, Kliwicki, S, König, B, Kusumi, I, Lackner, N, Laje, G, Landén, M, Lavebratt, C, Leboyer, M, Leckband, SG, Jaramillo, CAL, Macqueen, G, Manchia, M, Martinsson, L, Mattheisen, M, McCarthy, MJ, McElroy, SL, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nöthen, MM, Ösby, U, Ozaki, N, Perlis, RH, Pfennig, A, Reich-Erkelenz, D, Rouleau, GA, Schofield, PR, Schubert, KO, Schweizer, BW, Seemüller, F, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Smoller, JW, Squassina, A, Stamm, T, Stopkova, P, Tighe, SK, Tortorella, A, Turecki, G, Volkert, J, Witt, S, Wright, A, Young, LT, Zandi, PP, Potash, JB, Depaulo, JR, Hou, L, Heilbronner, U, Degenhardt, F, Adli, M, Akiyama, K, Akula, N, Ardau, R, Arias, B, Backlund, L, Banzato, CEM, Benabarre, A, Bengesser, S, Bhattacharjee, AK, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Bui, ET, Cervantes, P, Chen, GB, Chen, HC, Chillotti, C, Cichon, S, Clark, SR, Colom, F, Cousins, DA, Cruceanu, C, Czerski, PM, Dantas, CR, Dayer, A, Étain, B, Falkai, P, Forstner, AJ, Frisén, L, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Hofmann, A, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kittel-Schneider, S, Kliwicki, S, König, B, Kusumi, I, Lackner, N, Laje, G, Landén, M, Lavebratt, C, Leboyer, M, Leckband, SG, Jaramillo, CAL, Macqueen, G, Manchia, M, Martinsson, L, Mattheisen, M, McCarthy, MJ, McElroy, SL, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nöthen, MM, Ösby, U, Ozaki, N, Perlis, RH, Pfennig, A, Reich-Erkelenz, D, Rouleau, GA, Schofield, PR, Schubert, KO, Schweizer, BW, Seemüller, F, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Smoller, JW, Squassina, A, Stamm, T, Stopkova, P, Tighe, SK, Tortorella, A, Turecki, G, Volkert, J, Witt, S, Wright, A, Young, LT, Zandi, PP, Potash, JB, and Depaulo, JR

Abstract

Background Lithium is a first-line treatment in bipolar disorder, but individual response is variable. Previous studies have suggested that lithium response is a heritable trait. However, no genetic markers of treatment response have been reproducibly identified. Methods Here, we report the results of a genome-wide association study of lithium response in 2563 patients collected by 22 participating sites from the International Consortium on Lithium Genetics (ConLiGen). Data from common single nucleotide polymorphisms (SNPs) were tested for association with categorical and continuous ratings of lithium response. Lithium response was measured using a well established scale (Alda scale). Genotyped SNPs were used to generate data at more than 6 million sites, using standard genomic imputation methods. Traits were regressed against genotype dosage. Results were combined across two batches by meta-analysis. Findings A single locus of four linked SNPs on chromosome 21 met genome-wide significance criteria for association with lithium response (rs79663003, p=1·37×10-8; rs78015114, p=1·31×10-8; rs74795342, p=3·31×10-9; and rs75222709, p=3·50×10-9). In an independent, prospective study of 73 patients treated with lithium monotherapy for a period of up to 2 years, carriers of the response-associated alleles had a significantly lower rate of relapse than carriers of the alternate alleles (p=0·03268, hazard ratio 3·8, 95% CI 1·1-13·0). Interpretation The response-associated region contains two genes for long, non-coding RNAs (lncRNAs), AL157359.3 and AL157359.4. LncRNAs are increasingly appreciated as important regulators of gene expression, particularly in the CNS. Confirmed biomarkers of lithium response would constitute an important step forward in the clinical management of bipolar disorder. Further studies are needed to establish the biological context and potential clinical utility of these findings. Funding Deutsche Forschungsgemeinschaft, National Institute of Mental Hea

Published
2016

63. Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder

Author

Hou, L, Bergen, SE, Akula, N, Song, J, Hultman, CM, Landén, M, Adli, M, Alda, M, Ardau, R, Arias, B, Aubry, JM, Backlund, L, Badner, JA, Barrett, TB, Bauer, M, Baune, BT, Bellivier, F, Benabarre, A, Bengesser, S, Berrettini, WH, Bhattacharjee, AK, Biernacka, JM, Birner, A, Bloss, CS, Brichant-Petitjean, C, Bui, ET, Byerley, W, Cervantes, P, Chillotti, C, Cichon, S, Colom, F, Coryell, W, Craig, DW, Cruceanu, C, Czerski, PM, Davis, T, Dayer, A, Degenhardt, F, Del Zompo, M, DePaulo, JR, Edenberg, HJ, Étain, B, Falkai, P, Foroud, T, Forstner, AJ, Frisén, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Gershon, ES, Goes, FS, Greenwood, TA, Grigoroiu-Serbanescu, M, Hauser, J, Heilbronner, U, Heilmann-Heimbach, S, Herms, S, Hipolito, M, Hitturlingappa, S, Hoffmann, P, Hofmann, A, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kelsoe, JR, Kittel-Schneider, S, Kliwicki, S, Koller, DL, König, B, Lackner, N, Laje, G, Lang, M, Lavebratt, C, Lawson, WB, Leboyer, M, Leckband, SG, Liu, C, Maaser, A, Mahon, PB, Maier, W, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, McInnis, MG, McKinney, R, Mitchell, PB, Mitjans, M, Mondimore, FM, Monteleone, P, Mühleisen, TW, Nievergelt, CM, Nöthen, MM, Novák, T, Nurnberger, JI, Nwulia, EA, Ösby, U, Hou, L, Bergen, SE, Akula, N, Song, J, Hultman, CM, Landén, M, Adli, M, Alda, M, Ardau, R, Arias, B, Aubry, JM, Backlund, L, Badner, JA, Barrett, TB, Bauer, M, Baune, BT, Bellivier, F, Benabarre, A, Bengesser, S, Berrettini, WH, Bhattacharjee, AK, Biernacka, JM, Birner, A, Bloss, CS, Brichant-Petitjean, C, Bui, ET, Byerley, W, Cervantes, P, Chillotti, C, Cichon, S, Colom, F, Coryell, W, Craig, DW, Cruceanu, C, Czerski, PM, Davis, T, Dayer, A, Degenhardt, F, Del Zompo, M, DePaulo, JR, Edenberg, HJ, Étain, B, Falkai, P, Foroud, T, Forstner, AJ, Frisén, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Gershon, ES, Goes, FS, Greenwood, TA, Grigoroiu-Serbanescu, M, Hauser, J, Heilbronner, U, Heilmann-Heimbach, S, Herms, S, Hipolito, M, Hitturlingappa, S, Hoffmann, P, Hofmann, A, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kelsoe, JR, Kittel-Schneider, S, Kliwicki, S, Koller, DL, König, B, Lackner, N, Laje, G, Lang, M, Lavebratt, C, Lawson, WB, Leboyer, M, Leckband, SG, Liu, C, Maaser, A, Mahon, PB, Maier, W, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, McInnis, MG, McKinney, R, Mitchell, PB, Mitjans, M, Mondimore, FM, Monteleone, P, Mühleisen, TW, Nievergelt, CM, Nöthen, MM, Novák, T, Nurnberger, JI, Nwulia, EA, and Ösby, U

Abstract

Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behaviour. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of > 9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ~2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the X-chromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, P= 5.87×10-9; odds ratio (OR)=1.12) and markers within ERBB2 (rs2517959, P= 4.53×10-9; OR=1.13). No significant X-chromosome associations were detected and Xlinked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.

Published
2016

69. Relationship between sunlight and the age of onset of bipolar disorder: An international multisite study

Author

Bauer, M, Glenn, T, Alda, M, Andreassen, OA, Angelopoulos, E, Ardau, R, Baethge, C, Bauer, R, Bellivier, F, Belmaker, RH, Berk, M, Bjella, TD, Bossini, L, Bersudsky, Y, Cheung, EYW, Conell, J, Del Zompo, M, Dodd, S, Etain, B, Fagiolini, A, Frye, MA, Fountoulakis, KN, Garneau-Fournier, J, Gonzalez-Pinto, A, Harima, H, Hassel, S, Henry, C, Iacovides, A, Isometsa, ET, Kapczinski, F, Kliwicki, S, Koenig, B, Krogh, R, Kunz, M, Lafer, B, Larsen, ER, Lewitzka, U, Lopez-Jaramillo, C, MacQueen, G, Manchia, M, Marsh, W, Martinez-Cengotitabengoa, M, Melle, I, Monteith, S, Morken, G, Munoz, R, Nery, FG, O'Donovan, C, Osher, Y, Pfennig, A, Quiroz, D, Ramesar, R, Rasgon, N, Reif, A, Ritter, P, Rybakowski, JK, Sagduyu, K, Scippa, AM, Severus, E, Simhandl, C, Stein, DJ, Strejilevich, S, Sulaiman, AH, Suominen, K, Tagata, H, Tatebayashi, Y, Torrent, C, Vieta, E, Viswanath, B, Wanchoo, MJ, Zetin, M, Whybrow, PC, Bauer, M, Glenn, T, Alda, M, Andreassen, OA, Angelopoulos, E, Ardau, R, Baethge, C, Bauer, R, Bellivier, F, Belmaker, RH, Berk, M, Bjella, TD, Bossini, L, Bersudsky, Y, Cheung, EYW, Conell, J, Del Zompo, M, Dodd, S, Etain, B, Fagiolini, A, Frye, MA, Fountoulakis, KN, Garneau-Fournier, J, Gonzalez-Pinto, A, Harima, H, Hassel, S, Henry, C, Iacovides, A, Isometsa, ET, Kapczinski, F, Kliwicki, S, Koenig, B, Krogh, R, Kunz, M, Lafer, B, Larsen, ER, Lewitzka, U, Lopez-Jaramillo, C, MacQueen, G, Manchia, M, Marsh, W, Martinez-Cengotitabengoa, M, Melle, I, Monteith, S, Morken, G, Munoz, R, Nery, FG, O'Donovan, C, Osher, Y, Pfennig, A, Quiroz, D, Ramesar, R, Rasgon, N, Reif, A, Ritter, P, Rybakowski, JK, Sagduyu, K, Scippa, AM, Severus, E, Simhandl, C, Stein, DJ, Strejilevich, S, Sulaiman, AH, Suominen, K, Tagata, H, Tatebayashi, Y, Torrent, C, Vieta, E, Viswanath, B, Wanchoo, MJ, Zetin, M, and Whybrow, PC

Abstract

BACKGROUND: The onset of bipolar disorder is influenced by the interaction of genetic and environmental factors. We previously found that a large increase in sunlight in springtime was associated with a lower age of onset. This study extends this analysis with more collection sites at diverse locations, and includes family history and polarity of first episode. METHODS: Data from 4037 patients with bipolar I disorder were collected at 36 collection sites in 23 countries at latitudes spanning 3.2 north (N) to 63.4 N and 38.2 south (S) of the equator. The age of onset of the first episode, onset location, family history of mood disorders, and polarity of first episode were obtained retrospectively, from patient records and/or direct interview. Solar insolation data were obtained for the onset locations. RESULTS: There was a large, significant inverse relationship between maximum monthly increase in solar insolation and age of onset, controlling for the country median age and the birth cohort. The effect was reduced by half if there was no family history. The maximum monthly increase in solar insolation occurred in springtime. The effect was one-third smaller for initial episodes of mania than depression. The largest maximum monthly increase in solar insolation occurred in northern latitudes such as Oslo, Norway, and warm and dry areas such as Los Angeles, California. LIMITATIONS: Recall bias for onset and family history data. CONCLUSIONS: A large springtime increase in sunlight may have an important influence on the onset of bipolar disorder, especially in those with a family history of mood disorders.

Published
2014

73. Assessment of Response to Lithium Maintenance Treatment in Bipolar Disorder: A Consortium on Lithium Genetics (ConLiGen) Report

Author

Manchia, M, Adli, M, Akula, N, Ardau, R, Aubry, JM, Backlund, L, Banzato, CEM, Baune, BT, Bellivier, F, Bengesser, S, Biernacka, JM, Brichant-Petitjean, C, Bui, E, Calkin, CV, Cheng, ATA, Chillotti, C, Cichon, S, Clark, S, Czerski, PM, Dantas, C, Del Zompo, M, DePaulo, JR, Detera-Wadleigh, SD, Etain, B, Falkai, P, Frisén, L, Frye, MA, Fullerton, J, Gard, S, Garnham, J, Goes, FS, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Heilbronner, U, Hoban, R, Hou, L, Jamain, S, Kahn, JP, Kassem, L, Kato, T, Kelsoe, JR, Kittel-Schneider, S, Kliwicki, S, Kuo, PH, Kusumi, I, Laje, G, Lavebratt, C, Leboyer, M, Leckband, SG, López Jaramillo, CA, Maj, M, Malafosse, A, Martinsson, L, Masui, T, Mitchell, PB, Mondimore, F, Monteleone, P, Nallet, A, Neuner, M, Novák, T, O'Donovan, C, Ösby, U, Ozaki, N, Perlis, RH, Pfennig, A, Potash, JB, Reich-Erkelenz, D, Reif, A, Reininghaus, E, Richardson, S, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schubert, OK, Schweizer, B, Seemüller, F, Grigoroiu-Serbanescu, M, Severino, G, Seymour, LR, Slaney, C, Smoller, JW, Squassina, A, Stamm, T, Steele, J, Stopkova, P, Tighe, SK, Tortorella, A, Turecki, G, Wray, NR, Wright, A, Zandi, PP, Zilles, D, Bauer, M, Rietschel, M, McMahon, FJ, Schulze, TG, Alda, M, Manchia, M, Adli, M, Akula, N, Ardau, R, Aubry, JM, Backlund, L, Banzato, CEM, Baune, BT, Bellivier, F, Bengesser, S, Biernacka, JM, Brichant-Petitjean, C, Bui, E, Calkin, CV, Cheng, ATA, Chillotti, C, Cichon, S, Clark, S, Czerski, PM, Dantas, C, Del Zompo, M, DePaulo, JR, Detera-Wadleigh, SD, Etain, B, Falkai, P, Frisén, L, Frye, MA, Fullerton, J, Gard, S, Garnham, J, Goes, FS, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Heilbronner, U, Hoban, R, Hou, L, Jamain, S, Kahn, JP, Kassem, L, Kato, T, Kelsoe, JR, Kittel-Schneider, S, Kliwicki, S, Kuo, PH, Kusumi, I, Laje, G, Lavebratt, C, Leboyer, M, Leckband, SG, López Jaramillo, CA, Maj, M, Malafosse, A, Martinsson, L, Masui, T, Mitchell, PB, Mondimore, F, Monteleone, P, Nallet, A, Neuner, M, Novák, T, O'Donovan, C, Ösby, U, Ozaki, N, Perlis, RH, Pfennig, A, Potash, JB, Reich-Erkelenz, D, Reif, A, Reininghaus, E, Richardson, S, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schubert, OK, Schweizer, B, Seemüller, F, Grigoroiu-Serbanescu, M, Severino, G, Seymour, LR, Slaney, C, Smoller, JW, Squassina, A, Stamm, T, Steele, J, Stopkova, P, Tighe, SK, Tortorella, A, Turecki, G, Wray, NR, Wright, A, Zandi, PP, Zilles, D, Bauer, M, Rietschel, M, McMahon, FJ, Schulze, TG, and Alda, M

Abstract

Objective:The assessment of response to lithium maintenance treatment in bipolar disorder (BD) is complicated by variable length of treatment, unpredictable clinical course, and often inconsistent compliance. Prospective and retrospective methods of assessment of lithium response have been proposed in the literature. In this study we report the key phenotypic measures of the "Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder" scale currently used in the Consortium on Lithium Genetics (ConLiGen) study.Materials and Methods:Twenty-nine ConLiGen sites took part in a two-stage case-vignette rating procedure to examine inter-rater agreement [Kappa (κ)] and reliability [intra-class correlation coefficient (ICC)] of lithium response. Annotated first-round vignettes and rating guidelines were circulated to expert research clinicians for training purposes between the two stages. Further, we analyzed the distributional properties of the treatment response scores available for 1,308 patients using mixture modeling.Results:Substantial and moderate agreement was shown across sites in the first and second sets of vignettes (κ = 0.66 and κ = 0.54, respectively), without significant improvement from training. However, definition of response using the A score as a quantitative trait and selecting cases with B criteria of 4 or less showed an improvement between the two stages (ICC1 = 0.71 and ICC2 = 0.75, respectively). Mixture modeling of score distribution indicated three subpopulations (full responders, partial responders, non responders).Conclusions:We identified two definitions of lithium response, one dichotomous and the other continuous, with moderate to substantial inter-rater agreement and reliability. Accurate phenotypic measurement of lithium response is crucial for the ongoing ConLiGen pharmacogenomic study.

Published
2013

77. Admixture analysis of age at symptom onset and age at disorder onset in a large sample of patients with obsessive-compulsive disorder

Author

Umberto Volpe, Alfonso Tortorella, Bernardo Carpiniello, Gianluca Rosso, Umberto Albert, Giuseppe Maina, Mirko Manchia, Albert, U., Manchia, M., Tortorella, A., Volpe, U., Rosso, G., Carpiniello, B., Maina, G., Albert U., Manchia M., Tortorella A., Volpe U., Rosso G., Carpiniello B., Maina G., Albert, U, Manchia, M, Tortorella, A, Volpe, Umberto, Rosso, G, and Carpiniello, B

Subjects
Adult, Male, Obsessive-Compulsive Disorder, Pediatrics, medicine.medical_specialty, Adolescent, Population, Disorder onset, Late onset, Severity of Illness Index, Obsessive–compulsive disorder, Obsessive–compulsive disorder Age at onset Admixture analysis Early onset, Severity of illness, medicine, Humans, Symptom onset, Age of Onset, education, Retrospective Studies, Early onset, education.field_of_study, Medicine (all), Age at onset, Admixture analysis, Retrospective cohort study, Middle Aged, Admixture analysi, Psychiatry and Mental health, Clinical Psychology, Female, Age of onset, Obsessive-compulsive disorder, Psychiatry and Mental Health, Psychology
Abstract

Background A number of studies tested for the presence of different homogeneous subgroups of obsessive–compulsive disorder (OCD) patients depending on the age at onset (AAO). However, none of the various thresholds of AAO have been validated. No study examined whether age at symptoms onset (ASO) and age at disorder onset (ADO) each define specific and diverse OCD subgroups. Methods We used normal distribution mixture analysis in a sample of 483 OCD patients to test whether we could identify subgroups of patients according to the AAO. We tested whether ASO and ADO had different distributions and identified different subgroups of OCD patients, and whether clinical correlates had similar patterns of associations with patients subgroups identified with ASO or ADO. Results The mixture analysis showed a trimodal distribution for ASO (mean ASO: 6.9 years for the early onset, 14.99 years for the intermediate onset, and 27.7 years for the late onset component), and confirmed a bimodal distribution for ADO (mean ADO: 18.0 and 29.5 years). Significant differences in the clinical profile of the subgroups emerged, particularly when identified using ASO. Limitations Limitations of our study are the retrospective investigation of AAO, and the fact that our sample may not represent the OCD population, as we enrolled patients referring to a tertiary center specialized in the treatment of OCD. Our findings need to be confirmed in community samples. Another limitation is the lack of information on medication status at enrollment. Conclusions Age at symptom onset and ADO showed distinct patterns of distributions. Similarly, phenotypic delineation was specific for ASO and ADO identified subgroups. Accurate clinical and biological profiling of ADO and ASO subgroups might show distinct genetic liabilities, ultimately leading to better nosological models and possibly to improved treatment decision making of OCD patients.

Published
2015

78. Sustained symptomatic remission in schizophrenia: Course and predictors from a two-year prospective study

Author

Mirko Manchia, Massimo Tusconi, Bernardo Carpiniello, Federica Pinna, Roberto Cavallaro, Marta Bosia, Carpiniello, B., Pinna, F., Manchia, M., Tusconi, M., Cavallaro, R., and Bosia, M.

Subjects
Psychosis, medicine.medical_specialty, Duration of illness, Schizoaffective disorder, Basal (phylogenetics), Internal medicine, medicine, Humans, Prospective Studies, Prospective cohort study, Cognitive symptoms, Biological Psychiatry, Survival analysis, Psychiatric Status Rating Scales, Positive and Negative Syndrome Scale, business.industry, Regression analysis, Antipsychotic treatment, Positive and negative syndrome scale, medicine.disease, Clinical setting, Psychiatry and Mental health, Treatment Outcome, Psychotic Disorders, Schizophrenia, Schizophrenic Psychology, business, Antipsychotic Agents, Follow-Up Studies
Abstract

Background Although remission is a priority target in psychosis, reported rates show a marked variation across studies and instability over time. Such variability, partly due to methodology, emphasizes the need to define the optimal assessment procedure, as well as to identify reliable predictors. This study aims to: 1. longitudinally compare remission status according to different criteria; 2. identify predictors of duration and stability. Methods 112 patients with schizophrenia or schizoaffective disorder underwent comprehensive clinical evaluations, with 24-month follow-up. Remission was assessed using three criteria: Remission in Schizophrenia Working Group (RSWG) vs Positive and Negative Syndrome Scale (PANSS) positive and negative scales (PANSS-PN) vs total score (PANSS-T). Kaplan-Meier survival analysis was used for longitudinal comparison, regression models to identify predictors of duration and stability. Results At enrolment 50% of patients were in remission according to RSWG, while only 23.2% reached the other criteria. PANSS-T cumulative remission rates showed the greatest stability. Stable remission according to RSWG criteria was predicted by negative symptoms, while no significant predictors emerged for PANSS-T. Remission duration was predicted by negative, positive and cognitive symptoms and treatment dosage for RSWG criteria, while for PANSS-T the predictors were cognitive symptoms and duration of illness. Conclusion Results are in line with previous literature on remission rates and further support the role of basal clinical predictors. In addition, this study shows that more stringent criteria are more stable over time, suggesting their predictive value and the relevance of their use to optimize evaluations also in clinical settings.

Published
2022

79. Association of polygenic score for major depression with response to lithium in patients with bipolar disorder

Author

Amare, Azmeraw T., Schubert, Klaus Oliver, Hou, Liping, Clark, Scott R., Papiol, Sergi, Cearns, Micah, Heilbronner, Urs, Degenhardt, Franziska, Tekola-Ayele, Fasil, Hsu, Yi Hsiang, Shekhtman, Tatyana, Adli, Mazda, Akula, Nirmala, Akiyama, Kazufumi, Ardau, Raffaella, Arias, Bárbara, Aubry, Jean Michel, Backlund, Lena, Bhattacharjee, Abesh Kumar, Bellivier, Frank, Benabarre, Antonio, Bengesser, Susanne, Biernacka, Joanna M., Birner, Armin, Brichant-Petitjean, Clara, Cervantes, Pablo, Chen, Hsi Chung, Chillotti, Caterina, Cichon, Sven, Cruceanu, Cristiana, Czerski, Piotr M., Dalkner, Nina, Dayer, Alexandre, Del Zompo, Maria, DePaulo, J. Raymond, Étain, Bruno, Jamain, Stephane, Falkai, Peter, Forstner, Andreas J., Frisen, Louise, Frye, Mark A., Fullerton, Janice M., Gard, Sébastien, Garnham, Julie S., Goes, Fernando S., Grigoroiu-Serbanescu, Maria, Grof, Paul, Hashimoto, Ryota, Hauser, Joanna, Herms, Stefan, Hoffmann, Per, Hofmann, Andrea, Jiménez, Esther, Kahn, Jean Pierre, Kassem, Layla, Kuo, Po Hsiu, Kato, Tadafumi, Kelsoe, John R., Kittel-Schneider, Sarah, Kliwicki, Sebastian, König, Barbara, Kusumi, Ichiro, Laje, Gonzalo, Landén, Mikael, Lavebratt, Catharina, Leboyer, Marion, Leckband, Susan G., Tortorella, Alfonso, Manchia, Mirko, Martinsson, Lina, McCarthy, Michael J., McElroy, Susan L., Colom, Francesc, Mitjans, Marina, Mondimore, Francis M., Monteleone, Palmiero, Nievergelt, Caroline M., Nöthen, Markus M., Novák, Tomas, O’Donovan, Claire, Ozaki, Norio, Ösby, Urban, Pfennig, Andrea, Potash, James B., Reif, Andreas, Wray, Naomi R., Ripke, Stephan, Mattheisen, Manuel, Trzaskowski, Maciej, Byrne, Enda M., Abdellaoui, Abdel, Adams, Mark J., Agerbo, Esben, Air, Tracy M., Andlauer, Till F.M., Bacanu, Silviu Alin, Bækvad-Hansen, Marie, Beekman, Aartjan T.F., Bigdeli, Tim B., Binder, Elisabeth B., Blackwood, Douglas H.R., Bryois, Julien, Buttenschøn, Henriette N., Bybjerg-Grauholm, Jonas, Cai, Na, Castelao, Enrique, Christensen, Jane varregaard, Clarke, Toni Kim, Coleman, Jonathan R.I., Colodro-Conde, Lucía, Couvy-Duchesne, Baptiste, Craddock, Nick, Crawford, Gregory E., Davies, Gail, Deary, Ian J., Derks, Eske M., Direk, Nese, Dolan, Conor V., Dunn, Erin C., Eley, Thalia C., Escott-Price, Valentina, Kiadeh, Farnush Farhadi Hassan, Finucane, Hilary K., Frank, Josef, Gaspar, Héléna A., Gill, Michael, Gordon, Scott D., Grove, Jakob, Hall, Lynsey S., Hansen, Christine Søholm, Hansen, Thomas F., Hickie, Ian B., Homuth, Georg, Horn, Carsten, Hottenga, Jouke Jan, Hougaard, David M., Ising, Marcus, Jansen, Rick, Jorgenson, Eric, Knowles, James A., Kohane, Isaac S., Kraft, Julia, Kretzschmar, Warren W., Krogh, Jesper, Kutalik, Zoltán, Li, Yihan, Lind, Penelope A., MacIntyre, Donald J., MacKinnon, Dean F., Maier, Robert M., Maier, Wolfgang, Marchini, Jonathan, Mbarek, Hamdi, McGrath, Patrick, McGuffin, Peter, Medland, Sarah E., Mehta, Divya, Middeldorp, Christel M., Mihailov, Evelin, Milaneschi, Yuri, Milani, Lili, Montgomery, Grant W., Mostafavi, Sara, Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nivard, Michel G., Nyholt, Dale R., O’Reilly, Paul F., Oskarsson, Hogni, Owen, Michael J., Painter, Jodie N., Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Peterson, Roseann E., Pettersson, Erik, Peyrot, Wouter J., Pistis, Giorgio, Posthuma, Danielle, Quiroz, Jorge A., Qvist, Per, Rice, John P., Riley, Brien P., Rivera, Margarita, Mirza, Saira Saeed, Schoevers, Robert, Schulte, Eva C., Shen, Ling, Shi, Jianxin, Shyn, Stanley I., Sigurdsson, Engilbert, Sinnamon, Grant C.B., Smit, Johannes H., Smith, Daniel J., Stefansson, Hreinn, Steinberg, Stacy, Streit, Fabian, Strohmaier, Jana, Tansey, Katherine E., Teismann, Henning, Teumer, Alexander, Thompson, Wesley, Thomson, Pippa A., Thorgeirsson, Thorgeir E., Traylor, Matthew, Treutlein, Jens, Trubetskoy, Vassily, Uitterlinden, André G., Umbricht, Daniel, Van der Auwera, Sandra, van Hemert, Albert M., Viktorin, Alexander, Visscher, Peter M., Wang, Yunpeng, Webb, Bradley T., Weinsheimer, Shantel Marie, Wellmann, Jürgen, Willemsen, Gonneke, Witt, Stephanie H., Wu, Yang, Xi, Hualin S., Yang, Jian, Zhang, Futao, Arolt, Volker, Baune, Bernhard T., Berger, Klaus, Boomsma, Dorret I., Dannlowski, Udo, de Geus, E. J.C., Domenici, Enrico, Domschke, Katharina, Esko, Tõnu, Grabe, Hans J., Hamilton, Steven P., Hayward, Caroline, Heath, Andrew C., Kendler, Kenneth S., Kloiber, Stefan, Lewis, Glyn, Li, Qingqin S., Lucae, Susanne, Madden, Pamela A.F., Magnusson, Patrik K., Martin, Nicholas G., McIntosh, Andrew M., Metspalu, Andres, Mors, Ole, Mortensen, Preben Bo, Müller-Myhsok, Bertram, Nordentoft, Merete, O’Donovan, Michael C., Paciga, Sara A., Pedersen, Nancy L., Penninx, Brenda W.J.H., Perlis, Roy H., Porteous, David J., Preisig, Martin, Rietschel, Marcella, Schaefer, Catherine, Schulze, Thomas G., Smoller, Jordan W., Stefansson, Kari, Tiemeier, Henning, Uher, Rudolf, Völzke, Henry, Weissman, Myrna M., Werge, Thomas, Lewis, Cathryn M., Levinson, Douglas F., Breen, Gerome, Børglum, Anders D., Sullivan, Patrick F., Reininghaus, Eva, Rouleau, Guy A., Rybakowski, Janusz K., Schalling, Martin, Schofield, Peter R., Schweizer, Barbara W., Severino, Giovanni, Shilling, Paul D., Shimoda, Katzutaka, Simhandl, Christian, Slaney, Claire M., Squassina, Alessio, Stamm, Thomas, Stopkova, Pavla, Maj, Mario, Turecki, Gustavo, Vieta, Eduard, Veeh, Julia, Wright, Adam, Zandi, Peter P., Mitchell, Philip B., Bauer, Michael, Alda, Martin, McMahon, Francis J., APH - Mental Health, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Reproduction & Development (AR&D), Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Human genetics, APH - Digital Health, APH - Methodology, Biological Psychology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Complex Trait Genetics, Clinical Cognitive Neuropsychiatry Research Program (CCNP), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Jamain, Stéphane, University of Adelaide, South Australian Health and Medical Research Institute [ Adelaide] (SAHMRI), Mental Health Services [Adelaide, SA, Australia], National Institute of Mental Health (NIMH), Ludwig Maximilian University [Munich] (LMU), Georg-August-University = Georg-August-Universität Göttingen, Institut für Genetik - Universität Bonn / Institute of Genetics - University of Bonn, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), Harvard Medical School [Boston] (HMS), Harvard School of Public Health, University of California [San Diego] (UC San Diego), University of California (UC), Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Dokkyo Medical University, Università degli Studi di Cagliari = University of Cagliari (UniCa), Universitat Autònoma de Barcelona (UAB), Centro de Investigación Biomédica en Red de Salud Mental [Barcelona, Spain] (CIBERSAM), Hospital Sant Joan de Déu [Barcelona], Geneva University Hospital (HUG), Karolinska Institutet [Stockholm], Karolinska University Hospital [Stockholm], Optimisation thérapeutique en Neuropsychopharmacologie (OPTeN (UMR_S_1144 / U1144)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona (UB), Karl-Franzens-Universität Graz, Mayo Clinic [Rochester], McGill University Health Center [Montreal] (MUHC), National Taiwan University [Taiwan] (NTU), University Hospital Basel [Basel], Poznan University of Medical Sciences [Poland] (PUMS), Johns Hopkins University (JHU), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Fondation FondaMental [Créteil], IMRB - 'Neuropsychiatrie translationnelle' [Créteil] (U955 Inserm - UPEC), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), University of Basel (Unibas), Neuroscience Research Australia [Sydney, NSW, Australia] (NRA), University of New South Wales [Sydney] (UNSW), Psychiatrie de l'enfant et de l'adolescent [CH C. Perrens, Bordeaux], SECOP - centre hospitalier Charles Perrens, Dalhousie University [Halifax], 'Prof. Dr. Alexandru Obregia' Clinical Hospital of Psychiatry [Bucharest, Romania], Mood Disorders Center of Ottawa (MDCO), University of Ottawa [Ottawa], Osaka University [Osaka], Graduate School of Medicine [Osaka], Centro de Investigación Biomédica en Red Salud Mental [Madrid] (CIBER-SAM), Psychiatrie et Psychologie Clinique de Liaison [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Centre Psychothérapique de Nancy (CPN), National Institutes of Health [Bethesda] (NIH), Environmental Molecular Biology Laboratory (RIKEN), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), Goethe-University Frankfurt am Main, Landesklinikum Neunkirchen (LK Neunkirchen), Hokkaido University Graduate School of Medicine [Sapporo, Japan], Sahlgrenska Academy at University of Gothenburg [Göteborg], Research Service VA San Diego Healthcare System, Università degli Studi di Perugia = University of Perugia (UNIPG), University of Cincinnati (UC), IMIM-Hospital del Mar, Generalitat de Catalunya, Max Planck Institute of Experimental Medicine [Göttingen] (MPI), Max-Planck-Gesellschaft, University of Salerno (UNISA), University of the Study of Campania Luigi Vanvitelli, National Institute of Mental Health [Klecany, Czech Republic] (NIMH), Nagoya University Graduate School of Medicine [Japon], Technische Universität Dresden = Dresden University of Technology (TU Dresden), Medical University Graz, Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada], Sigmund Freud University (SFU), Douglas Mental Health University Institute [Montréal], University of Heidelberg, Medical Faculty, Black Dog Institute [Sydney, Australia], Johns Hopkins Bloomberg School of Public Health [Baltimore], Westfälische Wilhelms-Universität Münster = University of Münster (WWU), Melbourne Medical School [Melbourne], Faculty of Medicine, Dentistry and Health Sciences [Melbourne], University of Melbourne-University of Melbourne, The Florey Institute of Neuroscience and Mental Health [Parkville, VIC, Australie], University of Melbourne, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium: Naomi R Wray, Stephan Ripke, Manuel Mattheisen, Maciej Trzaskowski, Enda M Byrne, Abdel Abdellaoui, Mark J Adams, Esben Agerbo, Tracy M Air, Till F M Andlauer, Silviu-Alin Bacanu, Marie Bækvad-Hansen, Aartjan T F Beekman, Tim B Bigdeli, Elisabeth B Binder, Douglas H R Blackwood, Julien Bryois, Henriette N Buttenschøn, Jonas Bybjerg-Grauholm, Na Cai, Enrique Castelao, Jane Varregaard Christensen, Toni-Kim Clarke, Jonathan R I Coleman, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Nick Craddock, Gregory E Crawford, Gail Davies, Ian J Deary, Franziska Degenhardt, Eske M Derks, Nese Direk, Conor V Dolan, Erin C Dunn, Thalia C Eley, Valentina Escott-Price, Farnush Farhadi Hassan Kiadeh, Hilary K Finucane, Andreas J Forstner, Josef Frank, Héléna A Gaspar, Michael Gill, Fernando S Goes, Scott D Gordon, Jakob Grove, Lynsey S Hall, Christine Søholm Hansen, Thomas F Hansen, Stefan Herms, Ian B Hickie, Per Hoffmann, Georg Homuth, Carsten Horn, Jouke-Jan Hottenga, David M Hougaard, Marcus Ising, Rick Jansen, Eric Jorgenson, James A Knowles, Isaac S Kohane, Julia Kraft, Warren W Kretzschmar, Jesper Krogh, Zoltán Kutalik, Yihan Li, Penelope A Lind, Donald J MacIntyre, Dean F MacKinnon, Robert M Maier, Wolfgang Maier, Jonathan Marchini, Hamdi Mbarek, Patrick McGrath, Peter McGuffin, Sarah E Medland, Divya Mehta, Christel M Middeldorp, Evelin Mihailov, Yuri Milaneschi, Lili Milani, Francis M Mondimore, Grant W Montgomery, Sara Mostafavi, Niamh Mullins, Matthias Nauck, Bernard Ng, Michel G Nivard, Dale R Nyholt, Paul F O'Reilly, Hogni Oskarsson, Michael J Owen, Jodie N Painter, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Roseann E Peterson, Erik Pettersson, Wouter J Peyrot, Giorgio Pistis, Danielle Posthuma, Jorge A Quiroz, Per Qvist, John P Rice, Brien P Riley, Margarita Rivera, Saira Saeed Mirza, Robert Schoevers, Eva C Schulte, Ling Shen, Jianxin Shi, Stanley I Shyn, Engilbert Sigurdsson, Grant C B Sinnamon, Johannes H Smit, Daniel J Smith, Hreinn Stefansson, Stacy Steinberg, Fabian Streit, Jana Strohmaier, Katherine E Tansey, Henning Teismann, Alexander Teumer, Wesley Thompson, Pippa A Thomson, Thorgeir E Thorgeirsson, Matthew Traylor, Jens Treutlein, Vassily Trubetskoy, André G Uitterlinden, Daniel Umbricht, Sandra Van der Auwera, Albert M van Hemert, Alexander Viktorin, Peter M Visscher, Yunpeng Wang, Bradley T Webb, Shantel Marie Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Stephanie H Witt, Yang Wu, Hualin S Xi, Jian Yang, Futao Zhang, Volker Arolt, Bernhard T Baune, Klaus Berger, Dorret I Boomsma, Sven Cichon, Udo Dannlowski, E J C de Geus, J Raymond DePaulo, Enrico Domenici, Katharina Domschke, Tõnu Esko, Hans J Grabe, Steven P Hamilton, Caroline Hayward, Andrew C Heath, Kenneth S Kendler, Stefan Kloiber, Glyn Lewis, Qingqin S Li, Susanne Lucae, Pamela A F Madden, Patrik K Magnusson, Nicholas G Martin, Andrew M McIntosh, Andres Metspalu, Ole Mors, Preben Bo Mortensen, Bertram Müller-Myhsok, Merete Nordentoft, Markus M Nöthen, Michael C O'Donovan, Sara A Paciga, Nancy L Pedersen, Brenda W J H Penninx, Roy H Perlis, David J Porteous, James B Potash, Martin Preisig, Marcella Rietschel, Catherine Schaefer, Thomas G Schulze, Jordan W Smoller, Kari Stefansson, Henning Tiemeier, Rudolf Uher, Henry Völzke, Myrna M Weissman, Thomas Werge, Cathryn M Lewis, Douglas F Levinson, Gerome Breen, Anders D Børglum, Patrick F Sullivan., Epidemiology, Internal Medicine, Child and Adolescent Psychiatry / Psychology, Georg-August-University [Göttingen], University of California, Universita degli Studi di Cagliari [Cagliari], Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), University of Graz, Università degli Studi di Perugia (UNIPG), University of Münster, Karl-Franzens-Universität [Graz, Autriche], Amare, A. T., Schubert, K. O., Hou, L., Clark, S. R., Papiol, S., Cearns, M., Heilbronner, U., Degenhardt, F., Tekola-Ayele, F., Hsu, Y. -H., Shekhtman, T., Adli, M., Akula, N., Akiyama, K., Ardau, R., Arias, B., Aubry, J. -M., Backlund, L., Bhattacharjee, A. K., Bellivier, F., Benabarre, A., Bengesser, S., Biernacka, J. M., Birner, A., Brichant-Petitjean, C., Cervantes, P., Chen, H. -C., Chillotti, C., Cichon, S., Cruceanu, C., Czerski, P. M., Dalkner, N., Dayer, A., Del Zompo, M., Depaulo, J. R., Etain, B., Jamain, S., Falkai, P., Forstner, A. J., Frisen, L., Frye, M. A., Fullerton, J. M., Gard, S., Garnham, J. S., Goes, F. S., Grigoroiu-Serbanescu, M., Grof, P., Hashimoto, R., Hauser, J., Herms, S., Hoffmann, P., Hofmann, A., Jimenez, E., Kahn, J. -P., Kassem, L., Kuo, P. -H., Kato, T., Kelsoe, J. R., Kittel-Schneider, S., Kliwicki, S., Konig, B., Kusumi, I., Laje, G., Landen, M., Lavebratt, C., Leboyer, M., Leckband, S. G., Tortorella, A., Manchia, M., Martinsson, L., Mccarthy, M. J., Mcelroy, S. L., Colom, F., Mitjans, M., Mondimore, F. M., Monteleone, P., Nievergelt, C. M., Nothen, M. M., Novak, T., O'Donovan, C., Ozaki, N., Osby, U., Pfennig, A., Potash, J. B., Reif, A., Wray, N. R., Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., Agerbo, E., Air, T. M., Andlauer, T. F. M., Bacanu, S. -A., Baekvad-Hansen, M., Beekman, A. T. F., Bigdeli, T. B., Binder, E. B., Blackwood, D. H. R., Bryois, J., Buttenschon, H. N., Bybjerg-Grauholm, J., Cai, N., Castelao, E., Christensen, J., Clarke, T. -K., Coleman, J. R. I., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Crawford, G. E., Davies, G., Deary, I. J., Derks, E. M., Direk, N., Dolan, C. V., Dunn, E. C., Eley, T. C., Escott-Price, V., Kiadeh, F. F. H., Finucane, H. K., Frank, J., Gaspar, H. A., Gill, M., Gordon, S. D., Grove, J., Hall, L. S., Hansen, C. S., Hansen, T. F., Hickie, I. B., Homuth, G., Horn, C., Hottenga, J. -J., Hougaard, D. M., Ising, M., Jansen, R., Jorgenson, E., Knowles, J. A., Kohane, I. S., Kraft, J., Kretzschmar, W. W., Krogh, J., Kutalik, Z., Li, Y., Lind, P. A., Macintyre, D. J., Mackinnon, D. F., Maier, R. M., Maier, W., Marchini, J., Mbarek, H., Mcgrath, P., Mcguffin, P., Medland, S. E., Mehta, D., Middeldorp, C. M., Mihailov, E., Milaneschi, Y., Milani, L., Montgomery, G. W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M. G., Nyholt, D. R., O'Reilly, P. F., Oskarsson, H., Owen, M. J., Painter, J. N., Pedersen, C. B., Pedersen, M. G., Peterson, R. E., Pettersson, E., Peyrot, W. J., Pistis, G., Posthuma, D., Quiroz, J. A., Qvist, P., Rice, J. P., Riley, B. P., Rivera, M., Mirza, S. S., Schoevers, R., Schulte, E. C., Shen, L., Shi, J., Shyn, S. I., Sigurdsson, E., Sinnamon, G. C. B., Smit, J. H., Smith, D. J., Stefansson, H., Steinberg, S., Streit, F., Strohmaier, J., Tansey, K. E., Teismann, H., Teumer, A., Thompson, W., Thomson, P. A., Thorgeirsson, T. E., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A. G., Umbricht, D., Van der Auwera, S., van Hemert, A. M., Viktorin, A., Visscher, P. M., Wang, Y., Webb, B. T., Weinsheimer, S. M., Wellmann, J., Willemsen, G., Witt, S. H., Wu, Y., Xi, H. S., Yang, J., Zhang, F., Arolt, V., Baune, B. T., Berger, K., Boomsma, D. I., Dannlowski, U., de Geus, E. J. C., Domenici, E., Domschke, K., Esko, T., Grabe, H. J., Hamilton, S. P., Hayward, C., Heath, A. C., Kendler, K. S., Kloiber, S., Lewis, G., Li, Q. S., Lucae, S., Madden, P. A. F., Magnusson, P. K., Martin, N. G., Mcintosh, A. M., Metspalu, A., Mors, O., Mortensen, P. B., Muller-Myhsok, B., Nordentoft, M., O'Donovan, M. C., Paciga, S. A., Pedersen, N. L., Penninx, B. W. J. H., Perlis, R. H., Porteous, D. J., Preisig, M., Rietschel, M., Schaefer, C., Schulze, T. G., Smoller, J. W., Stefansson, K., Tiemeier, H., Uher, R., Volzke, H., Weissman, M. M., Werge, T., Lewis, C. M., Levinson, D. F., Breen, G., Borglum, A. D., Sullivan, P. F., Reininghaus, E., Rouleau, G. A., Rybakowski, J. K., Schalling, M., Schofield, P. R., Schweizer, B. W., Severino, G., Shilling, P. D., Shimoda, K., Simhandl, C., Slaney, C. M., Squassina, A., Stamm, T., Stopkova, P., Maj, M., Turecki, G., Vieta, E., Veeh, J., Wright, A., Zandi, P. P., Mitchell, P. B., Bauer, M., Alda, M., Mcmahon, F. J., and Adult Psychiatry

Subjects
0301 basic medicine, Netherlands Twin Register (NTR), Lithium (medication), [SDV.MHEP.PSM] Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Genome-wide association study, Logistic regression, THERAPY, ddc:616.89, 0302 clinical medicine, Medicine, Major depression, PREDICTORS, Depression (differential diagnoses), RISK, Depression, Psychiatry and Mental health, Quartile, Cohort, AUGMENTATION, medicine.drug, POLARITY, medicine.medical_specialty, GENETICS, Bipolar disorder, [SDV.GEN.GH] Life Sciences [q-bio]/Genetics/Human genetics, Lithium, PROPHYLACTIC LITHIUM, 03 medical and health sciences, Cellular and Molecular Neuroscience, SDG 3 - Good Health and Well-being, Internal medicine, Humans, ddc:610, AGENTS, Molecular Biology, Genetic association, Depressive Disorder, Major, business.industry, medicine.disease, EFFICACY, 030104 developmental biology, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, PHARMACOLOGICAL-TREATMENTS, business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

© 2020, The Author(s), under exclusive licence to Springer Nature Limited.Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18–2.01) and European sample: OR = 1.75 (95% CI: 1.30–2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61–4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.

Published
2021

80. Melatonin and aggressive behavior: A systematic review of the literature on preclinical and clinical evidence

Author

Pasquale Paribello, Mirko Manchia, Marta Bosia, Federica Pinna, Bernardo Carpiniello, Stefano Comai, Paribello, P., Manchia, M., Bosia, M., Pinna, F., Carpiniello, B., and Comai, S.

Subjects
fish, psychopharmacology, Aggression, Endocrinology, rodents, aggressive behavior, humans, melatonin, Animals, Violence, Melatonin
Abstract

The melatonin system and circadian disruption have well-established links with aggressive behaviors; however, the biological underpinnings have not been thoroughly investigated. Here, we aimed at examining the current knowledge regarding the neurobiological and psychopharmacological involvement of the melatonin system in aggressive/violent behaviors. To this end, we performed a systematic review on Embase and Pubmed/MEDLINE of preclinical and clinical evidence linking the melatonin system, melatonin, and melatoninergic drugs with aggressive/violent behaviors. Two blinded raters performed an independent screening of the relevant literature. Overall, this review included 38 papers distributed between clinical and preclinical models. Eleven papers specifically addressed the existing evidence in rodent models, five in fish models, and 21 in humans. The data indicate that depending on the species, model, and timing of administration, melatonin may exert a complex influence on aggressive/violent behaviors. Particularly, the apparent contrasting findings on the link between the melatonin system and aggression/violence (with either increased, no, or decreased effect) shown in preclinical models underscore the need for further research to develop more accurate and fruitful translational models. Likewise, the significant heterogeneity found in the results of clinical studies does not allow yet to draw any firm conclusion on the efficacy of melatonin or melatonergic drugs on aggressive/violent behaviors. However, findings in children and in traits associated with aggressive/violent behavior, including irritability and anger, are emerging and deserve empirical attention given the low toxicity of melatonin and melatonergic drugs.

Published
2022

81. Translating preclinical findings in clinically relevant new antipsychotic targets: focus on the glutamatergic postsynaptic density. Implications for treatment resistant schizophrenia

Author

Giordano D’Urso, Mirko Manchia, Andrea de Bartolomeis, Camilla Avagliano, Licia Vellucci, Elisabetta F. Buonaguro, Felice Iasevoli, Luigi D’Ambrosio, de Bartolomeis, A., Avagliano, C., Vellucci, Licia, D'Ambrosio, L., Manchia, M., D'Urso, G., Buonaguro, E. F., and Iasevoli, F.

Subjects
Psychosis, Aptamer, Homer1, Cognitive Neuroscience, medicine.medical_treatment, Negative symptom, HOMER1, Nerve Tissue Proteins, Receptors, N-Methyl-D-Aspartate, tDCS, Translational Research, Biomedical, Antipsychotic, Shank, 03 medical and health sciences, Behavioral Neuroscience, 0302 clinical medicine, mental disorders, medicine, Haloperidol, Animals, Humans, 0501 psychology and cognitive sciences, 050102 behavioral science & comparative psychology, Clozapine, PSD-95, Treatment resistant psychosis, microRNA, business.industry, 05 social sciences, Post-Synaptic Density, medicine.disease, Glutamatergic postsynaptic density, Neuropsychology and Physiological Psychology, Receptors, Glutamate, nervous system, Schizophrenia, TMS, business, Neuroscience, Postsynaptic density, Positive symptom, 030217 neurology & neurosurgery, Antipsychotic Agents, medicine.drug
Abstract

There is a growing interest in new molecular targets for antipsychotic therapy. Multiple signal transduction systems have been recently implicated in the pathophysiology of schizophrenia. However, the weight of each specific mechanism remains controversial. A need for a more vigorous approach to the pharmacotherapy of schizophrenia arises from the bedside: about 30-40% of patients do not respond to antipsychotic therapy. Postsynaptic Density (PSD) proteins have recently attracted attention for their role in signal transduction modulation and for their potential implication in psychosis and cognition. The involvement of PSD in the pathophysiology of schizophrenia is supported by post mortem studies, preclinical animal models, modulation by antipsychotics, and association of PSD genes with schizophrenia in GWAS. Taken together, these studies underline the role of PSD modulation, its effects on striatal function and its relationship with motor, executive- and cognitive-like functions suggesting a potential role of PSD proteins as a l target of novel intervention in the treatment of refractory psychosis.

Published
2019

82. Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients

Author

Michael McCarthy, Claire O'Donovan, Urs Heilbronner, Ichiro Kusumi, Eduard Vieta, Liping Hou, Hsi-Chung Chen, Claire Slaney, Maria Grigoroiu-Serbanescu, Kazufumi Akiyama, Michael Bauer, Janusz K. Rybakowski, Frank Bellivier, Marion Leboyer, Katzutaka Shimoda, Palmiero Monteleone, Cristiana Cruceanu, Alessio Squassina, Stephanie H. Witt, Tadafumi Kato, Giovanni Severino, Alfonso Tortorella, J. Raymond DePaulo, Martin Alda, Louise Frisén, Mazda Adl, Martin Schalling, Per Hoffmann, Susan G. Leckband, Jean-Pierre Kahn, Jean-Michel Aubry, Francis J. McMahon, Sven Cichon, Alexandre Dayer, Tatyana Shekhtman, Franziska Degenhardt, James B. Potash, Bruno Etain, Joseph Frank, Antonio Benabarre, Bernhard T. Baune, Gloria Roberts, Ryota Hashimoto, Tomas Novak, Paul D. Shilling, Julia Veeh, Joanna M. Biernacka, Barbara König, Peter Falkai, Philip B. Mitchell, Urban Ösby, Esther Jiménez, Sébastien Gard, Mark A. Frye, Sarah Kittel-Schneider, Layla Kassem, Fasil Tekola-Ayele, Armin Birner, Cynthia Marie-Claire, Raffaella Ardau, Abesh Kumar Bhattacharjee, Stéphane Jamain, Julie Garnham, Guy A. Rouleau, Caterina Chillotti, Piotr M. Czerski, Thomas G. Schulze, Gustavo Turecki, Anbupalam Thalamuthu, Claudia Pisanu, Azmeraw T. Amare, Marina Mitjans, Sergi Papiol, Mario Maj, Bárbara Arias, Janice M. Fullerton, Nina Dalkner, Peter R. Schofield, Susanne Bengesser, Stefan Herms, Klaus Oliver Schubert, Francis M. Mondimore, Eva Z. Reininghaus, Fernando S. Goes, Lena Backlund, Francesc Colom, Catharina Lavebratt, Christian Simhandl, Marcella Rietschel, Micah Cearns, Mikael Landén, Norio Ozaki, Gonzalo Laje, Barbara W. Schweizer, Nirmala Akula, Andrea Pfennig, Yi-Hsiang Hsu, John R. Kelsoe, Lina Martinsson, Markus M. Nöthen, Caroline M. Nievergelt, Pavla Stopkova, Mirko Manchia, Susan L. McElroy, Peter P. Zandi, Scott R. Clark, Joanna Hauser, Andreas J. Forstner, Po-Hsiu Kuo, Andreas Reif, Maria Del Zompo, Paul Grof, Fabian Streit, Ewa Ferensztajn-Rochowiak, Pablo Cervantes, Thomas Stamm, APH - Mental Health, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Amsterdam Neuroscience - Complex Trait Genetics, Psychiatry, APH - Digital Health, Schubert, K. O., Thalamuthu, A., Amare, A. T., Frank, J., Streit, F., Adl, M., Akula, N., Akiyama, K., Ardau, R., Arias, B., Aubry, J. -M., Backlund, L., Bhattacharjee, A. K., Bellivier, F., Benabarre, A., Bengesser, S., Biernacka, J. M., Birner, A., Marie-Claire, C., Cearns, M., Cervantes, P., Chen, H. -C., Chillotti, C., Cichon, S., Clark, S. R., Cruceanu, C., Czerski, P. M., Dalkner, N., Dayer, A., Degenhardt, F., Del Zompo, M., Depaulo, J. R., Etain, B., Falkai, P., Forstner, A. J., Frisen, L., Frye, M. A., Fullerton, J. M., Gard, S., Garnham, J. S., Goes, F. S., Grigoroiu-Serbanescu, M., Grof, P., Hashimoto, R., Hauser, J., Heilbronner, U., Herms, S., Hoffmann, P., Hou, L., Hsu, Y. -H., Jamain, S., Jimenez, E., Kahn, J. -P., Kassem, L., Kuo, P. -H., Kato, T., Kelsoe, J., Kittel-Schneider, S., Ferensztajn-Rochowiak, E., Konig, B., Kusumi, I., Laje, G., Landen, M., Lavebratt, C., Leboyer, M., Leckband, S. G., Maj, M., Manchia, M., Martinsson, L., Mccarthy, M. J., Mcelroy, S., Colom, F., Mitjans, M., Mondimore, F. M., Monteleone, P., Nievergelt, C. M., Nothen, M. M., Novak, T., O'Donovan, C., Ozaki, N., Osby, U., Papiol, S., Pfennig, A., Pisanu, C., Potash, J. B., Reif, A., Reininghaus, E., Rouleau, G. A., Rybakowski, J. K., Schalling, M., Schofield, P. R., Schweizer, B. W., Severino, G., Shekhtman, T., Shilling, P. D., Shimoda, K., Simhandl, C., Slaney, C. M., Squassina, A., Stamm, T., Stopkova, P., Tekola-Ayele, F., Tortorella, A., Turecki, G., Veeh, J., Vieta, E., Witt, S. H., Roberts, G., Zandi, P. P., Alda, M., Bauer, M., Mcmahon, F. J., Mitchell, P. B., Schulze, T. G., Rietschel, M., and Baune, B. T.

Subjects
Oncology, Multifactorial Inheritance, Treatment response, medicine.medical_specialty, Lithium (medication), Bipolar disorder, Poor responder, Neurosciences. Biological psychiatry. Neuropsychiatry, Lithium, DISEASE, Article, Cellular and Molecular Neuroscience, Risk Factors, Internal medicine, medicine, Humans, Manic-depressive illness, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, Depressió psíquica, METAANALYSIS, Biological Psychiatry, Depression (differential diagnoses), MANIA, Depressive Disorder, Depressive Disorder, Major, Trastorn bipolar, Depression, business.industry, Major, medicine.disease, Pathway analysis, Liti, COMPARATIVE EFFICACY, Psychiatry and Mental health, Mental depression, Schizophrenia, Polygenic risk score, Esquizofrènia, Pharmacogenomics, business, RC321-571, medicine.drug
Abstract

Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium’s therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.

Published
2021

83. Predominant Polarity and Polarity Index of Maintenance Treatments for Bipolar Disorder: A Validation Study in a Large Naturalistic Sample in Italy

Author

Umberto Albert, Sofia Burato, Mirko Manchia, Gianluca Rosso, Giuseppe Maina, Federica Pinna, Gabriele Di Salvo, Bernardo Carpiniello, Albert, U., Manchia, M., Burato, S., Carpiniello, B., Di Salvo, G., Pinna, F., Rosso, G., and Maina, G.

Subjects
bipolar disorder, polarity index, predominant polarity, medicine.medical_specialty, Validation study, Medicine (General), Bipolar Disorder, medicine.drug_class, Polarity (physics), Polarity index, Article, R5-920, Internal medicine, Predominant polarity, medicine, Humans, Prospective Studies, Bipolar disorder, Prospective cohort study, Antidepressive Agents, Italy, business.industry, Clinical course, Mood stabilizer, General Medicine, medicine.disease, Large sample, Prospective Studie, Mood, Antidepressive Agent, business, Human
Abstract

Background and Objectives: Predominant polarity (PP) may be a useful course specifier in at least a significant proportion of patients with Bipolar Disorder (BD), being associated with several clinically relevant correlates. Emerging evidence suggests that the concept of PP might influence the selection of maintenance treatments, based on a drug polarity index (PI) which measures the greater antidepressive vs. antimanic preventive efficacy of mood stabilizers over long-term maintenance treatment. In this study, we aimed to validate the PI in a large sample of Italian BD patients with accurate longitudinal characterization of the clinical course, which ensured a robust definition of the PP. Materials and Methods: Our sample is comprised of 653 patients with BD, divided into groups based on the predominant polarity (manic/hypomanic predominant polarity—MPP, depressive predominant polarity—DPP and no predominant polarity). Subsequently we calculated the mean total polarity index for each group, and we compared the groups. Results: When we examined the mean PI of treatments prescribed to individuals with DPP, MPP and no predominant polarity, calculated using two different methods, we failed to find significant differences, with the exception of the PI calculated with the Popovic method and using the less stringent criterion for predominant polarity (PP50%). Conclusions: Future prospective studies are needed in order to determine whether the predominant polarity is indeed one clinical factor that might guide the clinician in choosing the right mood stabilizer for BD maintenance treatment.

Published
2021

84. Characterisation of age and polarity at onset in bipolar disorder

Author

Kalman, Janos, Olde Loohuis, Loes, Vreeker, Annabel, Mcquillin, Andrew, Stahl, Eli, Ruderfer, Douglas, Grigoroiu-Serbanescu, Maria, Panagiotaropoulou, Georgia, Ripke, Stephan, Bigdeli, Tim, Stein, Frederike, Meller, Tina, Meinert, Susanne, Pelin, Helena, Streit, Fabian, Papiol, Sergi, Adams, Mark, Adolfsson, Rolf, Adorjan, Kristina, Agartz, Ingrid, Aminoff, Sofie, Anderson-Schmidt, Heike, Andreassen, Ole, Ardau, Raffaella, Aubry, Jean-Michel, Balaban, Ceylan, Bass, Nicholas, Baune, Bernhard, Bellivier, Frank, Benabarre, Antoni, Bengesser, Susanne, Berrettini, Wade, Boks, Marco, Bromet, Evelyn, Brosch, Katharina, Budde, Monika, Byerley, William, Cervantes, Pablo, Chillotti, Catina, Cichon, Sven, Clark, Scott, Comes, Ashley, Corvin, Aiden, Coryell, William, Craddock, Nick, Craig, David, Croarkin, Paul, Cruceanu, Cristiana, Czerski, Piotr, Dalkner, Nina, Dannlowski, Udo, Degenhardt, Franziska, del Zompo, Maria, Depaulo, J Raymond, Djurovic, Srdjan, Edenberg, Howard, Eissa, Mariam Al, Elvsåshagen, Torbjørn, Etain, Bruno, Fanous, Ayman, Fellendorf, Frederike, Fiorentino, Alessia, Forstner, Andreas, Frye, Mark, Fullerton, Janice, Gade, Katrin, Garnham, Julie, Gershon, Elliot, Gill, Michael, Goes, Fernando, Gordon-Smith, Katherine, Grof, Paul, Guzman-Parra, Jose, Hahn, Tim, Hasler, Roland, Heilbronner, Maria, Heilbronner, Urs, Jamain, Stephane, Jimenez, Esther, Jones, Ian, Jones, Lisa, Jonsson, Lina, Kahn, Rene, Kelsoe, John, Kennedy, James, Kircher, Tilo, Kirov, George, Kittel-Schneider, Sarah, Klöhn-Saghatolislam, Farah, Knowles, James, Kranz, Thorsten, Lagerberg, Trine Vik, Landen, Mikael, Lawson, William, Leboyer, Marion, Li, Qingqin, Maj, Mario, Malaspina, Dolores, Manchia, Mirko, Mayoral, Fermin, Mcelroy, Susan, Mcinnis, Melvin, McIntosh, Andrew, Medeiros, Helena, Melle, Ingrid, Milanova, Vihra, Mitchell, Philip, Monteleone, Palmiero, Monteleone, Alessio Maria, Nöthen, Markus, Novak, Tomas, Nurnberger, John, O'Brien, Niamh, O'Connell, Kevin, O'Donovan, Claire, O'Donovan, Michael, Opel, Nils, Ortiz, Abigail, Owen, Michael, Pålsson, Erik, Pato, Carlos, Pato, Michele, Pawlak, Joanna, Pfarr, Julia-Katharina, Pisanu, Claudia, Potash, James, Rapaport, Mark, Reich-Erkelenz, Daniela, Reif, Andreas, Reininghaus, Eva, Repple, Jonathan, Richard-Lepouriel, Hélène, Rietschel, Marcella, Ringwald, Kai, Roberts, Gloria, Rouleau, Guy, Schaupp, Sabrina, Scheftner, William, Schmitt, Simon, Schofield, Peter, Schubert, K Oliver, Schulte, Eva, Schweizer, Barbara, Senner, Fanny, Severino, Giovanni, Sharp, Sally, Slaney, Claire, Smeland, Olav, Sobell, Janet, Squassina, Alessio, Stopkova, Pavla, Strauss, John, Tortorella, Alfonso, Turecki, Gustavo, Twarowska-Hauser, Joanna, Veldic, Marin, Vieta, Eduard, Vincent, John, Xu, Wei, Zai, Clement, Zandi, Peter, Di Florio, Arianna, Smoller, Jordan, Biernacka, Joanna, Mcmahon, Francis, Alda, Martin, Müller-Myhsok, Bertram, Koutsouleris, Nikolaos, Falkai, Peter, Freimer, Nelson, Andlauer, Till, Schulze, Thomas, Ophoff, Roel, Depaulo, J. Raymond, Schubert, K. Oliver, Andlauer, Till F.M., Optimisation thérapeutique en Neuropsychopharmacologie (OPTeN (UMR_S_1144 / U1144)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Hôpital Lariboisière-Fernand-Widal [APHP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), IMRB - 'Neuropsychiatrie translationnelle' [Créteil] (U955 Inserm - UPEC), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Etain, Bruno, Child and Adolescent Psychiatry / Psychology, Psychiatry, Kalman, J. L., Loohuis, L. M. O., Vreeker, A., Mcquillin, A., Stahl, E. A., Ruderfer, D., Grigoroiu-Serbanescu, M., Panagiotaropoulou, G., Ripke, S., Bigdeli, T. B., Stein, F., Meller, T., Meinert, S., Pelin, H., Streit, F., Papiol, S., Adams, M. J., Adolfsson, R., Adorjan, K., Agartz, I., Aminoff, S. R., Anderson-Schmidt, H., Andreassen, O. A., Ardau, R., Aubry, J. -M., Balaban, C., Bass, N., Baune, B. T., Bellivier, F., Benabarre, A., Bengesser, S., Berrettini, W. H., Boks, M. P., Bromet, E. J., Brosch, K., Budde, M., Byerley, W., Cervantes, P., Chillotti, C., Cichon, S., Clark, S. R., Comes, A. L., Corvin, A., Coryell, W., Craddock, N., Craig, D. W., Croarkin, P. E., Cruceanu, C., Czerski, P. M., Dalkner, N., Dannlowski, U., Degenhardt, F., Del Zompo, M., Depaulo, J. R., Djurovic, S., Edenberg, H. J., Al Eissa, M., Elvsashagen, T., Etain, B., Fanous, A. H., Fellendorf, F., Fiorentino, A., Forstner, A. J., Frye, M. A., Fullerton, J. M., Gade, K., Garnham, J., Gershon, E., Gill, M., Goes, F. S., Gordon-Smith, K., Grof, P., Guzman-Parra, J., Hahn, T., Hasler, R., Heilbronner, M., Heilbronner, U., Jamain, S., Jimenez, E., Jones, I., Jones, L., Jonsson, L., Kahn, R. S., Kelsoe, J. R., Kennedy, J. L., Kircher, T., Kirov, G., Kittel-Schneider, S., Klohn-Saghatolislam, F., Knowles, J. A., Kranz, T. M., Lagerberg, T. V., Landen, M., Lawson, W. B., Leboyer, M., Li, Q. S., Maj, M., Malaspina, D., Manchia, M., Mayoral, F., Mcelroy, S. L., Mcinnis, M. G., Mcintosh, A. M., Medeiros, H., Melle, I., Milanova, V., Mitchell, P. B., Monteleone, P., Monteleone, A. M., Nothen, M. M., Novak, T., Nurnberger, J. I., O'Brien, N., O'Connell, K. S., O'Donovan, C., O'Donovan, M. C., Opel, N., Ortiz, A., Owen, M. J., Palsson, E., Pato, C., Pato, M. T., Pawlak, J., Pfarr, J. -K., Pisanu, C., Potash, J. B., Rapaport, M. H., Reich-Erkelenz, D., Reif, A., Reininghaus, E., Repple, J., Richard-Lepouriel, H., Rietschel, M., Ringwald, K., Roberts, G., Rouleau, G., Schaupp, S., Scheftner, W. A., Schmitt, S., Schofield, P. R., Schubert, K. O., Schulte, E. C., Schweizer, B., Senner, F., Severino, G., Sharp, S., Slaney, C., Smeland, O. B., Sobell, J. L., Squassina, A., Stopkova, P., Strauss, J., Tortorella, A., Turecki, G., Twarowska-Hauser, J., Veldic, M., Vieta, E., Vincent, J. B., Xu, W., Zai, C. C., Zandi, P. P., Di Florio, A., Smoller, J. W., Biernacka, J. M., Mcmahon, F. J., Alda, M., Muller-Myhsok, B., Koutsouleris, N., Falkai, P., Freimer, N. B., Andlauer, T. F. M., Schulze, T. G., and Ophoff, R. A.

Subjects
Paper, Multifactorial Inheritance, medicine.medical_specialty, Autism Spectrum Disorder, Bipolar disorder, MESH: Age of Onset, [SDV.MHEP.PSM] Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Medizin, GWAS, age at onset, polarity at onset, polygenic score, MESH: Depressive Disorder, Major, BF, Genome-wide association study, Disease, Psykiatri, SDG 3 - Good Health and Well-being, ddc:150, Polarity at onset, Internal medicine, MESH: Bipolar Disorder, Polygenic score, medicine, Humans, Academic Psychiatry, Age of Onset, Genetic association, Psychiatry, MESH: Autism Spectrum Disorder, Depressive Disorder, Major, MESH: Humans, business.industry, Age at onset, Heritability, medicine.disease, Genetic architecture, ddc, Psychiatry and Mental health, Schizophrenia, Autism spectrum disorder, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, MESH: Genome-Wide Association Study, RC0321, MESH: Multifactorial Inheritance, business, Genome-Wide Association Study
Abstract

BackgroundStudying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.AimsTo examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.MethodGenome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.ResultsEarlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.ConclusionsAAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Published
2021

85. Variations in seasonal solar insolation are associated with a history of suicide attempts in bipolar I disorder

Author

Bauer, Michael, Glenn, Tasha, Achtyes, Eric, Alda, Martin, Agaoglu, Esen, Altınbaş, Kürşat, Andreassen, Ole, Angelopoulos, Elias, Ardau, Raffaella, Vares, Edgar Arrua, Aydin, Memduha, Ayhan, Yavuz, Baethge, Christopher, Bauer, Rita, Baune, Bernhard, Balaban, Ceylan, Becerra-Palars, Claudia, Behere, Aniruddh, Behere, Prakash, Belete, Habte, Belete, Tilahun, Belizario, Gabriel Okawa, Bellivier, Frank, Belmaker, Robert, Benedetti, Francesco, Berk, Michael, Bersudsky, Yuly, Bicakci, Şule, Birabwa-Oketcho, Harriet, Bjella, Thomas, Brady, Conan, Cabrera, Jorge, Cappucciati, Marco, Castro, Angela Marianne Paredes, Chen, Wei-Ling, Cheung, Eric, Chiesa, Silvia, Crowe, Marie, Cuomo, Alessandro, Dallaspezia, Sara, del Zompo, Maria, Desai, Pratikkumar, Dodd, Seetal, Donix, Markus, Etain, Bruno, Fagiolini, Andrea, Fellendorf, Frederike, Ferensztajn-Rochowiak, Ewa, Fiedorowicz, Jess, Fountoulakis, Kostas, Frye, Mark, Geoffroy, Pierre, Gonzalez-Pinto, Ana, Gottlieb, John, Grof, Paul, Haarman, Bartholomeus, Harima, Hirohiko, Hasse-Sousa, Mathias, Henry, Chantal, Høffding, Lone, Houenou, Josselin, Imbesi, Massimiliano, Isometsä, Erkki, Ivkovic, Maja, Janno, Sven, Johnsen, Simon, Kapczinski, Flávio, Karakatsoulis, Gregory, Kardell, Mathias, Kessing, Lars Vedel, Kim, Seong Jae, König, Barbara, Kot, Timur, Koval, Michael, Kunz, Mauricio, Lafer, Beny, Landén, Mikael, Larsen, Erik, Lenger, Melanie, Lewitzka, Ute, Licht, Rasmus, Lopez-Jaramillo, Carlos, Mackenzie, Alan, Madsen, Helle Østergaard, Madsen, Simone Alberte Kongstad A, Mahadevan, Jayant, Mahardika, Agustine, Manchia, Mirko, Marsh, Wendy, Martinez-Cengotitabengoa, Monica, Martiny, Klaus, Mashima, Yuki, Mcloughlin, Declan, Meesters, Ybe, Melle, Ingrid, Meza-Urzúa, Fátima, Ming, Mok Yee, Monteith, Scott, Moorthy, Muthukumaran, Morken, Gunnar, Mosca, Enrica, Mozzhegorov, Anton, Munoz, Rodrigo, Mythri, Starlin, Nacef, Fethi, Nadella, Ravi, Nakanotani, Takako, Nielsen, René Ernst, O'Donovan, Claire, Omrani, Adel, Osher, Yamima, Ouali, Uta, Pantovic-Stefanovic, Maja, Pariwatcharakul, Pornjira, Petite, Joanne, Pfennig, Andrea, Ruiz, Yolanda Pica, Pilhatsch, Maximilian, Pinna, Marco, Pompili, Maurizio, Porter, Richard, Quiroz, Danilo, Rabelo-Da-Ponte, Francisco Diego, Ramesar, Raj, Rasgon, Natalie, Ratta-Apha, Woraphat, Ratzenhofer, Michaela, Redahan, Maria, Reddy, M., Reif, Andreas, Reininghaus, Eva, Richards, Jenny Gringer, Ritter, Philipp, Rybakowski, Janusz, Sathyaputri, Leela, Scippa, Ângela, Simhandl, Christian, Severus, Emanuel, Smith, Daniel, Smith, José, Stackhouse, Paul, Stein, Dan, Stilwell, Kellen, Strejilevich, Sergio, Su, Kuan-Pin, Subramaniam, Mythily, Sulaiman, Ahmad Hatim, Suominen, Kirsi, Tanra, Andi, Tatebayashi, Yoshitaka, Teh, Wen Lin, Tondo, Leonardo, Torrent, Carla, Tuinstra, Daniel, Uchida, Takahito, Vaaler, Arne, Veeh, Julia, Vieta, Eduard, Viswanath, Biju, Yoldi-Negrete, Maria, Yalcinkaya, Oguz Kaan, Young, Allan, Zgueb, Yosra, Whybrow, Peter, Madsen, Simone Alberte Kongstad A., Bauer, M., Glenn, T., Achtyes, E. D., Alda, M., Agaoglu, E., Altinbas, K., Andreassen, O. A., Angelopoulos, E., Ardau, R., Vares, E. A., Aydin, M., Ayhan, Y., Baethge, C., Bauer, R., Baune, B. T., Balaban, C., Becerra-Palars, C., Behere, A. P., Behere, P. B., Belete, H., Belete, T., Belizario, G. O., Bellivier, F., Belmaker, R. H., Benedetti, F., Berk, M., Bersudsky, Y., Bicakci, S., Birabwa-Oketcho, H., Bjella, T. D., Brady, C., Cabrera, J., Cappucciati, M., Castro, A. M. P., Chen, W. -L., Cheung, E. Y. W., Chiesa, S., Crowe, M., Cuomo, A., Dallaspezia, S., Del Zompo, M., Desai, P., Dodd, S., Donix, M., Etain, B., Fagiolini, A., Fellendorf, F. T., Ferensztajn-Rochowiak, E., Fiedorowicz, J. G., Fountoulakis, K. N., Frye, M. A., Geoffroy, P. A., Gonzalez-Pinto, A., Gottlieb, J. F., Grof, P., Haarman, B. C. M., Harima, H., Hasse-Sousa, M., Henry, C., Hoffding, L., Houenou, J., Imbesi, M., Isometsa, E. T., Ivkovic, M., Janno, S., Johnsen, S., Kapczinski, F., Karakatsoulis, G. N., Kardell, M., Kessing, L. V., Kim, S. J., Konig, B., Kot, T. L., Koval, M., Kunz, M., Lafer, B., Landen, M., Larsen, E. R., Lenger, M., Lewitzka, U., Licht, R. W., Lopez-Jaramillo, C., Mackenzie, A., Madsen, H. O., Madsen, S. A. K. A., Mahadevan, J., Mahardika, A., Manchia, M., Marsh, W., Martinez-Cengotitabengoa, M., Martiny, K., Mashima, Y., Mcloughlin, D. M., Meesters, Y., Melle, I., Meza-Urzua, F., Ming, M. Y., Monteith, S., Moorthy, M., Morken, G., Mosca, E., Mozzhegorov, A. A., Munoz, R., Mythri, S. V., Nacef, F., Nadella, R. K., Nakanotani, T., Nielsen, R. E., O'Donovan, C., Omrani, A., Osher, Y., Ouali, U., Pantovic-Stefanovic, M., Pariwatcharakul, P., Petite, J., Pfennig, A., Ruiz, Y. P., Pilhatsch, M., Pinna, M., Pompili, M., Porter, R., Quiroz, D., Rabelo-da-Ponte, F. D., Ramesar, R., Rasgon, N., Ratta-apha, W., Ratzenhofer, M., Redahan, M., Reddy, M. S., Reif, A., Reininghaus, E. Z., Richards, J. G., Ritter, P., Rybakowski, J. K., Sathyaputri, L., Scippa, A. M., Simhandl, C., Severus, E., Smith, D., Smith, J., Stackhouse, P. W., Stein, D. J., Stilwell, K., Strejilevich, S., Su, K. -P., Subramaniam, M., Sulaiman, A. H., Suominen, K., Tanra, A. J., Tatebayashi, Y., Teh, W. L., Tondo, L., Torrent, C., Tuinstra, D., Uchida, T., Vaaler, A. E., Veeh, J., Vieta, E., Viswanath, B., Yoldi-Negrete, M., Yalcinkaya, O. K., Young, A. H., Zgueb, Y., Whybrow, P. C., Etain, Bruno, Optimisation thérapeutique en Neuropsychopharmacologie (OPTeN (UMR_S_1144 / U1144)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Maladies neurodéveloppementales et neurovasculaires (NeuroDiderot (UMR_S_1141 / U1141)), GHU Paris Psychiatrie et Neurosciences, Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Service NEUROSPIN (NEUROSPIN), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Fondation FondaMental [Créteil], Clinical Cognitive Neuropsychiatry Research Program (CCNP), Department of Pathology, and Faculty of Health Sciences

Subjects
Neurophysiology and neuropsychology, Psychiatry, Bipolar disorder, QP351-495, Research, Seasonal variation, [SDV.MHEP.PSM] Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Circadian, Neurosciences. Biological psychiatry. Neuropsychiatry, Solar insolation, Suicide, Sunlight, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, RC321-571
Abstract

Background Bipolar disorder is associated with circadian disruption and a high risk of suicidal behavior. In a previous exploratory study of patients with bipolar I disorder, we found that a history of suicide attempts was associated with differences between winter and summer levels of solar insolation. The purpose of this study was to confirm this finding using international data from 42% more collection sites and 25% more countries. Methods Data analyzed were from 71 prior and new collection sites in 40 countries at a wide range of latitudes. The analysis included 4876 patients with bipolar I disorder, 45% more data than previously analyzed. Of the patients, 1496 (30.7%) had a history of suicide attempt. Solar insolation data, the amount of the sun’s electromagnetic energy striking the surface of the earth, was obtained for each onset location (479 locations in 64 countries). Results This analysis confirmed the results of the exploratory study with the same best model and slightly better statistical significance. There was a significant inverse association between a history of suicide attempts and the ratio of mean winter insolation to mean summer insolation (mean winter insolation/mean summer insolation). This ratio is largest near the equator which has little change in solar insolation over the year, and smallest near the poles where the winter insolation is very small compared to the summer insolation. Other variables in the model associated with an increased risk of suicide attempts were a history of alcohol or substance abuse, female gender, and younger birth cohort. The winter/summer insolation ratio was also replaced with the ratio of minimum mean monthly insolation to the maximum mean monthly insolation to accommodate insolation patterns in the tropics, and nearly identical results were found. All estimated coefficients were significant at p

Published
2021

86. Glycine Signaling in the Framework of Dopamine-Glutamate Interaction and Postsynaptic Density. Implications for Treatment-Resistant Schizophrenia

Author

Licia Vellucci, Felice Iasevoli, Andrea de Bartolomeis, Mirko Manchia, Annarita Barone, Federica Marmo, de Bartolomeis, A., Manchia, M., Marmo, F., Vellucci, L., Iasevoli, F., and Barone, A.

Subjects
Bitopertin, glycine transporter 1, lcsh:RC435-571, glutamate, Review, Reuptake, 03 medical and health sciences, Glutamatergic, 0302 clinical medicine, lcsh:Psychiatry, Glycine receptor, PSD-95, Psychiatry, biology, Chemistry, antipsychotic, 030227 psychiatry, Psychiatry and Mental health, antipsychotics, Homer, disk-1, Glycine transporter 1, Glycine, biology.protein, NMDA receptor, Glutamatergic synapse, dopamine, Neuroscience, 030217 neurology & neurosurgery, N-methyl-d-aspartate
Abstract

Treatment-resistant schizophrenia (TRS) or suboptimal response to antipsychotics affects almost 30% of schizophrenia (SCZ) patients, and it is a relevant clinical issue with significant impact on the functional outcome and on the global burden of disease. Among putative novel treatments, glycine-centered therapeutics (i.e. sarcosine, glycine itself, D-Serine, and bitopertin) have been proposed, based on a strong preclinical rationale with, however, mixed clinical results. Therefore, a better appraisal of glycine interaction with the other major players of SCZ pathophysiology and specifically in the framework of dopamine – glutamate interactions is warranted. New methodological approaches at cutting edge of technology and drug discovery have been applied to study the role of glycine in glutamate signaling, both at presynaptic and post-synaptic level and have been instrumental for unveiling the role of glycine in dopamine-glutamate interaction. Glycine is a non-essential amino acid that plays a critical role in both inhibitory and excitatory neurotransmission. In caudal areas of central nervous system (CNS), such as spinal cord and brainstem, glycine acts as a powerful inhibitory neurotransmitter through binding to its receptor, i.e. the Glycine Receptor (GlyR). However, glycine also works as a co-agonist of the N-Methyl-D-Aspartate receptor (NMDAR) in excitatory glutamatergic neurotransmission. Glycine concentration in the synaptic cleft is finely tuned by glycine transporters, i.e. GlyT1 and GlyT2, that regulate the neurotransmitter's reuptake, with the first considered a highly potential target for psychosis therapy. Reciprocal regulation of dopamine and glycine in forebrain, glycine modulation of glutamate, glycine signaling interaction with postsynaptic density proteins at glutamatergic synapse, and human genetics of glycinergic pathways in SCZ are tackled in order to highlight the exploitation of this neurotransmitters and related molecules in SCZ and TRS.

Published
2020

87. Investigating the relationship between melatonin levels, melatonin system, microbiota composition and bipolar disorder psychopathology across the different phases of the disease

Author

Beatrice Guiso, Vittoria Pulcinelli, Federica Pinna, Mirko Manchia, Donatella Congiu, Alessio Squassina, Claudia Pisanu, Pasquale Paribello, Stefano Comai, Mario Garzilli, Bernardo Carpiniello, Federico Suprani, Flavia Valtorta, Maria Novella Iaselli, Manchia, M., Squassina, A., Pisanu, C., Congiu, D., Garzilli, M., Guiso, B., Suprani, F., Paribello, P., Pulcinelli, V., Iaselli, M. N., Pinna, F., Valtorta, F., Carpiniello, B., and Comai, S.

Subjects
Oncology, medicine.medical_specialty, Study Protocols, Bipolar disorder, Disease, Impulsivity, lcsh:RC321-571, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Observational study, medicine, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Biological Psychiatry, Melatonin, business.industry, Genetic variability, Microbiota, lcsh:QP351-495, medicine.disease, 030227 psychiatry, Psychiatry and Mental health, Hypomania, Mood, lcsh:Neurophysiology and neuropsychology, Psychopharmacology, medicine.symptom, business, Mania, 030217 neurology & neurosurgery, Psychopathology
Abstract

Background Bipolar disorder (BD) is characterized by recurrent episodes of depression and mania/hypomania alternating with intervals of well-being. The neurobiological underpinnings of BD are still veiled although there is evidence pointing to a malfunction of the circadian clock system that is regulated by the neuromodulator melatonin (MLT). Small sample size studies in BD patients have shown that changes in the levels of MLT are associated with shifts in illness status. Moreover, mood stabilizers (including lithium and valproic acid) influence the MLT system. Of interest, MLT also modulates intestinal microbiota, and recent work suggests an important role of microbiota alterations in neuropsychiatric disorders, including BD. This study is designed to explore whether the possible patterns of associations between changes in the levels of MLT and its precursors and BD mood phases are modulated by variants within the genes encoding for the elements of the MLT system and/or by the microbiota composition. Methods We will conduct a 2-year follow-up study in 50 BD patients during the three different mood phases of the disease. For each phase, we will perform a blood withdrawal for the analysis of MLT levels and of variants of the genes related to the MLT pathway between 8 and 10 a.m. after an overnight fasting, a stool specimen collection for the analysis of microbiota composition, and a detailed psychometric assessment for depression, mania, impulsivity and cognitive abilities. We will also recruit 50 healthy age-matched controls in whom we will perform a blood withdrawal between 8 and 10 a.m. after an overnight fasting, a stool specimen collection, and a psychometric assessment to exclude the presence of psychiatric disorders. Discussion In this cross sectional (case–control vs. BD comparisons) and longitudinal (24 months) study, we expect to clarify the link between the MLT system, microbiota and BD psychopathology. We expect to identify some typical BD symptomatic clusters that will be more strictly associated with variations in the MLT system. In a personalized medicine perspective, this subgroup of BD patients may benefit from a pharmacological therapy targeting the MLT system. Trial registration This study protocol was approved by the Ethics Committee of the University Hospital Agency of Cagliari (PG/2019/6277)

Published
2019

88. Eating disorders: What age at onset?

Author

Palmiero Monteleone, Alfonso Tortorella, Alessio Maria Monteleone, Mirko Manchia, Umberto Volpe, Umberto Albert, Volpe, Umberto, Tortorella, Alfonso, Manchia, Mirko, Monteleone Alessio, M., Albert, Umberto, Monteleone, Palmiero, Tortorella, A, Manchia, M, Monteleone, Am, Albert, U, Monteleone, P., Volpe Umberto, Tortorella Alfonso, Manchia Mirko, Monteleone Alessio M., Albert Umberto, and Monteleone Palmiero

Subjects
Age at onset, Eating disorders, Prognosis, Adolescent, Adult, Age of Onset, Anorexia Nervosa, Bulimia Nervosa, Feeding and Eating Disorders, Female, Humans, Male, Young Adult, Psychiatry and Mental Health, Biological Psychiatry, 050103 clinical psychology, Pediatrics, medicine.medical_specialty, Prognosi, 03 medical and health sciences, 0302 clinical medicine, Clinical history, medicine, Feeding and Eating Disorder, 0501 psychology and cognitive sciences, Young adult, Early onset, Bulimia nervosa, 05 social sciences, Eating disorder, medicine.disease, 030227 psychiatry, Psychiatry and Mental health, Anorexia nervosa (differential diagnoses), Age of onset, Biological psychiatry, Psychology, Clinical psychology, Human
Abstract

Age at onset (AAO) of eating disorders has classically been described in adolescence. We analyzed data from 806 subjects with anorexia nervosa (AN) or bulimia nervosa (BN) and performed a normal distribution admixture analysis to determine their AAO. No significant differences were found concerning the AAO functions of AN and BN subjects. Both groups had a mean AAO of about 18 years. Most of the subjects with AN (753%) and BN (83.3%) belonged to the early onset group. The definition of AAO for ED may be crucial for planning treatment modalities, with specific consideration of their clinical history and course. (C) 2016 Elsevier Ireland Ltd. All rights reserved.

Published
2016

89. Clinical correlates of age at onset distribution in bipolar disorder: a comparison between diagnostic subgroups

Author

Alfonso Tortorella, Luca Steardo, Giuseppe Maina, Virginio Salvi, Bernardo Carpiniello, Martin Alda, Mirko Manchia, Umberto Albert, Virginia D'Ambrosio, Manchia, M., Maina, G., Carpiniello, B., Steardo, L., D’Ambrosio, V., Salvi, V., Alda, M., Tortorella, A., and Albert, U.

Subjects
Pharmacology, medicine.medical_specialty, Pediatrics, Bipolar disorder, age at onset, business.industry, medicine.disease, Bipolar disorder, age at onset, Psychiatry and Mental health, Neurology, medicine, Distribution (pharmacology), Pharmacology (medical), Neurology (clinical), Psychiatry, business, Biological Psychiatry
Abstract

Bipolar disorder (BD) is a heritable psychiatric illness typically characterized by cyclic mood episodes of opposite polarity al- ternating with intervals of well-being. As in other psychiatric complex genetic diseases, the relatively high clinical heterogeneity of BD might have hindered the identification of molecular and clinical determinants of risk as well as of predictors of treatment outcome. The magnitude of heterogeneity might be modifiable by studying subgroups of BD patients sharing specific clinical char- acteristics such as, for instance, patterns of treatment response, mood incongruent psychosis or early illness onset. Indeed, the extensive analysis of age at onset (AAO) BD subgroups through admixture analysis has shown clinical and genetic characteristics specific, particularly, to early onset (EO) BD. As the vast majority of studies investigated BD type 1 (BD1) samples, it remains to be established, however, whether this clinical delineation of EO is present also in BD type 2 (BD2) patients. Furthermore, the distributional properties of AAO have never been investigated in sample exclusively comprised of BD2 patients. This study aims to test whether bipolar disorder type 1 (BD1) and bipolar disorder type 2 (BD2) differed in terms of age at onset (AAO) distributions and whether early onset (EO) BD patients had clinical characteristics specific for each diagnostic-subgroup. We studied 515 BD patients (279 BD1 and 224 BD2 and 12 BDNOS) diagnosed according to DSM-IV criteria. AAO was defined as the first reliably diagnosed hypo/manic or depressive episode according to diagnostic criteria. We used normal distribution mixture analysis to test whether we could identify subgroups of patients according to the AAO. We investigated a range of number of AAO groups (1 to 9). The choice of the mixture model that best fit the distribution of AAO was made according to the Schwarz’s Bayesian information criteria (BIC). Specifically, the analysis performed with the “Mclust” package implemented in R indicates the best model as the one with the highest BIC among the fitted models. Cut off points were derived using the theoretical AAO function and calculating each data point’s probability of belonging to each class. Clinical correlates of early onset were analyzed using univariate analysis (t-test or contingency tables as appropriate). Multivariate logistic regression analysis was used to account for intercorrelations. A two normal components model best fitted the observed distribution of AAO in BD1 (BIC = −1599.3), BD2 (BIC = −2158.4), and in the whole sample (BIC = −3854.9). Early onset (EO) BD1 had a lower age at interview and a longer duration of illness than late onset (LO) BD1. Early onset BD2 had also a lower age at interview and longer illness duration than LO BD2, as well as higher rate of comorbidity with alcohol dependence. A higher number of EO BD2 presented with a DMI course, whilst a higher rate of MDI course was found in EO BD1. We showed the presence of similar, bimodal, AAO distributions in BD1 and BD2, confirming however significant differences in terms of clinical characteristics of the different onset subgroups

Published
2016

90. Assessment of Response to Lithium Maintenance Treatment in Bipolar Disorder: A Consortium on Lithium Genetics (ConLiGen) Report

Author

J. Raymond DePaulo, Martin Alda, Alfonso Tortorella, Susan G. Leckband, Jean-Michel Aubry, James B. Potash, Clara Brichant-Petitjean, Layla Kassem, Joanna Hauser, Tomas Novak, David Zilles, Claire O'Donovan, Rebecca Hoban, Sarah Kittel-Schneider, Claire Slaney, Lena Backlund, Peter Falkai, Andrew T. A. Cheng, John R. Kelsoe, Andrea Pfennig, Janice M. Fullerton, Marcella Rietschel, Caterina Chillotti, Stéphane Jamain, Elise Bui, Po-Hsiu Kuo, Alessio Squassina, Claudio E. M. Banzato, Joanna M. Biernacka, Lisa R. Seymour, Naomi R. Wray, Ichiro Kusumi, Thomas Stamm, Fernando S. Goes, Audrey Nallet, Sarah K. Tighe, Giovanni Severino, Jean-Pierre Kahn, Maria Neuner, Nirmala Akula, Norio Ozaki, Francis J. McMahon, Frank Bellivier, Andreas Reif, Ryota Hashimoto, Barbara W. Schweizer, Palmiero Monteleone, Florian Seemüller, Urs Heilbronner, Sevilla D. Detera-Wadleigh, Pavla Stopkova, Martin Schalling, Julie Garnham, Sébastien Gard, Mark A. Frye, Eva Z. Reininghaus, Lina Martinsson, Urban Ösby, Maria Grigoroiu-Serbanescu, Sara Richardson, Tadafumi Kato, Marion Leboyer, Catharina Lavebratt, Piotr M. Czerski, Scott R. Clark, Daniela Reich-Erkelenz, Sebastian Kliwicki, Guy A. Rouleau, Oliver Gruber, Gonzalo Laje, Adam Wright, Gustavo Turecki, Roy H. Perlis, Takuya Masui, Mirko Manchia, Bernhard T. Baune, Mazda Adli, Michael Bauer, Sven Cichon, Frank Mondimore, Bruno Etain, Philip B. Mitchell, Thomas G. Schulze, Peter P. Zandi, Raffaella Ardau, Peter R. Schofield, Susanne Bengesser, Liping Hou, Janusz K. Rybakowski, Mario Maj, Clarissa de Rosalmeida Dantas, Louise Frisén, O. Schubert, Carlos Jaramillo, Maria Del Zompo, Paul Grof, Cynthia V. Calkin, Jo Steele, Jordan W. Smoller, Alain Malafosse, Manchia, M, Adli, M, Akula, N, Ardau, R, Aubry, Jm, Backlund, L, Banzato, Ce, Baune, Bt, Bellivier, F, Bengesser, S, Biernacka, Jm, Brichant Petitjean, C, Bui, E, Calkin, Cv, Cheng, At, Chillotti, C, Cichon, S, Clark, S, Czerski, Pm, Dantas, C, Zompo, Md, Depaulo, Jr, Detera Wadleigh, Sd, Etain, B, Falkai, P, Frisén, L, Frye, Ma, Fullerton, J, Gard, S, Garnham, J, Goes, F, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Heilbronner, U, Hoban, R, Hou, L, Jamain, S, Kahn, Jp, Kassem, L, Kato, T, Kelsoe, Jr, Kittel Schneider, S, Kliwicki, S, Kuo, Ph, Kusumi, I, Laje, G, Lavebratt, C, Leboyer, M, Leckband, Sg, López Jaramillo, Ca, Maj, Mario, Malafosse, A, Martinsson, L, Masui, T, Mitchell, Pb, Mondimore, F, Monteleone, P, Nallet, A, Neuner, M, Novák, T, O'Donovan, C, Osby, U, Ozaki, N, Perlis, Rh, Pfennig, A, Potash, Jb, Reich Erkelenz, D, Reif, A, Reininghaus, E, Richardson, S, Rouleau, Ga, Rybakowski, Jk, Schalling, M, Schofield, Pr, Schubert, Ok, Schweizer, B, Seemüller, F, Grigoroiu Serbanescu, M, Severino, G, Seymour, Lr, Slaney, C, Smoller, Jw, Squassina, A, Stamm, T, Steele, J, Stopkova, P, Tighe, Sk, Tortorella, Alfonso Antonio Vincenzo, Turecki, G, Wray, Nr, Wright, A, Zandi, Pp, Zilles, D, Bauer, M, Rietschel, M, Mcmahon, Fj, Schulze, Tg, Alda, M., Department of Psychiatry, Dalhousie University [Halifax], Department of Psychiatry and Psychotherapy, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Human Genetics Branch, National Institutes of Health [Bethesda] (NIH)-National Institute of Mental Health (NIMH), Unit of Clinical Pharmacology, University-Hospital of Cagliari, Department of Mental Health and Psychiatry, University Hospital of Geneva, Trinity College Dublin-St. James's Hospital, University of Campinas [Campinas] (UNICAMP), University of Adelaide, Pôle de Psychiatrie, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Groupe Hospitalier Saint Louis - Lariboisière - Fernand Widal [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Medical University Graz, Mayo Clinic, Division of Epidemiology and Genetics, Academia Sinica-Institute of Biomedical Sciences (ICB/USP), Universidade de São Paulo (USP)-Universidade de São Paulo (USP), Department of Genomics, Life and Brain Center, University of Bonn, Psychiatric Genetic Unit, Poznan University of Medical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-IFR10, University of Homburg, Genetics of Mental Illness and Brain Function, Neuroscience Research Australia, Service de psychiatrie adulte, Université Bordeaux Segalen - Bordeaux 2-Hôpital Charles Perrens-Centre Expert Trouble Bipolaire, Mood Disorders Center of Ottawa (MDCO), University of Ottawa [Ottawa], University of Toronto, Georg-August-University [Göttingen], Osaka University Graduate School of Medicine, University of California [San Diego] (UC San Diego), University of California-University of California, Service de Psychiatrie et Psychologie Clinique, Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Hôpital Jeanne-d'Arc, Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Center for Brain Science [Wako] (RIKEN CBS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN)-RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), Mental Health Sciences Unit, University College of London [London] (UCL), Department of Adult Psychiatry, Institute of Epidemiology and Preventive Medicine, National Taiwan University [Taiwan] (NTU), Hokkaido University Graduate School of Medicine, Molecular Medicine and Surgery department, Karolinska Institutet [Stockholm], Center for Molecular Medicine, Karolinska University Hospital [Stockholm], Department of Pharmacy, Veterans Affairs San Diego Healthcare System, Skaggs School of Pharmacy and Pharmaceutical Sciences [San Diego], University of Antioquia, University of Napoli, School of Psychiatry, University of New South Wales [Sydney] (UNSW)-Black Dog Institute, Prague Psychiatric Center, University of Prague, Fujita Health University School of Medicine, Nagoya University Graduate School of Medicine, Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], Technische Universität Dresden = Dresden University of Technology (TU Dresden), University of Iowa [Iowa City], Center of Excellence in Neuroscience, CHU de Montréal, Department of Medicine, Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CR CHUM), Centre Hospitalier de l'Université de Montréal (CHUM), Université de Montréal (UdeM)-Université de Montréal (UdeM)-Centre Hospitalier de l'Université de Montréal (CHUM), Université de Montréal (UdeM)-Université de Montréal (UdeM), Biometric Psychiatric Genetics Research Unit, Alexandru Obregia Psychiatric Hospital, McGill Group for Suicide Studies, Douglas Mental Health University Institute, Queensland Brain Institute, University of Queensland [Brisbane], Department of Mental Health, Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU)-Johns Hopkins University (JHU), Department of Genetic Epidemiology in Psychiatry [Mannhein], Universität Heidelberg [Heidelberg]-Central Institute of Mental Health Mannheim, The work on assessment of lithium response has been supported by a grant from Canadian Institutes of Health Research #64410 to MA. MG-S was supported by Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii (UEFISCDI), Bucharest, Romania (grant no. 89/2012). JMA and AN were supported by a grant from the Swiss National Foundation (#32003B_125469/1 to JM Aubry). ConLiGen is in part supported by funds from the Intramural Research Program of the National Institute of Mental Health (NIMH) at the National Institutes of Health (NIH), Department of Health and Human Services, United States Government, Aubry, Jean-Michel, Universidade Estadual de Campinas = University of Campinas (UNICAMP), Universidade de São Paulo = University of São Paulo (USP)-Universidade de São Paulo = University of São Paulo (USP), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Georg-August-University = Georg-August-Universität Göttingen, University of California (UC)-University of California (UC), Guellaen, Georges, Université Bordeaux Segalen - Bordeaux 2-Centre hospitalier Charles Perrens [Bordeaux]-Centre Expert Trouble Bipolaire, and Ikeda, Kazutaka

Subjects
Male, Bipolar Disorder, Lithium (medication), Psychometrics, Psychopharmacology, Epidemiology, International Cooperation, lcsh:Medicine, Lithium, Maintenance Treatment, ConLiGen, ddc:616.89, 0302 clinical medicine, Antimanic Agents, Psychology, lcsh:Science, Reliability (statistics), Psychiatry, Genetics, 0303 health sciences, Multidisciplinary, ASSOCIATION, Genomics, Pharmacoepidemiology, 3. Good health, Mental Health, Phenotype, Treatment Outcome, MAPPING SUSCEPTIBILITY GENES, Behavioral Pharmacology, RELIABILITY, Lithium Compounds, Medicine, Female, Research Article, medicine.drug, Drugs and Devices, MAPPING SUSCEPTIBILITY GENES, PROPHYLACTIC LITHIUM, OBSERVER AGREEMENT, MOOD DISORDERS, ONSET, ASSOCIATION, RELIABILITY, MORTALITY, ILLNESS, AGE, ILLNESS, PROPHYLACTIC LITHIUM, 03 medical and health sciences, AGE, Neuropharmacology, Genomic Medicine, [SDV.BBM] Life Sciences [q-bio]/Biochemistry, Molecular Biology, Genome-Wide Association Studies, medicine, Humans, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, Bipolar disorder, ddc:610, Biology, 030304 developmental biology, Mood Disorders, business.industry, MORTALITY, lcsh:R, Computational Biology, Reproducibility of Results, Models, Theoretical, medicine.disease, OBSERVER AGREEMENT, Mood disorders, Pharmacogenetics, Therapies, ONSET, lcsh:Q, Pharmacogenomics, business, 030217 neurology & neurosurgery, Kappa
Abstract

Objective: The assessment of response to lithium maintenance treatment in bipolar disorder (BD) is complicated by variable length of treatment, unpredictable clinical course, and often inconsistent compliance. Prospective and retrospective methods of assessment of lithium response have been proposed in the literature. In this study we report the key phenotypic measures of the "Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder" scale currently used in the Consortium on Lithium Genetics (ConLiGen) study. Materials and Methods: Twenty-nine ConLiGen sites took part in a two-stage case-vignette rating procedure to examine inter-rater agreement [Kappa (\(\kappa\))] and reliability [intra-class correlation coefficient (ICC)] of lithium response. Annotated first-round vignettes and rating guidelines were circulated to expert research clinicians for training purposes between the two stages. Further, we analyzed the distributional properties of the treatment response scores available for 1,308 patients using mixture modeling. Results: Substantial and moderate agreement was shown across sites in the first and second sets of vignettes (\(\kappa\) = 0.66 and \(\kappa\) = 0.54, respectively), without significant improvement from training. However, definition of response using the A score as a quantitative trait and selecting cases with B criteria of 4 or less showed an improvement between the two stages (\(ICC_1 = 0.71\) and \(ICC_2 = 0.75\), respectively). Mixture modeling of score distribution indicated three subpopulations (full responders, partial responders, non responders). Conclusions: We identified two definitions of lithium response, one dichotomous and the other continuous, with moderate to substantial inter-rater agreement and reliability. Accurate phenotypic measurement of lithium response is crucial for the ongoing ConLiGen pharmacogenomic study.

Published
2013

91. Effects of antipsychotic treatment on cardio-cerebrovascular related mortality in schizophrenia: A subanalysis of a systematic review and meta-analysis with meta-regression of moderators.

Author

Solmi M, Croatto G, Gupta A, Fabiano N, Wong S, Fornaro M, Schneider LK, Rohani-Montez SC, Fairley L, Smith N, Bitter I, Gorwood P, Taipale H, Tiihonen J, Cortese S, Dragioti E, Rietz ED, Nielsen RE, Firth J, Fusar-Poli P, Hartman C, Holt RIG, Høye A, Koyanagi A, Larsson H, Lehto K, Lindgren P, Manchia M, Nordentoft M, Skonieczna-Żydecka K, Stubbs B, Vancampfort D, De Prisco M, Boyer L, Vieta E, and Correll CU

Subjects
Humans, Schizophrenia drug therapy, Schizophrenia mortality, Antipsychotic Agents therapeutic use, Cerebrovascular Disorders mortality, Cardiovascular Diseases mortality
Abstract

To further explore the role of different antipsychotic treatments for cardio-cerebrovascular mortality, we performed several subgroup, sensitivity and meta-regression analyses based on a large previous meta-analysis focusing on cohort studies assessing mortality relative risk (RR) for cardio-cerebrovascular disorders in people with schizophrenia, comparing antipsychotic treatment versus no antipsychotic. Quality assessment through the Newcastle-Ottawa Scale (NOS) and publication bias was measured. We meta-analyzed 53 different studies (schizophrenia patients: n = 2,513,359; controls: n = 360,504,484) to highlight the differential effects of antipsychotic treatment regimens on cardio-cerebrovascular-related mortality in incident and prevalent samples of patients with schizophrenia. We found first generation antipsychotics (FGA) to be associated with higher mortality in incident samples of schizophrenia (oral FGA [RR=2.20, 95 %CI=1.29-3.77, k = 1] and any FGA [RR=1.70, 95 %CI=1.20-2.41, k = 1]). Conversely, second generation antipsychotics (SGAs) and clozapine were associated with reduced cardio-cerebrovascular-related mortality, in prevalent samples of schizophrenia. Subgroup analyses with NOS score ≥7 (higher quality) demonstrated a significantly increased cardio-cerebrovascular disorder-related mortality, among those exposed to FGAs vs SGAs. Meta-regression analyses demonstrated a larger association between antipsychotics and decreased risk of mortality with longer follow-up, recent study year, and higher number of adjustment variables. Overall, this subanalysis of a systematic review contributes to the evolving understanding of the complex role of antipsychotic treatment for cardio-cerebrovascular mortality in schizophrenia, paving the way for more targeted interventions and improved patient outcomes., Competing Interests: Declaration of competing interest MS received honoraria/has been a consultant for AbbVie, Angelini, Lundbeck, Otsuka. IB received consulting fees from Gedeon Richter and Janssen/Janssen-Cilag; speaker's honoraria from Gedeon Richter, Hikma Pharmaceuticals, Janssen/Janssen-Cilag, KRKA, Lundbeck and Medichem Pharmaceuticals Inc. by Unilab; received research grant from Gedeon Richter; royalties from Oxford University Press. JT has participated in research projects funded by grants from Janssen-Cilag to his employing institution; he has been a consultant to HLS Therapeutics, Janssen, Orion, Teva, and WebMed Global and received lecture fees from Janssen, Lundbeck and Otsuka. PG received during the last 5 years fees for presentations at congresses or participation in scientific boards from Biogen, Janssen, Lundbeck, Merk, Otsuka, Richter and Viatris. R.E.N. has, within the past 3 years, been an investigator for Compass Pharmaceuticals, Janssen-Cilag, Sage and Boehringer-Ingelheim for clinical trials; has received speaking fees from Lundbeck, Teva Pharmaceuticals, Janssen-Cilag and Otsuka Pharmaceuticals; and has acted as advisor to Lundbeck and Janssen-Cilag. JF is supported by a UK Research and Innovation Future Leaders Fellowship (MR/T021780/1) and has received honoraria / consultancy fees from Atheneum, Informa, Gillian Kenny Associates, Bayer, Big Health, Hedonia, Strive Coaching, Wood For Trees, Nutritional Medicine Institute, Angelini, ParachuteBH, Richmond Foundation and Nirakara, independent of this work. RIGH has received fees for lecturing from EASD, Eli Lilly, Encore, Liberum, Novo Nordisk, ROVI and funding for conference attendance from Novo Nordisk and Eli Lilly. HT has participated in research projects funded by grants from Janssen-Cilag to her employing institution; and she has received lecture fees from Gedeon Richter, Janssen, Lundbeck and Otsuka. MF received honoraria for his speaker activity from the American Society of Clinical Psychopharmacology (ASCP) and served as a consultant for Angelini, Otsuka, Lundbeck, Sanofi-Aventis, and Boehringer Ingelheim. BS is on the Editorial Board of Ageing Research Reviews, Mental Health and Physical Activity, The Journal of Evidence Based Medicine, and The Brazilian Journal of Psychiatry. Brendon has received honorarium from a co-edited book on exercise and mental illness (Elsevier), and unrelated advisory work from ASICS, in addition to honorarium and stock options at FitXR LTD. HL reports receiving grants from Shire Pharmaceuticals; personal fees from and serving as a speaker for Medice, Shire/Takeda Pharmaceuticals and Evolan Pharma AB; all outside the submitted work. Henrik Larsson is editor-in-chief of JCPP Advances. CUC has been a consultant and/or advisor to or has received honoraria from: AbbVie, Acadia, Adock Ingram, Alkermes, Allergan, Angelini, Aristo, Biogen, Boehringer-Ingelheim, Bristol-Meyers Squibb, Cardio Diagnostics, Cerevel, CNX Therapeutics, Compass Pathways, Darnitsa, Delpor, Denovo, Gedeon Richter, Hikma, Holmusk, IntraCellular Therapies, Jamjoom Pharma, Janssen/J&J, Karuna, LB Pharma, Lundbeck, MedInCell, Merck, Mindpax, Mitsubishi Tanabe Pharma, Maplight, Mylan, Neumora Therapeutics, Neurocrine, Neurelis, Newron, Noven, Novo Nordisk, Otsuka, PPD Biotech, Recordati, Relmada, Reviva, Rovi, Sage, Seqirus, SK Life Science, Sumitomo Pharma America, Sunovion, Sun Pharma, Supernus, Tabuk, Takeda, Teva, Tolmar, Vertex, Viatris and Xenon Pharmaceuticals. He provided expert testimony for Janssen and Otsuka. He served on a Data Safety Monitoring Board for Compass Pathways, Denovo, Lundbeck, Relmada, Reviva, Rovi, Supernus, and Teva. He has received grant support from Janssen and Takeda. He received royalties from UpToDate and is also a stock option holder of Cardio Diagnostics, Kuleon Biosciences, LB Pharma, Mindpax, and Quantic. PL reports institutional grants from AstraZeneca, Biogen, Jansen, MSD and Novartis. EV has received grants and served as consultant, advisor or CME speaker for the following entities: AB-Biotics, AbbVie, Adamed, Angelini, Biogen, Beckley-Psytech, Biohaven, Boehringer-Ingelheim, Celon Pharma, Compass, Dainippon Sumitomo Pharma, Ethypharm, Ferrer, Gedeon Richter, GH Research, Glaxo-Smith Kline, HMNC, Idorsia, Johnson & Johnson, Lundbeck, Luye Pharma, Medincell, Merck, Newron, Novartis, Orion Corporation, Organon, Otsuka, Roche, Rovi, Sage, Sanofi-Aventis, Sunovion, Takeda, Teva, and Viatris, outside the submitted work., (Copyright © 2024. Published by Elsevier B.V.)

Published
2024
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92. Refining criteria for a neurodevelopmental sub-phenotype of bipolar disorders: a FondaMental Advanced Centers of Expertise for Bipolar Disorders study.

Author

Lefrere A, Godin O, Jamain S, Dansou Y, Samalin L, Alda M, Aouizerate B, Aubin V, Rey R, Contu M, Courtet P, Dubertret C, Haffen E, Januel D, Leboyer M, Llorca PM, Marlinge E, Manchia M, Neilson S, Olié E, Paribello P, Pinna M, Polosan M, Roux P, Schwan R, Tondo L, Walter M, Tzavara E, Auzias G, Deruelle C, Etain B, and Belzeaux R

Abstract

Background: Bipolar disorder (BD) is a complex and heterogeneous psychiatric disorder. Neurodevelopmental factors were suggested to contribute to the etiology of BD, yet a specific neurodevelopmental phenotype of the disorder remains unidentified. Our objective was to define and characterize a neurodevelopmental phenotype (NDP) in BD and validate its associations with clinical outcomes, polygenic risk scores (PGS), and treatment responses., Method: We analyzed the FACE-BD cohort of 4,468 BD patients, a validation cohort of 101 BD patients, and two independent replication datasets of 274 and 89 BD patients. Using factor analyses, we identified a set of criteria for defining NDP. We next developed a scoring system for NDP-load and assessed its association with prognosis, neurological soft signs, polygenic risk scores for neurodevelopmental disorders, and responses to treatment using multiple regressions, adjusted for age and sex with bootstrap replications., Results: Our study established a NDP in BD consisting of nine clinical features: advanced paternal age, advanced maternal age, childhood maltreatment, attention deficit hyperactivity disorder (ADHD), early onset of BD, early onset of substance use disorders, early onset of anxiety disorders, early onset of eating disorders, specific learning disorders. Patients with higher NDP-load showed a worse prognosis and increased neurological soft signs. Notably, these individuals exhibited a poorer response to lithium treatment. Furthermore, a significant positive correlation was observed between the NDP-load and PGS for ADHD suggesting potential overlapping genetic factors or pathophysiological mechanisms between BD and ADHD., Conclusions: The proposed NDP constitutes a promising clinical tool for patient stratification in BD., (Copyright © 2024. Published by Elsevier Inc.)

Published
2024
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93. Risk factors, prevention and treatment of weight gain associated with the use of antidepressants and antipsychotics: a state-of-the-art clinical review.

Author

Solmi M, Miola A, Capone F, Pallottino S, Højlund M, Firth J, Siskind D, Holt RIG, Corbeil O, Cortese S, Dragioti E, Du Rietz E, Nielsen RE, Nordentoft M, Fusar-Poli P, Hartman CA, Høye A, Koyanagi A, Larsson H, Lehto K, Lindgren P, Manchia M, Skonieczna-Żydecka K, Stubbs B, Vancampfort D, Vieta E, Taipale H, and Correll CU

Subjects
Humans, Risk Factors, Mental Disorders drug therapy, Life Style, Antipsychotic Agents adverse effects, Antipsychotic Agents administration & dosage, Weight Gain drug effects, Antidepressive Agents adverse effects, Antidepressive Agents administration & dosage, Obesity chemically induced
Abstract

Introduction: People with severe mental illness have poor cardiometabolic health. Commonly used antidepressants and antipsychotics frequently lead to weight gain, which may further contribute to adverse cardiovascular outcomes., Areas Covered: We searched MEDLINE up to April 2023 for umbrella reviews, (network-)meta-analyses, trials and cohort studies on risk factors, prevention and treatment strategies of weight gain associated with antidepressants/antipsychotics. We developed 10 clinical recommendations., Expert Opinion: To prevent, manage, and treat antidepressant/antipsychotic-related weight gain, we recommend i) assessing risk factors for obesity before treatment, ii) monitoring metabolic health at baseline and regularly during follow-up, iii) offering lifestyle interventions including regular exercise and healthy diet based on patient preference to optimize motivation, iv) considering first-line psychotherapy for mild-moderate depression and anxiety disorders, v)choosing medications based on medications' and patient's weight gain risk, vi) choosing medications based on acute vs long-term treatment, vii) using effective, tolerated medications, viii) switching to less weight-inducing antipsychotics/antidepressants where possible, ix) using early weight gain as a predictor of further weight gain to inform the timing of intervention/switch options, and x) considering adding metformin or glucagon-like peptide-1 receptor agonists, or topiramate(second-line due to potential adverse cognitive effects) to antipsychotics, or aripiprazole to clozapine or olanzapine.

Published
2024
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94. Sex differences in shared genetic determinants between severe mental disorders and metabolic traits.

Author

Pisanu C, Congiu D, Meloni A, Paribello P, Severino G, Ardau R, Chillotti C, Als TD, Børglum AD, Del Zompo M, Manchia M, and Squassina A

Abstract

High rates of metabolic risk factors contribute to premature mortality in patients with severe mental disorders, but the molecular underpinnings of this association are largely unknown. We performed the first analysis on shared genetic factors between severe mental disorders and metabolic traits considering the effect of sex. We applied an integrated analytical pipeline on the largest sex-stratified genome-wide association datasets available for bipolar disorder (BD), major depressive disorder (MDD), schizophrenia (SZ), and for body mass index (BMI) and waist-to-hip ratio (WHR) (all including participants of European origin). We observed extensive genetic overlap between all severe mental disorders and variants associated with BMI in women or men and identified several genetic loci shared between BD, or SZ and BMI in women (24 and 91, respectively) or men (13 and 208, respectively), with mixed directions of effect. A large part of the identified genetic variants showed sex differences in terms of location, genes modulated in adipose tissue and/or brain regions, and druggable targets. By providing a complete picture of disorder specific and cross-disorder shared genetic determinants, our results highlight potential sex differences in the genetic liability to metabolic comorbidities in patients with severe mental disorders., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Published
2024
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95. The role of affective temperaments in self-care and medication adherence among individuals with bipolar disorder: a moderation analysis.

Author

Visalli G, Longobardi G, Iazzolino AM, D'Angelo M, Stefano VD, Paribello P, Steardo L, Manchia M, and Steardo L Jr

Abstract

Background: Affective temperament, defined as the fundamental predisposition from which normal affective states originate or as the constitutional core of personality, play a crucial role in mood disorders, particularly bipolar disorders. Understanding the relationship between temperaments, treatment adherence, and self-care is crucial for effective management and improved clinical results., Objectives: This study aims to (1) assess the correlation between affective temperaments and treatment adherence, (2) investigate the relationship between affective temperaments and self-care abilities, (3) identify predictors of treatment adherence, and (4) explore the moderating effect of self-care on the relationship between treatment adherence and depressive temperament in individuals with bipolar disorder., Methods: A cross-sectional study was conducted with 231 individuals diagnosed with bipolar disorder (BD) type I (N=160) and type II (N=71). The participants were evaluated using the following psychometric tools: Temperament Evaluation of Memphis, Pisa, and San Diego (TEMPS) to assess affective temperaments, Personal and Social Performance Scale (PSP) to evaluate social functioning and self-care abilities, and Morisky Medication Adherence Scale (MMAS) to measure treatment adherence. The study involved statistical analyses to examine correlations, identify predictors, and explore moderating effects., Results: The findings revealed significant correlations between affective temperaments and both treatment adherence and self-care abilities. Specifically, hyperthymic temperament was positively associated with higher treatment adherence, whereas cyclothymic and depressive temperaments were linked to lower adherence. Self-care abilities were found to mediate the relationship between depressive temperament and treatment adherence, suggesting that improved self-care can enhance adherence in individuals with depressive temperament., Conclusions: Affective temperaments significantly influence treatment adherence and self-care abilities in individuals with bipolar disorder. The mediating role of self-care highlights the importance of developing targeted interventions to improve self-care practices, thereby enhancing treatment adherence and overall well-being. Personalized treatment strategies based on temperament assessments could lead to better clinical outcomes and quality of life for individuals with bipolar disorder., 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. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Visalli, Longobardi, Iazzolino, D’Angelo, Stefano, Paribello, Steardo, Manchia and Steardo.)

Published
2024
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96. Lower Plasma Levels of Selective VGF (Non-Acronymic) Peptides in Bipolar Disorder: Comparative Analysis Reveals Distinct Patterns across Mood Disorders and Healthy Controls.

Author

Cocco C, Noli B, Manconi B, Contini C, Manca E, Pisanu C, Meloni A, Manchia M, Paribello P, Chillotti C, Ardau R, Severino G, and Squassina A

Abstract

Introduction: Discriminating bipolar disorder (BD) from major depressive disorder (MDD) remains a challenging clinical task. Identifying specific peripheral biosignatures that can differentiate between BD and MDD would significantly increase diagnostic accuracy. Dysregulated neuroplasticity is implicated in BD and MDD, and psychotropic medications restore specific disrupted processes by increasing neurotrophic signalling. The nerve growth factor inducible vgf gene (non-acronymic) encodes a precursor protein named proVGF, which undergoes proteolytic processing to produce several VGF peptides, some of which were suggested to be implicated in mood disorders and have antidepressant effects. Since the presence of VGF peptides in humans has been exclusively investigated in brain and cerebrospinal fluid, we aimed to identify which VGF peptides are present in the plasma and to investigate whether their levels could differentiate BD from MDD as well as responders from non-responders to pharmacological interventions., Methods: VGF peptides were investigated in plasma from patients diagnosed with MDD (n = 37) or BD (n = 40 under lithium plus n = 29 never exposed to lithium), as well as healthy controls (HC; n = 36)., Results: Three VGF peptides (TLQP-11, AQEE-14, and NAPP-19) were identified using spectrometry analysis of plasma from HC. These peptides were then measured in the entire sample using ELISA, which showed significantly lower levels of AQEE and NAPP in BD than in HC and MDD (p = 5.0 × 10-5, p = 0.001, respectively)., Conclusion: Our findings suggest that lower plasma levels of NAPP and AQEE are specifically associated with BD, thus possibly representing a diagnostic biomarker in mood disorders., (© 2024 The Author(s). Published by S. Karger AG, Basel.)

Published
2024
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97. Leukocyte Telomere Length and Mitochondrial DNA Copy Number in Treatment-Resistant Depression and Response to Electroconvulsive Therapy: A Pilot Longitudinal Study.

Author

Squassina A, Pisanu C, Menesello V, Meloni A, Congiu D, Manchia M, Paribello P, Abate M, Bortolomasi M, Baune BT, Gennarelli M, and Minelli A

Abstract

Objectives: In this study, we investigated if changes in leukocyte telomere length (LTL) and mitochondrial DNA copy number (mtDNA-cn), 2 markers of cellular aging, are associated with treatment-resistant depression (TRD) and with response to electroconvulsive therapy (ECT)., Methods: LTL and mtDNA-cn were measured in 31 TRD patients before (T0), 1 week (T1), and 4 weeks (T2) after the ECT course, as well as in a sample of 65 healthy controls., Results: TRD patients had significantly shorter LTL and higher mtDNA-cn compared with healthy controls at baseline. In the TRD sample, LTL was inversely correlated with Montgomery-Åsberg Depression Rating Scale scores at baseline. Baseline levels of LTL or mtDNA-cn were not correlated with response to ECT. Similarly, changes in LTL or mtDNA-cn were not associated with response to ECT either when considered as a dichotomous trait (responders vs nonresponders) or as a percentage change in symptoms improvements., Conclusions: Ours is the first longitudinal study exploring the role of LTL and mtDNA-cn in response to ECT. Findings of this pilot investigation suggest that LTL and mtDNA-cn may constitute disease biomarkers for TRD but are not involved in response to ECT., Competing Interests: The authors have no conflicts of interest or financial disclosures to report., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Published
2024
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98. Phenotypic clustering of bipolar disorder supports stratification by lithium responsiveness over diagnostic subtypes.

Author

Scott K, O'Donovan C, Brancati GE, Cervantes P, Ardau R, Manchia M, Severino G, Rybakowski J, Tondo L, Grof P, Alda M, and Nunes A

Subjects
Humans, Male, Female, Adult, Middle Aged, Cluster Analysis, Antimanic Agents therapeutic use, Antimanic Agents pharmacology, Bipolar Disorder drug therapy, Bipolar Disorder classification, Bipolar Disorder diagnosis, Phenotype, Lithium Compounds pharmacology, Lithium Compounds therapeutic use
Abstract

Introduction: The aim of this study was to determine whether the clinical profiles of bipolar disorder (BD) patients could be differentiated more clearly using the existing classification by diagnostic subtype or by lithium treatment responsiveness., Methods: We included adult patients with BD-I or II (N = 477 across four sites) who were treated with lithium as their principal mood stabilizer for at least 1 year. Treatment responsiveness was defined using the dichotomized Alda score. We performed hierarchical clustering on phenotypes defined by 40 features, covering demographics, clinical course, family history, suicide behaviour, and comorbid conditions. We then measured the amount of information that inferred clusters carried about (A) BD subtype and (B) lithium responsiveness using adjusted mutual information (AMI) scores. Detailed phenotypic profiles across clusters were then evaluated with univariate comparisons., Results: Two clusters were identified (n = 56 and n = 421), which captured significantly more information about lithium responsiveness (AMI range: 0.033 to 0.133) than BD subtype (AMI: 0.004 to 0.011). The smaller cluster had disproportionately more lithium responders (n = 47 [83.8%]) when compared to the larger cluster (103 [24.4%]; p = 0.006)., Conclusions: Phenotypes derived from detailed clinical data may carry more information about lithium responsiveness than the current classification of diagnostic subtype. These findings support lithium responsiveness as a valid approach to stratification in clinical samples., (© 2024 The Authors. Acta Psychiatrica Scandinavica published by John Wiley & Sons Ltd.)

Published
2024
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99. A Secondary Analysis of the Complex Interplay between Psychopathology, Cognitive Functions, Brain Derived Neurotrophic Factor Levels, and Suicide in Psychotic Disorders: Data from a 2-Year Longitudinal Study.

Author

Paribello P, Manchia M, Isayeva U, Upali M, Orrù D, Pinna F, Collu R, Primavera D, Deriu L, Caboni E, Iaselli MN, Sundas D, Tusconi M, Scherma M, Pisanu C, Meloni A, Zai CC, Congiu D, Squassina A, Fratta W, Fadda P, and Carpiniello B

Subjects
Humans, Male, Female, Adult, Longitudinal Studies, Middle Aged, Suicidal Ideation, Schizophrenia blood, Schizophrenia metabolism, Suicide, Attempted psychology, Suicide psychology, Biomarkers blood, Psychopathology, Brain-Derived Neurotrophic Factor blood, Psychotic Disorders blood, Psychotic Disorders psychology, Psychotic Disorders metabolism, Cognition
Abstract

Identifying phenotypes at high risk of suicidal behaviour is a relevant objective of clinical and translational research and can facilitate the identification of possible candidate biomarkers. We probed the potential association and eventual stability of neuropsychological profiles and serum BDNF concentrations with lifetime suicide ideation and attempts (LSI and LSA, respectively) in individuals with schizophrenia (SCZ) and schizoaffective disorder (SCA) in a 2-year follow-up study. A secondary analysis was conducted on a convenience sample of previously recruited subjects from a single outpatient clinic. Retrospectively assessed LSI and LSA were recorded by analysing the available longitudinal clinical health records. LSI + LSA subjects consistently exhibited lower PANSS-defined negative symptoms and better performance in the BACS-letter fluency subtask. There was no significant association between BDNF levels and either LSI or LSA. We found a relatively stable pattern of lower negative symptoms over two years among patients with LSI and LSA. No significant difference in serum BDNF concentrations was detected. The translational viability of using neuropsychological profiles as a possible avenue for the identification of populations at risk for suicide behaviours rather than the categorical diagnosis represents a promising option but requires further confirmation.

Published
2024
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100. Lithium and its effects: does dose matter?

Author

Manchia M, Paribello P, Pinna M, Steardo L Jr, Carpiniello B, Pinna F, Pisanu C, Squassina A, and Hajek T

Abstract

Background: Decades of clinical research have demonstrated the efficacy of lithium in treating acute episodes (both manic and depressive), as well as in preventing recurrences of bipolar disorder (BD). Specific to lithium is its antisuicidal effect, which appears to extend beyond its mood-stabilizing properties. Lithium's clinical effectiveness is, to some extent, counterbalanced by its safety and tolerability profile. Indeed, monitoring of lithium levels is required by its narrow therapeutic index. There is consensus that adequate serum levels should be above 0.6 mEq/L to achieve clinical effectiveness. However, few data support the choice of this threshold, and increasing evidence suggests that lithium might have clinical and molecular effects at much lower concentrations., Content: This narrative review is aimed at: (1) reviewing and critically interpreting the clinical evidence supporting the use of the 0.6 mEq/L threshold, (2) reporting a narrative synthesis of the evidence supporting the notion that lithium might be effective in much lower doses. Among these are epidemiological studies of lithium in water, evidence on the antisuicidal, anti-aggressive, and neuroprotective effects, including efficacy in preventing cognitive impairment progression, Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS), of lithium; and (3) revieweing biological data supporting clinically viable uses of lithium at low levels with the delineation of a mechanistic hypothesis surrounding its purported mechanism of action. The study selection was based on the authors' preference, reflecting the varied and extensive expertise on the review subject, further enriched with an extensive pearl-growing strategy for relevant reviews and book sections., Conclusions: Clinical and molecular effects of lithium are numerous, and its effects also appear to have a certain degree of specificity related to the dose administered. In sum, the clinical effects of lithium are maximal for mood stabilisation at concentrations higher than 0.6 mEq/l. However, lower levels may be sufficient for preventing depressive recurrences in older populations of patients, and microdoses could be effective in decreasing suicide risk, especially in patients with BD. Conversely, lithium's ability to counteract cognitive decline appears to be exerted at subtherapeutic doses, possibly corresponding to its molecular neuroprotective effects. Indeed, lithium may reduce inflammation and induce neuroprotection even at doses several folds lower than those commonly used in clinical settings. Nevertheless, findings surrounding its purported mechanism of action are missing, and more research is needed to investigate the molecular targets of low-dose lithium adequately., (© 2024. The Author(s).)

Published
2024
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