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

Author: Hibar, DP, Westlye, LT, Doan, NT, Jahanshad, N, Cheung, JW, Ching, CRK, Versace, A, Bilderbeck, AC, Uhlmann, A, Mwangi, B, Krämer, B, Overs, B, Hartberg, CB, Abé, C, Dima, D, Grotegerd, D, Sprooten, E, Bøen, E, Jimenez, E, Howells, FM, Delvecchio, G, Temmingh, H, Starke, J, Almeida, JRC, Goikolea, JM, Houenou, J, Beard, LM, Rauer, L, Abramovic, L, Bonnin, M, Ponteduro, MF, Keil, M, Rive, MM, Yao, N, Yalin, N, Najt, P, Rosa, PG, Redlich, R, Trost, S, Hagenaars, S, Fears, SC, Alonso-Lana, S, van Erp, TGM, Nickson, T, Chaim-Avancini, TM, Meier, TB, Elvsåshagen, T, Haukvik, UK, Lee, WH, Schene, AH, Lloyd, AJ, Young, AH, Nugent, A, Dale, AM, Pfennig, A, McIntosh, AM, Lafer, B, Baune, BT, Ekman, CJ, Zarate, CA, Bearden, CE, Henry, C, Simhandl, C, McDonald, C, Bourne, C, Stein, DJ, Wolf, DH, Cannon, DM, Glahn, DC, Veltman, DJ, Pomarol-Clotet, E, Vieta, E, Canales-Rodriguez, EJ, Nery, FG, Duran, FLS, Busatto, GF, Roberts, G, Pearlson, GD, Goodwin, GM, Kugel, H, Whalley, HC, Ruhe, HG, Soares, JC, Fullerton, JM, Rybakowski, JK, Savitz, J, Chaim, KT, Fatjó-Vilas, M, Soeiro-de-Souza, MG, Boks, MP, Zanetti, MV, Otaduy, MCG, Schaufelberger, MS, Alda, M, Ingvar, M, Phillips, ML, Kempton, MJ, Bauer, M, Landén, M, and Lawrence, NS
Subjects: Brain, Cerebral Cortex, Frontal Lobe, Prefrontal Cortex, Temporal Lobe, Humans, Magnetic Resonance Imaging, Case-Control Studies, Bipolar Disorder, Psychotic Disorders, Age Factors, Sex Factors, Adolescent, Adult, Middle Aged, Female, Male, Young Adult, Neuroimaging, Gray Matter, Clinical Research, Serious Mental Illness, Biomedical Imaging, Brain Disorders, Mental Health, Neurosciences, 2.1 Biological and endogenous factors, Aetiology, Mental health, Neurological, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract: Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 × 10-21), left fusiform gyrus (d=-0.288; P=8.25 × 10-21) and left rostral middle frontal cortex (d=-0.276; P=2.99 × 10-19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.
Published: 2018

2. Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group

Author: Schmaal, L, Hibar, DP, Sämann, PG, Hall, GB, Baune, BT, Jahanshad, N, Cheung, JW, van Erp, TGM, Bos, D, Ikram, MA, Vernooij, MW, Niessen, WJ, Tiemeier, H, Hofman, A, Wittfeld, K, Grabe, HJ, Janowitz, D, Bülow, R, Selonke, M, Völzke, H, Grotegerd, D, Dannlowski, U, Arolt, V, Opel, N, Heindel, W, Kugel, H, Hoehn, D, Czisch, M, Couvy-Duchesne, B, Rentería, ME, Strike, LT, Wright, MJ, Mills, NT, de Zubicaray, GI, McMahon, KL, Medland, SE, Martin, NG, Gillespie, NA, Goya-Maldonado, R, Gruber, O, Krämer, B, Hatton, SN, Lagopoulos, J, Hickie, IB, Frodl, T, Carballedo, A, Frey, EM, van Velzen, LS, Penninx, BWJH, van Tol, M-J, van der Wee, NJ, Davey, CG, Harrison, BJ, Mwangi, B, Cao, B, Soares, JC, Veer, IM, Walter, H, Schoepf, D, Zurowski, B, Konrad, C, Schramm, E, Normann, C, Schnell, K, Sacchet, MD, Gotlib, IH, MacQueen, GM, Godlewska, BR, Nickson, T, McIntosh, AM, Papmeyer, M, Whalley, HC, Hall, J, Sussmann, JE, Li, M, Walter, M, Aftanas, L, Brack, I, Bokhan, NA, Thompson, PM, and Veltman, DJ
Subjects: Biological Psychology, Biomedical and Clinical Sciences, Clinical Sciences, Psychology, Major Depressive Disorder, Serious Mental Illness, Neurosciences, Biomedical Imaging, Depression, Basic Behavioral and Social Science, Mental Health, Brain Disorders, Clinical Research, Pediatric, Behavioral and Social Science, 2.3 Psychological, social and economic factors, Aetiology, 2.1 Biological and endogenous factors, Neurological, Mental health, Adolescent, Adult, Brain, Cerebral Cortex, Depressive Disorder, Major, Female, Frontal Lobe, Gray Matter, Gyrus Cinguli, Humans, Magnetic Resonance Imaging, Male, Neuroimaging, Prefrontal Cortex, Temporal Lobe, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract: The neuro-anatomical substrates of major depressive disorder (MDD) are still not well understood, despite many neuroimaging studies over the past few decades. Here we present the largest ever worldwide study by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Major Depressive Disorder Working Group on cortical structural alterations in MDD. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2148 MDD patients and 7957 healthy controls were analysed with harmonized protocols at 20 sites around the world. To detect consistent effects of MDD and its modulators on cortical thickness and surface area estimates derived from MRI, statistical effects from sites were meta-analysed separately for adults and adolescents. Adults with MDD had thinner cortical gray matter than controls in the orbitofrontal cortex (OFC), anterior and posterior cingulate, insula and temporal lobes (Cohen's d effect sizes: -0.10 to -0.14). These effects were most pronounced in first episode and adult-onset patients (>21 years). Compared to matched controls, adolescents with MDD had lower total surface area (but no differences in cortical thickness) and regional reductions in frontal regions (medial OFC and superior frontal gyrus) and primary and higher-order visual, somatosensory and motor areas (d: -0.26 to -0.57). The strongest effects were found in recurrent adolescent patients. This highly powered global effort to identify consistent brain abnormalities showed widespread cortical alterations in MDD patients as compared to controls and suggests that MDD may impact brain structure in a highly dynamic way, with different patterns of alterations at different stages of life.
Published: 2017

3. Subcortical volumetric abnormalities in bipolar disorder.

Author: Hibar, DP, Westlye, LT, van Erp, TGM, Rasmussen, J, Leonardo, CD, Faskowitz, J, Haukvik, UK, Hartberg, CB, Doan, NT, Agartz, I, Dale, AM, Gruber, O, Krämer, B, Trost, S, Liberg, B, Abé, C, Ekman, CJ, Ingvar, M, Landén, M, Fears, SC, Freimer, NB, Bearden, CE, Costa Rica/Colombia Consortium for Genetic Investigation of Bipolar Endophenotypes, Sprooten, E, Glahn, DC, Pearlson, GD, Emsell, L, Kenney, J, Scanlon, C, McDonald, C, Cannon, DM, Almeida, J, Versace, A, Caseras, X, Lawrence, NS, Phillips, ML, Dima, D, Delvecchio, G, Frangou, S, Satterthwaite, TD, Wolf, D, Houenou, J, Henry, C, Malt, UF, Bøen, E, Elvsåshagen, T, Young, AH, Lloyd, AJ, Goodwin, GM, Mackay, CE, Bourne, C, Bilderbeck, A, Abramovic, L, Boks, MP, van Haren, NEM, Ophoff, RA, Kahn, RS, Bauer, M, Pfennig, A, Alda, M, Hajek, T, Mwangi, B, Soares, JC, Nickson, T, Dimitrova, R, Sussmann, JE, Hagenaars, S, Whalley, HC, McIntosh, AM, Thompson, PM, and Andreassen, OA
Subjects: Costa Rica/Colombia Consortium for Genetic Investigation of Bipolar Endophenotypes, Brain, Humans, Magnetic Resonance Imaging, Organ Size, Case-Control Studies, Retrospective Studies, Bipolar Disorder, Adult, Middle Aged, Female, Male, Clinical Research, Mental Health, Brain Disorders, Serious Mental Illness, Neurosciences, Aetiology, 2.1 Biological and endogenous factors, Mental health, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract: Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case-control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen's d=-0.232; P=3.50 × 10-7) and thalamus (d=-0.148; P=4.27 × 10-3) and enlarged lateral ventricles (d=-0.260; P=3.93 × 10-5) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons.
Published: 2016

4. Hippocampal subfield volumes in mood disorders

Author: Cao, B, Passos, I C, Mwangi, B, Amaral-Silva, H, Tannous, J, Wu, M-J, Zunta-Soares, G B, and Soares, J C
Published: 2017
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5. Structural brain alterations associated with suicidal thoughts and behaviors in young people: results from 21 international studies from the ENIGMA Suicidal Thoughts and Behaviours consortium

Author: van Velzen, LS, Dauvermann, MR, Colic, L, Villa, LM, Savage, HS, Toenders, YJ, Zhu, AH, Bright, JK, Campos, A, Salminen, LE, Ambrogi, S, Ayesa-Arriola, R, Banaj, N, Basgoze, Z, Bauer, J, Blair, K, Blair, RJ, Brosch, K, Cheng, Y, Colle, R, Connolly, CG, Corruble, E, Couvy-Duchesne, B, Crespo-Facorro, B, Cullen, KR, Dannlowski, U, Davey, CG, Dohm, K, Fullerton, JM, Gonul, AS, Gotlib, IH, Grotegerd, D, Hahn, T, Harrison, BJ, He, M, Hickie, IB, Ho, TC, Iorfino, F, Jansen, A, Jollant, F, Kircher, T, Klimes-Dougan, B, Klug, M, Leehr, EJ, Lippard, ETC, McLaughlin, KA, Meinert, S, Miller, AB, Mitchell, PB, Mwangi, B, Nenadic, I, Ojha, A, Overs, BJ, Pfarr, J-K, Piras, F, Ringwald, KG, Roberts, G, Romer, G, Sanches, M, Sheridan, MA, Soares, JC, Spalletta, G, Stein, F, Teresi, G, Tordesillas-Gutierrez, D, Uyar-Demir, A, van der Wee, NJA, van der Werff, SJ, Vermeiren, RRJM, Winter, A, Wu, M-J, Yang, TT, Thompson, PM, Renteria, ME, Jahanshad, N, Blumberg, HP, Van Harmelen, A-L, Schmaal, L, van Velzen, LS, Dauvermann, MR, Colic, L, Villa, LM, Savage, HS, Toenders, YJ, Zhu, AH, Bright, JK, Campos, A, Salminen, LE, Ambrogi, S, Ayesa-Arriola, R, Banaj, N, Basgoze, Z, Bauer, J, Blair, K, Blair, RJ, Brosch, K, Cheng, Y, Colle, R, Connolly, CG, Corruble, E, Couvy-Duchesne, B, Crespo-Facorro, B, Cullen, KR, Dannlowski, U, Davey, CG, Dohm, K, Fullerton, JM, Gonul, AS, Gotlib, IH, Grotegerd, D, Hahn, T, Harrison, BJ, He, M, Hickie, IB, Ho, TC, Iorfino, F, Jansen, A, Jollant, F, Kircher, T, Klimes-Dougan, B, Klug, M, Leehr, EJ, Lippard, ETC, McLaughlin, KA, Meinert, S, Miller, AB, Mitchell, PB, Mwangi, B, Nenadic, I, Ojha, A, Overs, BJ, Pfarr, J-K, Piras, F, Ringwald, KG, Roberts, G, Romer, G, Sanches, M, Sheridan, MA, Soares, JC, Spalletta, G, Stein, F, Teresi, G, Tordesillas-Gutierrez, D, Uyar-Demir, A, van der Wee, NJA, van der Werff, SJ, Vermeiren, RRJM, Winter, A, Wu, M-J, Yang, TT, Thompson, PM, Renteria, ME, Jahanshad, N, Blumberg, HP, Van Harmelen, A-L, and Schmaal, L
Abstract: Identifying brain alterations associated with suicidal thoughts and behaviors (STBs) in young people is critical to understanding their development and improving early intervention and prevention. The ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium analyzed neuroimaging data harmonized across sites to examine brain morphology associated with STBs in youth. We performed analyses in three separate stages, in samples ranging from most to least homogeneous in terms of suicide assessment instrument and mental disorder. First, in a sample of 577 young people with mood disorders, in which STBs were assessed with the Columbia Suicide Severity Rating Scale (C-SSRS). Second, in a sample of young people with mood disorders, in which STB were assessed using different instruments, MRI metrics were compared among healthy controls without STBs (HC; N = 519), clinical controls with a mood disorder but without STBs (CC; N = 246) and young people with current suicidal ideation (N = 223). In separate analyses, MRI metrics were compared among HCs (N = 253), CCs (N = 217), and suicide attempters (N = 64). Third, in a larger transdiagnostic sample with various assessment instruments (HC = 606; CC = 419; Ideation = 289; HC = 253; CC = 432; Attempt=91). In the homogeneous C-SSRS sample, surface area of the frontal pole was lower in young people with mood disorders and a history of actual suicide attempts (N = 163) than those without a lifetime suicide attempt (N = 323; FDR-p = 0.035, Cohen's d = 0.34). No associations with suicidal ideation were found. When examining more heterogeneous samples, we did not observe significant associations. Lower frontal pole surface area may represent a vulnerability for a (non-interrupted and non-aborted) suicide attempt; however, more research is needed to understand the nature of its relationship to suicide risk.
Published: 2022

6. The Role of Educational Attainment and Brain Morphology in Major Depressive Disorder: Findings From the ENIGMA Major Depressive Disorder Consortium

Author: Whittle, S, Rakesh, D, Schmaal, L, Veltman, DJ, Thompson, PM, Singh, A, Gonul, AS, Aleman, A, Demir, AU, Krug, A, Mwangi, B, Kramer, B, Baune, BT, Stein, DJ, Grotegerd, D, Pomarol-Clotet, E, Rodriguez-Cano, E, Melloni, E, Benedetti, F, Stein, F, Grabe, HJ, Volzke, H, Gotlib, IH, Nenadic, I, Soares, JC, Repple, J, Sim, K, Brosch, K, Wittfeld, K, Berger, K, Hermesdorf, M, Portella, MJ, Sacchet, MD, Wu, M-J, Opel, N, Groenewold, NA, Gruber, O, Fuentes-Claramonte, P, Salvador, R, Goya-Maldonado, R, Sarro, S, Poletti, S, Meinert, SL, Kircher, T, Dannlowski, U, Pozzi, E, Whittle, S, Rakesh, D, Schmaal, L, Veltman, DJ, Thompson, PM, Singh, A, Gonul, AS, Aleman, A, Demir, AU, Krug, A, Mwangi, B, Kramer, B, Baune, BT, Stein, DJ, Grotegerd, D, Pomarol-Clotet, E, Rodriguez-Cano, E, Melloni, E, Benedetti, F, Stein, F, Grabe, HJ, Volzke, H, Gotlib, IH, Nenadic, I, Soares, JC, Repple, J, Sim, K, Brosch, K, Wittfeld, K, Berger, K, Hermesdorf, M, Portella, MJ, Sacchet, MD, Wu, M-J, Opel, N, Groenewold, NA, Gruber, O, Fuentes-Claramonte, P, Salvador, R, Goya-Maldonado, R, Sarro, S, Poletti, S, Meinert, SL, Kircher, T, Dannlowski, U, and Pozzi, E
Abstract: Brain structural abnormalities and low educational attainment are consistently associated with major depressive disorder (MDD), yet there has been little research investigating the complex interaction of these factors. Brain structural alterations may represent a vulnerability or differential susceptibility marker, and in the context of low educational attainment, predict MDD. We tested this moderation model in a large multisite sample of 1958 adults with MDD and 2921 controls (aged 18 to 86) from the ENIGMA MDD working group. Using generalized linear mixed models and within-sample split-half replication, we tested whether brain structure interacted with educational attainment to predict MDD status. Analyses revealed that cortical thickness in a number of occipital, parietal, and frontal regions significantly interacted with education to predict MDD. For the majority of regions, models suggested a differential susceptibility effect, whereby thicker cortex was more likely to predict MDD in individuals with low educational attainment, but less likely to predict MDD in individuals with high educational attainment. Findings suggest that greater thickness of brain regions subserving visuomotor and social-cognitive functions confers susceptibility to MDD, dependent on level of educational attainment. Longitudinal work, however, is ultimately needed to establish whether cortical thickness represents a preexisting susceptibility marker. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Published: 2022

7. Everyday adaptation practices by coffee farmers in three mountain regions in Africa

Author: Cuni-Sanchez, A., Twinomuhangi, I., Aneseyee, A.B., Mwangi, B., Olaka, L., Bitariho, R., Soromessa, T., Zafra-Calvo, N., Cuni-Sanchez, A., Twinomuhangi, I., Aneseyee, A.B., Mwangi, B., Olaka, L., Bitariho, R., Soromessa, T., and Zafra-Calvo, N.
Abstract: Mountain environments in East Africa experience more rapid increases in temperature than lower elevations, which, together with changing rainfall patterns, often negatively affect coffee production. However, little is known about the adaptation strategies used by smallholder coffee farmers in Africa. Using the lens of everyday adaptation, semi-structured interviews were carried out with 450 smallholder farmers living near the Bale Mountains in Ethiopia (n = 150), Mount Kenya in Kenya (n = 150), and Kigezi Highlands in Uganda (n = 150). We report similarities in adaptation strategies used (e.g., increased use of improved seeds, inputs, soil-conservation techniques) but also differences across and within regions (e.g., irrigation, coffee-farming abandonment), related to different biophysical, economic, and sociocultural factors. In all regions, access to land, funds, and limited mutual-learning opportunities between farmers and other agents of change constrained further adaptation options. Local people have capacity and means to determine how best they can adapt to climate change, and government agencies and NGOs could implement more participatory engagement with smallholder coffee farmers, attuned to the opportunities and constraints in everyday life to facilitate adaptation to predicted changes in climate.
Published: 2022

8. Identification of Ralstonia solanacearum resistant rootstocks for tomato grafting

Author: Mbaka Jesca, Kanyua Stella, and Mwangi B. Maina
Subjects: 0106 biological sciences, 0301 basic medicine, Ralstonia solanacearum, fungi, food and beverages, Biology, biology.organism_classification, 01 natural sciences, 03 medical and health sciences, Horticulture, 030104 developmental biology, Tomato grafting, Identification (biology), Rootstock, 010606 plant biology & botany
Abstract: Bacterial wilt, caused by Ralstonia solanacearum, causes severe losses to tomato (Solanum lycopersicum L). Current management measures are not fully effective. Grafting with resistant rootstocks may be an effective strategy for managing the disease. However, R. solanacearum populations maintain considerable diversity, and little information is known regarding the efficacy of available rootstocks for use in grafting to reduce bacterial wilt incidence and subsequent crop loss. Tomato belongs to family Solanaceae which includes other well-known species, such as eggplant (aubergine), peppers, tobacco and potato. The objective of this study was to identify bacterial wilt resistant germplasm that can be used as rootstocks in tomato grafting. The potential candidates for the study included species that belong to solanaceae family. Rootstocks included tomato cultivar Mt56, Eggplant (Solanum melongena), Capsicum and Sodom apple (Solanum incarnum). Tomato cultivars Anna F1 and Cal J were used as sources of scions. Diseased plants were collected from farmers’ fields and bacterial inoculum isolated using CPG Medium with TZC used to identify distinct colonies of R.solanacearum. The inoculum was applied on the test plants by injecting into the soil planted with tomatoes. Disease severity data was recorded using 0 to 5 scoring scale. Data was subjected to ANOVA using Genstat version 15 and significantly different treatment means separated using LSD at P < 0.05. Solanum melongena, Solanum incarnum and tomato cultivar (Mt56) did not develop infection while tomato cultivar Anna F1 and Cal J (used as positive controls) and Capsicum developed infection. It was concluded that resistant germplasm to bacterial wilt exists and can be utilized to graft susceptible tomato cultivars and contribute to management of bacterial wilt.
Published: 2020

9. Concurrent antiepileptic and antipsychotic use moderates lithium’s effects on regional brain volumes: a mega-analysis from the ENIGMA-Bipolar Disorder Working Group

Author: King, S., Tronchin, G., Nabulsi, L., Thomopoulos, S.I., Fontana, E., Radua, J., Sim, K., Gruber, O., Yatham, L., Dannlowski, U., Kircher, T., Nenadic, I., Stein, F., Brosch, K., Howells, F., Haarman, B.C.M., Pomarol-Clotet, E., Vieta, E., Landen, M., Cannon, D., Alnæs, D., Westlye, L.T., Jaramillo, C. López, Soeiro-de-Souza, M. Gerhardt, Berk, M., Elvsåshagen, T., Roberts, G., Mitchell, P.B., Fullerton, J.M., Green, M.J., Quidé, Y., Hermesdorf, M., Berger, K., Soares, J., Satterthwaite, T., Savitz, J., Benedetti, F., Glahn, D., Hajek, T., Kuplicki, R., Gotlib, I.H., Amoretti, S., Sacchet, M., Favre, P., Van Rheenen, T., Karantonis, J. Anthony, Furlong, L., Forte, F., Rossell, S., Goldstein, B., Kennedy, K., Canales-Rodriguez, E., Lahud, E., Mwangi, B., Rodriguez-Cano, E., Salvador, R., Wu, M.-J., Houenou, J., Rodrigue, A., Melloni, E.M.T., Sponheim, S., Urosevic, S., Demro, C., Goya-Maldonado, R., Eyler, L., Thompson, P.M., Andreassan, O.A., Ching, C.R.K., and McDonald, C.
Published: 2022
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10. The efficacy of smartphone-based interventions in bipolar disorder: systematic-review and meta-analyses. A position paper from the ISBD Big Data Task-Force

Author: Anmella, G., Hidalgo-Mazzei, D., Faurhoilt-Jepsen, M., Passos, I., Ballester, P., Kapczinski, F., Mwangi, B., Birmaher, B., Brietzke, E., Hajek, T., Lopez-Jaramillo, C., Mansur, R., Alda, M., Haarman, B., Isometsa, E., Lam, R., McIntyre, R., Minuzzi, L., Yatham, L., Duffy, A., Hafeman, D., Goldstein, T., Meier, S., Kessing, L., Vieta, E., and Clinical Cognitive Neuropsychiatry Research Program (CCNP)
Subjects: MENTAL-HEALTH INTERVENTIONS, SYMPTOMS, METAANALYSIS
Published: 2021

11. P.0092 The efficacy of smartphone-based interventions in bipolar disorder: systematic-review and meta-analyses. A position paper from the ISBD Big Data Task-Force

Author: Anmella, G., primary, Hidalgo-Mazzei, D., additional, Faurhoilt-Jepsen, M., additional, Passos, I., additional, Ballester, P., additional, Kapczinski, F., additional, Mwangi, B., additional, Birmaher, B., additional, Brietzke, E., additional, Hajek, T., additional, Lopez-Jaramillo, C., additional, Mansur, R., additional, Alda, M., additional, Haarman, B., additional, Isometsa, E., additional, Lam, R., additional, McIntyre, R., additional, Minuzzi, L., additional, Yatham, L., additional, Duffy, A., additional, Hafeman, D., additional, Goldstein, T., additional, Meier, S., additional, Kessing, L., additional, and Vieta, E., additional
Published: 2021
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12. Predictive classification of individual magnetic resonance imaging scans from children and adolescents

Author: Johnston, B. A., Mwangi, B., Matthews, K., Coghill, D., and Steele, J. D.
Published: 2013
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13. Multi-Site Meta-Analysis of Morphometry

Author: Jahanshad, N, Faskowitz, J, Roshchupkin, Gennady, Hibar, DP, Gutman, B A, Tustison, NJ, Adams, Hieab, Niessen, Wiro, Vernooij, Meike, Ikram, Arfan, Zwiers, MP, Vasquez, AA, Franke, B, Kroll, JL, Mwangi, B, Soares, JC, Ing, A, Desrivieres, S, Schumann, G, Hansell, NK, de Zubicaray, GI, McMahon, KL, Martin, NG, Wright, MJ, Thompson, PM, Alzheimer's Dis Neuroimaging, I, Epidemiology, Medical Informatics, Radiology & Nuclear Medicine, and Neurology
Subjects: Adult, Male, Databases, Factual, Imaging genetics, Computer science, 0206 medical engineering, Big data, Neuroimaging, Genome-wide association study, Genomics, 02 engineering and technology, computer.software_genre, Polymorphism, Single Nucleotide, Article, 150 000 MR Techniques in Brain Function, Young Adult, All institutes and research themes of the Radboud University Medical Center, Meta-Analysis as Topic, Alzheimer Disease, Genetics, Humans, Aged, Aged, 80 and over, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], business.industry, Applied Mathematics, Brain, Computational Biology, 220 Statistical Imaging Neuroscience, Middle Aged, Magnetic Resonance Imaging, Data sharing, Meta-analysis, Female, Data mining, business, computer, 020602 bioinformatics, Genome-Wide Association Study, Biotechnology
Abstract: Genome-wide association studies (GWAS) link full genome data to a handful of traits. However, in neuroimaging studies, there is an almost unlimited number of traits that can be extracted for full image-wide big data analyses. Large populations are needed to achieve the necessary power to detect statistically significant effects, emphasizing the need to pool data across multiple studies. Neuroimaging consortia, e.g., ENIGMA and CHARGE, are now analyzing MRI data from over 30,000 individuals. Distributed processing protocols extract harmonized features at each site, and pool together only the cohort statistics using meta analysis to avoid data sharing. To date, such MRI projects have focused on single measures such as hippocampal volume, yet voxelwise analyses (e.g., tensor-based morphometry; TBM) may help better localize statistical effects. This can lead to $10^{13}$1013 tests for GWAS and become underpowered. We developed an analytical framework for multi-site TBM by performing multi-channel registration to cohort-specific templates. Our results highlight the reliability of the method and the added power over alternative options while preserving single site specificity and opening the doors for well-powered image-wide genome-wide discoveries.
Published: 2019

14. Identifying neuroanatomical signatures of anorexia nervosa: a multivariate machine learning approach

Author: Lavagnino, L., Amianto, F., Mwangi, B., DʼAgata, F., Spalatro, A., Zunta-Soares, G. B., Abbate Daga, G., Mortara, P., Fassino, S., and Soares, J. C.
Published: 2015
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15. Changes in the corpus callosum in women with late-stage bipolar disorder

Author: Lavagnino, L., Cao, B., Mwangi, B., Wu, M.-J., Sanches, M., Zunta-Soares, G. B., Kapczinski, F., and Soares, J.
Published: 2015
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16. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Author: Han, L.K.M., Dinga, R., Hahn, T., Ching, C.R., Eyler, L.T., Aftanas, L., Aghajani, M., Aleman, A., Baune, B.T., Berger, K., Brak, I., Filho, G.B., Carballedo, A., Connolly, C.G., Couvy-Duchesne, B., Cullen, K.R., Dannlowski, U., Davey, C.G., Dima, D., Duran, F.L.S., Enneking, V., Filimonova, E., Frenzel, S., Frodl, T., Fu, C.H.Y., Godlewska, B.R., Gotlib, I.H., Grabe, H.J., Groenewold, N.A., Grotegerd, D., Gruber, O., Hall, G.B., Harrison, B.J., Hatton, S.N., Hermesdorf, M., Hickie, I.B., Ho, T.C., Hosten, N., Jansen, Andreas, Kähler, C., Kircher, T., Klimes-Dougan, B., Krämer, B., Krug, A., Lagopoulos, J., Leenings, R., MacMaster, F.P., MacQueen, G., McIntosh, A., McLellan, Q., McMahon, K.L., Medland, S.E., Mueller, B.A., Mwangi, B., Osipov, E., Portella, M.J., Pozzi, E., Reneman, L., Repple, J., Rosa, P.G., Sacchet, M.D., Sämann, P.G., Schnell, K., Schrantee, A., Simulionyte, E., Soares, J.C., Sommer, J., Stein, D.J., Steinsträter, O., Strike, L.T., Thomopoulos, S.I., Tol, M.J.D. van, Veer, I.M., Vermeiren, R., Walter, H., Wee, N.J.A. van der, Werff, S.J.A. van der, Whalley, H., Winter, N.R., Wittfeld, K., Wright, M.J., Wu, M.J., Völzke, H., Yang, T.T., Zannias, V., Zubicaray, G.I. de, Zunta-Soares, G.B., Abé, C., Alda, M., Andreassen, O.A., Bøen, E., Bonnin, C.M., Canales-Rodriguez, E.J., Cannon, D., Caseras, X., Chaim-Avancini, T.M., Elvsåshagen, T., Favre, P., Foley, S.F., Fullerton, J.M., Ruhé, H.G., Schene, A.H., Marquand, A.F., Cole, J., Schmaal, L., Han, L.K.M., Dinga, R., Hahn, T., Ching, C.R., Eyler, L.T., Aftanas, L., Aghajani, M., Aleman, A., Baune, B.T., Berger, K., Brak, I., Filho, G.B., Carballedo, A., Connolly, C.G., Couvy-Duchesne, B., Cullen, K.R., Dannlowski, U., Davey, C.G., Dima, D., Duran, F.L.S., Enneking, V., Filimonova, E., Frenzel, S., Frodl, T., Fu, C.H.Y., Godlewska, B.R., Gotlib, I.H., Grabe, H.J., Groenewold, N.A., Grotegerd, D., Gruber, O., Hall, G.B., Harrison, B.J., Hatton, S.N., Hermesdorf, M., Hickie, I.B., Ho, T.C., Hosten, N., Jansen, Andreas, Kähler, C., Kircher, T., Klimes-Dougan, B., Krämer, B., Krug, A., Lagopoulos, J., Leenings, R., MacMaster, F.P., MacQueen, G., McIntosh, A., McLellan, Q., McMahon, K.L., Medland, S.E., Mueller, B.A., Mwangi, B., Osipov, E., Portella, M.J., Pozzi, E., Reneman, L., Repple, J., Rosa, P.G., Sacchet, M.D., Sämann, P.G., Schnell, K., Schrantee, A., Simulionyte, E., Soares, J.C., Sommer, J., Stein, D.J., Steinsträter, O., Strike, L.T., Thomopoulos, S.I., Tol, M.J.D. van, Veer, I.M., Vermeiren, R., Walter, H., Wee, N.J.A. van der, Werff, S.J.A. van der, Whalley, H., Winter, N.R., Wittfeld, K., Wright, M.J., Wu, M.J., Völzke, H., Yang, T.T., Zannias, V., Zubicaray, G.I. de, Zunta-Soares, G.B., Abé, C., Alda, M., Andreassen, O.A., Bøen, E., Bonnin, C.M., Canales-Rodriguez, E.J., Cannon, D., Caseras, X., Chaim-Avancini, T.M., Elvsåshagen, T., Favre, P., Foley, S.F., Fullerton, J.M., Ruhé, H.G., Schene, A.H., Marquand, A.F., Cole, J., and Schmaal, L.
Abstract: Item does not contain fulltext, Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.
Published: 2021

17. Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders (May, 2020, 10.1038/s41380-020-0774-9)

Author: Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Samann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, IV, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, van der Auwera, S, Wittfeld, K, Hosten, N, Volzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, Dannlowski, U, Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Samann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, IV, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, van der Auwera, S, Wittfeld, K, Hosten, N, Volzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, and Dannlowski, U
Published: 2021

18. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

Author: Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abe, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargallo, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bulow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjo-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, Gur, RE, Gur, RC, Haar, S, Haarman, BCM, Haavik, J, Hahn, T, Hajek, T, Harrison, BJ, Harrison, NA, Hartman, CA, Whalley, HC, Heslenfeld, DJ, Hibar, DP, Hilland, E, Hirano, Y, Ho, TC, Hoekstra, PJ, Hoekstra, L, Hohmann, S, Hong, LE, Hoschl, C, Hovik, MF, Howells, FM, Nenadic, I, Jalbrzikowski, M, James, AC, Janssen, J, Jaspers-Fayer, F, Xu, J, Jonassen, R, Karkashadze, G, King, JA, Kircher, T, Kirschner, M, Koch, K, Kochunov, P, Kohls, G, Konrad, K, Kramer, B, Krug, A, Kuntsi, J, Kwon, JS, Landen, M, Landro, NI, Lazaro, L, Lebedeva, IS, Leehr, EJ, Lera-Miguel, S, Lesch, K-P, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Malpas, CB, Portella, MJ, Marsh, R, Martyn, FM, Mataix-Cols, D, Mathalon, DH, McCarthy, H, McDonald, C, McPhilemy, G, Meinert, S, Menchon, JM, Minuzzi, L, Mitchell, PB, Moreno, C, Morgado, P, Muratori, F, Murphy, CM, Murphy, D, Mwangi, B, Nabulsi, L, Nakagawa, A, Nakamae, T, Namazova, L, Narayanaswamy, J, Jahanshad, N, Nguyen, DD, Nicolau, R, O'Gorman Tuura, RL, O'Hearn, K, Oosterlaan, J, Opel, N, Ophoff, RA, Oranje, B, Garcia de la Foz, VO, Overs, BJ, Paloyelis, Y, Pantelis, C, Parellada, M, Pauli, P, Pico-Perez, M, Picon, FA, Piras, F, Plessen, KJ, Pomarol-Clotet, E, Preda, A, Puig, O, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Rauer, L, Reddy, J, Redlich, R, Reif, A, Reneman, L, Repple, J, Retico, A, Richarte, V, Richter, A, Rosa, PGP, Rubia, KK, Hashimoto, R, Sacchet, MD, Salvador, R, Santonja, J, Sarink, K, Sarro, S, Satterthwaite, TD, Sawa, A, Schall, U, Schofield, PR, Schrantee, A, Seitz, J, Serpa, MH, Setien-Suero, E, Shaw, P, Shook, D, Silk, TJ, Sim, K, Simon, S, Simpson, HB, Singh, A, Skoch, A, Skokauskas, N, Soares, JC, Soreni, N, Soriano-Mas, C, Spalletta, G, Spaniel, F, Lawrie, SM, Stern, ER, Stewart, SE, Takayanagi, Y, Temmingh, HS, Tolin, DF, Tomecek, D, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, van Amelsvoort, T, van der Wee, NJA, van der Werff, SJA, van Haren, NEM, van Wingen, GA, Vance, A, Vazquez-Bourgon, J, Vecchio, D, Venkatasubramanian, G, Vieta, E, Vilarroya, O, Vives-Gilabert, Y, Voineskos, AN, Volzke, H, von Polier, GG, Walton, E, Weickert, TW, Weickert, CS, Weideman, AS, Wittfeld, K, Wolf, DH, Wu, M-J, Yang, TT, Yang, K, Yoncheva, Y, Yun, J-Y, Cheng, Y, Zanetti, MV, Ziegler, GC, Franke, B, Hoogman, M, Buitelaar, JK, van Rooij, D, Andreassen, OA, Ching, CRK, Veltman, DJ, Schmaal, L, Stein, DJ, van den Heuvel, OA, Turner, JA, van Erp, TGM, Pausova, Z, Thompson, PM, Paus, T, Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abe, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargallo, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bulow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjo-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, Gur, RE, Gur, RC, Haar, S, Haarman, BCM, Haavik, J, Hahn, T, Hajek, T, Harrison, BJ, Harrison, NA, Hartman, CA, Whalley, HC, Heslenfeld, DJ, Hibar, DP, Hilland, E, Hirano, Y, Ho, TC, Hoekstra, PJ, Hoekstra, L, Hohmann, S, Hong, LE, Hoschl, C, Hovik, MF, Howells, FM, Nenadic, I, Jalbrzikowski, M, James, AC, Janssen, J, Jaspers-Fayer, F, Xu, J, Jonassen, R, Karkashadze, G, King, JA, Kircher, T, Kirschner, M, Koch, K, Kochunov, P, Kohls, G, Konrad, K, Kramer, B, Krug, A, Kuntsi, J, Kwon, JS, Landen, M, Landro, NI, Lazaro, L, Lebedeva, IS, Leehr, EJ, Lera-Miguel, S, Lesch, K-P, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Malpas, CB, Portella, MJ, Marsh, R, Martyn, FM, Mataix-Cols, D, Mathalon, DH, McCarthy, H, McDonald, C, McPhilemy, G, Meinert, S, Menchon, JM, Minuzzi, L, Mitchell, PB, Moreno, C, Morgado, P, Muratori, F, Murphy, CM, Murphy, D, Mwangi, B, Nabulsi, L, Nakagawa, A, Nakamae, T, Namazova, L, Narayanaswamy, J, Jahanshad, N, Nguyen, DD, Nicolau, R, O'Gorman Tuura, RL, O'Hearn, K, Oosterlaan, J, Opel, N, Ophoff, RA, Oranje, B, Garcia de la Foz, VO, Overs, BJ, Paloyelis, Y, Pantelis, C, Parellada, M, Pauli, P, Pico-Perez, M, Picon, FA, Piras, F, Plessen, KJ, Pomarol-Clotet, E, Preda, A, Puig, O, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Rauer, L, Reddy, J, Redlich, R, Reif, A, Reneman, L, Repple, J, Retico, A, Richarte, V, Richter, A, Rosa, PGP, Rubia, KK, Hashimoto, R, Sacchet, MD, Salvador, R, Santonja, J, Sarink, K, Sarro, S, Satterthwaite, TD, Sawa, A, Schall, U, Schofield, PR, Schrantee, A, Seitz, J, Serpa, MH, Setien-Suero, E, Shaw, P, Shook, D, Silk, TJ, Sim, K, Simon, S, Simpson, HB, Singh, A, Skoch, A, Skokauskas, N, Soares, JC, Soreni, N, Soriano-Mas, C, Spalletta, G, Spaniel, F, Lawrie, SM, Stern, ER, Stewart, SE, Takayanagi, Y, Temmingh, HS, Tolin, DF, Tomecek, D, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, van Amelsvoort, T, van der Wee, NJA, van der Werff, SJA, van Haren, NEM, van Wingen, GA, Vance, A, Vazquez-Bourgon, J, Vecchio, D, Venkatasubramanian, G, Vieta, E, Vilarroya, O, Vives-Gilabert, Y, Voineskos, AN, Volzke, H, von Polier, GG, Walton, E, Weickert, TW, Weickert, CS, Weideman, AS, Wittfeld, K, Wolf, DH, Wu, M-J, Yang, TT, Yang, K, Yoncheva, Y, Yun, J-Y, Cheng, Y, Zanetti, MV, Ziegler, GC, Franke, B, Hoogman, M, Buitelaar, JK, van Rooij, D, Andreassen, OA, Ching, CRK, Veltman, DJ, Schmaal, L, Stein, DJ, van den Heuvel, OA, Turner, JA, van Erp, TGM, Pausova, Z, Thompson, PM, and Paus, T
Abstract: IMPORTANCE: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. OBJECTIVE: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. DESIGN, SETTING, AND PARTICIPANTS: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. MAIN OUTCOMES AND MEASURES: Interregional profiles of group difference in cortical thickness between cases and controls. RESULTS: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene
Published: 2021

19. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group.

Author: Han, LKM, Dinga, R, Hahn, T, Ching, CRK, Eyler, LT, Aftanas, L, Aghajani, M, Aleman, A, Baune, BT, Berger, K, Brak, I, Filho, GB, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, CG, Dima, D, Duran, FLS, Enneking, V, Filimonova, E, Frenzel, S, Frodl, T, Fu, CHY, Godlewska, BR, Gotlib, IH, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Hosten, N, Jansen, A, Kähler, C, Kircher, T, Klimes-Dougan, B, Krämer, B, Krug, A, Lagopoulos, J, Leenings, R, MacMaster, FP, MacQueen, G, McIntosh, A, McLellan, Q, McMahon, KL, Medland, SE, Mueller, BA, Mwangi, B, Osipov, E, Portella, MJ, Pozzi, E, Reneman, L, Repple, J, Rosa, PGP, Sacchet, MD, Sämann, PG, Schnell, K, Schrantee, A, Simulionyte, E, Soares, JC, Sommer, J, Stein, DJ, Steinsträter, O, Strike, LT, Thomopoulos, SI, van Tol, M-J, Veer, IM, Vermeiren, RRJM, Walter, H, van der Wee, NJA, van der Werff, SJA, Whalley, H, Winter, NR, Wittfeld, K, Wright, MJ, Wu, M-J, Völzke, H, Yang, TT, Zannias, V, de Zubicaray, GI, Zunta-Soares, GB, Abé, C, Alda, M, Andreassen, OA, Bøen, E, Bonnin, CM, Canales-Rodriguez, EJ, Cannon, D, Caseras, X, Chaim-Avancini, TM, Elvsåshagen, T, Favre, P, Foley, SF, Fullerton, JM, Goikolea, JM, Haarman, BCM, Hajek, T, Henry, C, Houenou, J, Howells, FM, Ingvar, M, Kuplicki, R, Lafer, B, Landén, M, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Nabulsi, L, Otaduy, MCG, Overs, BJ, Polosan, M, Pomarol-Clotet, E, Radua, J, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarró, S, Satterthwaite, TD, Savitz, J, Schene, AH, Schofield, PR, Serpa, MH, Sim, K, Soeiro-de-Souza, MG, Sutherland, AN, Temmingh, HS, Timmons, GM, Uhlmann, A, Vieta, E, Wolf, DH, Zanetti, MV, Jahanshad, N, Thompson, PM, Veltman, DJ, Penninx, BWJH, Marquand, AF, Cole, JH, Schmaal, L, Han, LKM, Dinga, R, Hahn, T, Ching, CRK, Eyler, LT, Aftanas, L, Aghajani, M, Aleman, A, Baune, BT, Berger, K, Brak, I, Filho, GB, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, CG, Dima, D, Duran, FLS, Enneking, V, Filimonova, E, Frenzel, S, Frodl, T, Fu, CHY, Godlewska, BR, Gotlib, IH, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Hosten, N, Jansen, A, Kähler, C, Kircher, T, Klimes-Dougan, B, Krämer, B, Krug, A, Lagopoulos, J, Leenings, R, MacMaster, FP, MacQueen, G, McIntosh, A, McLellan, Q, McMahon, KL, Medland, SE, Mueller, BA, Mwangi, B, Osipov, E, Portella, MJ, Pozzi, E, Reneman, L, Repple, J, Rosa, PGP, Sacchet, MD, Sämann, PG, Schnell, K, Schrantee, A, Simulionyte, E, Soares, JC, Sommer, J, Stein, DJ, Steinsträter, O, Strike, LT, Thomopoulos, SI, van Tol, M-J, Veer, IM, Vermeiren, RRJM, Walter, H, van der Wee, NJA, van der Werff, SJA, Whalley, H, Winter, NR, Wittfeld, K, Wright, MJ, Wu, M-J, Völzke, H, Yang, TT, Zannias, V, de Zubicaray, GI, Zunta-Soares, GB, Abé, C, Alda, M, Andreassen, OA, Bøen, E, Bonnin, CM, Canales-Rodriguez, EJ, Cannon, D, Caseras, X, Chaim-Avancini, TM, Elvsåshagen, T, Favre, P, Foley, SF, Fullerton, JM, Goikolea, JM, Haarman, BCM, Hajek, T, Henry, C, Houenou, J, Howells, FM, Ingvar, M, Kuplicki, R, Lafer, B, Landén, M, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Nabulsi, L, Otaduy, MCG, Overs, BJ, Polosan, M, Pomarol-Clotet, E, Radua, J, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarró, S, Satterthwaite, TD, Savitz, J, Schene, AH, Schofield, PR, Serpa, MH, Sim, K, Soeiro-de-Souza, MG, Sutherland, AN, Temmingh, HS, Timmons, GM, Uhlmann, A, Vieta, E, Wolf, DH, Zanetti, MV, Jahanshad, N, Thompson, PM, Veltman, DJ, Penninx, BWJH, Marquand, AF, Cole, JH, and Schmaal, L
Abstract: Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.
Published: 2021

20. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

Author: Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S.I., Pozzi, E., Abe, Y., Abé, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S.H., Anagnostou, E., McIntosh, A.A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C.E., Baranov, A., Bargalló, N., Bau, C.H.D., Baumeister, S., Baune, B.T., Bellgrove, M.A., Benedetti, F., Bertolino, A., Boedhoe, P.S.W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B.P., Bruggemann, J.M., Bülow, R., Busatto, G.F., Calderoni, S., Calhoun, V.D., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carr, V.J., Cascella, N., Cercignani, M., Chaim-Avancini, T.M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A.I., Cullen, K.R., Cupertino, R.B., Daly, E., Dannlowski, U., Davey, C.G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E.W., Dima, D., Dohm, K., Ehrlich, S., Ely, B.A., Erwin-Grabner, T., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V., Fatjó-Vilas, M., Fedor, J.M., Fitzgerald, K.D., Ford, J.M., Frodl, T., Fu, C.H.Y., Fullerton, J.M., Gabel, M.C., Glahn, D.C., Roberts, G., Gogberashvili, T., Goikolea, J.M., Gotlib, I.H., Goya-Maldonado, R., Grabe, H.J., Green, M.J., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R.E., Gur, R.C., Haar, S., Haarman, B.C.M., Haavik, J., Hahn, T., Hajek, T., Harrison, B.J., Harrison, N.A., Hartman, C.A., Whalley, H.C., Heslenfeld, D.J., Hibar, D.P., Hilland, E., Hirano, Y., Ho, T.C., Hoekstra, P.J., Hoekstra, L., Hohmann, S., Hong, L.E., Höschl, C., Høvik, M.F., Howells, F.M., Nenadic, I., Jalbrzikowski, M., James, A.C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J.A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Krämer, B., Krug, A., Kuntsi, J., Kwon, J.S., Landén, M., Landrø, N.I., Lazaro, L., Lebedeva, I.S., Leehr, E.J., Lera-Miguel, S., Lesch, K.-P., Lochner, C., Louza, M.R., Luna, B., Lundervold, A.J., Macmaster, F.P., Maglanoc, L.A., Malpas, C.B., Portella, M.J., Marsh, R., Martyn, F.M., Mataix-Cols, D., Mathalon, D.H., McCarthy, H., McDonald, C., McPhilemy, G., Meinert, S., Menchón, J.M., Minuzzi, L., Mitchell, P.B., Moreno, C., Morgado, P., Muratori, F., Murphy, C.M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D.D., Nicolau, R., O'Gorman Tuura, R.L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R.A., Oranje, B., García De La Foz, V.O., Overs, B.J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Picó-Pérez, M., Picon, F.A., Piras, F., Plessen, K.J., Pomarol-Clotet, E., Preda, A., Puig, O., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P.G.P., Rubia, K.K., Hashimoto, R., Sacchet, M.D., Salvador, R., Santonja, J., Sarink, K., Sarró, S., Satterthwaite, T.D., Sawa, A., Schall, U., Schofield, P.R., Schrantee, A., Seitz, J., Serpa, M.H., Setién-Suero, E., Shaw, P., Shook, D., Silk, T.J., Sim, K., Simon, S., Simpson, H.B., Singh, A., Skoch, A., Skokauskas, N., Soares, J.C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S.M., Stern, E.R., Stewart, S.E., Takayanagi, Y., Temmingh, H.S., Tolin, D.F., Tomecek, D., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N.J.A., Van Der Werff, S.J.A., Van Haren, N.E.M., Van Wingen, G.A., Vance, A., Vázquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A.N., Völzke, H., Von Polier, G.G., Walton, E., Weickert, T.W., Weickert, C.S., Weideman, A.S., Wittfeld, K., Wolf, D.H., Wu, M.-J., Yang, T.T., Yang, K., Yoncheva, Y., Yun, J.-Y., Cheng, Y., Zanetti, M.V., Ziegler, G.C., Franke, B., Hoogman, M., Buitelaar, J.K., Van Rooij, D., Andreassen, O.A., Ching, C.R.K., Veltman, D.J., Schmaal, L., Stein, D.J., Van Den Heuvel, O.A., Turner, J.A., Van Erp, T.G.M., Pausova, Z., Thompson, P.M., Paus, T., Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S.I., Pozzi, E., Abe, Y., Abé, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S.H., Anagnostou, E., McIntosh, A.A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C.E., Baranov, A., Bargalló, N., Bau, C.H.D., Baumeister, S., Baune, B.T., Bellgrove, M.A., Benedetti, F., Bertolino, A., Boedhoe, P.S.W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B.P., Bruggemann, J.M., Bülow, R., Busatto, G.F., Calderoni, S., Calhoun, V.D., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carr, V.J., Cascella, N., Cercignani, M., Chaim-Avancini, T.M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A.I., Cullen, K.R., Cupertino, R.B., Daly, E., Dannlowski, U., Davey, C.G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E.W., Dima, D., Dohm, K., Ehrlich, S., Ely, B.A., Erwin-Grabner, T., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V., Fatjó-Vilas, M., Fedor, J.M., Fitzgerald, K.D., Ford, J.M., Frodl, T., Fu, C.H.Y., Fullerton, J.M., Gabel, M.C., Glahn, D.C., Roberts, G., Gogberashvili, T., Goikolea, J.M., Gotlib, I.H., Goya-Maldonado, R., Grabe, H.J., Green, M.J., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R.E., Gur, R.C., Haar, S., Haarman, B.C.M., Haavik, J., Hahn, T., Hajek, T., Harrison, B.J., Harrison, N.A., Hartman, C.A., Whalley, H.C., Heslenfeld, D.J., Hibar, D.P., Hilland, E., Hirano, Y., Ho, T.C., Hoekstra, P.J., Hoekstra, L., Hohmann, S., Hong, L.E., Höschl, C., Høvik, M.F., Howells, F.M., Nenadic, I., Jalbrzikowski, M., James, A.C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J.A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Krämer, B., Krug, A., Kuntsi, J., Kwon, J.S., Landén, M., Landrø, N.I., Lazaro, L., Lebedeva, I.S., Leehr, E.J., Lera-Miguel, S., Lesch, K.-P., Lochner, C., Louza, M.R., Luna, B., Lundervold, A.J., Macmaster, F.P., Maglanoc, L.A., Malpas, C.B., Portella, M.J., Marsh, R., Martyn, F.M., Mataix-Cols, D., Mathalon, D.H., McCarthy, H., McDonald, C., McPhilemy, G., Meinert, S., Menchón, J.M., Minuzzi, L., Mitchell, P.B., Moreno, C., Morgado, P., Muratori, F., Murphy, C.M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D.D., Nicolau, R., O'Gorman Tuura, R.L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R.A., Oranje, B., García De La Foz, V.O., Overs, B.J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Picó-Pérez, M., Picon, F.A., Piras, F., Plessen, K.J., Pomarol-Clotet, E., Preda, A., Puig, O., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P.G.P., Rubia, K.K., Hashimoto, R., Sacchet, M.D., Salvador, R., Santonja, J., Sarink, K., Sarró, S., Satterthwaite, T.D., Sawa, A., Schall, U., Schofield, P.R., Schrantee, A., Seitz, J., Serpa, M.H., Setién-Suero, E., Shaw, P., Shook, D., Silk, T.J., Sim, K., Simon, S., Simpson, H.B., Singh, A., Skoch, A., Skokauskas, N., Soares, J.C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S.M., Stern, E.R., Stewart, S.E., Takayanagi, Y., Temmingh, H.S., Tolin, D.F., Tomecek, D., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N.J.A., Van Der Werff, S.J.A., Van Haren, N.E.M., Van Wingen, G.A., Vance, A., Vázquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A.N., Völzke, H., Von Polier, G.G., Walton, E., Weickert, T.W., Weickert, C.S., Weideman, A.S., Wittfeld, K., Wolf, D.H., Wu, M.-J., Yang, T.T., Yang, K., Yoncheva, Y., Yun, J.-Y., Cheng, Y., Zanetti, M.V., Ziegler, G.C., Franke, B., Hoogman, M., Buitelaar, J.K., Van Rooij, D., Andreassen, O.A., Ching, C.R.K., Veltman, D.J., Schmaal, L., Stein, D.J., Van Den Heuvel, O.A., Turner, J.A., Van Erp, T.G.M., Pausova, Z., Thompson, P.M., and Paus, T.
Abstract: Importance Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. Objective To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. Design, Setting, and Participants Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. Main Outcomes and Measures Interregional profiles of group difference in cortical thickness between cases and controls. Results A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (exce
Published: 2021
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21. ENIGMA-anxiety working group: Rationale for and organization of large-scale neuroimaging studies of anxiety disorders

Author: Bas-Hoogendam, J. M., Groenewold, N. A., Aghajani, M., Freitag, G. F., Harrewijn, A., Hilbert, K., Jahanshad, N., Thomopoulos, S. I., Thompson, P. M., Veltman, D. J., Winkler, A. M., Lueken, U., Pine, D. S., van der Wee, N. J. A., Stein, D. J., Agosta, F., Ahs, F., An, I., Alberton, B. A. V., Andreescu, C., Asami, T., Assaf, M., Avery, S. N., Nicholas, L., Balderston, Barber, J. P., Battaglia, M., Bayram, A., Beesdo-Baum, K., Benedetti, F., Berta, R., Bjorkstrand, J., Blackford, J. U., Blair, J. R., Karina, S., Blair, Boehme, S., Brambilla, P., Burkhouse, K., Cano, M., Canu, E., Cardinale, E. M., Cardoner, N., Clauss, J. A., Cividini, C., Critchley, H. D., Udo, Dannlowski, Deckert, J., Demiralp, T., Diefenbach, G. J., Domschke, K., Doruyter, A., Dresler, T., Erhardt, A., Fallgatter, A. J., Fananas, L., Brandee, Feola, Filippi, C. A., Filippi, M., Fonzo, G. A., Forbes, E. E., Fox, N. A., Fredrikson, M., Furmark, T., Ge, T., Gerber, A. J., Gosnell, S. N., Grabe, H. J., Grotegerd, D., Gur, R. E., Gur, R. C., Harmer, C. J., Harper, J., Heeren, A., Hettema, J., Hofmann, D., Hofmann, S. G., Jackowski, A. P., Andreas, Jansen, Kaczkurkin, A. N., Kingsley, E., Kircher, T., Kosti c, M., Kreifelts, B., Krug, A., Larsen, B., Lee, S. -H., Leehr, E. J., Leibenluft, E., Lochner, C., Maggioni, E., Makovac, E., Mancini, M., Manfro, G. G., Mansson, K. N. T., Meeten, F., Michalowski, J., Milrod, B. L., Muhlberger, A., Lilianne, R., Mujica-Parodi, Munjiza, A., Mwangi, B., Myers, M., Igor Nenadi, C., Neufang, S., Nielsen, J. A., Oh, H., Ottaviani, C., Pan, P. M., Pantazatos, S. P., Martin, P., Paulus, Perez-Edgar, K., Penate, W., Perino, M. T., Peterburs, J., Pfleiderer, B., Phan, K. L., Poletti, S., Porta-Casteras, D., Price, R. B., Pujol, J., Andrea, Reinecke, Rivero, F., Roelofs, K., Rosso, I., Saemann, P., Salas, R., Salum, G. A., Satterthwaite, T. D., Schneier, F., Schruers, K. R. J., Schulz, S. M., Schwarzmeier, H., Seeger, F. R., Smoller, J. W., Soares, J. C., Stark, R., Stein, M. B., Straube, B., Straube, T., Strawn, J. R., Suarez-Jimenez, B., Boris, Suchan, Sylvester, C. M., Talati, A., Tamburo, E., Tukel, R., van den Heuvel, O. A., Van der Auwera, S., van Nieuwenhuizen, H., van Tol, M. -J., van Velzen, L. S., Bort, C. V., Vermeiren, R. R. J. M., Visser, R. M., Volman, I., Wannemuller, A., Wendt, J., Werwath, K. E., Westenberg, P. M., Wiemer, J., Katharina, Wittfeld, M. -J., Wu, Yang, Y., Zilverstand, A., Zugman, A., Zwiebel, H. L., Bas-Hoogendam, J. M., Groenewold, N. A., Aghajani, M., Freitag, G. F., Harrewijn, A., Hilbert, K., Jahanshad, N., Thomopoulos, S. I., Thompson, P. M., Veltman, D. J., Winkler, A. M., Lueken, U., Pine, D. S., van der Wee, N. J. A., Stein, D. J., ENIGMA-anxiety working, Group, Filippi, M, and UCL - SSH/IPSY - Psychological Sciences Research Institute
Subjects: Córtex pré-frontal, Review Article, Anxiety, Prefrontal cortex, Specific phobia, 0302 clinical medicine, limbic system, magnetic resonance imaging, Multicenter Studies as Topic, genetics, Review Articles, prefrontal cortex, neuroimaging, Radiological and Ultrasound Technology, 05 social sciences, Social anxiety, amygdala, Amygdala, Anxiety Disorders, Transtornos de ansiedade, Neurology, multicentric network, Anatomy, medicine.symptom, Psychology, Neurovetenskaper, Clinical psychology, endocrine system, Generalized anxiety disorder, brain, Neuroimaging, Sistema límbico, 050105 experimental psychology, 03 medical and health sciences, Global mental health, Limbic system, Magnetic resonance imaging, Imatges per ressonància magnètica, medicine, Genetics, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Neuroimagem, Psykologi (exklusive tillämpad psykologi), Panic disorder, neurosciences, Imageamento por ressonância magnética, Tonsila do cerebelo, medicine.disease, anxiety disorders, Genética, Psychology (excluding Applied Psychology), Ansietat, Neurology (clinical), Working group, 030217 neurology & neurosurgery, Anxiety disorders
Abstract: Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA‐Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA‐Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA‐Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders., Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA‐Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA‐Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders.
Published: 2020

22. Compatibility and performance of susceptible tomato cultivars grafted onto bacterial wilt (Ralstonia solanacearum) resistant rootstock

Author: Mbaka Jesca, Kanyua Stella, and Mwangi B. Maina
Subjects: 0106 biological sciences, 0303 health sciences, Ralstonia solanacearum, biology, Bacterial wilt, fungi, food and beverages, biology.organism_classification, 01 natural sciences, 03 medical and health sciences, Horticulture, Compatibility (mechanics), Cultivar, Rootstock, Grafting, Compatibility, Performance, 030304 developmental biology, 010606 plant biology & botany
Abstract: Objective: Tomato (Solanum lycopersicum L.) belongs to the Solanaceae family and currently is one of the most important vegetable crops. Bacterial wilt, caused by Ralstonia solanacearum is a soil borne disease of tomato causing significant economic damage on tomatoes, tobacco and potatoes. Bacterial wilt is difficult to manage because the pathogen can survive in soil for long periods in association with a wide range of crops such as pepper, potato, capsicum, eggplants and weeds such as Jimson weed and nightshade. The objective of this study was to determine compatibility and performance of susceptible tomato cultivars grafted onto bacterial wilt resistant rootstocks. Methodology: Scions from susceptible tomato commercial cultivars (Anna F1 and Cal J) were grafted onto rootstocks of Eggplant, Sodom apple and tomato cultivar Mt56 that were determined to be resistant to bacterial wilt in a previous study. Cleft grafting technique was used in the experiment. Data on compatibility was assessed daily to check on the healing of the graft union and number of established plants. The grafted plants were considered compatible if 67% of the grafted plants had healed and growth established fourteen days after grafting. Data were subjected to ANOVA using GenStat version 15 and significantly different treatment means separated using LSD at P < 0.05. Results and application: The grafted plants were compatible at varying rates, that is Mt56 + Anna F1 (93.30%), Mt56 + Cal J (76.7%), S. melongena + Anna F1 (96.7%), S. melongena + Cal J (83.3%), S. incarnum + Anna F1 (73.3% ), and S. incarnum + Cal J (100%). It was concluded that tomato scions and the botanically related wilt resistant rootstocks are compatible. All the grafted plants performed well except those on Sodom apple rootstock whose stem did not expand at the rate as the scion stem. It is recommended that the proven resistant rootstocks be deployed to tomato farmers for use in tomato grafting and subsequent increase in their production. Key words: Grafting, Compatibility, Performance, Bacterial wilt
Published: 2020

23. Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Author: Nunes, A, Schnack, HG, Ching, CRK, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Bauer, J, Baune, BT, Bøen, E, Bonnin, CDM, Busatto, GF, Canales-Rodríguez, EJ, Cannon, DM, Caseras, X, Chaim-Avancini, TM, Dannlowski, U, Díaz-Zuluaga, AM, Dietsche, B, Doan, NT, Duchesnay, E, Elvsåshagen, T, Emden, D, Eyler, LT, Fatjó-Vilas, M, Favre, P, Foley, SF, Fullerton, JM, Glahn, DC, Goikolea, JM, Grotegerd, D, Hahn, T, Henry, C, Hibar, DP, Houenou, J, Howells, FM, Jahanshad, N, Kaufmann, T, Kenney, J, Kircher, TTJ, Krug, A, Lagerberg, TV, Lenroot, RK, López-Jaramillo, C, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Mwangi, B, Nabulsi, L, Opel, N, Overs, BJ, Pineda-Zapata, JA, Pomarol-Clotet, E, Redlich, R, Roberts, G, Rosa, PG, Salvador, R, Satterthwaite, TD, Soares, JC, Stein, DJ, Temmingh, HS, Trappenberg, T, Uhlmann, A, van Haren, NEM, Vieta, E, Westlye, LT, Wolf, DH, Yüksel, D, Zanetti, MV, Andreassen, OA, Thompson, PM, Hajek, T, Nunes, A, Schnack, HG, Ching, CRK, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Bauer, J, Baune, BT, Bøen, E, Bonnin, CDM, Busatto, GF, Canales-Rodríguez, EJ, Cannon, DM, Caseras, X, Chaim-Avancini, TM, Dannlowski, U, Díaz-Zuluaga, AM, Dietsche, B, Doan, NT, Duchesnay, E, Elvsåshagen, T, Emden, D, Eyler, LT, Fatjó-Vilas, M, Favre, P, Foley, SF, Fullerton, JM, Glahn, DC, Goikolea, JM, Grotegerd, D, Hahn, T, Henry, C, Hibar, DP, Houenou, J, Howells, FM, Jahanshad, N, Kaufmann, T, Kenney, J, Kircher, TTJ, Krug, A, Lagerberg, TV, Lenroot, RK, López-Jaramillo, C, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Mwangi, B, Nabulsi, L, Opel, N, Overs, BJ, Pineda-Zapata, JA, Pomarol-Clotet, E, Redlich, R, Roberts, G, Rosa, PG, Salvador, R, Satterthwaite, TD, Soares, JC, Stein, DJ, Temmingh, HS, Trappenberg, T, Uhlmann, A, van Haren, NEM, Vieta, E, Westlye, LT, Wolf, DH, Yüksel, D, Zanetti, MV, Andreassen, OA, Thompson, PM, and Hajek, T
Abstract: Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.
Published: 2020

24. Brain structural correlates of insomnia severity in 1053 individuals with major depressive disorder: results from the ENIGMA MDD working group

Author: Leerssen, J, Blanken, TF, Pozzi, E, Jahanshad, N, Aftanas, L, Andreassen, OA, Baune, BT, Ching, CRK, Dannlowski, U, Frodl, T, Godlewska, BR, Gotlib, IH, Grotegerd, D, Gruber, O, Hatton, SN, Hickie, IB, Jaworska, N, Kircher, T, Krug, A, Lagopoulos, J, Li, M, MacMaster, FP, McIntosh, AM, Mwangi, B, Osipov, E, Portella, MJ, Sacchet, MD, Samann, PG, Simulionyte, E, Soares, JC, Walter, M, Whalley, HC, Veltman, DJ, Thompson, PM, Schmaal, L, Van Someren, EJW, Leerssen, J, Blanken, TF, Pozzi, E, Jahanshad, N, Aftanas, L, Andreassen, OA, Baune, BT, Ching, CRK, Dannlowski, U, Frodl, T, Godlewska, BR, Gotlib, IH, Grotegerd, D, Gruber, O, Hatton, SN, Hickie, IB, Jaworska, N, Kircher, T, Krug, A, Lagopoulos, J, Li, M, MacMaster, FP, McIntosh, AM, Mwangi, B, Osipov, E, Portella, MJ, Sacchet, MD, Samann, PG, Simulionyte, E, Soares, JC, Walter, M, Whalley, HC, Veltman, DJ, Thompson, PM, Schmaal, L, and Van Someren, EJW
Published: 2020

25. Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders Evidence through univariate and multivariate mega-analysis including 6420 participants from the ENIGMA MDD working group

Author: Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Saemann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, I, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, Van der Auwera, S, Wittfeld, K, Hosten, N, Voelzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, Dannlowski, U, Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Saemann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, I, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, Van der Auwera, S, Wittfeld, K, Hosten, N, Voelzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, and Dannlowski, U
Abstract: Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = -0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.
Published: 2020

26. P.250 Prediction of bipolar disorder four years before onset in a 22-year population-based birth cohort using advanced machine learning techniques

Author: Rabelo-Da-Ponte, F.D., primary, Feiten, J.G., additional, Mwangi, B., additional, Barros, F.C., additional, Wehrmeister, F.C., additional, Menezes, A.M., additional, Kapczinski, F., additional, Passos, I.C., additional, and Kunz, M., additional
Published: 2020
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27. Early identification of bipolar disorder among young adults – a 22‐year community birth cohort

Author: Rabelo‐da‐Ponte, F. D., primary, Feiten, J. G., additional, Mwangi, B., additional, Barros, F. C., additional, Wehrmeister, F. C., additional, Menezes, A. M., additional, Kapczinski, F., additional, Passos, I. C., additional, and Kunz, M., additional
Published: 2020
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28. Validation of the bag‐mediated filtration system for environmental surveillance of poliovirus in Nairobi, Kenya

Author: Fagnant‐Sperati, C.S., primary, Ren, Y., additional, Zhou, N.A., additional, Komen, E., additional, Mwangi, B., additional, Hassan, J., additional, Chepkurui, A., additional, Nzunza, R., additional, Nyangao, J., additional, Zyl, W.B., additional, Wolfaardt, M., additional, Matsapola, P.N., additional, Ngwana, F.B., additional, Jeffries‐Miles, S., additional, Coulliette‐Salmond, A., additional, Peñaranda, S., additional, Vega, E., additional, Shirai, J.H., additional, Kossik, A.L., additional, Beck, N.K., additional, Boyle, D.S., additional, Burns, C.C., additional, Taylor, M.B., additional, Borus, P., additional, and Meschke, J.S., additional
Published: 2020
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29. The Association between familial risk and brain abnormalities Is disease specific: an ENIGMA-relatives study of schizophrenia and bipolar disorder

Author: Zwarte, S. M. C., Brouwer, R. M., Agartz, I., Alda, M., Aleman, A., Alpert, K. I., Bearden, C. E., Bertolino, A., Bois, C., Bonvino, A., Bramon, E., Buimer, E., Cahn, W., Cannon, D. M., Cannon, T. D., Caseras, X., Castro-Fornieles, J., Chen, Q., Serna, E., Giorgio, A. D., Doucet, G., Eker, M. C., Erk, S., Fears, S., Foley, S., Frangou, S., Frankland, A., Fullerton, J., Glahn, D., Goghari, V., Goldman, A., Gonul, A., Gruber, O., Haan, L., Hajek, T., Hawkins, E., Heinz, A., Hillegers, M., Pol, H., Hultman, C., Ingvar, M., Johansson, V., Jönsson, E., Kane, K., Kempton, M., Koenis, M., Kopecek, M., Krabbendam, L., Krämer, B., Lawrie, S., Lenroot, R., Marcelis, M., Marsman, J-B, Mattay, V., McDonald, C., Meyer-Lindenberg, A., Michielse, S., Mitchell, P., Moreno, D., Murray, R., Mwangi, B., Najt, P., Neilson, E., Newport, J., Os, J., Overs, B., Özerdem, A., Picchioni, M., Richter, A., Roberts, G., Aydoğan, A. S., Schofield, P., Şimşek, F., Soares, J., Sugranyes, G., Toulopoulou, Timothea, Tronchin, G., Walter, H., Wang, L., Weinberger, D., Whalley, H., Yalın, N., Andreassen, O., Ching, C., Erp, T., Turner, J., Jahanshad, N., Thompson, P., Kahn, R., Haren, N., and Toulopoulou, Timothea
Subjects: Meta-analysis, Familial riskImaging, Bipolar disorder, Neurodevelopment, Schizophrenia
Abstract: Background Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects. Methods We performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects. Results FDRs-BD had significantly larger ICV (d = +0.16, q < .05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = −0.12, q < .05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d < −0.09, q < .05 corrected); and third ventricle was larger (d = +0.15, q < .05 corrected). The findings were not explained by psychopathology in the relatives or control subjects. Conclusions Despite shared genetic liability, FDRs-SZ and FDRs-BD show a differential pattern of structural brain abnormalities, specifically a divergent effect in ICV. This may imply that the neurodevelopmental trajectories leading to brain anomalies in schizophrenia or bipolar disorder are distinct.
Published: 2019

30. The Association Between Familial Risk and Brain Abnormalities Is Disease Specific: An ENIGMA-Relatives Study of Schizophrenia and Bipolar Disorder

Author: de Zwarte, SMC, Brouwer, RM, Agartz, I, Alda, M, Aleman, A, Alpert, KI, Bearden, CE, Bertolino, A, Bois, C, Bonvino, A, Bramon, E, Buimer, EEL, Cahn, W, Cannon, DM, Cannon, TD, Caseras, X, Castro-Fornieles, J, Chen, Q, Chung, Y, De la Serna, E, Di Giorgio, A, Doucet, GE, Eker, MC, Erk, S, Fears, SC, Foley, SF, Frangou, S, Frankland, A, Fullerton, JM, Glahn, DC, Goghari, VM, Goldman, AL, Gonul, AS, Gruber, O, de Haan, L, Hajek, T, Hawkins, EL, Heinz, A, Hillegers, MHJ, Hulshoff Pol, HE, Hultman, CM, Ingvar, M, Johansson, V, Jönsson, EG, Kane, F, Kempton, MJ, Koenis, MMG, Kopecek, M, Krabbendam, L, Krämer, B, Lawrie, SM, Lenroot, RK, Marcelis, M, Marsman, JBC, Mattay, VS, McDonald, C, Meyer-Lindenberg, A, Michielse, S, Mitchell, PB, Moreno, D, Murray, RM, Mwangi, B, Najt, P, Neilson, E, Newport, J, van Os, J, Overs, B, Ozerdem, A, Picchioni, MM, Richter, A, Roberts, G, Aydogan, AS, Schofield, PR, Simsek, F, Soares, JC, Sugranyes, G, Toulopoulou, T, Tronchin, G, Walter, H, Wang, L, Weinberger, DR, Whalley, HC, Yalin, N, Andreassen, OA, Ching, CRK, van Erp, TGM, Turner, JA, Jahanshad, N, Thompson, PM, Kahn, RS, van Haren, NEM, de Zwarte, SMC, Brouwer, RM, Agartz, I, Alda, M, Aleman, A, Alpert, KI, Bearden, CE, Bertolino, A, Bois, C, Bonvino, A, Bramon, E, Buimer, EEL, Cahn, W, Cannon, DM, Cannon, TD, Caseras, X, Castro-Fornieles, J, Chen, Q, Chung, Y, De la Serna, E, Di Giorgio, A, Doucet, GE, Eker, MC, Erk, S, Fears, SC, Foley, SF, Frangou, S, Frankland, A, Fullerton, JM, Glahn, DC, Goghari, VM, Goldman, AL, Gonul, AS, Gruber, O, de Haan, L, Hajek, T, Hawkins, EL, Heinz, A, Hillegers, MHJ, Hulshoff Pol, HE, Hultman, CM, Ingvar, M, Johansson, V, Jönsson, EG, Kane, F, Kempton, MJ, Koenis, MMG, Kopecek, M, Krabbendam, L, Krämer, B, Lawrie, SM, Lenroot, RK, Marcelis, M, Marsman, JBC, Mattay, VS, McDonald, C, Meyer-Lindenberg, A, Michielse, S, Mitchell, PB, Moreno, D, Murray, RM, Mwangi, B, Najt, P, Neilson, E, Newport, J, van Os, J, Overs, B, Ozerdem, A, Picchioni, MM, Richter, A, Roberts, G, Aydogan, AS, Schofield, PR, Simsek, F, Soares, JC, Sugranyes, G, Toulopoulou, T, Tronchin, G, Walter, H, Wang, L, Weinberger, DR, Whalley, HC, Yalin, N, Andreassen, OA, Ching, CRK, van Erp, TGM, Turner, JA, Jahanshad, N, Thompson, PM, Kahn, RS, and van Haren, NEM
Abstract: Background: Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects. Methods: We performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects. Results: FDRs-BD had significantly larger ICV (d = +0.16, q <.05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = −0.12, q <.05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d < −0.09, q <.05 corrected); and third ventricle was larger (d = +0.15, q <.05 corrected). The findings were not explained by psychopathology in the relatives or control subjects. Conclusions: Despite shared genetic liability, FDRs-SZ and FDRs-BD show a differential pattern of structural brain abnormalities, specifically a divergent effect in ICV. This may imply that the neurodevelopmental trajectories leading to brain anomalies in schizophrenia or bipolar disorder are distinct.
Published: 2019

31. The use of component-wise gradient boosting to assess the possible role of cognitive measures as markers of vulnerability to pediatric bipolar disorder.

Author: Bauer, IE, Suchting, R, Van Rheenen, TE, Wu, M-J, Mwangi, B, Spiker, D, Zunta-Soares, GB, Soares, JC, Bauer, IE, Suchting, R, Van Rheenen, TE, Wu, M-J, Mwangi, B, Spiker, D, Zunta-Soares, GB, and Soares, JC
Abstract: BACKGROUND AND AIMS: Cognitive impairments are primary hallmarks symptoms of bipolar disorder (BD). Whether these deficits are markers of vulnerability or symptoms of the disease is still unclear. This study used a component-wise gradient (CGB) machine learning algorithm to identify cognitive measures that could accurately differentiate pediatric BD, unaffected offspring of BD parents, and healthy controls. METHODS: 59 healthy controls (HC; 11.19 ± 3.15 yo; 30 girls), 119 children and adolescents with BD (13.31 ± 3.02 yo, 52 girls) and 49 unaffected offspring of BD parents (UO; 9.36 ± 3.18 yo; 22 girls) completed the CANTAB cognitive battery. RESULTS: CGB achieved accuracy of 73.2% and an AUROC of 0.785 in classifying individuals as either BD or non-BD on a dataset held out for validation for testing. The strongest cognitive predictors of BD were measures of processing speed and affective processing. Measures of cognition did not differentiate between UO and HC. CONCLUSIONS: Alterations in processing speed and affective processing are markers of BD in pediatric populations. Longitudinal studies should determine whether UO with a cognitive profile similar to that of HC are at less or equal risk for mood disorders. Future studies should include relevant measures for BD such as verbal memory and genetic risk scores.
Published: 2019

32. Antipyretic Properties of Dichloromethane: Methanolic Leaf and Root Bark Extracts of Carissa edulis in Rats

Author: Njoroge W. Ann, Njagi J. Muriithi, Ngugi M Piero, Aliyu Umar, Gitahi S Maina, Mburu N. David, Mwonjoria K. John, Mworia J. Kiambi, Juma K Kelvin, and Mwangi B. Maina
Subjects: Conventional medicine, Aspirin, Traditional medicine, business.industry, Rectal temperature, visual_art, visual_art.visual_art_medium, medicine, General Materials Science, Bark, Antipyretic, Carissa edulis, Medicinal plants, Adverse effect, business, medicine.drug
Abstract: Although pyrexia benefits the nonspecific immune response to invading microor ganisms and tissue damage, it is also viewed as a source of discomfort and hence is commonly suppressed with some medication. However, conventional medications are expensive and arguably associated with various severe adverse side effects hence the need to develop herbal agents that are effective, cheaply available as alternative and complementary to conventional therapeutic drugs. Today herbal remedies are gaining popularity because the efficacy of conventional medicine is on the wane. Through ages Carissa edulis has been used as folklore remedy for various common ailments afflicting people in various parts of the world. However, although C. edulis (Forssk.)Vahl is widely used for pyrexia in the traditional medicine, an extensive search of the literature reveals no scientifically investigated report of its described effects. Thus, this study was to scientifically evaluate the ethnomedicinal importance of C. edulis (Forssk.)Vahl as an alternative and complementally intervention for the treatment of fever. The experimental groups were treated with leaf and root bark extracts at concentration of 50mg/kg, 100mg/kg and 150mg/kg. Antipyretic activities in rats were compared with aspirin (100mg/kg) as the standard conventional drug. The leaf extracts reduced the rectal temperature by between 0.02% - 2.98% while the root bark extracts reduced it by between 0.15% - 2.55%. Aspirin reduced the elevated rectal temperature by between 1.08% - 2.53%. Results indicate that both leaf and root bark extracts of C. edulis have profound antipyretic activities comparable to the conventional antipyretic drug, aspirin.
Published: 2015

33. Antinociceptive properties of dichloromethane: methanolic leaf and root bark extracts of Carissa edulis in rats

Author: Gitahi S. Maina, Juma K. Kelvin, Mwangi B. Maina, Njagi J. Muriithi, Mworia J. Kiambi, Aliyu Umar, Mwonjoria K. John, Njoroge W. Ann, Mburu N. David, and Ngugi M. Piero
Abstract: Conventional medications are expensive and arguably associated with various severe adverse effects, hence the need to develop herbal agents that are effective as alternative. Carissa edulis (Forssk.) Vahl is the herb that has previously made thousands of people flock to a remote Loliondo village in Northern Tanzania, for its cure said to apply to all diseases such as cancer, HIV/AIDS, ulcers, hypertension, and diabetes. Although C. edulis (Forssk.)Vahl is widely used for pain in the traditional system of medicine; review of the literature shows no scientifically investigated report of its described effects. This study was, therefore, designed to bioscreen the DCM: methanolic extract of the leaf and root bark of C. edulis on anti-nociceptive potential. The plant parts were collected from Siakago-Mbeere north sub-county, Embu County, Kenya. Pain was induced into the rats experimentally using formalin. Anti-nociceptive activities in rats were compared with diclofenac (15 mg/kg) as the standard conventional drug. The leaf extract reduced pain by between 47.04% - 47.19% (in the early phase) and 38.96% - 89.26% (in the late phase) while the root bark extracts reduced it by between 21.5% - 41.89% (in the early phase) and between 21.4% - 90.62% (in the later phase). Diclofenac reduced pain by between 27.37% - 34.9% (in the early phase) and 88.24% - 90.28% (in the late phase). Further, the phytochemical screening results showed that the extract had alkaloids, flavonoids, steroids, saponins, phenolics and terpenoids which have been associated with anti-nociceptive activities. Therefore, the study has established that the DCM: methanolic extracts of C. edulis (Forssk.)Vahl are effective in the management of pain.
Published: 2015

34. Validation of the bag‐mediated filtration system for environmental surveillance of poliovirus in Nairobi, Kenya.

Author: Fagnant‐Sperati, C.S., Ren, Y., Zhou, N.A., Komen, E., Mwangi, B., Hassan, J., Chepkurui, A., Nzunza, R., Nyangao, J., Zyl, W.B., Wolfaardt, M., Matsapola, P.N., Ngwana, F.B., Jeffries‐Miles, S., Coulliette‐Salmond, A., Peñaranda, S., Vega, E., Shirai, J.H., Kossik, A.L., and Beck, N.K.
Subjects: POLIOVIRUS, POLIOMYELITIS vaccines, ORAL vaccines, DIAGNOSTIC reagents & test kits, ENVIRONMENTAL sampling
Abstract: Aims: This study compared the bag‐mediated filtration system (BMFS) and standard WHO two‐phase separation methods for poliovirus (PV) environmental surveillance, examined factors impacting PV detection and monitored Sabin‐like (SL) PV type 2 presence with withdrawal of oral polio vaccine type 2 (OPV2) in April 2016. Methods and Results: Environmental samples were collected in Nairobi, Kenya (Sept 2015–Feb 2017), concentrated via BMFS and two‐phase separation methods, then assayed using the WHO PV isolation algorithm and intratypic differentiation diagnostic screening kit. SL1, SL2 and SL3 were detected at higher rates in BMFS than two‐phase samples (P < 0·05). In BMFS samples, SL PV detection did not significantly differ with volume filtered, filtration time or filter shipment time (P > 0·05), while SL3 was detected less frequently with higher shipment temperatures (P = 0·027). SL2 was detected more frequently before OPV2 withdrawal in BMFS and two‐phase samples (P < 1 × 10−5). Conclusions: Poliovirus was detected at higher rates with the BMFS, a method that includes a secondary concentration step, than using the standard WHO two‐phase method. SL2 disappearance from the environment was commensurate with OPV2 withdrawal. Significance and Impact of the Study: The BMFS offers comparable or improved PV detection under the conditions in this study, relative to the two‐phase method. [ABSTRACT FROM AUTHOR]
Published: 2021
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35. Cortical abnormalities in bipolar disorder: an MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group

Author: Hibar, D.P., Westlye, L.T., Doan, N.T., Jahanshad, N., Cheung, J.W., Ching, C.R., Versace, A., Bilderbeck, A.C., Uhlmann, A., Mwangi, B., Kramer, B., Overs, B., Hartberg, C.B., Abe, C., Dima, D., Grotegerd, D., Sprooten, E., Boen, E., Jimenez, E., Howells, F.M., Delvecchio, G., Temmingh, H., Starke, J., Almeida, J.R. de, Goikolea, J.M., Houenou, J., Beard, L.M., Rauer, L., Abramovic, L., Bonnin, M., Ponteduro, M.F., Keil, M., Rive, M.M., Yao, N., Yalin, N., Najt, P., Rosa, P.G., Redlich, R., Trost, S., Hagenaars, S., Fears, S.C., Alonso-Lana, S., Erp, T.G. van, Nickson, T., Chaim-Avancini, T.M., Meier, T.B., Elvsashagen, T., Haukvik, U.K., Lee, W.H., Schene, A.H., Lloyd, A.J., Young, A.H., Nugent, A., Dale, A.M., Pfennig, A., McIntosh, A.M., Lafer, B., Baune, B.T., Ekman, C.J., Zarate, C.A., Bearden, C.E., Henry, C., Simhandl, C., McDonald, C., Bourne, C., Stein, D.J., Wolf, D.H., Cannon, D.M., Glahn, D.C., Veltman, D.J., Pomarol-Clotet, E., Vieta, E., Canales-Rodriguez, E.J., Nery, F.G., Duran, F.L.S., Busatto, G.F., Roberts, G., Pearlson, G.D., Goodwin, G.M., Kugel, H., Whalley, H.C., Ruhe, H.G., Soares, J.C., Fullerton, J.M., Rybakowski, J.K., Savitz, J., Chaim, K.T., Fatjo-Vilas, M., Soeiro-de-Souza, M.G., Boks, M.P., Zanetti, M.V., Otaduy, M.C.G., Schaufelberger, M.S., Alda, M., Ingvar, M., Phillips, M.L., Kempton, M.J., Bauer, M., Landen, M., Lawrence, N.S., Hibar, D.P., Westlye, L.T., Doan, N.T., Jahanshad, N., Cheung, J.W., Ching, C.R., Versace, A., Bilderbeck, A.C., Uhlmann, A., Mwangi, B., Kramer, B., Overs, B., Hartberg, C.B., Abe, C., Dima, D., Grotegerd, D., Sprooten, E., Boen, E., Jimenez, E., Howells, F.M., Delvecchio, G., Temmingh, H., Starke, J., Almeida, J.R. de, Goikolea, J.M., Houenou, J., Beard, L.M., Rauer, L., Abramovic, L., Bonnin, M., Ponteduro, M.F., Keil, M., Rive, M.M., Yao, N., Yalin, N., Najt, P., Rosa, P.G., Redlich, R., Trost, S., Hagenaars, S., Fears, S.C., Alonso-Lana, S., Erp, T.G. van, Nickson, T., Chaim-Avancini, T.M., Meier, T.B., Elvsashagen, T., Haukvik, U.K., Lee, W.H., Schene, A.H., Lloyd, A.J., Young, A.H., Nugent, A., Dale, A.M., Pfennig, A., McIntosh, A.M., Lafer, B., Baune, B.T., Ekman, C.J., Zarate, C.A., Bearden, C.E., Henry, C., Simhandl, C., McDonald, C., Bourne, C., Stein, D.J., Wolf, D.H., Cannon, D.M., Glahn, D.C., Veltman, D.J., Pomarol-Clotet, E., Vieta, E., Canales-Rodriguez, E.J., Nery, F.G., Duran, F.L.S., Busatto, G.F., Roberts, G., Pearlson, G.D., Goodwin, G.M., Kugel, H., Whalley, H.C., Ruhe, H.G., Soares, J.C., Fullerton, J.M., Rybakowski, J.K., Savitz, J., Chaim, K.T., Fatjo-Vilas, M., Soeiro-de-Souza, M.G., Boks, M.P., Zanetti, M.V., Otaduy, M.C.G., Schaufelberger, M.S., Alda, M., Ingvar, M., Phillips, M.L., Kempton, M.J., Bauer, M., Landen, M., and Lawrence, N.S.
Abstract: Contains fulltext : 191289.pdf (publisher's version ) (Open Access), Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 x 10(-21)), left fusiform gyrus (d=-0.288; P=8.25 x 10(-21)) and left rostral middle frontal cortex (d=-0.276; P=2.99 x 10(-19)). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.
Published: 2018

36. Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Author: Nunes, A. (Abraham), Schnack, H. (Hugo), Ching, C.R.K. (Christopher), Agartz, I. (Ingrid), Akudjedu, T.N. (Theophilus N.), Alda, M. (Martin), Alnæs, D. (Dag), Alonso-Lana, S. (Silvia), Bauer, J. (Jochen), Baune, B.T., Bøen, E. (Erlend), Bonnin, C.M. (Caterina del Mar), Busatto, G.F. (Geraldo F.), Canales-Rodríguez, E.J. (Erick J.), Cannon, D.M. (Dara), Caseras, X. (Xavier), Chaim-Avancini, T.M. (Tiffany M.), Dannlowski, U. (Udo), Díaz-Zuluaga, A.M. (Ana M.), Dietsche, B. (Bruno), Doan, N.T. (Nhat Trung), Duchesnay, E. (Edouard), Elvsåshagen, T. (Torbjørn), Emden, D. (Daniel), Eyler, L.T. (Lisa T.), Fatjó-Vilas, M. (Mar), Favre, P. (Pauline), Foley, S.F. (Sonya F.), Fullerton, J.M. (Janice M.), Glahn, D.C. (David), Goikolea, J.M. (Jose M.), Grotegerd, D. (Dominik), Hahn, T. (Tim), Henry, C. (C.), Hibar, D.P. (Derrek P.), Houenou, J. (Josselin), Howells, F.M. (Fleur M.), Jahanshad, N. (Neda), Kaufmann, T. (Tobias), Kenney, J. (Joanne), Kircher, T.T.J. (Tilo T. J.), Krug, A. (Axel), Lagerberg, T.V. (Trine V.), Lenroot, R.K. (Rhoshel), López-Jaramillo, C. (Carlos), Machado-Vieira, R. (Rodrigo), Malt, U.F. (Ulrik), McDonald, C. (Colm), Mitchell, P.B. (Philip B.), Mwangi, B. (Benson), Nabulsi, L. (Leila), Opel, N. (Nils), Overs, B.J. (Bronwyn J.), Pineda-Zapata, J.A. (Julian A.), Pomarol-Clotet, E. (Edith), Redlich, R. (Ronny), Roberts, G. (Gloria), Rosa, P.G. (Pedro G.), Salvador, R. (Raymond), Satterthwaite, T.D. (Theodore), Soares, J.C. (Jair C.), Stein, D.J. (Dan), Temmingh, H.S. (Henk S.), Trappenberg, T. (Thomas), Uhlmann, A. (Anne), van Haren, N.E.M. (Neeltje E. M.), Vieta, E. (Eduard), Westlye, L.T. (Lars), Wolf, D.H. (Daniel H.), Yüksel, D. (Dilara), Zanetti, M.V. (Marcus V.), Andreassen, O.A. (Ole), Thompson, P.M. (Paul), Hajek, T. (Tomas), Nunes, A. (Abraham), Schnack, H. (Hugo), Ching, C.R.K. (Christopher), Agartz, I. (Ingrid), Akudjedu, T.N. (Theophilus N.), Alda, M. (Martin), Alnæs, D. (Dag), Alonso-Lana, S. (Silvia), Bauer, J. (Jochen), Baune, B.T., Bøen, E. (Erlend), Bonnin, C.M. (Caterina del Mar), Busatto, G.F. (Geraldo F.), Canales-Rodríguez, E.J. (Erick J.), Cannon, D.M. (Dara), Caseras, X. (Xavier), Chaim-Avancini, T.M. (Tiffany M.), Dannlowski, U. (Udo), Díaz-Zuluaga, A.M. (Ana M.), Dietsche, B. (Bruno), Doan, N.T. (Nhat Trung), Duchesnay, E. (Edouard), Elvsåshagen, T. (Torbjørn), Emden, D. (Daniel), Eyler, L.T. (Lisa T.), Fatjó-Vilas, M. (Mar), Favre, P. (Pauline), Foley, S.F. (Sonya F.), Fullerton, J.M. (Janice M.), Glahn, D.C. (David), Goikolea, J.M. (Jose M.), Grotegerd, D. (Dominik), Hahn, T. (Tim), Henry, C. (C.), Hibar, D.P. (Derrek P.), Houenou, J. (Josselin), Howells, F.M. (Fleur M.), Jahanshad, N. (Neda), Kaufmann, T. (Tobias), Kenney, J. (Joanne), Kircher, T.T.J. (Tilo T. J.), Krug, A. (Axel), Lagerberg, T.V. (Trine V.), Lenroot, R.K. (Rhoshel), López-Jaramillo, C. (Carlos), Machado-Vieira, R. (Rodrigo), Malt, U.F. (Ulrik), McDonald, C. (Colm), Mitchell, P.B. (Philip B.), Mwangi, B. (Benson), Nabulsi, L. (Leila), Opel, N. (Nils), Overs, B.J. (Bronwyn J.), Pineda-Zapata, J.A. (Julian A.), Pomarol-Clotet, E. (Edith), Redlich, R. (Ronny), Roberts, G. (Gloria), Rosa, P.G. (Pedro G.), Salvador, R. (Raymond), Satterthwaite, T.D. (Theodore), Soares, J.C. (Jair C.), Stein, D.J. (Dan), Temmingh, H.S. (Henk S.), Trappenberg, T. (Thomas), Uhlmann, A. (Anne), van Haren, N.E.M. (Neeltje E. M.), Vieta, E. (Eduard), Westlye, L.T. (Lars), Wolf, D.H. (Daniel H.), Yüksel, D. (Dilara), Zanetti, M.V. (Marcus V.), Andreassen, O.A. (Ole), Thompson, P.M. (Paul), and Hajek, T. (Tomas)
Abstract: Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the resul
Published: 2018
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37. Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group

Author: Schmaal, L. (L.), Hibar, D.P. (D. P.), Sämann, P.G. (Philipp), Hall, G.B. (Garry), Baune, B.T., Jahanshad, N. (Neda), Cheung, J.W. (J. W.), Erp, T.G.M. (Theo G.) van, Bos, D. (Daniel), Ikram, M.K. (Kamran), Vernooij, M.W. (Meike), Niessen, W.J. (Wiro), Tiemeier, H.W. (Henning), Hofman, A. (Albert), Wittfeld, K. (Katharina), Grabe, H.J. (Hans Jörgen), Janowitz, D. (Deborah), Bülow, R. (R.), Selonke, M. (M.), Völzke, H. (Henry), Grotegerd, D. (D.), Dannlowski, U. (U.), Arolt, V. (Volker), Opel, N. (N.), Heindel, W. (W.), Kugel, H. (H.), Hoehn, D. (David), Czisch, M. (Michael), Couvy-Duchesne, B. (Baptiste), Rentería, M.E. (Miguel), Strike, L.T. (Lachlan), Wright, M.J. (Margaret), Mills, N.T., Zubicaray, G.I. (Greig) de, Mcmahon, K.L. (Katie), Medland, S.E. (Sarah), Martin, N.G. (Nicholas), Gillespie, N.A. (N. A.), Goya-Maldonado, R., Gruber, O. (Oliver), Krämer, B.K. (Bernhard), Hatton, W., Lagopoulos, J. (Jim), Hickie, I.B. (Ian), Frodl, T. (Thomas), Carballedo, A., Frey, E.M., Van Velzen, L.S., Penninx, B.W.J.H. (Brenda), Tol, M.J.D. (Marie-José) van, Wee, N.J. (Nic) van der, Davey, C.G. (Christopher), Harrison, B.J. (B. J.), Mwangi, B. (Benson), Cao, B. (B.), Soares, J.C. (J. C.), Veer, I.M. (Ilya), Walter, H.J. (Henrik), Schoepf, D., Zurowski, B., Konrad, C. (C.), Schramm, E. (E.), Normann, C., Schnell, K. (Kerry), Sacchet, M.D. (M. D.), Gotlib, I.H. (I. H.), MacQueen, G.M. (Glenda), Godlewska, B. (Beata), Nickson, T., McIntosh, A.M. (Andrew), Papmeyer, M. (Martina), Whalley, H.C. (H. C.), Hall, J. (Jeremy), Sussmann, J. (Jessika), Li, M. (M.), Walter, M. (M.), Aftanas, L. (L.), Brack, I. (I.), Bokhan, N.A. (N. A.), Thompson, P.M. (Paul), Veltman, D.J. (Dick), Schmaal, L. (L.), Hibar, D.P. (D. P.), Sämann, P.G. (Philipp), Hall, G.B. (Garry), Baune, B.T., Jahanshad, N. (Neda), Cheung, J.W. (J. W.), Erp, T.G.M. (Theo G.) van, Bos, D. (Daniel), Ikram, M.K. (Kamran), Vernooij, M.W. (Meike), Niessen, W.J. (Wiro), Tiemeier, H.W. (Henning), Hofman, A. (Albert), Wittfeld, K. (Katharina), Grabe, H.J. (Hans Jörgen), Janowitz, D. (Deborah), Bülow, R. (R.), Selonke, M. (M.), Völzke, H. (Henry), Grotegerd, D. (D.), Dannlowski, U. (U.), Arolt, V. (Volker), Opel, N. (N.), Heindel, W. (W.), Kugel, H. (H.), Hoehn, D. (David), Czisch, M. (Michael), Couvy-Duchesne, B. (Baptiste), Rentería, M.E. (Miguel), Strike, L.T. (Lachlan), Wright, M.J. (Margaret), Mills, N.T., Zubicaray, G.I. (Greig) de, Mcmahon, K.L. (Katie), Medland, S.E. (Sarah), Martin, N.G. (Nicholas), Gillespie, N.A. (N. A.), Goya-Maldonado, R., Gruber, O. (Oliver), Krämer, B.K. (Bernhard), Hatton, W., Lagopoulos, J. (Jim), Hickie, I.B. (Ian), Frodl, T. (Thomas), Carballedo, A., Frey, E.M., Van Velzen, L.S., Penninx, B.W.J.H. (Brenda), Tol, M.J.D. (Marie-José) van, Wee, N.J. (Nic) van der, Davey, C.G. (Christopher), Harrison, B.J. (B. J.), Mwangi, B. (Benson), Cao, B. (B.), Soares, J.C. (J. C.), Veer, I.M. (Ilya), Walter, H.J. (Henrik), Schoepf, D., Zurowski, B., Konrad, C. (C.), Schramm, E. (E.), Normann, C., Schnell, K. (Kerry), Sacchet, M.D. (M. D.), Gotlib, I.H. (I. H.), MacQueen, G.M. (Glenda), Godlewska, B. (Beata), Nickson, T., McIntosh, A.M. (Andrew), Papmeyer, M. (Martina), Whalley, H.C. (H. C.), Hall, J. (Jeremy), Sussmann, J. (Jessika), Li, M. (M.), Walter, M. (M.), Aftanas, L. (L.), Brack, I. (I.), Bokhan, N.A. (N. A.), Thompson, P.M. (Paul), and Veltman, D.J. (Dick)
Abstract: The neuro-anatomical substrates of major depressive disorder (MDD) are still not well understood, despite many neuroimaging studies over the past few decades. Here we present the largest ever worldwide study by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Major Depressive Disorder Working Group on cortical structural alterations in MDD. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2148 MDD patients and 7957 healthy controls were analysed with harmonized protocols at 20 sites around the world. To detect consistent effects of MDD and its modulators on cortical thickness and surface area estimates derived from MRI, statistical effects from sites were meta-analysed separately for adults and adolescents. Adults with MDD had thinner cortical gray matter than controls in the orbitofrontal cortex (OFC), anterior and posterior cingulate, insula and temporal lobes (Cohen's d effect sizes: -0.10 to -0.14). These effects were most pronounced in first episode and adult-onset patients (>21 years). Compared to matched controls, adolescents with MDD had lower total surface area (but no differences in cortical thickness) and regional reductions in frontal regions (medial OFC and superior frontal gyrus) and primary and higher-order visual, somatosensory and motor areas (d: -0.26 to -0.57). The strongest effects were found in recurrent adolescent patients. This highly powered global effort to identify consistent brain abnormalities showed widespread cortical alterations in MDD patients as compared to controls and suggests that MDD may impact brain structure in a highly dynamic way, with different patterns of alterations at different stages of life.
Published: 2017
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38. Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

Author: Guadalupe, T, Mathias, SR, vanErp, TGM, Whelan, CD, Zwiers, MP, Abe, Y, Abramovic, L, Agartz, I, Andreassen, OA, Arias-Vásquez, A, Aribisala, BS, Armstrong, NJ, Arolt, V, Artiges, E, Ayesa-Arriola, R, Baboyan, VG, Banaschewski, T, Barker, G, Bastin, ME, Baune, BT, Blangero, J, Bokde, ALW, Boedhoe, PSW, Bose, A, Brem, S, Brodaty, H, Bromberg, U, Brooks, S, Büchel, C, Buitelaar, J, Calhoun, VD, Cannon, DM, Cattrell, A, Cheng, Y, Conrod, PJ, Conzelmann, A, Corvin, A, Crespo-Facorro, B, Crivello, F, Dannlowski, U, de Zubicaray, GI, de Zwarte, SMC, Deary, IJ, Desrivières, S, Doan, NT, Donohoe, G, Dørum, ES, Ehrlich, S, Espeseth, T, Fernández, G, Flor, H, Fouche, J-P, Frouin, V, Fukunaga, M, Gallinat, J, Garavan, H, Gill, M, Suarez, AG, Gowland, P, Grabe, HJ, Grotegerd, D, Gruber, O, Hagenaars, S, Hashimoto, R, Hauser, TU, Heinz, A, Hibar, DP, Hoekstra, PJ, Hoogman, M, Howells, FM, Hu, H, Hulshoff Pol, HE, Huyser, C, Ittermann, B, Jahanshad, N, Jönsson, EG, Jurk, S, Kahn, RS, Kelly, S, Kraemer, B, Kugel, H, Kwon, JS, Lemaitre, H, Lesch, K-P, Lochner, C, Luciano, M, Marquand, AF, Martin, NG, Martínez-Zalacaín, I, Martinot, J-L, Mataix-Cols, D, Mather, K, McDonald, C, McMahon, KL, Medland, SE, Menchón, JM, Morris, DW, Mothersill, O, Maniega, SM, Mwangi, B, Nakamae, T, Nakao, T, Narayanaswaamy, JC, Nees, F, Nordvik, JE, Onnink, AMH, Opel, N, Ophoff, R, Paillère Martinot, M-L, Papadopoulos Orfanos, D, Pauli, P, Paus, T, Poustka, L, Reddy, JY, Renteria, ME, Roiz-Santiáñez, R, Roos, A, Royle, NA, Sachdev, P, Sánchez-Juan, P, Schmaal, L, Schumann, G, Shumskaya, E, Smolka, MN, Soares, JC, Soriano-Mas, C, Stein, DJ, Strike, LT, Toro, R, Turner, JA, Tzourio-Mazoyer, N, Uhlmann, A, Hernández, MV, van den Heuvel, OA, van der Meer, D, van Haren, NEM, Veltman, DJ, Venkatasubramanian, G, Vetter, NC, Vuletic, D, Walitza, S, Walter, H, Walton, E, Wang, Z, Wardlaw, J, Wen, W, Westlye, LT, Whelan, R, Wittfeld, K, Wolfers, T, Wright, MJ, Xu, J, Xu, X, Yun, J-Y, Zhao, J, Franke, B, Thompson, PM, Glahn, DC, Mazoyer, B, Fisher, SE, Francks, C, Guadalupe, T, Mathias, SR, vanErp, TGM, Whelan, CD, Zwiers, MP, Abe, Y, Abramovic, L, Agartz, I, Andreassen, OA, Arias-Vásquez, A, Aribisala, BS, Armstrong, NJ, Arolt, V, Artiges, E, Ayesa-Arriola, R, Baboyan, VG, Banaschewski, T, Barker, G, Bastin, ME, Baune, BT, Blangero, J, Bokde, ALW, Boedhoe, PSW, Bose, A, Brem, S, Brodaty, H, Bromberg, U, Brooks, S, Büchel, C, Buitelaar, J, Calhoun, VD, Cannon, DM, Cattrell, A, Cheng, Y, Conrod, PJ, Conzelmann, A, Corvin, A, Crespo-Facorro, B, Crivello, F, Dannlowski, U, de Zubicaray, GI, de Zwarte, SMC, Deary, IJ, Desrivières, S, Doan, NT, Donohoe, G, Dørum, ES, Ehrlich, S, Espeseth, T, Fernández, G, Flor, H, Fouche, J-P, Frouin, V, Fukunaga, M, Gallinat, J, Garavan, H, Gill, M, Suarez, AG, Gowland, P, Grabe, HJ, Grotegerd, D, Gruber, O, Hagenaars, S, Hashimoto, R, Hauser, TU, Heinz, A, Hibar, DP, Hoekstra, PJ, Hoogman, M, Howells, FM, Hu, H, Hulshoff Pol, HE, Huyser, C, Ittermann, B, Jahanshad, N, Jönsson, EG, Jurk, S, Kahn, RS, Kelly, S, Kraemer, B, Kugel, H, Kwon, JS, Lemaitre, H, Lesch, K-P, Lochner, C, Luciano, M, Marquand, AF, Martin, NG, Martínez-Zalacaín, I, Martinot, J-L, Mataix-Cols, D, Mather, K, McDonald, C, McMahon, KL, Medland, SE, Menchón, JM, Morris, DW, Mothersill, O, Maniega, SM, Mwangi, B, Nakamae, T, Nakao, T, Narayanaswaamy, JC, Nees, F, Nordvik, JE, Onnink, AMH, Opel, N, Ophoff, R, Paillère Martinot, M-L, Papadopoulos Orfanos, D, Pauli, P, Paus, T, Poustka, L, Reddy, JY, Renteria, ME, Roiz-Santiáñez, R, Roos, A, Royle, NA, Sachdev, P, Sánchez-Juan, P, Schmaal, L, Schumann, G, Shumskaya, E, Smolka, MN, Soares, JC, Soriano-Mas, C, Stein, DJ, Strike, LT, Toro, R, Turner, JA, Tzourio-Mazoyer, N, Uhlmann, A, Hernández, MV, van den Heuvel, OA, van der Meer, D, van Haren, NEM, Veltman, DJ, Venkatasubramanian, G, Vetter, NC, Vuletic, D, Walitza, S, Walter, H, Walton, E, Wang, Z, Wardlaw, J, Wen, W, Westlye, LT, Whelan, R, Wittfeld, K, Wolfers, T, Wright, MJ, Xu, J, Xu, X, Yun, J-Y, Zhao, J, Franke, B, Thompson, PM, Glahn, DC, Mazoyer, B, Fisher, SE, and Francks, C
Abstract: The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders.
Published: 2017

39. In Vitro Anti-Acetylcholinesterase Activity of Dichloromethane Leaf Extracts of Carphalea glaucescens in Chilo partellus Larvae

Author: Mwangi B. Maina, Njagi J. Muriithi, Matheri Felix, Aliyu Umar, Njoroge W Anne, Ngugi M Piero, Gitahi S Maina, Mworia J. Kiambi, and Ngure G Mutero
Subjects: chemistry.chemical_classification, biology, Aché, fungi, General Medicine, Chilo, biology.organism_classification, Terpenoid, language.human_language, chemistry.chemical_compound, Enzyme, Phytochemical, chemistry, Biochemistry, medicine, language, Phenols, IC50, Acetylcholine, medicine.drug
Abstract: Acetlycholinesterase (AChE) hydrolyses the neurotransmitter acetylcholine resulting in the termination of nerve impulse at the synapse. Anti-acetylcholinesterase activities stop the passage of the nerve impulse at the synapse resulting in continuous stimulation which can lead to death. The manufacturers of many pesticides target the AChE because it interferes with the passage of the nerve impulse. In vitro study revealed that DCM leaf extract of Carphalea glaucescens has anti-acetylcholinesterase activity against crude acetlycholinesterase (AChE) enzyme extracted from Chilo partellus and an IC50 of 12.02 mg/ml was calculated. After qualitative phytochemical screening was carried out the phytochemicals which were present were tannins, phenols, flavonoids, steroids, terpenoids and alkaloids.
Published: 2016

40. Bio Efficacy of Aqueous Crude Fruit Sap Extract of Solanum incanum against Green Peach Aphids Myzus persicae Sulzer (Homoptera: Aphididae)

Author: Mworia J. Kiambi, Allan Jalemba Mgutu, Mwonjoria K. John, Aliyu Umar, Gitahi S Maina, Ngugi M Piero, Ngure G Mutero, Njoroge W. Ann, Mwangi B. Maina, and Njagi J. Muriithi
Subjects: Aphid, biology, Homoptera, food and beverages, Aphididae, Pesticide, biology.organism_classification, chemistry.chemical_compound, Horticulture, Phytochemical, chemistry, Solanum incanum, Myzus persicae, Dimethoate
Abstract: Conventional insecticides are expensive and arguably associated with various severe adverse side effects hence the need to develop botanical pesticides that are effective as alternative. Though S. incanum fruits sap has been used by the local farmers to control aphids, literature show no scientifically investigated report of its effectiveness and the mode of its insecticidal action. This study was therefore designed to evaluate anti-aphids properties of crude fruit sap extract of S. incanum. A total of 180 kales were planted in the Plant Transformation Laboratory of Kenyatta University. They were divided into six groups with 10 plant stands each. Each group was subjected to routine spray with 10, 25, 50 and 75% S. incanum extract. Dimethoate was utilized as reference insecticide while the last group was not sprayed. The number of live and dead aphids was counted for two weeks after every pray in each group with an interval of one day to determine the deterrent and insecticidal activity. The extract at different tested concentrations showed some level of insecticidal and deterrent activities against green peach aphid. Further, phytochemical screening results showed that the crude fruits sap extract of S. incanum have phytochemicals associated with insecticidal and deterrent activity. The study has established that the crude fruits sap extract of S. incanum are effective in managing insects’ pest.
Published: 2016

41. Brain gyrification and neuroprogression in bipolar disorder

Author: Cao, B., primary, Passos, I. C., additional, Wu, M.-J., additional, Zunta-Soares, G. B., additional, Mwangi, B., additional, and Soares, J. C., additional
Published: 2017
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42. In Vitro Anti-Acetylcholinesterase Activity of Crude Fruits Sap Extract of Solanum incanum in Green Peach Aphids

Author: Mwonjoria K. John, Njagi J. Muriithi, Aliyu Umar, Ngugi M Piero, Ngure G Mutero, Njoroge W. Ann, Allan Jalemba Mgutu, Mworia J. Kiambi, Mwangi B. Maina, and Gitahi S Maina
Subjects: chemistry.chemical_classification, biology, Aché, food and beverages, biochemical phenomena, metabolism, and nutrition, biology.organism_classification, Acetylcholinesterase, In vitro, language.human_language, chemistry.chemical_compound, Hydrolysis, Enzyme, chemistry, Botany, language, medicine, Solanum incanum, Food science, IC50, Acetylcholine, medicine.drug
Abstract: Acetylcholinesterase is a key enzyme that terminates nerve impulses by catalyzing the hydrolysis of neurotransmitter, acetylcholine, in the nervous system in various organisms. Irreversible inhibitors have been developed as insecticides such as organophosphates and carbamates. Aqueous crude fruit sap extract of S. incanum was evaluated for acetylcholinesterase activity in green peach aphids using Ellman’s method and is found active in inhibiting the ACHe of green peach aphids. All tested concentrations of crude fruits sap extract of S. incanum possessed the ability to inhibit acetylcholinesterase of green peach aphids at dose dependent manner and IC50 of 49.9 was calculated. This study suggest that aqueous crude fruit sap extract of S. incanum inhibit the acetylcholinesterase of the green peach aphids and it is possible the extract has compounds that increase both the level and duration of the neurotransmitter action.
Published: 2015

43. Antinociceptive Properties of Dichloromethane:Methanolic Leaf Extracts of Caesalpinia volkensii and Maytenus obscura in Animal Models

Author: Ngure G Mutero, Aliyu Umar, Ngugi M Piero, Mburu N. David, Mwonjoria K. John, Mworia J. Kiambi, Njoroge W. Ann, Juma K Kelvin, Gitahi S Maina, Mwangi B. Maina, and Njagi J. Muriithi
Subjects: biology, business.industry, Maytenus, food and beverages, Pharmacology, biology.organism_classification, Terpenoid, Carrageenan, chemistry.chemical_compound, Nociception, Diclofenac, Caesalpinia volkensii, Phytochemical, chemistry, Medicine, Early phase, business, medicine.drug
Abstract: The purpose of physiological pain is protection. Pain is associated with high morbidity and socioeconomic burden. Conventional medication of pain is expensive and arguably associated with various severe adverse effects hence the need to develop herbal agents that are effective as alternative. This study was designed to evaluate the antinociceptive of C. volkensii and M. obscura growing in Embu County, Kenya. Experimental animals were divided into four groups; normal group, diseased negative control group, diseased reference group and diseased experimental groups. Pain was induced into rats using formalin. The experimental groups were treated with leaf extracts of the plants at dose levels of 50 mg/kg, 100 mg/kg and 150 mg/kg. Anti-nociceptive activities in rats were compared with diclofenac (15 mg/kg) as the standard conventional drug. In antinociceptive study, the leaf extract C. volkensii reduced pain by between 6.82-15.24% only in the early phase while the leaf extracts of M. obscura reduced pain by between 12.39-34.81% (in the early phase) and between 6.4-12.4% (in the late phase). Diclofenac reduced pain by between 7.58-9.66% (in the early phase) and by 69.87% in the late phase. Further, the phytochemical screening results showed that the extracts of C. volkensii had flavonoids, steroids and phenolics while the leaf extracts M. obscura had phenolics, terpenoids and saponins. flavonoids. Therefore, the study has established that the DCM: methanolic leaf extracts of Caesalpinia volkensii and Maytenus obscura are effective in management of pain.
Published: 2015

44. Determination of Hematological Effects of Methanolic Leaf Extract of Vernonia lasiopus in Normal Mice

Author: Aliyu Umar, Mworia J. Kiambi, Gitahi S Maina, Njagi Nm Eliud, Njoroge W. Ann, Mwonjoria K. John, Njagi J. Muriithi, Mwangi B. Maina, Juma K Kelvin, and Ngugi M Piero
Subjects: Hematological disorders, Traditional medicine, Phytochemical, business.industry, Chemical constituents, Immunology, Therapeutic effect, Vernonia lasiopus, Medicine, Medicinal plants, business, Thrombopoietin
Abstract: Hematologicarl disordes have attained epidemic proportions worldwide today. As a result, many people turn to medicinal plants for treatment thereby boosting and enhancing health because professional care is not immediately available, is too inconvenient, costly and time consuming. Certain medicinal plants are believed to promote positive health and maintain organic resistance against infection. The use of medicinal plants which are readily available and arguably efficacious would therefore over a better and affordable alternative for boosting and enhancing health. Assessment of hematological parameters can be used to determine the extent of deleterious effect of foreign compounds including plant extracts on the bloodconstituents of an animal. Various chemical constituents of Vernonia lasiopus are believed to possess therapeutic effects on hematological parameters. However, these effects have not been subjected to systematic studies to substantiate the therapeutic claims made regarding their clinical utility. This study was designed to investigate the hematological effects of V. lasiopus (O. Hoffman) in normal mice. The experimental groups were treated with leaf extracts at concentration of 50 mg/kg and 100 mg/kg orally once per two days for a period of fourteen days. Hematological parameters and indices were determined from unclotted blood samples using standard protocols. Presence of various types of phytochemicals was assessed using standard procedures. The leaf extract of V. lasiopus (O. Hoffman) induced changes in erythrocytes and related parameter profiles, total and differential WBC counts, platelets and their related parameters in normal mice at the two tested dose levels of 50 mg/kgbw and 100 mg/kgbw. Further, the phytochemical screening results showed that the leaf extract of V. lasiopus (O. Hoffman) have phytochemicals associated with erythropoietin promoting activity, immunostimulatory activities and thrombopoietin stimulation.
Published: 2015

45. Subcortical volumetric abnormalities in bipolar disorder

Author: Hibar, D. P., Westlye, L. T., Van Erp, T. G M, Rasmussen, J., Leonardo, C. D., Faskowitz, J., Haukvik, U. K., Hartberg, C. B., Doan, N. T., Agartz, I., Dale, A. M., Gruber, O., Krämer, B., Trost, S., Liberg, B., Abé, C., Ekman, C. J., Ingvar, M., Landén, M., Fears, S. C., Freimer, N. B., Bearden, C. E., Sprooten, E., Glahn, D. C., Pearlson, G. D., Emsell, L., Kenney, J., Scanlon, C., McDonald, C., Cannon, D. M., Almeida, J., Versace, A., Caseras, X., Lawrence, N. S., Phillips, M. L., Dima, D., Delvecchio, G., Frangou, S., Satterthwaite, T. D., Wolf, D., Houenou, J., Henry, C., Malt, U. F., BØen, E., Elvs'shagen, T., Young, A. H., Lloyd, A. J., Goodwin, G. M., Mackay, C. E., Bourne, C., Bilderbeck, A., Abramovic, L., Boks, M. P., Van Haren, N. E M, Ophoff, R. A., Kahn, R. S., Bauer, M., Pfennig, A., Alda, M., Hajek, T., Mwangi, B., Soares, J. C., Nickson, T., Dimitrova, R., Sussmann, J. E., Hagenaars, S., Whalley, H. C., McIntosh, A. M., Thompson, P. M., Andreassen, O. A., Hibar, D. P., Westlye, L. T., Van Erp, T. G M, Rasmussen, J., Leonardo, C. D., Faskowitz, J., Haukvik, U. K., Hartberg, C. B., Doan, N. T., Agartz, I., Dale, A. M., Gruber, O., Krämer, B., Trost, S., Liberg, B., Abé, C., Ekman, C. J., Ingvar, M., Landén, M., Fears, S. C., Freimer, N. B., Bearden, C. E., Sprooten, E., Glahn, D. C., Pearlson, G. D., Emsell, L., Kenney, J., Scanlon, C., McDonald, C., Cannon, D. M., Almeida, J., Versace, A., Caseras, X., Lawrence, N. S., Phillips, M. L., Dima, D., Delvecchio, G., Frangou, S., Satterthwaite, T. D., Wolf, D., Houenou, J., Henry, C., Malt, U. F., BØen, E., Elvs'shagen, T., Young, A. H., Lloyd, A. J., Goodwin, G. M., Mackay, C. E., Bourne, C., Bilderbeck, A., Abramovic, L., Boks, M. P., Van Haren, N. E M, Ophoff, R. A., Kahn, R. S., Bauer, M., Pfennig, A., Alda, M., Hajek, T., Mwangi, B., Soares, J. C., Nickson, T., Dimitrova, R., Sussmann, J. E., Hagenaars, S., Whalley, H. C., McIntosh, A. M., Thompson, P. M., and Andreassen, O. A.
Published: 2016

46. Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

Author: Guadalupe, T., Mathias, S.R., vanErp, T.G.M., Whelan, C.D., Zwiers, M.P., Abe, Y., Abramovic, L., Agartz, I., Andreassen, O.A., Arias-Vasquez, A., Aribisala, B.S., Armstrong, N.J., Arolt, V., Artiges, E., Ayesa-Arriola, R., Baboyan, V.G., Banaschewski, T., Barker, G., Bastin, M.E., Baune, B.T., Blangero, J., Bokde, A.L.W., Boedhoe, P.S.W., Bose, A., Brem, S., Brodaty, H., Bromberg, U., Brooks, S., Büchel, C., Buitelaar, J., Calhoun, V.D., Cannon, D.M., Cattrell, A., Cheng, Y., Conrod, P.J., Conzelmann, A., Corvin, A., Crespo-Facorro, B., Crivello, F., Dannlowski, U., de Zubicaray, G.I., de Zwarte, S.M.C., Deary, I.J., Desrivières, S., Doan, N.T., Donohoe, G., Dørum, E.S., Ehrlich, S., Espeseth, T., Fernández, G., Flor, H., Fouche, J-P, Frouin, V., Fukunaga, M., Gallinat, J., Garavan, H., Gill, M., Suarez, A.G., Gowland, P., Grabe, H.J., Grotegerd, D., Gruber, O., Hagenaars, S., Hashimoto, R., Hauser, T.U., Heinz, A., Hibar, D.P., Hoekstra, P.J., Hoogman, M., Howells, F.M., Hu, H., Hulshoff Pol, H.E., Huyser, C., Ittermann, B., Jahanshad, N., Jönsson, E.G., Jurk, S., Kahn, R.S., Kelly, S., Kraemer, B., Kugel, H., Kwon, J.S., Lemaitre, H., Lesch, K-P, Lochner, C., Luciano, M., Marquand, A.F., Martin, N.G., Martínez-Zalacaín, I., Martinot, J-L, Mataix-Cols, D., Mather, K., McDonald, C., McMahon, K.L., Medland, S.E., Menchón, J.M., Morris, D.W., Mothersill, O., Maniega, S.M., Mwangi, B., Nakamae, T., Nakao, T., Narayanaswaamy, J.C., Nees, F., Nordvik, J.E., Onnink, A.M.H., Opel, N., Ophoff, R., Paillère Martinot, M-L, Papadopoulos Orfanos, D., Pauli, P., Paus, T., Poustka, L., Reddy, J.YC., Renteria, M.E., Roiz-Santiáñez, R., Roos, A., Royle, N.A., Sachdev, P., Sánchez-Juan, P., Schmaal, L., Schumann, G., Shumskaya, E., Smolka, M.N., Soares, J.C., Soriano-Mas, C., Stein, D.J., Strike, L.T., Toro, R., Turner, J.A., Tzourio-Mazoyer, N., Uhlmann, A., Hernández, M.V., van den Heuvel, O.A., van der Meer, D., van Haren, N.E.M ., Veltman, D.J., Venkatasubramanian, G., Vetter, N.C., Vuletic, D., Walitza, S., Walter, H., Walton, E., Wang, Z., Wardlaw, J., Wen, W., Westlye, L.T., Whelan, R., Wittfeld, K., Wolfers, T., Wright, M.J., Xu, J., Xu, X., Yun, J-Y, Zhao, J.J., Franke, B., Thompson, P.M., Glahn, D.C., Mazoyer, B., Fisher, S.E., Francks, C., Guadalupe, T., Mathias, S.R., vanErp, T.G.M., Whelan, C.D., Zwiers, M.P., Abe, Y., Abramovic, L., Agartz, I., Andreassen, O.A., Arias-Vasquez, A., Aribisala, B.S., Armstrong, N.J., Arolt, V., Artiges, E., Ayesa-Arriola, R., Baboyan, V.G., Banaschewski, T., Barker, G., Bastin, M.E., Baune, B.T., Blangero, J., Bokde, A.L.W., Boedhoe, P.S.W., Bose, A., Brem, S., Brodaty, H., Bromberg, U., Brooks, S., Büchel, C., Buitelaar, J., Calhoun, V.D., Cannon, D.M., Cattrell, A., Cheng, Y., Conrod, P.J., Conzelmann, A., Corvin, A., Crespo-Facorro, B., Crivello, F., Dannlowski, U., de Zubicaray, G.I., de Zwarte, S.M.C., Deary, I.J., Desrivières, S., Doan, N.T., Donohoe, G., Dørum, E.S., Ehrlich, S., Espeseth, T., Fernández, G., Flor, H., Fouche, J-P, Frouin, V., Fukunaga, M., Gallinat, J., Garavan, H., Gill, M., Suarez, A.G., Gowland, P., Grabe, H.J., Grotegerd, D., Gruber, O., Hagenaars, S., Hashimoto, R., Hauser, T.U., Heinz, A., Hibar, D.P., Hoekstra, P.J., Hoogman, M., Howells, F.M., Hu, H., Hulshoff Pol, H.E., Huyser, C., Ittermann, B., Jahanshad, N., Jönsson, E.G., Jurk, S., Kahn, R.S., Kelly, S., Kraemer, B., Kugel, H., Kwon, J.S., Lemaitre, H., Lesch, K-P, Lochner, C., Luciano, M., Marquand, A.F., Martin, N.G., Martínez-Zalacaín, I., Martinot, J-L, Mataix-Cols, D., Mather, K., McDonald, C., McMahon, K.L., Medland, S.E., Menchón, J.M., Morris, D.W., Mothersill, O., Maniega, S.M., Mwangi, B., Nakamae, T., Nakao, T., Narayanaswaamy, J.C., Nees, F., Nordvik, J.E., Onnink, A.M.H., Opel, N., Ophoff, R., Paillère Martinot, M-L, Papadopoulos Orfanos, D., Pauli, P., Paus, T., Poustka, L., Reddy, J.YC., Renteria, M.E., Roiz-Santiáñez, R., Roos, A., Royle, N.A., Sachdev, P., Sánchez-Juan, P., Schmaal, L., Schumann, G., Shumskaya, E., Smolka, M.N., Soares, J.C., Soriano-Mas, C., Stein, D.J., Strike, L.T., Toro, R., Turner, J.A., Tzourio-Mazoyer, N., Uhlmann, A., Hernández, M.V., van den Heuvel, O.A., van der Meer, D., van Haren, N.E.M ., Veltman, D.J., Venkatasubramanian, G., Vetter, N.C., Vuletic, D., Walitza, S., Walter, H., Walton, E., Wang, Z., Wardlaw, J., Wen, W., Westlye, L.T., Whelan, R., Wittfeld, K., Wolfers, T., Wright, M.J., Xu, J., Xu, X., Yun, J-Y, Zhao, J.J., Franke, B., Thompson, P.M., Glahn, D.C., Mazoyer, B., Fisher, S.E., and Francks, C.
Abstract: The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders.
Published: 2016

47. Areas of controversy in neuroprogression in bipolar disorder

Author: Passos, IC, Mwangi, B, Vieta, E, Berk, M, Kapczinski, F, Passos, IC, Mwangi, B, Vieta, E, Berk, M, and Kapczinski, F
Abstract: OBJECTIVE: We aimed to review clinical features and biological underpinnings related to neuroprogression in bipolar disorder (BD). Also, we discussed areas of controversy and future research in the field. METHOD: We systematically reviewed the extant literature pertaining to neuroprogression and BD by searching PubMed and EMBASE for articles published up to March 2016. RESULTS: A total of 114 studies were included. Neuroimaging and clinical evidence from cross-sectional and longitudinal studies show that a subset of patients with BD presents a neuroprogressive course with brain changes and unfavorable outcomes. Risk factors associated with these unfavorable outcomes are number of mood episodes, early trauma, and psychiatric and clinical comorbidity. CONCLUSION: Illness trajectories are largely variable, and illness progression is not a general rule in BD. The number of manic episodes seems to be the clinical marker more robustly associated with neuroprogression in BD. However, the majority of the evidence came from cross-sectional studies that are prone to bias. Longitudinal studies may help to identify signatures of neuroprogression and integrate findings from the field of neuroimaging, neurocognition, and biomarkers.
Published: 2016

48. Subcortical volumetric abnormalities in bipolar disorder

Author: Brain, Onderzoeksgroep 4, Onderzoeksgroep 2, Onderzoek, Circulatory Health, Hibar, D. P., Westlye, L. T., Van Erp, T. G M, Rasmussen, J., Leonardo, C. D., Faskowitz, J., Haukvik, U. K., Hartberg, C. B., Doan, N. T., Agartz, I., Dale, A. M., Gruber, O., Krämer, B., Trost, S., Liberg, B., Abé, C., Ekman, C. J., Ingvar, M., Landén, M., Fears, S. C., Freimer, N. B., Bearden, C. E., Sprooten, E., Glahn, D. C., Pearlson, G. D., Emsell, L., Kenney, J., Scanlon, C., McDonald, C., Cannon, D. M., Almeida, J., Versace, A., Caseras, X., Lawrence, N. S., Phillips, M. L., Dima, D., Delvecchio, G., Frangou, S., Satterthwaite, T. D., Wolf, D., Houenou, J., Henry, C., Malt, U. F., BØen, E., Elvs'shagen, T., Young, A. H., Lloyd, A. J., Goodwin, G. M., Mackay, C. E., Bourne, C., Bilderbeck, A., Abramovic, L., Boks, M. P., Van Haren, N. E M, Ophoff, R. A., Kahn, R. S., Bauer, M., Pfennig, A., Alda, M., Hajek, T., Mwangi, B., Soares, J. C., Nickson, T., Dimitrova, R., Sussmann, J. E., Hagenaars, S., Whalley, H. C., McIntosh, A. M., Thompson, P. M., Andreassen, O. A., Brain, Onderzoeksgroep 4, Onderzoeksgroep 2, Onderzoek, Circulatory Health, Hibar, D. P., Westlye, L. T., Van Erp, T. G M, Rasmussen, J., Leonardo, C. D., Faskowitz, J., Haukvik, U. K., Hartberg, C. B., Doan, N. T., Agartz, I., Dale, A. M., Gruber, O., Krämer, B., Trost, S., Liberg, B., Abé, C., Ekman, C. J., Ingvar, M., Landén, M., Fears, S. C., Freimer, N. B., Bearden, C. E., Sprooten, E., Glahn, D. C., Pearlson, G. D., Emsell, L., Kenney, J., Scanlon, C., McDonald, C., Cannon, D. M., Almeida, J., Versace, A., Caseras, X., Lawrence, N. S., Phillips, M. L., Dima, D., Delvecchio, G., Frangou, S., Satterthwaite, T. D., Wolf, D., Houenou, J., Henry, C., Malt, U. F., BØen, E., Elvs'shagen, T., Young, A. H., Lloyd, A. J., Goodwin, G. M., Mackay, C. E., Bourne, C., Bilderbeck, A., Abramovic, L., Boks, M. P., Van Haren, N. E M, Ophoff, R. A., Kahn, R. S., Bauer, M., Pfennig, A., Alda, M., Hajek, T., Mwangi, B., Soares, J. C., Nickson, T., Dimitrova, R., Sussmann, J. E., Hagenaars, S., Whalley, H. C., McIntosh, A. M., Thompson, P. M., and Andreassen, O. A.
Published: 2016

49. Areas of controversy in neuroprogression in bipolar disorder

Author: Passos, I. C., primary, Mwangi, B., additional, Vieta, E., additional, Berk, M., additional, and Kapczinski, F., additional
Published: 2016
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50. Antinociceptive properties of dichloromethane: methanolic leaf and root bark extracts of Carissa edulis in rats

Author: Maina, Gitahi S., primary, Kelvin, Juma K., additional, Maina, Mwangi B., additional, Muriithi, Njagi J., additional, Kiambi, Mworia J., additional, Umar, Aliyu, additional, John, Mwonjoria K., additional, Ann, Njoroge W., additional, David, Mburu N., additional, and Piero, Ngugi M., additional
Published: 2015
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