10Kin1day: a bottom-up neuroimaging initiative

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain

Country-level gender inequality is associated with structural differences in the brains of women and men

Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women's worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7,876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women's brains and provide initial evidence for neuroscience-informed policies for gender equality

Country-level gender inequality is associated with structural differences in the brains of women and men

男女間の不平等と脳の性差 --男女間の不平等は脳構造の性差と関連する--. 京都大学プレスリリース. 2023-05-10.Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women’s worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7, 876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women’s brains and provide initial evidence for neuroscience-informed policies for gender equality

In vivo hippocampal subfield volumes in bipolar disorder—A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta‐Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1‐weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed‐effects models and mega‐analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = −0.20), cornu ammonis (CA)1 (d = −0.18), CA2/3 (d = −0.11), CA4 (d = −0.19), molecular layer (d = −0.21), granule cell layer of dentate gyrus (d = −0.21), hippocampal tail (d = −0.10), subiculum (d = −0.15), presubiculum (d = −0.18), and hippocampal amygdala transition area (d = −0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non‐users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD

Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium

Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, using MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets in the ENIGMA consortium, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macro-structural asymmetry may reflect differences at the molecular, cytoarchitectonic or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia

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

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

10Kin1day: A Bottom-Up Neuroimaging Initiative.

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain

Imaging social and environmental factors as modulators of brain dysfunction: time to focus on developing, non-Western societies

Social and environmental factors are known risk factors and modulators of mental health disorders. We here conducted a nonsystematic review of the neuroimaging literature studying the effects of poverty, urbanicity, and community violence, highlighting the opportunities of studying non-Western developing societies such as those in Latin America. Social and environmental factors in these communities are widespread and have a large magnitude, as well as an unequal distribution, providing a good opportunity for their characterization. Studying the effect of poverty in these settings could help to explore the brain effect of economic improvements, disentangle the effect of absolute and relative poverty, and characterize the modulating impact of poverty on the underlying biology of mental health disorders. Exploring urbanicity effects in highly unequal cities could help identify the specific factors that modulate this effect as well as examine a possible dose–response effect by studying megacities. Studying brain changes in those living among violence, which is particularly high in places such as Latin America, could help to characterize the interplay between brain predisposition and exposure to violence. Furthermore, exploring the brain in an adverse environment should shed light on the mechanisms underlying resilience. We finally provide examples of two methodological approaches that could contribute to this field, namely a big cohort study in the developing world and a consortium-based meta-analytic approach, and argue about the potential translational value of this research on the development of effective social policies and successful personalized medicine in disadvantaged societies.Fil: Crossley, Nicolas A.. Pontificia Universidad Católica de Chile; ChileFil: Alliende, Luz Maria. Pontificia Universidad Católica de Chile; ChileFil: Ossandon, Tomas. Pontificia Universidad Católica de Chile; ChileFil: Castañeda, Carmen Paz. Instituto Psiquiátrico Dr. José Horwitz Barak; ChileFil: González Valderrama, Alfonso. Instituto Psiquiátrico Dr. José Horwitz Barak; Chile. Universidad Finis Terrae.; ChileFil: Undurraga, Juan. Universidad del Desarrollo; Chile. Instituto Psiquiátrico Dr. José Horwitz Barak; ChileFil: Castro, Mariana Nair. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Universidad de Buenos Aires. Facultad de Medicina; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Guinjoan, Salvador Martín. Universidad de Buenos Aires. Facultad de Medicina; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Díaz Zuluaga, Ana M.. Universidad de Antioquia; ColombiaFil: Pineda-Zapata, Julián A.. Instituto de Alta Tecnología Médica; ColombiaFil: López-Jaramillo, Carlos. Hospital Universitario San Vicente Fundación; Colombia. Universidad de Antioquia; ColombiaFil: Reyes Madrigal, Francisco. Instituto Nacional de Neurología y Neurocirugía; MéxicoFil: León-Ortíz, Pablo. Instituto Nacional de Neurología y Neurocirugía; MéxicoFil: de la Fuente-Sandoval, Camilo. Instituto Nacional de Neurología y Neurocirugía; MéxicoFil: Czepielewski, Leticia Sanguinetti. Hospital de Clinicas de Porto Alegre; BrasilFil: Gama, Clarissa S.. Hospital de Clinicas de Porto Alegre; BrasilFil: Zugman, Andre. Universidade Federal de Sao Paulo; BrasilFil: Gadelha, Ary. Universidade Federal de Sao Paulo; BrasilFil: Jackowski, Andrea. Universidade Federal de Sao Paulo; BrasilFil: Bressan, Rodrigo. Universidade Federal de Sao Paulo; Brasi

Geospatial investigations in Colombia reveal variations in the distribution of mood and psychotic disorders

Abstract Background Geographical variations in mood and psychotic disorders have been found in upper-income countries. We looked for geographic variation in these disorders in Colombia, a middle-income country. We analyzed electronic health records from the Clínica San Juan de Dios Manizales (CSJDM), which provides comprehensive mental healthcare for the one million inhabitants of Caldas. Methods We constructed a friction surface map of Caldas and used it to calculate the travel-time to the CSJDM for 16,295 patients who had received an initial diagnosis of mood or psychotic disorder. Using a zero-inflated negative binomial regression model, we determined the relationship between travel-time and incidence, stratified by disease severity. We employed spatial scan statistics to look for patient clusters. Results We show that travel-times (for driving) to the CSJDM are less than 1 h for ~50% of the population and more than 4 h for ~10%. We find a distance-decay relationship for outpatients, but not for inpatients: for every hour increase in travel-time, the number of expected outpatient cases decreases by 20% (RR = 0.80, 95% confidence interval [0.71, 0.89], p = 5.67E-05). We find nine clusters/hotspots of inpatients. Conclusions Our results reveal inequities in access to healthcare: many individuals requiring only outpatient treatment may live too far from the CSJDM to access healthcare. Targeting of resources to comprehensively identify severely ill individuals living in the observed hotspots could further address treatment inequities and enable investigations to determine factors generating these hotspots

Effects of socioeconomic status in cognition of people with schizophrenia:Results from a Latin American collaboration network with 1175 subjects

Background Cognition heavily relies on social determinants and genetic background. Latin America comprises approximately 8% of the global population and faces unique challenges, many derived from specific demographic and socioeconomic variables, such as violence and inequality. While such factors have been described to influence mental health outcomes, no large-scale studies with Latin American population have been carried out. Therefore, we aim to describe the cognitive performance of a representative sample of Latin American individuals with schizophrenia and its relationship to clinical factors. Additionally, we aim to investigate how socioeconomic status (SES) relates to cognitive performance in patients and controls. Methods We included 1175 participants from five Latin American countries (Argentina, Brazil, Chile, Colombia, and Mexico): 864 individuals with schizophrenia and 311 unaffected subjects. All participants were part of projects that included cognitive evaluation with MATRICS Consensus Cognitive Battery and clinical assessments. Results Patients showed worse cognitive performance than controls across all domains. Age and diagnosis were independent predictors, indicating similar trajectories of cognitive aging for both patients and controls. The SES factors of education, parental education, and income were more related to cognition in patients than in controls. Cognition was also influenced by symptomatology. Conclusions Patients did not show evidence of accelerated cognitive aging; however, they were most impacted by a lower SES suggestive of deprived environment than controls. These findings highlight the vulnerability of cognitive capacity in individuals with psychosis in face of demographic and socioeconomic factors in low-and middle-income countries.Fil: Sanguinetti Czepielewski, Letícia. Hospital de Clinicas de Porto Alegre; Brasil. Universidade Federal do Rio Grande do Sul; BrasilFil: Alliende, Luz Maria. Pontificia Universidad Católica de Chile; Chile. Instituto Psiquiátrico Dr. Horwitz Barak; ChileFil: Castañeda, Carmen Paz. Instituto Psiquiátrico Dr. Horwitz Barak; ChileFil: Castro, Mariana Nair. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia. Instituto de Neurociencias - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Neurociencias; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Ciencias Fisiológicas; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Salud Mental; ArgentinaFil: Guinjoan, Salvador Martín. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia. Instituto de Neurociencias - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Neurociencias; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Salud Mental; ArgentinaFil: Massuda, Raffael. Universidade Federal do Paraná; BrasilFil: Berberian, Arthur A.. Universidade Federal de Sao Paulo; BrasilFil: Fonseca, Ana Olivia. Universidade Federal de Sao Paulo; BrasilFil: Gadelha, Ary. Universidade Federal de Sao Paulo; BrasilFil: Bressan, Rodrigo. Universidade Federal de Sao Paulo; BrasilFil: Crivelaro, Marisa. Universidade de Sao Paulo; BrasilFil: Louzã, Mario. Universidade de Sao Paulo; BrasilFil: Undurraga, Juan. Universidad del Desarrollo; Chile. Instituto Psiquiátrico Dr. Horwitz Barak; ChileFil: González Valderrama, Alfonso. Instituto Psiquiátrico Dr. Horwitz Barak; Chile. Universidad Finis Terrae; ChileFil: Nachar, Rubén. Instituto Psiquiátrico Dr. Horwitz Barak; Chile. Universidad Finis Terrae; ChileFil: Nieto, Rodrigo. Universidad de Chile; ChileFil: Montes, Cristian. Universidad de Chile; ChileFil: Silva, Hernan. Universidad de Chile; ChileFil: Langer, Álvaro I.. Millennium Nucleus To Improve The Mental Health Of Adolescents And Youths; Chile. Millennium Institute For Research In Depression And Personality; Chile. Universidad Austral de Chile; ChileFil: Schmidt, Carlos. Universidad de Barcelona; España. Millennium Institute For Research In Depression And Personality; ChileFil: Mayol Troncoso, Rocío. Universidad de Chile. Facultad de Medicina; Chile. Millennium Nucleus To Improve The Mental Health Of Adolescents And Youths; ChileFil: Díaz Zuluaga, Ana M.. Universidad de Antioquia; ColombiaFil: Valencia Echeverry, Johanna. Universidad de Antioquia; ColombiaFil: López Jaramillo, Carlos. Universidad de Antioquia; ColombiaFil: Solís Vivanco, Rodolfo. Instituto Nacional de Neurología y Neurocirugía; MéxicoFil: Reyes Madrigal, Francisco. Instituto Nacional de Neurología y Neurocirugía; MéxicoFil: De La Fuente Sandoval, Camilo. Instituto Nacional de Neurología y Neurocirugía; MéxicoFil: Crossley, Nicolás A.. Universidad Católica de Chile; Chile. Pontificia Universidad Católica de Chile; Chile. King's College London; Reino UnidoFil: Gama, Clarissa S.. Universidade Federal do Rio Grande do Sul; Brasil. Hospital de Clinicas de Porto Alegre; Brasi