Bipolar symptoms, somatic burden and functioning in older-age bipolar disorder: A replication study from the global aging & geriatric experiments in bipolar disorder database (GAGE-BD) project.

OBJECTIVES: The Global Aging & Geriatric Experiments in Bipolar Disorder Database (GAGE-BD) project pools archival datasets on older age bipolar disorder (OABD). An initial Wave 1 (W1; n = 1369) analysis found both manic and depressive symptoms reduced among older patients. To replicate this finding, we gathered an independent Wave 2 (W2; n = 1232, mean ± standard deviation age 47.2 ± 13.5, 65% women, 49% aged over 50) dataset. DESIGN/METHODS: Using mixed models with random effects for cohort, we examined associations between BD symptoms, somatic burden and age and the contribution of these to functioning in W2 and the combined W1 + W2 sample (n = 2601). RESULTS: Compared to W1, the W2 sample was younger (p < 0.001), less educated (p < 0.001), more symptomatic (p < 0.001), lower functioning (p < 0.001) and had fewer somatic conditions (p < 0.001). In the full W2, older individuals had reduced manic symptom severity, but age was not associated with depression severity. Age was not associated with functioning in W2. More severe BD symptoms (mania p ≤ 0.001, depression p ≤ 0.001) were associated with worse functioning. Older age was significantly associated with higher somatic burden in the W2 and the W1 + W2 samples, but this burden was not associated with poorer functioning. CONCLUSIONS: In a large, independent sample, older age was associated with less severe mania and more somatic burden (consistent with previous findings), but there was no association of depression with age (different from previous findings). Similar to previous findings, worse BD symptom severity was associated with worse functioning, emphasizing the need for symptom relief in OABD to promote better functioning.

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures.

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.

Neuroanatomical Correlates of the Late Positive Potential in Youth with Pediatric Bipolar Disorder.

BACKGROUND: The late positive potential (LPP) could be a marker of emotion dysregulation in youth with pediatric bipolar disorder (PBD). However, the neuroanatomical correlates of the LPP are still not clarified. OBJECTIVE: To provide cortical and deep gray matter correlates of the LPP in youth, specifically, youth with PBD. METHODS: Twenty-four 7 to 17 years-old children with PBD and 28 healthy controls (HC) underwent cortical thickness and deep gray matter volumes measurements through magnetic resonance imaging and LPP measurement elicited by passively viewing emotional faces through electroencephalography. T-tests compared group differences in LPP, cortical thickness, and deep gray matter volumes. Linear regressions tested the relationship between LPP amplitude and cortical thickness/deep gray matter volumes. RESULTS: PBD had a more pronounced LPP amplitude for happy faces and a thinner cortex in prefrontal areas than HC. While considering both groups, a higher LPP amplitude was associated with a thicker cortex across occipital and frontal lobes, and with a smaller right globus pallidus volume. In addition, a higher LPP amplitude for happy faces was associated with smaller left caudate and left globus pallidus volumes across both groups. Finally, the LPP amplitude correlated negatively with right precentral gyrus thickness across youth with PBD, but positively across HC. CONCLUSION: Neural correlates of LPP in youth included fronto-occipital areas that have been associated also with emotion processing and control. The opposite relationship between BPD and HC of LPP amplitude and right precentral gyrus thickness might explain the inefficacy of the emotional control system in PBD.

Volume of subcortical brain regions in social anxiety disorder: mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group.

There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = -0.077, pFWE = 0.037; right: d = -0.104, pFWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = -0.034, pFWE = 0.045). Smaller bilateral putamen volumes (left: d = -0.141, pFWE < 0.001; right: d = -0.158, pFWE < 0.001) and larger bilateral pallidum volumes (left: d = 0.129, pFWE = 0.006; right: d = 0.099, pFWE = 0.046) were detected in adult SAD patients relative to controls, but no volumetric differences were apparent in adolescent SAD patients relative to controls. Comorbid anxiety disorders and age of SAD onset were additional determinants of SAD-related volumetric differences in subcortical regions. To conclude, subtle volumetric alterations in subcortical regions in SAD were detected. Heterogeneity in age and clinical characteristics may partly explain inconsistencies in previous findings. The association between alterations in subcortical volumes and SAD illness progression deserves further investigation, especially from adolescence into adulthood.

Temporal multi-step predictive modeling of remission in major depressive disorder using early stage treatment data; STAR*D based machine learning approach.

BACKGROUND: Artificial intelligence is currently being used to facilitate early disease detection, better understand disease progression, optimize medication/treatment dosages, and uncover promising novel treatments and potential outcomes. METHODS: Utilizing the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) dataset, we built a machine learning model to predict depression remission rates using same clinical data as features for each of the first three antidepressant treatment steps in STAR*D. We only used early treatment data (baseline and first follow up) in each STAR*D step to temporally analyze predictive features of remission at the end of the step. RESULTS: Our model showed significant prediction performance across the three treatment steps, At step 1, Model accuracy was 66 %; sensitivity-65 %, specificity-67 %, positive predictive value (PPV)-65.5 %, and negative predictive value (NPV)-66.6 %. At step 2, model accuracy was 71.3 %, sensitivity-74.3 %, specificity-69 %, PPV-64.5 %, and NPV-77.9 %. At step 3, accuracy reached 84.6 %; sensitivity-69 %, specificity-88.8 %, PPV-67 %, and NPV-91.1 %. Across all three steps, the early Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR) scores were key elements in predicting the final treatment outcome. The model also identified key sociodemographic factors that predicted treatment remission at different steps. LIMITATIONS: The retrospective design, lack of replication in an independent dataset, and the use of "a complete case analysis" model in our analysis. CONCLUSIONS: This proof-of-concept study showed that using early treatment data, multi-step temporal prediction of depressive symptom remission results in clinically useful accuracy rates. Whether these predictive models are generalizable deserves further study.

Neurocognitive Correlates of Cerebellar Volumetric Alterations in Youth with Pediatric Bipolar Spectrum Disorders and Bipolar Offspring.

BACKGROUND: Emerging evidence points towards the involvement of the cerebellum in the processing of emotions and pathophysiology of mood disorders. However, cerebellar and related cognitive alterations in youth with pediatric bipolar disorder (PBD) and those at high risk to develop the disorder, such as bipolar offspring (BD-OFF) are not clearly defined. OBJECTIVE: To investigate cerebellar gray and white matter volumes, cognition, and their relationship in youth with PBD and BD-OFF. METHODS: Thirty youth (7 to 17 years, inclusive) with PBD, 30 BD-OFF and 40 healthy controls (HC) were recruited. Study participants underwent a computer-based cognitive battery assessing affective processing, executive function, attention, psychomotor speed, and learning. Three-tesla MRI scan was performed to assess cerebellar white and gray matter volumes. Cerebellar segmentation was performed with FreeSurfer. Statistical analyses include between-group differences in cognitive domains, cerebellar gray, and white matter volumes. Relationships between cerebellar volumes and cognitive domains were examined. RESULTS: Youth with PBD showed greater cerebellar gray matter volumes than both BD-OFF and HC, whereas no differences were present between BD-OFF and HC. Both youth with PBD and BD-OFF showed altered processing of negative emotions and a bias towards positive emotions. In youth with PBD and BD-OFF, greater impairment in the processing of emotions correlated with greater cerebellar gray matter volumes. CONCLUSION: The present findings corroborate hypotheses on cerebellar involvement in the processing of emotions and the pathophysiology of PBD. The presence of cerebellar dysfunction in BD-OFF is unclear.

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.

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.

Brain Structure in Acutely Underweight and Partially Weight-Restored Individuals With Anorexia Nervosa: A Coordinated Analysis by the ENIGMA Eating Disorders Working Group.

BACKGROUND: The pattern of structural brain abnormalities in anorexia nervosa (AN) is still not well understood. While several studies report substantial deficits in gray matter volume and cortical thickness in acutely underweight patients, others find no differences, or even increases in patients compared with healthy control subjects. Recent weight regain before scanning may explain some of this heterogeneity. To clarify the extent, magnitude, and dependencies of gray matter changes in AN, we conducted a prospective, coordinated meta-analysis of multicenter neuroimaging data. METHODS: We analyzed T1-weighted structural magnetic resonance imaging scans assessed with standardized methods from 685 female patients with AN and 963 female healthy control subjects across 22 sites worldwide. In addition to a case-control comparison, we conducted a 3-group analysis comparing healthy control subjects with acutely underweight AN patients (n = 466) and partially weight-restored patients in treatment (n = 251). RESULTS: In AN, reductions in cortical thickness, subcortical volumes, and, to a lesser extent, cortical surface area were sizable (Cohen's d up to 0.95), widespread, and colocalized with hub regions. Highlighting the effects of undernutrition, these deficits were associated with lower body mass index in the AN sample and were less pronounced in partially weight-restored patients. CONCLUSIONS: The effect sizes observed for cortical thickness deficits in acute AN are the largest of any psychiatric disorder investigated in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Consortium to date. These results confirm the importance of considering weight loss and renutrition in biomedical research on AN and underscore the importance of treatment engagement to prevent potentially long-lasting structural brain changes in this population.

Smartphone-based interventions in bipolar disorder: Systematic review and meta-analyses of efficacy. A position paper from the International Society for Bipolar Disorders (ISBD) Big Data Task Force.

BACKGROUND: The clinical effects of smartphone-based interventions for bipolar disorder (BD) have yet to be established. OBJECTIVES: To examine the efficacy of smartphone-based interventions in BD and how the included studies reported user-engagement indicators. METHODS: We conducted a systematic search on January 24, 2022, in PubMed, Scopus, Embase, APA PsycINFO, and Web of Science. We used random-effects meta-analysis to calculate the standardized difference (Hedges' g) in pre-post change scores between smartphone intervention and control conditions. The study was pre-registered with PROSPERO (CRD42021226668). RESULTS: The literature search identified 6034 studies. Thirteen articles fulfilled the selection criteria. We included seven RCTs and performed meta-analyses comparing the pre-post change in depressive and (hypo)manic symptom severity, functioning, quality of life, and perceived stress between smartphone interventions and control conditions. There was significant heterogeneity among studies and no meta-analysis reached statistical significance. Results were also inconclusive regarding affective relapses and psychiatric readmissions. All studies reported positive user-engagement indicators. CONCLUSION: We did not find evidence to support that smartphone interventions may reduce the severity of depressive or manic symptoms in BD. The high heterogeneity of studies supports the need for expert consensus to establish ideally how studies should be designed and the use of more sensitive outcomes, such as affective relapses and psychiatric hospitalizations, as well as the quantification of mood instability. The ISBD Big Data Task Force provides preliminary recommendations to reduce the heterogeneity and achieve more valid evidence in the field.

The role of educational attainment and brain morphology in major depressive disorder: Findings from the ENIGMA major depressive disorder consortium.

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).

White matter microstructure associated with anhedonia among individuals with bipolar disorders and high-risk for bipolar disorders.

BACKGROUND: Anhedonia - a key symptom of depression - is highly associated with poorer outcomes and suicidal behavior. Alterations in the circuitry of reward-related brain regions have been robustly associated with anhedonia in unipolar depression, but not bipolar disorder (BD). We investigated white matter microstructures associated with anhedonia in participants with BD types I and II and first-degree relatives of patients with BD (BD-siblings). METHODS: Eighty participants (BD types I and II: 56 [70%], and BD-siblings: 24 [30%]) underwent diffusion tensor imaging (DTI); Fractional anisotropy (FA) of different tracts were computed. Anhedonia was assessed using item 8, ("inability to feel'') of the MADRS scale. General linear models were used to compare the FA of different tracts in participants with and without anhedonia controlling for several clinical and demographic variables. RESULTS: The mean age of the sample was 37 (± 11) years old, and 68.8% were female. Participants with anhedonia (32.5%) presented lower mean FA in the left uncinate fasciculus (UF) (p = 0.005), right temporal endings of the superior longitudinal fasciculus (SLFT) (p = 0.04), and in the left and right parietal endings of the superior longitudinal fasciculus (SLFP) (p = 0.003, and p = 0.04, respectively). Similar comparisons between participants with or without current depressive episodes and between participants with or without inner tension according to the MADRS did not show significant differences, specificity of the findings for anhedonia. CONCLUSIONS: Lower FA in the left UF and SLF are potential neuroimaging markers of anhedonia in individuals with BD and high-risk for BD.

Correlations between peripheral levels of inflammatory mediators and frontolimbic structures in bipolar disorder: an exploratory analysis.

BACKGROUND: Altered peripheral immune/inflammatory system and brain volumetric changes have been implicated in the pathophysiology of bipolar disorder (BD). This study aimed to evaluate how peripheral levels of cytokines are related to volumetric brain changes in euthymic patients with BD. METHODS: Euthymic patients with BD (n = 21) and healthy controls (n = 22) were enrolled in this exploratory study. Blood samples were collected on the same day of clinical assessment and neuroimaging. Cytokines were measured through cytometric bead array method. Neuroimaging data were acquired using a sagittal three-dimensional magnetic resonance imaging T1-weighted fast field echo sequence and was processed using FreeSurfer. RESULTS: Compared to controls, BD patients had significantly lower volumes in the cingulate, medial-orbitofrontal (MOF) and parahippocampal regions. We found a negative correlation between right MOF volume and interferon-gamma levels (ß = -0.431, P = .049) and a positive correlation between interleukin-10 levels and left posterior cingulate volume (ß = 0.457, P = .048). CONCLUSION: Our results support the involvement of inflammatory pathways in structural brain changes in BD.

Investigation of endophenotype potential of decreased fractional anisotropy in pediatric bipolar disorder patients and unrelated offspring of bipolar disorder patients.

BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder associated with structural and functional brain abnormalities, some of which have been found in unaffected relatives as well. In this study, we examined the potential role of decreased fractional anisotropy (FA) as a BD endophenotype, in adolescents at high risk for BD. METHODS: We included 15 offspring of patients with BD, 16 pediatric BD patients, and 16 matched controls. Diffusion weighted scans were obtained on a 3T scanner using an echo-planar sequence. Scans were segmented using FreeSurfer. RESULTS: Our results showed significantly decreased FA in six brain areas of offspring group; left superior temporal gyrus (LSTG; P < .0001), left transverse temporal gyrus (LTTG; P = .002), left banks of the superior temporal sulcus (LBSTS; P = .002), left anterior cingulum (LAC; P = .003), right temporal pole (RTP; P = .004) and left frontal pole (LFP; P = .017). On analysis, LSTG, LAC, and RTP demonstrated a potential to be an endophenotype when comparing all three groups. FA values in three regions, LBSTS, LTTG, and LFP were increased only in controls. CONCLUSION: Our findings point at decreased FA as a possible endophenotype for BD, as they were found in children of patients with BD. Most of these areas were previously found to have morphological and functional changes in adult and pediatric BD, and are thought to play important roles in affected domains of functioning. Prospective follow up studies should be performed to detect reliability of decreased FA as an endophenotype and effects of treatment on FA.

Prediction of suicide attempts in a prospective cohort study with a nationally representative sample of the US population.

BACKGROUND: There is still little knowledge of objective suicide risk stratification. METHODS: This study aims to develop models using machine-learning approaches to predict suicide attempt (1) among survey participants in a nationally representative sample and (2) among participants with lifetime major depressive episodes. We used a cohort called the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) that was conducted in two waves and included a nationally representative sample of the adult population in the United States. Wave 1 involved 43 093 respondents and wave 2 involved 34 653 completed face-to-face reinterviews with wave 1 participants. Predictor variables included clinical, stressful life events, and sociodemographic variables from wave 1; outcome included suicide attempt between wave 1 and wave 2. RESULTS: The model built with elastic net regularization distinguished individuals who had attempted suicide from those who had not with an area under the ROC curve (AUC) of 0.89, balanced accuracy 81.86%, specificity 89.22%, and sensitivity 74.51% for the general population. For participants with lifetime major depressive episodes, AUC was 0.89, balanced accuracy 81.64%, specificity 85.86%, and sensitivity 77.42%. The most important predictor variables were a diagnosis of borderline personality disorder, post-traumatic stress disorder, and being of Asian descent for the model in all participants; and previous suicide attempt, borderline personality disorder, and overnight stay in hospital because of depressive symptoms for the model in participants with lifetime major depressive episodes. Random forest and artificial neural networks had similar performance. CONCLUSIONS: Risk for suicide attempt can be estimated with high accuracy.

Mega-analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group.

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.

Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group.

The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5-90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.

Evidence of altered metabolism of cellular membranes in bipolar disorder comorbid with post-traumatic stress disorder.

In proton magnetic resonance spectroscopy (¹H MRS) studies, aberrant levels of choline-containing compounds that include glycerophosphocholine plus phosphocholine (GPC+PC), can signify alterations in the metabolism of cellular membrane phospholipids (MPLs) from a healthy baseline. In a recent ¹H MRS study, we reported increased GPC+PC in cortical and subcortical areas of adult patients with bipolar disorder I (BP-I). Post-traumatic stress disorder (PTSD) can worsen the severity of BP-I, but it is unclear whether the effect of a PTSD comorbidity in BP-I is associated with altered MPL metabolism. The purpose of this study was to re-investigate the ¹H MRS data to determine whether the regional extent of elevated GPC+PC was greater in BP-I patients with PTSD (BP-I/wPTSD) compared to BP-I without comorbid PTSD (BP-I/woPTSD) patients and healthy controls. GPC+PC levels from four brain areas [the anterior cingulate cortex (ACC), anterior-dorsal ACC, caudate, and putamen] were measured in 14 BP-I/wPTSD, 36 BP-I/woPTSD, and 44 healthy controls using a multi-voxel 1H MRS approach on a 3 Tesla system with high spatial resolution and absolute quantification. Results show a significant increase in GPC+PC levels from the caudate and putamen of BP-I/wPTSD patients compared to healthy controls (P<0.05) and in the putamen compared to BP-I/woPTSD patients (P<0.05). These findings are consistent with evidence of elevated degradation of MPLs in the neuropil that is more pronounced in BP-I patients with comorbid PTSD.

Land use effects on termite assemblages in Kenya.

Termites perform key ecological functions and they also cause crop damage. Land use change resulting from agricultural intensification can result in changes in termite species diversity and abundance. Termite species occurring in natural vegetation, maize monocrop and maize-beans intercrop macrohabitats were investigated in Embu and Machakos Counties, Kenya. Influence of soil properties and seasons was also evaluated. Across the two Counties, seven termite species were recorded with Machakos County having the highest number. Additive diversity partitioning of species richness and Simpson diversity showed that, α component contributed to 98.3% and 99.1% of the total diversity, respectively. Population densities of three termite species significantly varied between land use types in Machakos County but there were no differences in termite species abundance in Embu County. In addition, there were no significant differences in species richness between macrohabitats within each County. In Embu, season significantly influenced the abundance of Macrotermes subhyalinus, M. herus, and Coptotermes formosanus which occurred in greater numbers during the wet season. There was a significant influence of land use on Trinervitermes gratiosus and C. formosanus in Machakos with both species occurring in higher numbers in natural vegetation. Trinervitermes gratiosus was negatively associated with Mn and positively correlated to pH and sand. Macrotermes subhyalinus and M. herus showed a positive association with P and silt while C. formosanus was positively correlated to Ca and Mg. These findings provide an insight into the effects of land use change from natural vegetation to maize agro-ecosystems on termite diversity. It also provides a baseline for further studies on termite diversity in Kenya and their ecological significance.

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.

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.