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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.

Background and purpose. Depressive symptoms are frequently associated with heart failure (HF), but the brain mechanisms underlying such association are unclear. We hypothesized that the presence of major depressive disorder (MDD) emerging after the onset of HF would be associated with regional cerebral blood flow (rCBF) abnormalities in medial temporal regions previously implicated in primary MDD, namely the hippocampus and parahippocampal gyrus.Method. Using 99mTc-SPECT, we measured rCBF in 17 elderly MDD-HF patients, 17 non-depressed HF patients, and 18 healthy controls, matched for demographic variables. Group differences were investigated with Statistical Parametric Mapping.Results. Significant rCBF reductions in MDD-HF patients relative to both non-depressed HF patients and healthy controls were detected in the left anterior parahippocampal gyrus and hippocampus (ANOVA, p=0.008 corrected for multiple comparisons) and the right posterior hippocampus and parahippocampal gyrus (p=0.005 corrected). In the overall HF group, there was a negative correlation between the severity of depressive symptoms and rCBF in the right posterior hippocampal/parahippocampal region (p=0.045 corrected).Conclusions. These findings are consistent with the notion that the medial temporal region is vulnerable to brain perfusion deficits associated with HF, and provide evidence that such functional deficits may be specifically implicated in the pathophysiology of MDD associated with HF. [ABSTRACT FROM AUTHOR]

Objective: To investigate the relation between atrophy of the hippocampal region and brain functional patterns during episodic memory processing in Alzheimer's disease.Patients and Methods: Whole brain structural magnetic resonance imaging (MRI) data and single photon emission computed tomography (SPECT) measures of regional cerebral blood flow (rCBF) were obtained during a verbal recognition memory task in nine subjects with mild Alzheimer's disease and 10 elderly healthy controls. Using the statistical parametric mapping approach, voxel based comparisons were made on the MRI data to identify clusters of significantly reduced grey matter concentrations in the hippocampal region in the Alzheimer patients relative to the controls. The mean grey matter density in the voxel cluster of greatest hippocampal atrophy was extracted for each Alzheimer subject. This measure was used to investigate, on a voxel by voxel basis, the presence of significant correlations between the degree of hippocampal atrophy and the rCBF SPECT measures obtained during the memory task.Results: Direct correlations were detected between the hippocampal grey matter density and rCBF values in voxel clusters located bilaterally in the temporal neocortex, in the left medial temporal region, and in the left posterior cingulate cortex during the memory task in the Alzheimer's disease group (p < 0.001). Conversely, measures of hippocampal atrophy were negatively correlated with rCBF values in voxel clusters located in the frontal lobes, involving the right and left inferior frontal gyri and the insula (p < 0.001).Conclusions: Hippocampal atrophic changes in Alzheimer's disease are associated with reduced functional activity in limbic and associative temporal regions during episodic memory processing, but with increased activity in frontal areas, possibly on a compensatory basis. [ABSTRACT FROM AUTHOR]

Background: Schizophrenia (SCZ) is characterized by a disconnect from reality that manifests as various clinical and cognitive symptoms, and persistent neurobiological abnormalities. Sex-related differences in clinical presentation imply separate brain substrates. The present study characterized deep brain morphology using shape features to understand the independent effects of diagnosis and sex on the brain, and to determine whether the neurobiology of schizophrenia varies as a function of sex., Methods: This study analyzed multi-site archival data from 1,871 male (M) and 955 female (F) participants with SCZ, and 2,158 male and 1,877 female healthy controls (CON) from twenty-three cross-sectional samples from the ENIGMA Schizophrenia Workgroup. Harmonized shape analysis protocols were applied to each site's data for seven deep brain regions obtained from T1-weighted structural MRI scans. Effect sizes were calculated for the following main contrasts: 1) Sex effects;2) Diagnosis-by-Sex interaction; 3) within sex tests of diagnosis; 4) within diagnosis tests of sex differences. Meta-regression models between brain structure and clinical variables were also computed separately in men and women with schizophrenia., Results: Mass univariate meta-analyses revealed more concave-than-convex shape differences in all regions for women relative to men, across diagnostic groups ( d = -0.35 to 0.20, SE = 0.02 to 0.07); there were no significant diagnosis-by-sex interaction effects. Within men and women separately, we identified more-concave-than-convex shape differences for the hippocampus, amygdala, accumbens, and thalamus, with more-convex-than-concave differences in the putamen and pallidum in SCZ ( d = -0.30 to 0.30, SE = 0.03 to 0.10). Within CON and SZ separately, we found more-concave-than-convex shape differences in the thalamus, pallidum, putamen, and amygdala among females compared to males, with mixed findings in the hippocampus and caudate ( d = -0.30 to 0.20, SE = 0.03 to 0.09). Meta-regression models revealed similarly small, but significant relationships, with medication and positive symptoms in both SCZ-M and SCZ-F., Conclusions: Sex-specific variation is an overriding feature of deep brain shape regardless of disease status, underscoring persistent patterns of sex differences observed both within and across diagnostic categories, and highlighting the importance of including it as a critical variable in studies of neurobiology. Future work should continue to explore these dimensions independently to determine whether these patterns of brain morphology extend to other aspects of neurobiology in schizophrenia, potentially uncovering broader implications for diagnosis and treatment., Key Points: Statistical analyses revealed significant main effects for diagnosis and sex in deep brain shape morphology. Among patients with schizophrenia, there was a pattern of thinning and surface contraction in the bilateral hippocampus, amygdala, accumbens, and thalamus, and a pattern of significant thickening and surface expansion in the bilateral putamen and pallidum compared to healthy control participants. Between males and females, there was a pattern of significant thinning and surface contraction in the bilateral thalamus, pallidum, putamen, and amygdala in females compared to males.There was no significant interaction between diagnosis and biological sex, suggesting that sex differences in deep brain shape and asymmetry among patients with schizophrenia reflect those observed in healthy individuals.Small but statistically significant relationships exist between brain structure and clinical correlates of schizophrenia were similar for both men and women with the disease, such that higher CPZ was associated with shape-derived thinning and surface contraction in the caudate, accumbens, hippocampus, amygdala, and thalamus, and elevated positive symptoms were associated with shape-derived thinning and surface contraction in the bilateral caudate, right hippocampus, and right amygdala.

Only a small number of studies have assessed structural differences between the two hemispheres during childhood and adolescence. However, the existing findings lack consistency or are restricted to a particular brain region, a specific brain feature, or a relatively narrow age range. Here, we investigated associations between brain asymmetry and age as well as sex in one of the largest pediatric samples to date (n = 4265), aged 1-18 years, scanned at 69 sites participating in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. Our study revealed that significant brain asymmetries already exist in childhood, but their magnitude and direction depend on the brain region examined and the morphometric measurement used (cortical volume or thickness, regional surface area, or subcortical volume). With respect to effects of age, some asymmetries became weaker over time while others became stronger; sometimes they even reversed direction. With respect to sex differences, the total number of regions exhibiting significant asymmetries was larger in females than in males, while the total number of measurements indicating significant asymmetries was larger in males (as we obtained more than one measurement per cortical region). The magnitude of the significant asymmetries was also greater in males. However, effect sizes for both age effects and sex differences were small. Taken together, these findings suggest that cerebral asymmetries are an inherent organizational pattern of the brain that manifests early in life. Overall, brain asymmetry appears to be relatively stable throughout childhood and adolescence, with some differential effects in males and females., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and appendage development, while pathways of breast cancer indicate potential interplays between brain metastasis and PSCs associated with neurodegeneration and dementia. Using support vector machines, multi-scale PSCs effectively derive imaging signatures of several brain diseases. Our results elucidate genetic and biological underpinnings that influence structural covariance patterns in the human brain., Competing Interests: Competing interests statement:D.H.W. served as Site PI for studies by Biogen, Merck, and Eli Lilly/Avid. He has received consulting fees from GE Healthcare and Neuronix. He is on the DSMB for a trial sponsored by Functional Neuromodulation. A.J.S. receives support from multiple NIH grants (P30 AG010133, P30 AG072976, R01 AG019771, R01 AG057739, U01 AG024904, R01 LM013463, R01 AG068193, T32 AG071444, U01 AG068057, and U01 AG072177). He has also received support from Avid Radiopharmaceuticals, a subsidiary of Eli Lilly (in-kind contribution of PET tracer precursor); Bayer Oncology (Scientific Advisory Board); Eisai (Scientific Advisory Board); Siemens Medical Solutions, Inc. (Dementia Advisory Board); and Springer-Nature Publishing (Editorial Office Support as Editor-in-Chief, Brain Imaging, and Behavior). O.C. reports having received consulting fees from AskBio (2020) and Therapanacea (2022), having received payments for writing a lay audience short paper from Expression Santé (2019), and that his laboratory has received grants (paid to the institution) from Qynapse (2017 to present). Members of his laboratory have co-supervised a Ph.D. thesis with myBrainTechnologies (2016 to 2019) and with Qynapse (2017 to present). O.C.’s spouse is an employee and holds stock options of myBrainTechnologies (2015 to present). O.C. has a patent registered at the International Bureau of the World Intellectual Property Organization (PCT/IB2016/0526993, J.-B. Schiratti, S. Allassonniere, O.C., S. Durrleman, A method for determining the temporal progression of a biological phenomenon and associated methods and devices) (2017). M.E. receives support from multiple NIH grants, the Alzheimer’s Association, and the Alzheimer’s Therapeutic Research Institute. M.V.Z. serves as a consultant and/or speaker for the following pharmaceutical companies: Eurofarma, Lundbeck, Abbott, Greencare, Myralis, and Elleven Healthcare.

Intracellular peptides (InPeps) generated by the orchestrated action of the proteasome and intracellular peptidases have biological and pharmacological significance. Here, human plasma relative concentration of specific InPeps was compared between 175 patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and 45 SARS-CoV-2 non-infected patients; 2,466 unique peptides were identified, of which 67% were InPeps. The results revealed differences of a specific group of peptides in human plasma comparing non-infected individuals to patients infected by SARS-CoV-2, following the results of the semi-quantitative analyses by isotope-labeled electrospray mass spectrometry. The protein-protein interactions networks enriched pathways, drawn by genes encoding the proteins from which the peptides originated, revealed the presence of the coronavirus disease/COVID-19 network solely in the group of patients fatally infected by SARS-CoV-2. Thus, modulation of the relative plasma levels of specific InPeps could be employed as a predictive tool for disease outcome., Competing Interests: All authors declare no conflict of interest., (© 2023 The Author(s).)

Objectives: Schizophrenia-related psychosis is associated with abnormalities in white matter (WM) microstructure and structural brain dysconnectivity. However, the pathological process underlying such changes is unknown. We sought to investigate the potential association between peripheral cytokine levels and WM microstructure during the acute phase of first-episode psychosis (FEP) in a cohort of drug-naïve patients., Methods: Twenty-five non-affective FEP patients and 69 healthy controls underwent MRI scanning and blood collection at study entry. After achieving clinical remission, 21 FEP were reassessed; 38 age and biological sex-matched controls also had a second assessment. We measured fractional anisotropy (FA) of selected WM regions-of-interest (ROIs) and plasma levels of four cytokines (IL-6, IL-10, IFN-γ, and TNF-α)., Results: At baseline (acute psychosis), the FEP group showed reduced FA relative to controls in half the examined ROIs. Within the FEP group, IL-6 levels were negatively correlated with FA values. Longitudinally, patients showed increments of FA in several ROIs affected at baseline, and such changes were associated with reductions in IL-6 levels., Conclusions: A state-dependent process involving an interplay between a pro-inflammatory cytokine and brain WM might be associated with the clinical manifestation of FEP. This association suggests a deleterious effect of IL-6 on WM tracts during the acute phase of psychosis., Competing Interests: Declaration of competing interest None., (Copyright © 2023 Elsevier B.V. All rights reserved.)

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.

Objectives: This study investigated behavioral self-regulation problems using the Children's Hostility Inventory (CHI) in pediatric bipolar disorder (PBD), healthy offspring of bipolar disorder patients (HOBD), and healthy controls (HC) without previous history of psychiatric disorders., Methods: The CHI was administered to 41 consecutive children and adolescents diagnosed with PBD, to 16 HOBD, and to 22 HC. The inventory assessed irritability, expression, hostility, and aggression and was completed by the children with the help of their mothers. Adolescents and their respective parents were interviewed separately using the Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL)., Results: All subscales of the CHI presented statistically significant differences, except for the subscale assessing feelings of suspicion. Pairwise comparisons revealed consistently significant differences between the PBD group and controls, indicating more self-regulation difficulties in the PBD group, represented by high levels of hostility and aggressive behavior. There were no significant differences between the PBD and HOBD groups., Conclusions: Future studies should further investigate if such behavior is state-dependent or a trait of bipolar juvenile expression. Expression of hostility and irritability should be considered relevant targets in psychosocial approaches addressing this population., Competing Interests: The authors report no conflicts of interest.

Importance: Autism spectrum disorder (ASD) is associated with significant clinical, neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment., Objective: To assess distinct neuroanatomical dimensions of ASD using novel semisupervised machine learning methods and to test whether the dimensions can serve as endophenotypes also in non-ASD populations., Design, Setting, and Participants: This cross-sectional study used imaging data from the publicly available Autism Brain Imaging Data Exchange (ABIDE) repositories as the discovery cohort. The ABIDE sample included individuals diagnosed with ASD aged between 16 and 64 years and age- and sex-match typically developing individuals. Validation cohorts included individuals with schizophrenia from the Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging (PHENOM) consortium and individuals from the UK Biobank to represent the general population. The multisite discovery cohort included 16 internationally distributed imaging sites. Analyses were performed between March 2021 and March 2022., Main Outcomes and Measures: The trained semisupervised heterogeneity through discriminative analysis models were tested for reproducibility using extensive cross-validations. It was then applied to individuals from the PHENOM and the UK Biobank. It was hypothesized that neuroanatomical dimensions of ASD would display distinct clinical and genetic profiles and would be prominent also in non-ASD populations., Results: Heterogeneity through discriminative analysis models trained on T1-weighted brain magnetic resonance images of 307 individuals with ASD (mean [SD] age, 25.4 [9.8] years; 273 [88.9%] male) and 362 typically developing control individuals (mean [SD] age, 25.8 [8.9] years; 309 [85.4%] male) revealed that a 3-dimensional scheme was optimal to capture the ASD neuroanatomy. The first dimension (A1: aginglike) was associated with smaller brain volume, lower cognitive function, and aging-related genetic variants (FOXO3; Z = 4.65; P = 1.62 × 10-6). The second dimension (A2: schizophrenialike) was characterized by enlarged subcortical volumes, antipsychotic medication use (Cohen d = 0.65; false discovery rate-adjusted P = .048), partially overlapping genetic, neuroanatomical characteristics to schizophrenia (n = 307), and significant genetic heritability estimates in the general population (n = 14 786; mean [SD] h2, 0.71 [0.04]; P < 1 × 10-4). The third dimension (A3: typical ASD) was distinguished by enlarged cortical volumes, high nonverbal cognitive performance, and biological pathways implicating brain development and abnormal apoptosis (mean [SD] β, 0.83 [0.02]; P = 4.22 × 10-6)., Conclusions and Relevance: This cross-sectional study discovered 3-dimensional endophenotypic representation that may elucidate the heterogeneous neurobiological underpinnings of ASD to support precision diagnostics. The significant correspondence between A2 and schizophrenia indicates a possibility of identifying common biological mechanisms across the 2 mental health diagnoses.

Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups-a 'lower brain volume' subgroup (SG1) and an 'higher striatal volume' subgroup (SG2) with otherwise normal brain structure. In this study, we investigated whether the MRI signatures of these subgroups were also already present at the time of the first-episode of psychosis (FEP) and whether they were related to clinical presentation and clinical remission over 1-, 3-, and 5-years. We included 572 FEP and 424 healthy controls (HC) from 4 sites (Sao Paulo, Santander, London, Melbourne) of the PHENOM consortium. Our prior MRI subgrouping models (671 participants; USA, Germany, and China) were applied to both FEP and HC. Participants were assigned into 1 of 4 categories: subgroup 1 (SG1), subgroup 2 (SG2), no subgroup membership ('None'), and mixed SG1 + SG2 subgroups ('Mixed'). Voxel-wise analyses characterized SG1 and SG2 subgroups. Supervised machine learning analyses characterized baseline and remission signatures related to SG1 and SG2 membership. The two dominant patterns of 'lower brain volume' in SG1 and 'higher striatal volume' (with otherwise normal neuromorphology) in SG2 were identified already at the first episode of psychosis. SG1 had a significantly higher proportion of FEP (32%) vs. HC (19%) than SG2 (FEP, 21%; HC, 23%). Clinical multivariate signatures separated the SG1 and SG2 subgroups (balanced accuracy = 64%; p < 0.0001), with SG2 showing higher education but also greater positive psychosis symptoms at first presentation, and an association with symptom remission at 1-year, 5-year, and when timepoints were combined. Neuromorphological subtypes of schizophrenia are already evident at illness onset, separated by distinct clinical presentations, and differentially associated with subsequent remission. These results suggest that the subgroups may be underlying risk phenotypes that could be targeted in future treatment trials and are critical to consider when interpreting neuroimaging literature., (© 2023. The Author(s).)

The aim of this study was to determine whether Post-acute Sequelae of SARS-CoV-2 Infection (PASC) are associated with physical inactivity in COVID-19 survivors. This is a cohort study of COVID-19 survivors discharged from a tertiary hospital in Sao Paulo, Brazil. Patients admitted as inpatients due to laboratory-confirmed COVID-19 between March and August 2020 were consecutively invited for a follow-up in-person visit 6 to 11 months after hospitalization. Ten symptoms of PASC were assessed using standardized scales. Physical activity was assessed by questionnaire and participants were classified according to WHO Guidelines. 614 patients were analyzed (age: 56 ± 13 years; 53% male). Frequency of physical inactivity in patients exhibiting none, at least 1, 1-4, and 5 or more symptoms of PASC was 51%, 62%, 58%, and 71%, respectively. Adjusted models showed that patients with one or more persistent PASC symptoms have greater odds of being physically inactive than those without any persistent symptoms (OR: 1.57 [95% CI 1.04-2.39], P = 0.032). Dyspnea (OR: 2.22 [1.50-3.33], P < 0.001), fatigue (OR: 2.01 [1.40-2.90], P < 0.001), insomnia (OR: 1.69 [1.16-2.49], P = 0.007), post-traumatic stress (OR: 1.53 [1.05-2.23], P = 0.028), and severe muscle/joint pain (OR: 1.53 [95% CI 1.08-2.17], P = 0.011) were associated with greater odds of being physically inactive. This study suggests that PASC is associated with physical inactivity, which itself may be considered as a persistent symptom among COVID-19 survivors. This may help in the early identification of patients who could benefit from additional interventions tailored to combat inactivity (even after treatment of PASC), with potential beneficial impacts on overall morbidity/mortality and health systems worldwide., (© 2023. The Author(s).)

Purpose: Neuropathological studies have demonstrated distinct profiles of microglia activation and myelin injury among different multiple sclerosis (MS) phenotypes and disability stages. PET imaging using specific tracers may uncover the in vivo molecular pathology and broaden the understanding of the disease heterogeneity., Methods: We used the 18-kDa translocator protein (TSPO) tracer (R)-[ 11 C]PK11195 and [ 11 C]PIB PET images acquired in a hybrid PET/MR 3 T system to characterize, respectively, the profile of innate immune cells and myelin content in 47 patients with MS compared to 18 healthy controls (HC). For the volume of interest (VOI)-based analysis of the dynamic data, (R)-[ 11 C]PK11195 distribution volume (V T ) was determined for each subject using a metabolite-corrected arterial plasma input function while [ 11 C]PIB distribution volume ratio (DVR) was estimated using a reference region extracted by a supervised clustering algorithm. A voxel-based analysis was also performed using Statistical Parametric Mapping. Functional disability was evaluated by the Expanded Disability Status Scale (EDSS), Multiple Sclerosis Functional Composite (MSFC), and Symbol Digit Modality Test (SDMT)., Results: In the VOI-based analysis, [ 11 C]PIB DVR differed between patients and HC in the corpus callosum (P = 0.019) while no differences in (R)-[ 11 C]PK11195 V T were observed in patients relative to HC. Furthermore, no correlations or associations were observed between both tracers within the VOI analyzed. In the voxel-based analysis, high (R)-[ 11 C]PK11195 uptake was observed diffusively in the white matter (WM) when comparing the progressive phenotype and HC, and lower [ 11 C]PIB uptake was observed in certain WM regions when comparing the relapsing-remitting phenotype and HC. None of the tracers were able to differentiate phenotypes at voxel or VOI level in our cohort. Linear regression models adjusted for age, sex, and phenotype demonstrated that higher EDSS was associated with an increased (R)-[ 11 C]PK11195 V T and lower [ 11 C]PIB DVR in corpus callosum (P = 0.001; P = 0.023), caudate (P = 0.015; P = 0.008), and total T 2 lesion (P = 0.007; P = 0.012), while better cognitive scores in SDMT were associated with higher [ 11 C]PIB DVR in the corpus callosum (P = 0.001), and lower (R)-[ 11 C]PK11195 V T (P = 0.013)., Conclusions: Widespread innate immune cells profile and marked loss of myelin in T 2 lesions and regions close to the ventricles may occur independently and are associated with disability, in both WM and GM structures., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Non-invasive brain stimulation (NIBS) interventions are promising for the treatment of psychiatric disorders. Notwithstanding, the NIBS mechanisms of action over the dorsolateral prefrontal cortex (DLPFC), a hub that modulates affective and cognitive processes, have not been completely mapped. We aimed to investigate regional cerebral blood flow (rCBF) changes over the DLPFC and the subgenual anterior cingulate cortex (sgACC) of different NIBS protocols using Single-Photon Emission Computed Tomography (SPECT). A factorial, within-subjects, double-blinded study was performed. Twenty-three healthy subjects randomly underwent four sessions of NIBS applied once a week: transcranial direct current stimulation (tDCS), intermittent theta-burst stimulation (iTBS), combined tDCS + iTBS and placebo. The radiotracer 99m-Technetium-ethylene-cysteine-dimer was injected intravenously during the NIBS session, and SPECT neuroimages were acquired after the session. Results revealed that the combination of tDCS + iTBS increased right sgACC rCBF. Cathodal and anodal tDCS increased and decreased DLPFC rCBF, respectively, while iTBS showed no significant changes compared to the placebo. Our findings suggest that the combined protocol might optimize the activity in the right sgACC and encourage future trials with neuropsychiatric populations. Moreover, mechanistic studies to investigate the effects of tDCS and iTBS over the DLPFC are required.

Background: Despite the multitude of clinical manifestations of post-acute sequelae of SARS-CoV-2 infection (PASC), studies applying statistical methods to directly investigate patterns of symptom co-occurrence and their biological correlates are scarce., Methods: We assessed 30 symptoms pertaining to different organ systems in 749 adults (age = 55 ± 14 years; 47% female) during in-person visits conducted at 6-11 months after hospitalization due to coronavirus disease 2019 (COVID-19), including six psychiatric and cognitive manifestations. Symptom co-occurrence was initially investigated using exploratory factor analysis (EFA), and latent variable modeling was then conducted using Item Response Theory (IRT). We investigated associations of latent variable severity with objective indices of persistent physical disability, pulmonary and kidney dysfunction, and C-reactive protein and D-dimer blood levels, measured at the same follow-up assessment., Results: The EFA extracted one factor, explaining 64.8% of variance; loadings were positive for all symptoms, and above 0.35 for 16 of them. The latent trait generated using IRT placed fatigue, psychiatric, and cognitive manifestations as the most discriminative symptoms (coefficients > 1.5, p < 0.001). Latent trait severity was associated with decreased body weight and poorer physical performance (coefficients > 0.240; p ⩽ 0.003), and elevated blood levels of C-reactive protein (coefficient = 0.378; 95% CI 0.215-0.541; p < 0.001) and D-dimer (coefficient = 0.412; 95% CI 0.123-0.702; p = 0.005). Results were similar after excluding subjects with pro-inflammatory comorbidities., Conclusions: Different symptoms that persist for several months after moderate or severe COVID-19 may unite within one latent trait of PASC. This trait is dominated by fatigue and psychiatric symptoms, and is associated with objective signs of physical disability and persistent systemic inflammation.

Objective: The prevalence and significance of schizophrenia-related phenotypes at the population level is debated in the literature. Here, the authors assessed whether two recently reported neuroanatomical signatures of schizophrenia-signature 1, with widespread reduction of gray matter volume, and signature 2, with increased striatal volume-could be replicated in an independent schizophrenia sample, and investigated whether expression of these signatures can be detected at the population level and how they relate to cognition, psychosis spectrum symptoms, and schizophrenia genetic risk., Methods: This cross-sectional study used an independent schizophrenia-control sample (N=347; ages 16-57 years) for replication of imaging signatures, and then examined two independent population-level data sets: typically developing youths and youths with psychosis spectrum symptoms in the Philadelphia Neurodevelopmental Cohort (N=359; ages 16-23 years) and adults in the UK Biobank study (N=836; ages 44-50 years). The authors quantified signature expression using support-vector machine learning and compared cognition, psychopathology, and polygenic risk between signatures., Results: Two neuroanatomical signatures of schizophrenia were replicated. Signature 1 but not signature 2 was significantly more common in youths with psychosis spectrum symptoms than in typically developing youths, whereas signature 2 frequency was similar in the two groups. In both youths and adults, signature 1 was associated with worse cognitive performance than signature 2. Compared with adults with neither signature, adults expressing signature 1 had elevated schizophrenia polygenic risk scores, but this was not seen for signature 2., Conclusions: The authors successfully replicated two neuroanatomical signatures of schizophrenia and describe their prevalence in population-based samples of youths and adults. They further demonstrated distinct relationships of these signatures with psychosis symptoms, cognition, and genetic risk, potentially reflecting underlying neurobiological vulnerability.

Background: Sociodemographic and environmental factors are associated with incidence, severity, and mortality of COVID-19. However, little is known about the role of such factors in persisting symptoms among recovering patients. We designed a cohort study of hospitalized COVID-19 survivors to describe persistent symptoms and identify factors associated with post-COVID-19 syndrome., Methods: We included patients hospitalized between March to August 2020 who were alive six months after hospitalization. We collected individual and clinical characteristics during hospitalization and at follow-up assessed ten symptoms with standardized scales, 19 yes/no symptoms, a functional status and a quality-of-life scale and performed four clinical tests. We examined individual exposure to greenspace and air pollution and considered neighbourhood´s population density and socioeconomic conditions as contextual factors in multilevel regression analysis., Results: We included 749 patients with a median follow-up of 200 (IQR = 185-235) days, and 618 (83%) had at least one of the ten symptoms measured with scales. Pain (41%), fatigue (38%) and posttraumatic stress disorder (35%) were the most frequent. COVID-19 severity, comorbidities, BMI, female sex, younger age, and low socioeconomic position were associated with different symptoms. Exposure to ambient air pollution was associated with higher dyspnoea and fatigue scores and lower functional status., Conclusions: We identified a high frequency of persistent symptoms among COVID-19 survivors that were associated with clinical, sociodemographic, and environmental variables. These findings indicate that most patients recovering from COVID-19 will need post-discharge care, and an additional burden to health care systems, especially in LMICs, should be expected., Competing Interests: Disclosure of interest: The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author) and declare the following activities and relationships: Dr Ferreira received speaker fees from Medtronic, outside of the submitted work. Dr Burdmann received speaker fees from AstraZeneca and Fresenius, outside of the submitted work. Dr Guedes holds stock in Fleury Ltd, a clinical analysis laboratory, which is not the provider of tests for this study., (Copyright © 2022 by the Journal of Global Health. All rights reserved.)

Objective: The aim was to examine the psychometric properties of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) as a diagnostic tool to screen for dementia in aging individuals with Down syndrome (DS)., Methods: This was a cross-sectional study of 92 individuals with DS 30 y or above of age) evaluated with the IQCODE. Using the informant questionnaire of the Cambridge Examination for Mental Disorders of Older People with Down's Syndrome and Others with Intellectual Disabilities, we divided the subjects into 3 diagnostic groups: stable cognition; prodromal dementia; and dementia. The ability of the IQCODE to discriminate between diagnostic groups was analyzed by calculating the areas under the receiver operator characteristic curves (AUCs)., Results: The optimal IQCODE cutoffs were 3.14 for dementia versus stable cognition (AUC=0.993; P<0.001) and 3.11 for prodromal dementia+dementia versus stable cognition (AUC=0.975; P<0.001), with sensitivity/specificity/accuracy of 100%/96.8%/97.3%, and 93.3%/91.9%/92.4%, respectively. The IQCODE showed a weak-to-moderate correlation with cognitive performance (P<0.05)., Conclusion: The IQCODE is a useful tool to screen for cognitive decline in individuals with DS and is suitable for use in a primary care setting., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls, affecting widespread cortical regions. The possible impacts of these regional alterations in terms of structural network effects have not previously been characterized. Inter-regional morphological covariance analysis can capture network connectivity between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1455 individuals with ASD and 1560 controls, across 43 independent datasets of the ENIGMA consortium's ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered average asymmetry of networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, involving higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve executive functions, language-related and sensorimotor processes. These findings provide a network-level characterization of altered left-right brain asymmetry in ASD, based on a large combined sample. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity., (© 2022. The Author(s).)

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Disease heterogeneity is a significant obstacle to understanding pathological processes and delivering precision diagnostics and treatment. Clustering methods have gained popularity for stratifying patients into subpopulations (i.e., subtypes) of brain diseases using imaging data. However, unsupervised clustering approaches are often confounded by anatomical and functional variations not related to a disease or pathology of interest. Semi-supervised clustering techniques have been proposed to overcome this and, therefore, capture disease-specific patterns more effectively. An additional limitation of both unsupervised and semi-supervised conventional machine learning methods is that they typically model, learn and infer from data using a basis of feature sets pre-defined at a fixed anatomical or functional scale (e.g., atlas-based regions of interest). Herein we propose a novel method, "Multi-scAle heteroGeneity analysIs and Clustering" (MAGIC), to depict the multi-scale presentation of disease heterogeneity, which builds on a previously proposed semi-supervised clustering method, HYDRA. It derives multi-scale and clinically interpretable feature representations and exploits a double-cyclic optimization procedure to effectively drive identification of inter-scale-consistent disease subtypes. More importantly, to understand the conditions under which the clustering model can estimate true heterogeneity related to diseases, we conducted extensive and systematic semi-simulated experiments to evaluate the proposed method on a sizeable healthy control sample from the UK Biobank (N = 4403). We then applied MAGIC to imaging data from Alzheimer's disease (ADNI, N = 1728) and schizophrenia (PHENOM, N = 1166) patients to demonstrate its potential and challenges in dissecting the neuroanatomical heterogeneity of common brain diseases. Taken together, we aim to provide guidance regarding when such analyses can succeed or should be taken with caution. The code of the proposed method is publicly available at https://github.com/anbai106/MAGIC., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Objective: Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium., Methods: We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries., Results: There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing., Conclusion: Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait., (© 2021 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.)

The short-term memory binding (STMB) test involves the ability to hold in memory the integration between surface features, such as shapes and colours. The STMB test has been used to detect Alzheimer's disease (AD) at different stages, from preclinical to dementia, showing promising results. The objective of the present study was to verify whether the STMB test could differentiate patients with distinct biomarker profiles in the AD continuum. The sample comprised 18 cognitively unimpaired (CU) participants, 30 mild cognitive impairment (MCI) and 23 AD patients. All participants underwent positron emission tomography (PET) with Pittsburgh compound-B labelled with carbon-11 ([ 11 C]PIB) assessing amyloid beta (Aβ) aggregation (A) and 18fluorine-fluorodeoxyglucose ([ 18 F]FDG)-PET assessing neurodegeneration (N) (A-N- [n = 35]); A+N- [n = 11]; A+ N+ [n = 19]). Participants who were negative and positive for amyloid deposition were compared in the absence (A-N- vs. A+N-) of neurodegeneration. When compared with the RAVLT and SKT memory tests, the STMB was the only cognitive task that differentiated these groups, predicting the group outcome in logistic regression analyses. The STMB test showed to be sensitive to the signs of AD pathology and may represent a cognitive marker within the AD continuum., (Copyright © 2021 Elsevier Inc. All rights reserved.)