Geneviève Richard

Objective: Bipolar (BD) and psychotic disorders (PD) are severe mental disorders (SMDs) associated with higher cardiometabolic disease burden. Prior studies of body composition in SMDs are inconclusive. Magnetic resonance imaging (MRI) offers detailed insights into body composition and may improve our understanding of cardiometabolic disease risk in patients with SMDs. Methods: We derived body composition measures from MRI of patients with BD (n=36, 63.9% females, mean age=36.6±10.9 years), PD (n=27, 33.3% females, mean age=31.7±8.9 years), and controls (n=251, 78.8% females, mean age=40.7±12.1 years). Using linear models we tested for case-control differences in body mass index (BMI) and body composition in all patients and split by diagnostic group (BD and PD), accounting for age, sex, and scanner, and subsequently adding BMI. Next, we tested for age- and sex-adjusted associations between body composition and antipsychotic dose in patients. Results: Analyses showed significantly higher BMI (BD: Cohen’s d=0.70; PD: d=0.65), abdominal subcutaneous fat (BD: d=0.78; PD: d=0.71), visceral fat (BD: d=0.76; PD=0.68), liver fat (BD: d=0.53; PD: n.s.), and thigh muscle fat infiltration (BD: d=0.80; PD: d=0.87) in cases compared to controls. When accounting for BMI, muscle fat infiltration remained significantly higher (BD: d=0.54; PD: d=0.68) and thigh muscle volume was lower (BD: d=-0.65; PD: d=-0.63). There were no significant associations of antipsychotic dose with BMI or body composition. Conclusions: The observed case-control differences suggest that individuals with BD and PD, at the group level, exhibit higher regional fat accumulation and lower muscle volume, possibly contributing to the heightened risk for cardiometabolic comorbidity in SMDs.

Wellbeing is shaped by an interplay of genetic and environmental factors and is associated with both health and functioning. It remains unclear whether genetic influences on wellbeing are linked to brain structure and, in turn, early-life psychopathology. Here, we investigated associations between wellbeing polygenic scores (PGS), magnetic resonance imaging (MRI)-derived measures of brain structure, and parent-reported measures of child psychopathology in a large cross-sectional sample of children from the Adolescent Brain Cognitive Development (ABCD) Study (n = 8844; 8.9-11.0 years old). Preregistered analyses revealed no significant associations between wellbeing PGS and regional cortical thickness or subcortical volumes and only a small negative association with surface area of the parahippocampal cortex (β = −0.03, p=.002), while an exploratory analysis identified a small positive association with intracranial volume (ICV; β = 0.04, p<.001). Preregistered analyses showed small negative associations between wellbeing PGS and general psychopathology (β = −0.09, p<.001) and both internalizing (β = - 0.09, p<.001) and externalizing problems (β = −0.07, p<.001). ICV partially mediated the relationships between wellbeing PGS and psychopathology, accounting for 1.3-3.3% of these relationships. The findings suggest that while wellbeing PGS have limited associations with regional brain structure in children, they exhibit small protective effects against psychopathology. Highlights: Wellbeing PGS show limited associations with brain structure in children. Negative association found between wellbeing PGS and parahippocampal surface area. Positive association found between wellbeing PGS and intracranial volume. Wellbeing PGS linked to lower levels of parent-reported child psychopathology. Intracranial volume partially mediate wellbeing PGS-psychopathology associations.

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal ‘trajectory’ of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15–90. The effects of dementia, mild cognitive impairment, Parkinson’s disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p < 0.001), while neither depression nor ADHD showed consistent associations with VLM scores (p > 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders.

The cerebellum has been linked to motor coordination, cognitive and affective processing, in addition to a wide range of clinical illnesses. To enable robust quantification of individual cerebellar anatomy relative to population norms, we mapped the normative development and aging of the cerebellum across the lifespan using brain scans of > 54k participants. We estimated normative models at voxel-wise spatial precision, enabling integration with cerebellar atlases. Applying the normative models in independent samples revealed substantial heterogeneity within five clinical illnesses: autism spectrum disorder, mild cognitive impairment, Alzheimer’s disease, bipolar disorder, and schizophrenia. Notably, individuals with autism spectrum disorder and mild cognitive impairment exhibited increased numbers of both positive and negative extreme deviations in cerebellar anatomy, while schizophrenia and Alzheimer’s disease predominantly showed negative deviations. Finally, extreme deviations were associated with cognitive scores. Our results provide a voxel-wise mapping of cerebellar anatomy across the human lifespan and clinical illnesses, demonstrating cerebellum’s nuanced role in shaping human neurodiversity across the lifespan and in different clinical illnesses.

Cerebral blood flow (CBF) is critical for brain metabolism and function. Age-related changes in CBF are associated with increased risk of neurocognitive disorders and vascular events such as stroke. Identifying correlates and positive modifiers of age-related changes in CBF before the emergence of incipient clinical decline may inform public health advice and clinical practice. Former research has been inconclusive regarding the association between regular physical activity and CBF, and there is a lack of studies on the association between level of everyday activities and CBF, in older adults. To investigate these relationships, 118 healthy community-dwelling adults (65-89 years) underwent pseudo-continuous arterial spin labeling (ASL) MRI, neurocognitive, physical, and activity assessments at baseline. Eighty-six participants completed a follow-up ASL MRI, on average 506 (SD = 113) days after the baseline scan. Cross-sectional analysis revealed credible evidence for positive associations between time spent on low intensity physical activity and CBF in multiple cortical and subcortical regions, time spent on moderate to vigorous intensity physical activity and accumbens CBF, participation in social activity and CBF in multiple cortical regions, and between reading and thalamic CBF, indicating higher regional CBF in more active adults. Longitudinal analysis revealed anecdotal evidence for an interaction between time and baseline level of gardening on occipital and parietal CBF, and baseline reading on pallidum CBF, indicating more change in CBF in adults with lower level of activity. The findings support that malleable lifestyle factors contribute to healthy brain aging, with relevance for public health guidelines.

Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences. Significance Statement Data sharing can increase the quality and rigor of scientific claims, but with large scale data sharing comes an increased need to combine non-equivalent measurements across studies. Auditory verbal learning tasks (AVLTs) are one of the most common research and clinical tools to evaluate memory constructs, but numerous distinct AVLTs are in common use, which creates challenges for data aggregation. We report methods to convert raw scores across common verbal learning instruments, constructed using harmonizing data from 53 studies from around the world. This approach can be replicated in other domains to address long standing data compatibility issues for researchers and clinicians.

Background: Cerebral blood flow (CBF) is critical for brain metabolism and overall function. Age-related changes in CBF have been associated with cognitive deficits and increased risk of neurocognitive disorders and vascular events such as stroke. Exercise is considered among the protective factors for age-related brain and cognitive impairment, but how different lifestyle characteristics, such as low or moderate-to-vigorous physical activity or frequency of everyday activities, relate to cross-sectional and longitudinal measures of CBF has not been established. Objective: With the main aim of identifying potential targets for interventions, our objective was to examine associations between cortical and subcortical CBF and frequency of diverse everyday activities in healthy community-dwelling adults aged 65-89 years, and assess to which degree activity level at baseline is associated with longitudinal changes in CBF across a one-to-two years interval. Method: One hundred nineteen ( N = 119) adults underwent brain magnetic resonance imaging (MRI), neurocognitive, physical, and activity assessment at baseline. CBF was obtained using pseudo-continuous arterial spin labelling (ASL) MRI. Frequency of everyday activities were measured using Frenchay Activities index, while minutes of low and moderate-to-vigorous intensity physical activity were measured using a StepWatch Activity Monitor. Eighty-six participants completed a follow-up ASL MRI, on average 506 (SD = 113) days after the baseline scan. Results: Bayesian multilevel modelling revealed positive associations between baseline cortical and subcortical CBF and various everyday activities. Higher baseline accumbens, putamen and pallidum CBF was associated with more time spent on low intensity (> 0 steps/minute to < 100 steps/minute) physical activity, higher accumbens and caudate CBF with more moderate to vigorous intensity (≥ 100 steps/minute) physical activity, higher cerebral cortical CBF with more participation in social activity, higher cortical and thalamic CBF with more reading, and higher baseline pallidum CBF with more actively pursuing hobbies. We did not find evidence for an association between baseline activity level and longitudinal changes in CBF. Conclusion: The identified associations between everyday activity measures and CBF provide new knowledge on malleable lifestyle factors that may indicate or contribute to healthy brain aging. In addition to the relevance for prioritizing targets for public health guidelines, our findings contribute to disclose parts of the intricate connection between brain metabolism and everyday activities in aging.