Clara A. Moreau

This paper develops a lifespan normative model of brain white matter microstructure using diffusion MRI data from 54,583 individuals, enabling detection of microstructural deviations in diseases like Alzheimer's and 22q11.2 deletion syndrome.

The paper introduces a multiscale resource integrating genetics, brain imaging, and clinical data from autistic individuals and their relatives to explore genetic and neurobiological patterns in autism.

The paper investigates how rare genetic mutations affect brain asymmetry by analyzing CNVs in a cohort of individuals and linking genetic alterations to brain structure and function.

This study examines subcortical brain alterations in CNV carriers across multiple neuropsychiatric disorders, finding shared and distinct patterns of structural changes.

The paper maps the odds ratio for autism associated with rare LoF variants in autism-associated genes and shows sub-diagnostic effects in undiagnosed individuals.

The paper identifies functional connectivity subtypes associated with ASD diagnosis and shows their generalizability across independent data.

The paper investigates how eight rare CNVs affect brain structure and phenotypes across 534 carriers, finding structural divergence and phenotypic convergence despite different genetic origins.

The paper examines how rare and common genomic variants affect brain functional connectivity, revealing how polygenicity and pleiotropy influence psychiatric conditions and brain networks.

Neuropsychiatric CNVs reorganize brain connectivity along shared patterns linked to cognitive traits and disorder severity.

The paper examines how CNVs in 16p11.2 and 22q11.2 affect functional brain connectivity in neuropsychiatric disorders, identifying shared dysconnectivity patterns across ASD, SZ, and deletions.

The paper estimates the effect sizes of deletions and duplications on autism risk and IQ using statistical models applied to CNV data from multiple cohorts.

The paper identifies a functional connectivity endophenotype that significantly increases ASD diagnosis risk and generalizes across independent data.

The paper examines the effects of neuropsychiatric CNVs on brain structure using neuroimaging data and identifies shared anatomical patterns across multiple CNVs.