Marla Mendes de Aquino

The paper identifies ancestry-specific genetic loci associated with autism spectrum disorder using admixture mapping across diverse populations.

The paper uses an AI-driven framework to model perturbations in brain organoids and identifies candidate genes for autism using genomic and clinical data.

The paper introduces SPADE, a QC metric that reduces bias from gene-sex interaction signals in large-scale GWAS by adjusting for sex-specific disease prevalence and preserving informative variants.

The paper curates 222 genes associated with autism spectrum disorder (ASD) using the EAGLE framework, identifying 78 with definitive evidence and highlighting differential expression patterns between ASD and broader neurodevelopmental disorders.

The paper re-evaluates genome-wide significance thresholds for low-frequency variants in autism, identifying novel variants and their functional roles.

This study conducts the first XWAS in an African cohort, identifying X chromosome variants associated with Parkinson's disease susceptibility in males and females.

The paper evaluates the role of compound heterozygous deletion events in autism by analyzing 9,766 families and finds modest enrichment of rare DelCH events in autistic individuals.

EAGLE-AI automates gene-autism linkage evidence extraction and scoring with high accuracy, though challenges remain in handling unscreened papers and supplementary materials.

This study introduces a DNA foundation model to assess functional genetic variation across diverse populations, demonstrating its utility in understanding Alzheimer's disease risk and ancestry-specific gene expression.

The paper identifies shared and divergent genetic mechanisms across psychiatric disorders using gene-set burden analysis of copy number variants.

The paper analyzes genome-wide data from 432 Peruvian urban individuals to reveal fine-scale population structure, admixture dynamics, and demographic patterns shaped by ancient and recent events.

The paper identifies DDX53 genetic variants in individuals with ASD, showing a link between DDX53 and ASD, and highlights implications for genetic testing and mouse modeling.

This study performs an X chromosome-wide association study (XWAS) in ASD, identifying 59 variants associated with ASD, including novel candidate genes like FGF13.

The paper identifies adaptive introgression in circadian rhythm genes across 76 global populations, finding 303 genes and intergenic regions with archaically derived variants under positive selection.

The paper analyzes African genetic contributions to the Americas, showing regional ancestry patterns and admixture dynamics linked to historical factors.