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Biomedical subjects

Marla Mendes

Publications and source records attributed to Marla Mendes.

3 recordsLinked to original sources

Characterizing features of the genetic architecture underlying autism from a multi-ancestry perspective.

Autism spectrum disorder (ASD; MIM 209850) is reported to vary globally from 0.01% in East Asian populations to 4.36% in certain Australian cohorts. Despite high heritability estimates (61-94%), the genetic architecture underlying ASD susceptibility remains poorly characterized across diverse populations, as most genomic studies have initially focused on individuals of European ancestry. To investigate ancestry-specific genetic contributions to ASD, we analyzed whole-genome sequencing data from three independent ASD cohorts. We identified admixed ASD probands (n = 1 033) and ancestry-matched controls (n = 1 033) and performed admixture mapping (AM). AM using five continental reference populations (European, African, East Asian, South Asian, and Native American) identified five ancestry-specific ASD-susceptibility loci, including one African-related locus at 1p21.2 near S1PR1 and four Native American-associated loci at chromosome 11q13.4. Three of these latter loci were contiguous and encompassed genes previously implicated in ASD, notably SHANK2 and DHCR7, with fine-mapping identifying a significantly associated variant between the two genes (rs77695321; P = 1.52 × 10⁻⁷). The fourth Native American-associated signal at 11q13.4 overlapped the folate receptor genes FOLR1 and FOLR3, with fine-mapping identifying a genome-wide significant variant (rs7950807; P = 5.21 × 10⁻⁸). A secondary admixture mapping analysis restricted to Latin American individuals, incorporating 6 487 Brazilian controls, identified 16 additional ancestry-specific loci across seven genomic regions.

Journal Article

Peruvian Population Genomics: Unraveling the Genetic Landscape and Admixture Dynamics of Urban Populations.

Latin American populations exhibit high genetic and phenotypic diversity shaped by complex admixture histories, yet remain underrepresented in genomic research. Here, we analyze genome-wide data from 432 urban individuals across 13 regions of Peru, including 346 newly genotyped from the Peruvian Genome Project. We revealed fine-scale population structure and demographic patterns shaped by both ancient and recent events. Indigenous American ancestries in urban individuals trace back to ancient north-south interactions consisted with archaeological records, while admixture events occurring within the last 8-10 generations involved sources already admixed between distinct ancestral lineages. Identity-by-descent analyses reveal sustained gene flow in southern Peru, while effective population size trends highlight demographic stability in Lima over the past 25 generations. Sex-biased admixture patterns suggest Indigenous ancestry contribution preferentially mediated by females. These findings offer a comprehensive view of Peru's genetic heritage, advancing our understanding of human genetic diversity and historical demographic processes in Latin America.

Admixture

Genetics of Latin American Diversity Project: Insights into population genetics and association studies in admixed groups in the Americas.

Latin Americans are underrepresented in genetic studies, increasing disparities in personalized genomic medicine. Despite available genetic data from thousands of Latin Americans, accessing and navigating the bureaucratic hurdles for consent or access remains challenging. To address this, we introduce the Genetics of Latin American Diversity (GLAD) Project, compiling genome-wide information from 53,738 Latin Americans across 39 studies representing 46 geographical regions. Through GLAD, we identified heterogeneous ancestry composition and recent gene flow across the Americas. Additionally, we developed GLAD-match, a simulated annealing-based algorithm, to match the genetic background of external samples to our database, sharing summary statistics (i.e., allele and haplotype frequencies) without transferring individual-level genotypes. Finally, we demonstrate the potential of GLAD as a critical resource for evaluating statistical genetic software in the presence of admixture. By providing this resource, we promote genomic research in Latin Americans and contribute to the promises of personalized medicine to more people.

Humans