Maria Rivera Paz

Background: Parkinson’s disease (PD), the most common neurodegenerative movement disorder, is commonly thought of as an aging and sporadic disease; however, 5-14% of individuals experience disease onset before the age of 50 years (early-onset PD; EOPD) and about 20% have a positive family history. In the case of both EOPD and people with a family history of PD, evidence suggests higher rates of a disease-causing genetic contribution. Objectives: Our goal was to perform a variant screening of seven PD-related genes and 21 genes associated with related parkinsonian disorders to identify pathogenic/likely pathogenic variants and variants of uncertain significance within EOPD and family-history-positive individuals within the Latin American Research Consortium on the Genetics of PD (LARGE-PD). Methods: We performed short-read whole-genome sequencing on a subset of 263 individuals with EOPD and/or a familial history of PD who had no known pathogenic PD variant in genotyping data. Results: Of the analyzed individuals, a monogenic burden in primary and secondary PD genes due to pathogenic or likely pathogenic variants for PD was observed in 4.7%, an additional 5.5% had pathogenic or likely pathogenic variants for Gaucher’s disease, and 2.7% had known risk variants in GBA1 . Conclusions: By expanding the reported spectrum of disease-associated variants in a Latin American population, we identified previously unreported or underrepresented variants that would likely be missed by array-based or targeted screening approaches and contribute to the characterization of EOPD and familial PD in Latin America.

Although genetic variants are among the strongest risk factors for Alzheimer’s disease (AD), most associated variants reside in non-coding regions with unclear mechanisms. Here, we address that gap by fine-tuning the Akita DNA foundation model on high-resolution Hi-C data generated from neuronal progenitor cells (NPCs) and microglia to produce iNeuroAkita , a cell-context-aware three-dimensional (3D) genome model. iNeuroAkita shows improved correlation with experimental Hi-C contact maps and more accurate contact predictions at key AD loci (e.g. APOE and PSEN2) , and captures CTCF-dependent chromatin loops. Using in silico saturation mutagenesis (ISM) across 11,856 AD-associated single-nucleotide variants (SNVs) and 120 structural variants (SVs), we quantified impacts on chromatin spatial organization and identified two SNVs predicted to strongly disrupt 3D chromatin architecture: rs636317 at the MS4A locus that is predicted to disrupt local chromatic interactions and microglia eQTL rs7599054 that creates gained interactions connecting its surrounding region to CCNT2 and TMEM163 , consistent with enhancer–promoter activation in epigenomic and single-cell transcriptomic data. We also identified AD-associated deletions at the KANSL1 and ARMS2 that rewire local regulatory contacts and associate with cell-type-specific expression changes, demonstrating iNeuroAkita’s utility for systematic characterization of noncoding AD risk variants underlying 3D genome regulation.