Thiago Peixoto Leal

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.

Germline and somatic mutations have traditionally been studied independently because they arise in distinct biological contexts and are shaped by different selective pressures. Despite these differences, both originate from the same molecular processes of DNA damage, replication error, and DNA repair. Yet this separation has limited the opportunity of investigation of genomic loci recurrently mutated across both mutational landscapes. Identifying such mutational co-occurrences may provide unique insights into the principles governing recurrent mutation. Here, we show that common germline polymorphisms and cancer-associated somatic SNVs recur at identical genomic positions across the human genome, sharing the same nucleotide substitutions more frequently than expected by chance. This recurrence persists within coding regions, is only minimally explained by the canonical hotspot contexts evaluated here (CpG islands and microsatellites), and is associated with a mutational signature profile enriched for the ubiquitous clock-like SBS5 signature together with DNA repair-associated signatures. Importantly, this overlap pattern is not shared across other germline variation: rare (AF<1%) and clinically classified variants exhibit significantly less overlap than expected. Together, these findings support the existence of intrinsically vulnerable genomic loci and provide a framework for investigating the mechanisms underlying recurrent mutation.

The genetics of Parkinson’s disease (PD) in underrepresented populations remain poorly characterized, potentially overlooking population-specific contributions. We analyzed 461 Chilean PD cases from a movement disorders center. Pathogenic, likely pathogenic, or GBA1 risk variants were identified in 58 individuals (12.6%), mainly in LRRK2 (50%) and GBA1 (44.8%), while PRKN, SNCA , and SQSTM1 collectively represented 5.2%. All LRRK2 variants were p.G2019S, with an overall frequency of 6.3%, the highest reported in South America, and enrichment of Ashkenazi Jewish ancestry at this locus. These findings characterize the genetic landscape of PD in Chile and support its relevance for LRRK2 -targeted studies.

Background: Evidence on environmental determinants of Parkinson’s disease (PD) in Latin America is limited and their attributable burden remains poorly defined in the region. We examined associations between environmental exposures and PD and quantified their contribution to disease burden.Methods: We analyzed 9887 participants from nine Latin American countries in a case control study. Associations between environmental exposures and PD were estimated using logistic regression adjusted for age, sex, and country. Population attributable fractions (PAFs) were calculated for positively associated exposures, defined as severe head trauma or at least 5 years of exposure for other risk factors.Findings: Weekly caffeine consumption and tobacco use for at least 5 years were inversely associated with PD (adjusted OR [aOR] 0·77, p < 0·0001; aOR 0·83, p = 0·0009). Severe head trauma (aOR 1·35, p < 0·0001), occupational pesticide exposure (aOR 1·42, p = 0·0003), occupational metal exposure (aOR 1·29, p = 0·0299), rural living (aOR 1·60, p < 0·0001), and well water consumption (aOR 1·22, p = 0·0014) were positively associated with PD. Dose related associations were observed for caffeine, tobacco, occupational pesticides and metals, rural living, and well water consumption. The joint PAF across five risk exposures was 13·7% (95% CI 9·8 to 17·3), with higher estimates in El Salvador, Brazil, Colombia, males, and participants younger than 60 years. Sensitivity and lag analyses were directionally consistent.Interpretation: Selected environmental exposures may account for a meaningful proportion of PD burden in Latin America, supporting further research and public health attention to environmental determinants in the region.

Quantitative pupillometry provides a noninvasive window into brain state and neurological function, but its broader use across experimental and clinical settings is limited by challenges in achieving accurate, scalable, and generalizable measurements. Here, we present NeuroPupil, a deep learning framework for high-throughput, cross-species pupillometry that emphasizes robust generalization across subjects, behavioral contexts, and imaging conditions. Through systematic benchmarking of training strategies and network architectures, we identify pooled multi-subject training combined with an optimized U-Net architecture as a key determinant of reliable and transferable pupil tracking performance. Across diverse mouse and human datasets, NeuroPupil achieves improved accuracy and substantial gains in computational efficiency compared to existing approaches, enabling practical analysis of large-scale datasets. We further demonstrate that improved pupil tracking fidelity enhances downstream biological inference: NeuroPupil-derived pupil features significantly improve prediction of distributed cortical activity in behaving mice and preserve diagnostically relevant temporal structure in human clinical recordings. These findings highlight the importance of precise and scalable measurement for linking pupil dynamics to brain activity and clinical phenotypes. By integrating benchmarking, scalability, and accessible software tools, NeuroPupil provides a reproducible framework for large-scale pupillometry and facilitates its application in systems and translational neuroscience.

Background: Although levodopa is the gold standard treatment for Parkinson's disease (PD), its chronic use is associated with levodopa-induced dyskinesia (LID), a motor complication that impacts prognosis, quality of life, and treatment costs. Most known LID-associated factors have been identified in European-descendant populations. Objectives: To describe the epidemiology of LID in Latin American and Caribbean (LATAM) countries and assess the relevance of known and novel LID-associated factors in this population. Methods: We conducted a cross-sectional study using data from the Latin American Research consortium on the Genetics of Parkinson's Disease (LARGE-PD). We included PD patients with information on LID status and levodopa use from eight LATAM countries. LID prevalence was calculated overall and by country. Countries were compared on demographic and clinical variables. Logistic regression was used to identify associations with LID. Results: A total of 3695 PD patients (58.8% male) were included. Overall LID prevalence was 25.4% [95% CI: 24.06–26.87], ranging from 9.3% in Colombia to 45.1% in Puerto Rico. Prevalence increased progressively with longer disease duration. Country comparisons showed that not all known LID-associated factors explained prevalence differences. In logistic regression, fast disease progression was significantly associated with LID (OR: 1.55, 95%CI: 1.16–2.07), while sex was not (OR: 1.02, 95%CI: 0.87–1.18). Conclusions: This is the largest study on LID epidemiology in LATAM. While some known risk factors remain relevant, others, like sex, do not, underscoring the need for population-specific studies. Future work should integrate environmental, clinical, and genetic data to better understand LID mechanisms.

X chromosome-wide association studies (XWAS) have successfully identified risk loci on the X chromosome associated with Parkinson’s disease (PD) susceptibility. However, only three such studies have been completed to date. Here, we present the first XWAS using an African cohort, comprising 690 PD cases and 826 controls. We applied an established XWAS workflow to perform male- and female-stratified analyses, as well as a combined meta-analysis. The male-stratified analysis identified five significant variants, including one lead locus (rs200539602), while the female-stratified analysis revealed 29 significant variants and two lead loci (rs2499550 and rs58045540), where rs2499550 is an upstream variant of the protein-coding gene FAAH2 . The remaining female-stratified significant variants are expression quantitative trait loci for SPIN2A, SPIN2B , and SPIN3 , which are highly expressed in the brain and nerve tissues, making them strong candidates for further investigation. One previously reported PD XWAS locus (rs28602900) was also replicated at a significance threshold of 0.05. The meta-analysis identified five variants surpassing chromosome-wide significance, including two lead loci (rs140715059 and rs141026964), the latter has no significant expression quantitative trait locus information but lies closest to the protein-coding gene MAGEC2 , which may warrant further follow-up. None of the meta-analysis signals replicated in prior neurodegenerative disease XWAS. Overall, this study provides novel insights into the contribution of the X chromosome to PD susceptibility and represents the first PD XWAS to include participants of African ancestry, highlighting the importance of extending genetic studies to diverse populations.

Background: Although levodopa remains the gold standard treatment for Parkinson’s disease (PD), its chronic use is associated with levodopa-induced dyskinesia (LID), a motor complication that impacts prognosis, quality of life, and treatment costs. Most known LID-associated factors have been identified in European-descendant populations. Objectives: To describe the epidemiology of LID in Latin American and Caribbean (LATAM) countries and assess the relevance of known and novel LID-associated factors in this population. Methods: We conducted a cross-sectional study using data from the Latin American Research consortium on the Genetics of Parkinson’s Disease (LARGE-PD). We included PD patients with information on LID status and levodopa use from eight LATAM countries. LID prevalence was calculated overall and by country. Countries were compared on demographic and clinical variables. Logistic regression was used to identify associations with LID. Results: A total of 3,695 PD patients (58.8% male) were included. Overall LID prevalence was 25.4% [95% CI: 24.06–26.87], ranging from 9.3% in Colombia to 45.1% in Puerto Rico. Prevalence increased progressively with longer disease duration. Country comparisons showed that not all known LID-associated factors explained prevalence differences. In logistic regression, fast disease progression was significantly associated with LID (OR: 1.55, 95%CI: 1.16–2.07), while sex was not (OR: 1.02, 95%CI: 0.87–1.18). Conclusions: This is the largest study on LID epidemiology in LATAM. While some known risk factors remain relevant, others, like sex, do not, underscoring the need for population-specific studies. Future work should integrate environmental, clinical, and genetic data to better understand LID mechanisms.

Risk prediction models play a crucial role in advancing healthcare by enabling early detection and supporting personalized medicine. Nonetheless, polygenic risk scores (PRS) for Parkinson’s disease (PD) have not been extensively studied across diverse populations, contributing to health disparities. In this study, we constructed 105 PRS using individual-level data from seven ancestries and compared two different models. Model 1 was based on the cumulative effect of 90 known European PD risk variants, weighted by summary statistics from four independent ancestries (European, East Asian, Latino/Admixed American, and African/Admixed). Model 2 leveraged multi-ancestry summary statistics using a p-value thresholding approach to improve prediction across diverse populations. Our findings provide a comprehensive assessment of PRS performance across ancestries and highlight the limitations of a “one-size-fits-all” approach to genetic risk prediction. We observed variability in predictive performance between models, underscoring the need for larger sample sizes and ancestry-specific approaches to enhance accuracy. These results establish a foundation for future research aimed at improving generalizability in genetic risk prediction for PD.

The All of Us Research Program ( All of Us ) seeks to accelerate biomedical research and address the underrepresentation of minorities by recruiting over one million ethnically diverse participants across the United States. A key question is how self-identification with discrete, predefined race and ethnicity categories compares to genetic diversity at continental and subcontinental levels. To contextualize the genetic diversity in All of Us , we analyzed ∼2 million common variants from 230,016 unrelated whole genomes using classical population genetics methods, alongside reference panels such as the 1000 Genomes Project, Human Genome Diversity Project, and Simons Genome Diversity Project. Our analysis reveals that participants within self-identified race and ethnicity groups exhibit a gradient of genetic diversity rather than discrete clusters. The distributions of continental and subcontinental ancestries show considerable variation within race and ethnicity, both nationally and across states, reflecting the historical impacts of U.S. colonization, the transatlantic slave trade, and recent migrations. All of Us samples filled most gaps along the top five principal components of genetic diversity in current global reference panels. Notably, “Hispanic or Latino” participants spanned much of the three-way (African, Native American, and European) admixture spectrum. Ancestry was significantly associated with body mass index (BMI) and height, even after adjusting for socio-environmental covariates. In particular, West-Central and East African ancestries showed opposite associations with BMI. This study emphasizes the importance of assessing subcontinental ancestries, as the continental approach is insufficient to control for confounding in genetic association studies.