Kathryn Step

IntroductionAlthough there have been significant advances in the genetic etiology of Parkinson’s disease (PD), most of this research has been conducted in European populations. This study aimed to characterize the genetic landscape of PD in South Africa.MethodsWe recruited 689 PD probands across South Africa. These participants were genotyped using the NeuroBooster array in collaboration with the Global Parkinson’s Genetics Program (GP2). An in-house computational workflow was used to identify pathogenic missense variants, which were validated using Sanger sequencing. The CNV-Finder pipeline was used to screen for copy number variations (CNVs), which were validated using Multiplex Ligation-dependent Probe Amplification (MLPA). Previously identified pathogenic variants were used as positive controls in our analysis.ResultsWe identified 16 unique missense variants, confirming 15 with Sanger sequencing, in 47 individuals across seven well-established PD genes. Variants in GBA1 and PRKN were the most frequent. Additionally, 18 variants of unknown significance were found in known genes. Furthermore, seven new CNVs were identified, five in PRKN and two in SNCA, of which six were validated using MLPA. One of the CNVs was in the 5’ untranslated region of SNCA. When combining this data with previous findings, 3.5% of the probands have a genetic basis for their disease.ConclusionsWe conducted the largest pathogenic variant screening to date in this unique and underrepresented population, and our findings highlight the rare contribution of known pathogenic variants. This study underscores the importance of expanding genetic research in African cohorts to improve global understanding of PD etiology.

Young onset Parkinson’s disease may be caused by biallelic mutations in PRKN or other autosomal recessive Parkinson’s disease genes, but the majority of patients do not carry known monogenic variants. Previous studies have found an increased cumulative burden of common genetic risk variants for Parkinson’s disease in young onset patients, but the specific genetic architecture of non-monogenic young onset Parkinson’s disease is not well characterized. We conducted a genome-wide association study of 1,528 Parkinson’s disease patients with symptom onset between 18 and 40 years and 20,408 controls of European ancestry using data from The Global Parkinson’s Genetic Program, the International Parkinson’s Disease Genomics Consortium, and the NeuroGenetics Research Consortium. We performed meta-analyses of additive and recessive regression models and investigated associations between age at onset groups and different polygenic risk scores. An additive model meta-analysis identified six independent loci passing a genome-wide significance threshold, including three loci identified in previous genome-wide association studies (near SNCA , GBA1, and HIP1R ) and two loci not previously associated with Parkinson’s disease (rs74950462, P = 1.24×10 ^-8 and rs72848817, P = 4.89×10 ^-8 ). Furthermore, we identified a significant signal at the PRKN locus, prompting a follow-up analysis employing a recessive model. The recessive genome-wide association meta-analysis identified nine loci passing a genome-wide significance threshold, including SNCA , PRKN, and seven novel variants. Patients with onset between 18 and 40 years had significantly higher polygenic risk scores than later onset patients when the score was modelled specifically on genome-wide association statistics from independent young onset Parkinson’s disease participants versus healthy controls. This increased polygenic burden was driven in part by loci harbouring mitochondrial pathway genes. Our results indicate that previously unidentified common and low-frequency variants contribute specifically to the young onset subgroup of Parkinson’s disease. Association signals detected uniquely with a recessive model suggest that genetic susceptibility to young onset Parkinson’s disease may be partially driven by homozygous variation, in line with previous reports of increased runs of homozygosity in this particular group of patients and may be consistent with a loss of function mechanism. The findings support the notion of young onset Parkinson’s disease as a partly distinct subphenotype and highlight the mitochondrial pathway. These results may have implications for future precision medicine but should be interpreted with caution pending independent replication.

Background: Recessive genetic variation and extended runs of homozygosity (ROHs) may contribute to the unexplained heritability of Parkinson's disease (PD), particularly in diverse and understudied populations. Objective: We conducted the first large‐scale, multi‐ancestral investigation of PD to examine the impact of genome‐wide homozygosity on disease risk and age at onset (AAO). Using genotyping, imputed, and whole‐genome sequencing data from 36,127 PD cases and 19,475 controls across nine ancestral populations from the Global Parkinson's Genetics Program, we aimed to identify novel regions of homozygosity contributing to PD heritability. Methods: We analyzed ROHs for total length (SROH), number (NROH), average length (AVROH), and genomic inbreeding coefficient (FROH). ROHs were intersected with known PD, pallido‐pyramidal syndrome, and atypical parkinsonism gene regions and risk loci to assess pleomorphic or pleiotropic contributions. Homozygosity mapping identified ROH overlaps in families, consanguineous individuals, and early‐onset PD (EOPD) cases. Results: Significant differences in SROH, AVROH, NROH, and FROH were observed between case status across ancestries, persisting after excluding known PD‐associated recessive genes. Our analysis revealed distinct patterns of ROH enrichment associated with AAO, suggesting recessive genetic modifiers of PD. Homozygosity mapping was used to prioritize 52 variants either segregating in families or present in individuals with consanguinity. In total, 1,559 ROHs in consanguineous individuals and EOPD overlapped known PD gene regions and risk loci. Conclusions: ROH regions contribute to PD heritability across ancestries, partly reflecting recessive genetic architecture. Larger and more diverse whole‐genome sequencing studies are needed to identify rare recessive variants influencing PD risk. © 2026 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Parkinson’s disease (PD) is a complex neurodegenerative disorder with environmental and genetic influences. Using genotyping array data of 661 South African PD cases and 737 controls, we conduct a polygenic risk score (PRS) analysis using PRSice-2. Summary statistics from two PD association studies have been used as base datasets. We split the target dataset into training (70%; n = 979) and validation (30%; n = 419) cohorts. We test various clumping window sizes, linkage disequilibrium thresholds, and p -value thresholds to determine the optimal combination for risk prediction. Additionally, we investigate the variance explained by different combinations of covariates. Overall, we observe modest predictive performance (AUC: 0.5847-0.6183). Age at recruitment emerges as the strongest individual predictor, while sex contributes the least. These findings provide the first evaluation of PRS performance for PD in a highly admixed South African cohort, underscoring the importance of including underrepresented populations in genetic risk prediction. By systematically assessing predictive performance across two base datasets, we highlight how ancestry composition and study design affect risk estimation in diverse populations. This work lays a foundation for refining genomic prediction in admixed populations and contributes to ongoing efforts to ensure that advances in precision medicine are globally relevant.

Introduction: Although there have been significant advances in the genetic etiology of Parkinson’s disease (PD), most of this research has been conducted in European populations. This study aimed to characterize the genetic landscape of PD in South Africa.Methods: We recruited 689 PD probands across South Africa. These participants were genotyped using the NeuroBooster array in collaboration with the Global Parkinson’s Genetics Program (GP2). An in-house computational workflow was used to identify pathogenic missense variants. These were validated using Sanger sequencing. The CNV-Finder pipeline was used to screen for copy number variations (CNVs), which were validated using Multiplex Ligation-dependent Probe Amplification (MLPA). Previously identified pathogenic variants were used as positive controls in our analysis.Results: We identified 16 unique missense variants, confirming 15 with Sanger sequencing, in 47 individuals across seven well-established PD genes. Variants in GBA1 and PRKN were the most frequent. Additionally, 18 variants of unknown significance were found in known genes. Furthermore, seven new CNVs were identified, five in PRKN and two in SNCA, of which six were validated using MLPA. One of the CNVs was in the 5’ untranslated region of SNCA. When combining this data with previous findings, 3.5% of the probands have a genetic basis for their disease.Conclusions: We conducted the largest pathogenic variant screening to date in this unique and underrepresented population, and our findings highlight the rare contribution of known pathogenic variants. This study underscores the importance of expanding genetic research in African cohorts to improve global understanding of PD etiology.

Motivation: Copy Number Variations (CNVs) play pivotal roles in complex disease etiology, often requiring large sample sizes to analyze disease associations. While genotyping arrays offer a cost-effective approach for CNV detection using Log R Ratio (LRR) and B Allele Frequency (BAF) signals, existing independent array-based callers suffer from high false positive rates and noise susceptibility, burdening manual validation. Results: We present CNV-Finder, a deep learning pipeline employing Long Short-Term Memory (LSTM) networks for large-scale CNV identification within user-defined genomic regions. Trained on expert-annotated samples from the Global Parkinson’s Genetics Program across four neurodegenerative disease-associated genes (PRKN, LINGO2, MAPT, SNCA), CNV-Finder integrates human feedback to iteratively improve performance. In benchmarking across 105 936 samples spanning 11 ancestries and nearly 150 cohorts, the model achieved 91% and 89% visual confirmation rates for PRKN deletions and duplications at high-confidence thresholds. In two validation cohorts, CNV-Finder nominated 83% fewer candidates than a popular Hidden Markov Model-based caller while maintaining higher confirmation rates. Validation through MLPA, short-read, and long-read sequencing demonstrated robust performance, generalizing to diverse signatures including homozygous deletions and SNCA triplications absent from training. Our findings highlight human expertise’s value in complex loci like 17q21.31. Availability and implementation: CNV-Finder is freely available at https://github.com/nvk23/CNV-Finder.

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.

Parkinson’s disease (PD) is a complex neurodegenerative disorder with a substantial genetic influence. To better characterize the genetic landscape of PD in South Africa, we conducted the largest genetic screening to date for pathogenic single nucleotide and copy number variations (CNVs) using genotyping array data from 689 PD probands. We identified 16 unique missense variants, confirming 15 with Sanger sequencing, in 47 individuals across seven well-established PD genes, with GBA1 and PRKN being most frequent. Also in known PD genes, 18 variants of unknown significance were found. Additionally, CNV analysis using CNV-Finder revealed seven novel CNVs, five in PRKN and two in SNCA , of which, six were validated with Multiplex Ligation-dependent Probe Amplification. The findings highlight the contribution of both rare variants and structural rearrangements to PD in this underrepresented population. This study underscores the importance of expanding genetic research in African cohorts to improve global understanding of PD etiology.

Elucidating the genetic contributions to Parkinson’s disease aetiology across diverse ancestries is a critical priority for the development of targeted therapies in a global context. We conducted the largest sequencing characterization of potentially disease-causing, protein-altering and splicing mutations in 710 cases and 11 827 controls from genetically predicted African or African admixed ancestries. We explored copy number variants (CNVs) and runs of homozygosity in prioritized early onset and familial cases. Our study identified rare GBA1 coding variants to be the most frequent mutations among patients with Parkinson’s disease, with a frequency of 4% in our case cohort. Of the 18 GBA1 variants identified, 10 were previously classified as pathogenic or likely pathogenic, four were novel and four were reported as of uncertain clinical significance. The most common known disease-associated GBA1 variants in the Ashkenazi Jewish and European populations, p.Asn409Ser, p.Leu483Pro, p.Thr408Met and p.Glu365Lys, were not identified among the screened Parkinson’s disease cases of African and African admixed ancestry. Similarly, the European and Asian LRRK2 disease-causing mutational spectrum, including LRRK2 p.Gly2019Ser and p.Gly2385Arg genetic risk factors, did not appear to play a major role in Parkinson’s disease aetiology among West African ancestry populations. However, we found three heterozygous novel missense LRRK2 variants of uncertain significance, with two (p.Glu268Ala and p.Arg1538Cys) displaying higher frequencies in the African ancestry population reference datasets. Structural variant analyses revealed the presence of PRKN CNVs with a frequency of 0.7% in African and African admixed cases, with 66% of CNVs detected being compound heterozygous or homozygous in early-onset cases, providing further insights into the genetic underpinnings in early-onset juvenile Parkinson’s disease in these populations. Short tandem repeat analysis also identified ATXN3 CAG repeat expansions within the pathogenic range (CAGn > 45) in three patients with Parkinson’s disease of African ancestry. Novel genetic variation among screened genes warrants further replication and functional prioritization to unravel their pathogenic potential. Here, we created the most comprehensive genetic catalogue of both known and novel coding and splicing variants potentially linked to Parkinson’s disease aetiology in an underserved population and further conducted global and local ancestry analyses to further explore population-specific effects. Our study has the potential to guide the development of targeted therapies in the emerging era of precision medicine. By expanding genetics research to involve underrepresented populations, we hope that future Parkinson’s disease treatments are not only effective but also inclusive, addressing the needs of diverse ancestral groups.