A systematic review published in the Egyptian Journal of Medical Human Genetics synthesizes a decade of genome-wide association studies (GWAS) focused on Parkinson’s disease, highlighting both consistent genetic risk factors and significant gaps in population diversity. The study, authored by Mahinaz A. Mashhour, Manal Abdel Wahed, and Mai S. Mabrouk, analyzes 35 original research articles published between 2015 and 2025. By examining these studies, the researchers aim to clarify the current genetic landscape of Parkinson’s disease and identify methodological challenges that hinder the equitable translation of genetic discoveries into clinical practice.
Parkinson’s disease is a progressive neurodegenerative disorder affecting approximately 1% of the population over the age of 50. It is characterized by the loss of dopaminergic neurons in the substantia nigra and the accumulation of alpha-synuclein protein inclusions known as Lewy bodies. While clinical treatments aim to restore dopaminergic signaling, there are currently no preventive or disease-modifying therapeutic options available. The genetic component of the disease remains complex, with important aspects of ancestry-specific risk loci and the consistency of genetic signals across different study designs still requiring clarification.
The review employed a structured search strategy using PubMed and Scopus databases to identify relevant GWAS studies. After screening 563 retrieved articles and removing duplicates and ineligible studies, 35 studies met the inclusion criteria. These studies varied considerably in sample size, ancestry, genotyping platforms, and analytical approaches. The researchers assessed the methodological quality of these studies using validated tools, including the Newcastle-Ottawa Scale for case-control and cohort studies, and the AXIS tool for cross-sectional studies.
Several loci were consistently identified as significantly associated with Parkinson’s disease susceptibility across multiple independent cohorts. The SNCA locus, which encodes the alpha-synuclein protein, was the most frequently identified variant, particularly the SNP rs356182, reported in at least nine studies. The LRRK2 locus, involved in vesicular trafficking and autophagy, was also prominently reported, with SNPs such as rs76904798 and rs190807041. Additionally, the MAPT locus, associated with tauopathies and neurodegeneration, and the GBA1 locus, linked to glucocerebrosidase deficiency, were frequently observed across the included datasets.
Despite the replication of these major risk loci, the review highlights significant ancestry-specific associations. In East Asian cohorts, SNCA and LRRK2 variants were genome-wide significant, while the DPP6 locus was identified exclusively in a Chinese population. In contrast, European studies repeatedly identified SNCA, MAPT, and LRRK2 as the most replicated loci. The GBA1 locus was notably significant in African and African-admixed populations, a finding that underscores the need for further exploration in underrepresented groups. However, representation of African, South Asian, and Latino populations remains limited, with only one study focused on African ancestry and single studies representing South Asian and Latino cohorts among the 35 included.
The methodological landscape of Parkinson’s disease genomics has expanded beyond traditional single-variant GWAS. Several studies incorporated machine learning models, such as artificial neural networks and random forest classifiers, to enhance risk prediction. Other approaches included gene-based burden tests and variance-component models to detect rare or low-frequency variant associations. The use of advanced imputation panels, such as TOPMed and GenomeAsia, has improved genomic coverage and accuracy compared to earlier references. These methodological advances offer complementary insights but remain primarily research tools due to limited validation and interpretability in clinical settings.
Risk of bias assessment revealed recurring methodological concerns across the included studies. Common issues included limited justification of sample size, incomplete reporting of participant and control selection procedures, and the absence of explicit strategies to address non-response or attrition. These limitations can undermine statistical power and introduce selection bias, potentially distorting observed associations. The variability in study design and the lack of standardized reporting across different ancestries complicate the interpretation of results and limit the generalizability of findings.
The review emphasizes that genetic associations in GWAS are often influenced by population-specific allele frequencies and linkage disequilibrium patterns. This leads to heterogeneity in identified risk loci across ancestries, where variants significant in European cohorts may be absent or fail to replicate in non-European populations. For instance, the GBA1 variant rs3115534 was primarily identified in African populations, while the DPP6 variant was found only in Chinese cohorts. This variation highlights the necessity for continued GWAS efforts in diverse populations to discover novel risk loci and ensure equitable genomic insights.
Translational implications of these findings are constrained by the current lack of functional validation and the limited integration of environmental and lifestyle factors into genetic risk models. While polygenic risk scores show potential for precision medicine, their transferability across ancestries is reduced by population-specific effects. The review notes that most included studies did not conduct trans-ancestry meta-analyses or report fine-mapping results, which are critical for determining whether signals are influenced by shared causal variants or ancestry-specific patterns.
Future research must address these gaps by incorporating larger, more inclusive cohorts and integrating multi-omics data. The development of ancestry-aware fine-mapping and trans-ethnic meta-analyses will be essential to counter Eurocentric bias and improve the generalizability of genetic findings. By combining advanced statistical methods with diverse population representation, the field can move beyond association signals to deliver clinically useful insights for early diagnosis and personalized treatment strategies.
The consistent identification of loci such as SNCA, LRRK2, MAPT, and GBA1 reinforces their central role in Parkinson’s disease biology. However, the reliance on European cohorts limits the reach of these genetic insights. As the field progresses, addressing methodological inconsistencies and expanding ancestral diversity will be crucial for achieving a comprehensive and equitable understanding of the genetic architecture of Parkinson’s disease.
The review distinguishes between the robustness of core genetic associations and the variability of population-specific signals, noting that while major loci are replicated across diverse cohorts, the specific single nucleotide polymorphisms often differ by ancestry. For example, the SNCA locus was reported in both East Asian and European cohorts, but the specific variants identified varied, such as rs356182 in European and Latino groups versus rs3796661 in East Asian populations. This variation suggests that the genetic architecture of Parkinson’s disease is not uniform across all human populations. The authors argue that these differences may stem from variations in allele frequencies, linkage disequilibrium patterns, or environmental interactions that are unique to specific ancestral groups. Consequently, relying solely on data from European-ancestry cohorts may obscure risk factors that are prevalent in other populations, limiting the global applicability of current genetic findings.
Methodological heterogeneity among the 35 included studies presented a significant challenge for synthesis, leading the authors to adopt a narrative approach rather than a quantitative meta-analysis. The studies varied widely in their design, including cross-sectional, cohort, and case-control formats, as well as in the genotyping platforms and imputation methods used. Some studies utilized the Haplotype Reference Consortium for imputation, while others employed more recent panels like TOPMed or GenomeAsia, which offer denser genomic coverage. This diversity in analytical pipelines means that direct comparison of effect estimates across studies was not feasible. The authors emphasized that this heterogeneity reflects the evolving nature of genomic research over the past decade, where improvements in technology and statistical methods have allowed for more complex analyses but also introduced variability in how results are generated and reported.
A common issue was the insufficient justification of sample size, which can reduce statistical power and increase the likelihood of false-negative results, particularly for variants with modest effect sizes. Additionally, many studies did not adequately describe how they handled non-response or attrition, a factor that can introduce selection bias, especially in longitudinal designs tracking disease progression or age at onset. The authors noted that these procedural limitations may contribute to inconsistencies in locus replication across different studies, as unstable effect estimates from underpowered analyses can fail to replicate in independent cohorts. This underscores the need for transparent reporting and rigorous study design in future research to ensure the reliability of genetic associations.
The authors suggest that future studies must incorporate diverse ancestries and use ancestry-aware analytical approaches to improve the generalizability of genetic insights and support the development of equitable precision medicine strategies.
However, the review cautions that the presence of these associations does not automatically translate into clinical utility. By expanding the inclusion of African, South Asian, and Latino populations in genomic studies, researchers can discover novel risk loci and ensure that genetic insights are applicable to a broader range of patients.
Subject of Research: Systematic review of genome-wide association studies in Parkinson’s disease focusing on ancestry-specific insights and methodological advances from 2015 to 2025.
Article Title: A decade of GWAS in Parkinson’s disease: ancestry-specific insights and methodological advances (2015–2025)
Article References: Mashhour, M. A., Wahed, M. A., & Mabrouk, M. S. (2026). A decade of GWAS in Parkinson’s disease: ancestry-specific insights and methodological advances (2015–2025). Egyptian Journal of Medical Human Genetics, 27(1), Article 54. https://doi.org/10.1186/s43042-026-00873-1
Image Credits: AI Generated
DOI: 10.1186/s43042-026-00873-1
Keywords: Parkinson’s disease, GWAS, Genetics, Ancestry, SNCA, LRRK2, Systematic review, Neurodegeneration, Genomics, Methodology, decade, Parkinson