Enhancing Parkinson's Disease Research: Recommendations for Addressing Genetic and Environmental Influences in Family History Studies

We recently read with interest the article by Federica Arienti et al published in Movement Disorders Clinical Practice, entitled "Family History in Parkinson's Disease: A National Cross-Sectional Study".1 This research, which analyzed the family histories of 2035 Parkinson's disease patients across 28 centers in Italy, highlighted the differences in age of onset and symptoms between familial Parkinson's disease and sporadic Parkinson's disease. It provides critical insights into the familial genetic background of Parkinson's disease. We commend the authors for their substantial contributions to this field and offer several suggestions to enhance the study's applicability and depth. First, the study did not adequately control for potentially confounding variables such as lifestyle, occupational exposure, and socioeconomic status, which may influence the precise assessment of the familial aggregation of Parkinson's disease. We recommend that future research efforts should incorporate comprehensive data on environmental exposures and socioeconomic factors. Additionally, employing multivariate regression models2 to adjust for these potential confounders is advised. Utilizing propagation separation techniques to balance baseline covariates between treatment and control groups could more accurately elucidate the combined effects of genetic and environmental factors on familial aggregation of the disease, thereby enhancing the foundation for developing preventive and therapeutic strategies. Second, although the authors employed a basic categorization method to label cases as "probable" and "unknown," which enabled the continuation of the study despite gaps in data, this approach may compromise the accuracy and reliability of the results. To enhance the management of missing data, future studies should consider employing multiple imputation techniques to effectively reduce the statistical bias introduced by missing data and enhance the robustness of the findings.3 Furthermore, the article did not adequately distinguish between different Parkinson's disease phenotypes and disease processes, potentially impacting the understanding of genetics and family history. To address this limitation, future research should implement a more detailed classification system to differentiate various subtypes of Parkinson's disease and integrate genotyping4 with clinical presentations. This approach would facilitate a more precise examination of the relationships between specific phenotypes and genetic variations, provide a scientific basis for personalized treatment, and aid in the development of more effective therapeutic strategies. Finally, drawing on principles of emergency management, several recommendations can be advanced to enhance prevention and management strategies for Parkinson's disease.5 It is advisable to establish an early surveillance and intervention program specifically for families at high risk. This program should focus on the early detection and management of Parkinson's disease indicators, incorporating regular neurological assessments and educational initiatives aimed at heightening awareness of the disease's early symptoms. In summary, this study contributes valuable insights into genetic research and the management of Parkinson's disease. We hope that our commentary will be considered, and we look forward to future research that addresses these issues, thereby continuing to deepen our understanding of Parkinson's disease. (1) Research project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript: A. Writing of the first draft, B. Review and Critique. R.Z.: 1A, 1B, 1C, 2A, 2B, 3A H.T.: 1A, 1B, 1C, 2A, 3A S.Z.: 1A, 1B, 2C, 3B Ethical Compliance Statement: The authors confirm that the approval of an institutional review board or informed patient consent were not required for this work. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this work is consistent with those guidelines. Funding Sources and Conflict of Interest: We would like to thank Prof Sheng Zhou for the financial support from the National Natural Science Foundation of China (NO: 82360358). The authors declare that there are no conflicts of interest relevant to this work. Financial Disclosures for the Previous 12 Months: The authors declare that there are no additional disclosures to report. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.