Digital biomarkers for precision diagnosis and monitoring in Parkinson's disease.

Parkinson's disease (PD) is a multifactorial neurodegenerative disorder with high prevalence among the elderly, primarily manifested by progressive decline in motor function. The aging global demographic and increased life expectancy have led to a rapid surge in PD cases, imposing a significant societal burden. PD along with other neurodegenerative diseases has garnered increasing attention from the scientific community. In PD, motor symptoms are recognized when approximately 60% of dopaminergic neurons have been damaged. The irreversible feature of PD and benefits of early intervention underscore the importance of disease onset prediction and prompt diagnosis. The advent of digital health technology in recent years has elevated the role of digital biomarkers in precisely and sensitively detecting early PD clinical symptoms, evaluating treatment effectiveness, and guiding clinical medication, focusing especially on motor function, responsiveness and sleep quality assessments. This review examines prevalent digital biomarkers for PD and highlights the latest advancements.

The potential protective role of peripheral immunophenotypes in Alzheimer's disease: a Mendelian randomization study.

Introduction: Alzheimer's disease (AD) is the most widespread neurodegenerative disease in the world. Previous studies have shown that peripheral immune dysregulation plays a paramount role in AD, but whether there is a protective causal relationship between peripheral immunophenotypes and AD risk remains ambiguous. Methods: Two-sample Mendelian randomization (MR) was performed using large genome-wide association study (GWAS) genetic data to assess causal effects between peripheral immunophenotypes and AD risk. Utilizing the genetic associations of 731 immune cell traits as exposures. We adopted the inverse variance weighted method as the primary approach. The Weighted median and MR-Egger regression methods were employed as supplements. Various sensitivity analyses were performed to assess the robustness of the outcomes. Results: Based on the IVW method, we identified 14 immune cell traits that significantly reduced the risk of AD, of which six demonstrated statistical significance in both IVW and Weighted median methods. Among the seven immune traits, four were related to regulatory T (Treg) cells : (1) CD25++ CD45RA- CD4 not regulatory T cell % T cell (odds ratio (OR) [95% confidence interval (CI)] = 0.96 [0.95, 0.98], adjusted P = 1.17E-02), (2) CD25++ CD45RA- CD4 not regulatory T cell % CD4+ T cell (OR [95% CI] = 0.97 [0.96, 0.99], adjusted P = 3.77E-02), (3) Secreting CD4 regulatory T cell % CD4 regulatory T cell (OR [95% CI] = 0.98 [0.97, 0.99], adjusted P = 7.10E-03), (4) Activated & secreting CD4 regulatory T cell % CD4 regulatory T cell(OR [95% CI] = 0.98 [0.97, 0.99], adjusted P = 7.10E-03). In addition, HLA DR++ monocyte % monocyte (OR [95% CI] = 0.93 [0.89, 0.98], adjusted P = 4.87E-02) was associated with monocytes, and HLA DR on myeloid Dendritic Cell (OR [95% CI] = 0.93 [0.89, 0.97], adjusted P = 1.17E-02) was related to dendritic cells (DCs). Conclusion: These findings enhance the comprehension of the protective role of peripheral immunity in AD and provide further support for Treg and monocyte as potential targets for immunotherapy in AD.

Joint analysis of proteome, transcriptome, and multi-trait analysis to identify novel Parkinson's disease risk genes.

Genome-wide association studies (GWAS) have identified multiple risk variants for Parkinson's disease (PD). Nevertheless, how the risk variants confer the risk of PD remains largely unknown. We conducted a proteome-wide association study (PWAS) and summary-data-based mendelian randomization (SMR) analysis by integrating PD GWAS with proteome and protein quantitative trait loci (pQTL) data from human brain, plasma and CSF. We also performed a large transcriptome-wide association study (TWAS) and Fine-mapping of causal gene sets (FOCUS), leveraging joint-tissue imputation (JTI) prediction models of 22 tissues to identify and prioritize putatively causal genes. We further conducted PWAS, SMR, TWAS, and FOCUS using a multi-trait analysis of GWAS (MTAG) to identify additional PD risk genes to boost statistical power. In this large-scale study, we identified 16 genes whose genetically regulated protein abundance levels were associated with Parkinson's disease risk. We undertook a large-scale analysis of PD and correlated traits, through TWAS and FOCUS studies, and discovered 26 casual genes related to PD that had not been reported in previous TWAS. 5 genes (CD38, GPNMB, RAB29, TMEM175, TTC19) showed significant associations with PD at both the proteome-wide and transcriptome-wide levels. Our study provides new insights into the etiology and underlying genetic architecture of PD.

Association between irritable bowel syndrome and Parkinson's disease by Cohort study and Mendelian randomization analysis.

This study aimed to investigate the association between irritable bowel syndrome (IBS) and Parkinson's disease (PD) utilizing prospective cohort study and Mendelian randomization. The dataset contained a substantial cohort of 426,911 participants from the UK Biobank, discussing the association between IBS and PD with Cox proportional hazards models and case-control analysis while adjusting for covariates such as age, gender, ethnicity and education level. In univariate Cox regression model, the risk of PD was reduced in IBS patients (HR: 0.774, 95%CI: 0.625-0.956, P = 0.017), but the statistical significance diminished in the three models after adjusting for other variables. In a few subgroup analyses, IBS patients are less likely to develop into PD, and patients diagnosed with IBS after 2000 also had a lower risk (HR: 0.633, 95%CI: 0.403-0.994, P = 0.047) of subsequently developing PD. In addition, we matched five healthy control participants based on gender and age at the end of the study for each IBS patient diagnosed during the follow-up period, and logistic regression results (OR:1.239, 95%CI: 0.896-1.680, P = 0.181) showed that IBS was not associated with the risk of PD. Mendelian randomization did not find significant evidence of the causal relationship between IBS and Parkinson's disease (OR: 0.801, 95%CI: 0.570-1.278, P = 0.204). Overall, we suggest that IBS status is not associated with the risk of developing PD, and that these findings provide valuable insights into the clinical management and resource allocation of patients with IBS.