Genome-wide association studies (GWASs) have identified numerous susceptibility loci for Parkinson’s disease (PD), but its genetic architecture remains underexplored in populations of non-European ancestry. To identify genetic variants associated with PD in the Chinese population, we performed a GWAS using whole-genome sequencing (WGS) in 1,972 cases and 2,478 controls, and a replication study in a total of 8209 cases and 9454 controls. We identified one new risk variant rs61204179 (P_combined = 1.47 × 10⁻⁹) with low allele frequency, four previously reported risk variants (NUCKS1/RAB29-rs11557080,SNCA-rs356182,FYN-rs997368, andVPS13C-rs2251086), as well as three risk variants inLRRK2coding region (A419V, R1628P, and G2385R) with genome-wide significance (P < 5 × 10⁻⁸) for PD in Chinese population. Moreover, of the reported genome-wide significant risk variants found mostly in European ancestry populations, the correlation coefficient (r_b) of effect size accounting for sampling errors was 0.91 between datasets and 63.6% attainedP < 0.05 in Chinese population. Accordingly, we estimated a heritability of 0.14–0.18 for PD, and a moderate genetic correlation between European ancestry and Chinese populations (r_g = 0.47, se = 0.21). Polygenic risk score (PRS) analysis revealed that individuals with PRS values in the highest quartile had a 3.9-fold higher risk of developing PD than the lowest quartile. In conclusion, the present GWAS identified PD-associated variants in Chinese population, as well as genetic factors shared among distant populations. Our findings shed light on the genetic homogeneity and heterogeneity of PD in different ethnic groups and suggested WGS might continue to improve our understanding of the genetic architecture of PD.

Background: The mechanisms underlying the pathogenesis and progression of Parkinson’s disease (PD) remain elusive, but recent opinions and perspectives have focused on whether the inflammation process induced by microglia contributes to α-synuclein-mediated toxicity. Migration of microglia to the substantia nigra (SN) could precede neurodegeneration inA53Tmice. We hypothesized that CXCL12 could be a mediator in the α-synuclein-induced migration of microglia.Methods: After establishing appropriate animal and cell culture models, we explored the relationship between α-synuclein and CXCL12 inA53Tmice, primary microglia, and BV-2 cell lines. We also explored the mechanisms of these interactions and the signaling processes involved in neuroinflammation.Results: We confirmed the positive correlation between α-synuclein and CXCL12 in the postmortem brain tissue of PD patients and the upregulated CXCR4 expression in SN microglia ofA53Tmice. In addition, as expected, α-synuclein increased the production of CXCL12 in microglia via TLR4/IκB-α/NF-κB signaling. Importantly, CXCL12/CXCR4/FAK/Src/Rac1 signaling was shown to be involved in α-synuclein-induced microglial accumulation.Conclusions: Our study suggests that CXCL12 could be a novel target for the prevention of α-synuclein-triggered ongoing microglial responses. Blocking CXCL12/CXCR4 may be a potential therapeutic approach for PD progression.

BACKGROUND. Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) plays an important role in the clearance of pathological amyloid-β (Aβ) in Alzheimer’s disease (AD). This study aimed to explore sTREM2 as a central and peripheral predictor of the conversion from mild cognitive impairment (MCI) to AD. METHODS. sTREM2 and Aβ_1–42 levels in cerebrospinal fluid (CSF) and florbetapir-PET (AV45) images were analyzed for healthy control (HCs), patients with MCI, and patients with AD from the ADNI database. Peripheral plasma sTREM2 and Aβ_1–42 levels were determined for our Neurology database of Ruijin Hospital for Alzheimer’s Disease (NRHAD) cohort, and patients with MCI were reevaluated at follow-up visits to assess for progression to AD. The association between CSF and plasma sTREM2 levels was analyzed in data from the Chinese Alzheimer’s Biomarker and Lifestyle (CABLE) database. RESULTS. The results showed that patients with MCI who had low levels of CSF sTREM2 and Aβ_1–42 were more likely to develop AD. Among participants with positive Aβ deposition, as assessed by AV45 imaging, elevated CSF sTREM2 levels were associated with a decreased risk of MCI-to-AD conversion. Meanwhile, in the NRHAD cohort, individuals in the MCI group with high sTREM2 levels in plasma were at a greater risk for AD, whereas low Aβ_1–42 with high sTREM2 levels in plasma were associated with a faster cognitive decline. In addition, CSF sTREM2 levels were highly correlated with plasma sTREM2 levels in the CABLE database. CONCLUSION. These findings suggest that sTREM2 may be useful as a potential predictive biomarker of MCI-to-AD conversion. FUNDING. This study was supported by grants from the National Natural Science Foundation of China (grant nos. 82001341, 82071415, 81873778, and 82201392); the Shanghai Sailing Program (grant no. 22YF1425100); and the China Postdoctoral Science Foundation funded project (grant no. 2021M702169).

Background: Inflammations play crucial role in the pathogenesis of Parkinson’s disease (PD), however, their possible value in the diagnosis or tracking of the progress of PD is still limited, because of discordant results in the literature and a lack of information regarding its reproducibility. Thus, overall longitudinal and cross-sectional studies are needed. This multicentre study was designed to investigate the association between multiple peripheral immune biomarkers and the development and progression of PD. Methods: This was a longitudinal and multicentre study. First, we measured the levels of five typical cytokines and five focused chemokines in 76 PD patients and 76 healthy controls (HCs) in a discovery cohort. Then, a validation cohort of 80 PD and 80 HC participants was recruited from four multicentre locations. In addition, a prospective follow-up of early-stage PD patients was performed with significant biomarkers. Finally, we performed further verification in an exploratory set of patients with idiopathic REM sleep behaviour disorder (iRBD). Results: In the discovery set, CXCL12, CX3CL1 and IL-8 levels were significantly higher in PD patients than in HCs (p < 0.05). The receiver-operating characteristic (ROC) curve for a combination of these three biomarkers produced a high area under the curve (AUC) of 0.89 (p < 0.001). Moreover, four biomarkers (the previous three and CCL15) were significantly associated with PD in the discovery and validation cohorts. Furthermore, in the prospective follow-up cohort, CX3CL1 levels were associated with motor progression after a mean interval of 43 months. In addition, CX3CL1 and IL-8 levels were higher in iRBD patients than in HCs. Conclusion: We showed a correlation between a profile of four peripheral immune biomarkers and PD development and progression. Our findings may provide a basis whereby PD patients with abnormal inflammatory profiles can be identified and receive timely therapeutic interventions.

Parkinson’s disease (PD) lacks reliable, non-invasive biomarker tests for early intervention and management. Thus, a minimally invasive test for the early detection and monitoring of PD and REM sleep behavior disorder (iRBD) is a highly unmet need for developing drugs and planning patient care. Extracellular vehicles (EVs) are found in a wide variety of biofluids, including plasma. EV-mediated functional transfer of microRNAs (miRNAs) may be viable candidates as biomarkers for PD and iRBD. Next-generation sequencing (NGS) of EV-derived small RNAs was performed in 60 normal controls, 56 iRBD patients and 53 PD patients to profile small non-coding RNAs (sncRNAs). Moreover, prospective follow-up was performed for these 56 iRBD patients for an average of 3.3 years. Full-scale miRNA profiles of plasma EVs were evaluated by machine-learning methods. After optimizing the library construction method for low RNA inputs (named EVsmall-seq), we built a machine learning algorithm that identified diagnostic miRNA signatures for distinguishing iRBD patients (AUC 0.969) and PD patients (AUC 0.916) from healthy individuals; and PD patients (AUC 0.929) from iRBD patients. We illustrated all the possible expression patterns across healthy-iRBD-PD hierarchy. We also showed 20 examples of miRNAs with consistently increasing or decreasing expression levels from controls to iRBD to PD. In addition, four miRNAs were found to be correlated with iRBD conversion. Distinct characteristics of the miRNA profiles among normal, iRBD and PD samples were discovered, which provides a panel of promising biomarkers for the identification of PD patients and those in the prodromal stage iRBD.

Background: A number of promising biomarkers for predicting imminent α-synucleinopathies have been suggested in isolated rapid eye movement sleep behaviour disorder (iRBD). However, existing evidence is conflicting without quantitative evaluation.Methods: PubMed, Web of Science and ClinicalTrials.gov were searched through June 2021 to identify possible predictors of phenoconversion from iRBD to Parkinson’s disease (PD). The pooled HRs and standardised mean differences (SMDs) with 95% CIs were calculated using fixed-effects or random-effects model.Results: A total of 123 studies were included in the meta-analysis. Significant motor dysfunction (HR 1.83, 95% CI 1.33 to 2.51, I²=86.8%, p<0.001), constipation (HR 1.52, 95% CI 1.26 to 1.84, I²=8.3%, p=0.365), orthostatic hypotension (HR 1.93, 95% CI 1.05 to 3.53, I²=54.9%, p=0.084), hyposmia (HR 2.78, 95% CI 1.83 to 4.23, I²=23.9%, p=0.255), mild cognitive impairment (HR 2.27, 95% CI 1.58 to 3.27, I²=0%, p=0.681) and abnormal colour vision (SMD −0.34, 95% CI −0.63 to −0.05, I²=45.6%, p=0.087) correlated with susceptibility to PD. The process can also be traced by putaminal dopamine transporter imaging (HR 2.60, 95% CI 1.94 to 3.48, I²=0%, p=0.781) and tonic electromyographic activity (HR 1.50, 95% CI 1.04 to 2.15, I²=70%, p=0.018).Conclusions: The predictive value of each biomarker was initially highlighted with comprehensive evaluation. Combining specific predictors with high sensitivity is promising for detecting phenoconversion in the prodromal stage. Large-scale and multicentre studies are pivotal to extend our findings.