BACKGROUND:Loss of Y chromosome (LOY), an age-related somatic mutation, is associated with various age-related diseases, but its role in the onset and progression of Parkinson's disease (PD) remains unclear. This study investigated the relationship between blood LOY levels and the risk of PD onset and progression. METHODS:We estimated the LOY level for each male participant based on genome-wide arrays or whole genome sequencing data. We performed Cox proportional hazards regression analysis among 222,598 male participants in the UK Biobank and linear mixed model analysis involving 2574 male individuals with PD across 14 cohorts, encompassing 19,562 visits. In the Parkinson's Progression Markers Initiative (PPMI) cohort, we further compared brain structure using T1-weighted magnetic resonance imaging (MRI) scans, and carried out brain network functional connectivity analysis based on resting-state functional MRI (rs-fMRI) datasets. Additionally, we assessed the LOY status in single-nucleus RNA sequencing (snRNA-seq) data, which included 1,303,531 cells from 279 post-mortem samples across five brain regions, and performed temporal dynamic gene expression analysis. FINDINGS:Male participants with LOY had a slightly higher risk of developing PD during follow-up (HR = 1·16, 95% CI = 1·01-1·34, P = 0·04). Among males affected by PD, LOY carriers experienced accelerated neurodegenerative progression, manifesting as more rapid motor impairment (P = 0·0072) and cognitive decline (P = 0·0005) compared to non-LOY carriers. Patients with PD carrying LOY also exhibited decreased network functional connectivity in certain brain regions. Notably, LOY cells were particularly enriched in microglia/immune and vascular/epithelial cells, and a subset of genes in LOY-Mic P2RY12 cells were associated with PD progression. INTERPRETATION:This data-driven study highlights the potential association of LOY with the onset and progression of PD through the analysis of multi-scale data, including clinical phenotypes, brain neuroimaging maps, and molecular profiles from single-nucleus transcriptome across multi-brain regions. These findings suggest that LOY may be an accomplice to the onset and progression of PD. FUNDING:G.L.'s work is supported by the Shenzhen Fundamental Research Program (JCYJ20240813151132042), National Natural Science Foundation of China (32270701, 32470708), Young Talent Recruitment Project of Guangdong (2019QN01Y139), the Science and Technology Planning Project of Guangdong Province (2023B1212060018) and Shenzhen Key Laboratory for Systems Medicine in Inflammatory Diseases (ZDSYS20220606100803007). This study is supported by High-performance Computing Public Platform (Shenzhen Campus) of Sun Yat-sen University. C.R.S.'s work is supported by NIH grants NINDS/NIA R01NS115144, the U.S. Department of Defense, and the American Parkinson Disease Association Center for Advanced Parkinson Research. C.R.S.'s research work was funded in part by Aligning Science Across Parkinson's 000301 through the Michael J. Fox Foundation for Parkinson's Research (MJFF). The study was made possible in part by a philanthropic support for Illumina MEGA chip genotyping (to Brigham & Women's Hospital and C.R.S.). CHWG received funding support from an RCUK/UKRI Research Innovation Fellowship awarded by the Medical Research Council (MR/R007446/1; MR/W029235/1) and from the NIHR Cambridge Biomedical Research Centre (NIHR203312). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. For the purpose of open access, the author has applied a CC BY public copyright licence to all Author Accepted Manuscripts arising from this submission.

BACKGROUND:Accessible measurements for the early detection of mild cognitive impairment (MCI) due to Alzheimer's disease (AD) are urgently needed to address the increasing prevalence of AD. OBJECTIVE:To determine the benefits of a composite MemTrax Memory Test and AD-related blood biomarker assessment for the early detection of MCI-AD in non-specialty clinics. METHODS:The MemTrax Memory Test and Montreal Cognitive Assessment were administered to 99 healthy seniors with normal cognitive function and 101 patients with MCI-AD; clinical manifestation and peripheral blood samples were collected. We evaluated correlations between the MemTrax Memory Test and blood biomarkers using Spearman's rank correlation analyses and then built discrimination models using various machine learning approaches that combined the MemTrax Memory Test and blood biomarker results. The models' performances were assessed according to the areas under the receiver operating characteristic curve. RESULTS:The MemTrax Memory Test and Montreal Cognitive Assessment areas under the curve for differentiating patients with MCI-AD from the healthy controls were similar. The MemTrax Memory Test strongly correlated with phosphorylated tau 181 and amyloid-β42/40. The area under the curve for the best composite MemTrax Memory Test and blood biomarker model was 0.975 (95% confidence interval: 0.950-0.999). CONCLUSION:Combining MemTrax Memory Test and blood biomarker results is a promising new technique for the early detection of MCI-AD.

Accessible measurements to a large screening and early differentiation of mild cognitive impairment due to Alzheimer’s disease (MCI-AD) from healthy elderly is increasing urgent with the prevalence of Alzheimer’s disease (AD) expanded. an online cognitive assessment (Memtrax) and MoCA were performed, on 99 clinically diagnosed cognitively normal (CON) and 101 MCI-AD participants. The plasma levels of phosphorylated tau (p-tau)181 and neurofilament light (NfL) and amyloid beta (Aβ)42/40 were measured using Simoa assay. The relevance between Memtrax and blood biomarkers were conducted by Spearman correlation analysis. Discrimination models were built using assorted machine learning approaches combining Memtrax with blood biomarkers, and model performance was measured using Area Under the Receiver Operating Characteristic Curve (AUC). The AUC of Memtrax and MoCA in differentiating MCI-AD from CON was similar. Memtrax has a strong correlation with phosphorylated tau (p-tau)181 and neurofilament light (NfL), while less related to amyloid beta (Aβ)42/40. Combining Memtrax and blood biomarkers, the AUC of best model reach to 0.975 (95% CI: 0.950-0.999). The combination of Memtrax and blood biomarkers is promising to the large screening and early detection in MCI-AD.

Despite mounting evidence linking pyroptotic cell death to tumor growth, the clinical significance and disease mechanism of pyroptosis in cancer remain uncertain. In this study, we established a unique gene signature (π signature) that can be used as a predictive and prognostic tool in pyroptosis-related cancer subtypes. We found that the 13 core pyroptosis genes exerted opposite prognostic effects in different cancer types, which were subgrouped as pyroptosis positively related cancer and pyroptosis negatively related cancer. Subsequently, π signature was identified separately from the hub genes in pyroptosis positively related cancer and pyroptosis negatively related cancer subtypes. It was shown that π signature was well correlated with patient survival, pathological stages, tumor lymphocyte infiltration, and immunotherapy response. π signature was also applied as a predictive tool for chemotherapy drug responses and used as an independent factor for patient overall survival prediction. In short, this elaborated genetic signature could help us understand the oncogenic mechanism and pave the way for further therapeutic strategies based on pyroptosis.

Immune checkpoint blockade therapy has drastically improved the prognosis of certain advanced-stage cancers. However, low response rates and immune-related adverse events remain important limitations. Here, we report that inhibiting ALG3, an a-1,3-mannosyltransferase involved in protein glycosylation in the endoplasmic reticulum (ER), can boost the response of tumors to immune checkpoint blockade therapy. Deleting N-linked glycosylation gene ALG3 in mouse cancer cells substantially attenuates their growth in mice in a manner depending on cytotoxic T cells. Furthermore, ALG3 inhibition or N-linked glycosylation inhibitor tunicamycin treatment synergizes with anti-PD1 therapy in suppressing tumor growth in mouse models of cancer. Mechanistically, we found that inhibiting ALG3 induced deficiencies of post-translational N-linked glycosylation modification and led to excessive lipid accumulation through sterol-regulated element-binding protein (SREBP1)-dependent lipogenesis in cancer cells. N-linked glycosylation deficiency-mediated lipid hyperperoxidation induced immunogenic ferroptosis of cancer cells and promoted a pro-inflammatory microenvironment, which boosted anti-tumor immune responses. In human subjects with cancer, elevated levels of ALG3 expression in tumor tissues are associated with poor patient survival. Taken together, we reveal an unappreciated role of ALG3 in regulating tumor immunogenicity and propose a potential therapeutic strategy for enhancing cancer immunotherapy.

Background: Immune checkpoint inhibitors have been successfully used in a variety of tumors, however, the efficacy of immune checkpoint blockade therapy for patients with glioma is limited. In this study, we tried to clarify gene expression signatures related to the prognosis of gliomas and construct a signature to predict the survival of patients with gliomas. Methods: Calcium-related differential expressed genes (DEGs) between gliomas and normal brain tissues were comprehensively analyzed in two independent databases. Univariate, multivariate Cox regression analysis and proportional hazards model were used to identify the prognostic of calcium-related risk score signature. The CIBERSORT algorithm and association analysis were carried out to evaluate the relationship between calcium-related signature and characteristic clinical features, tumor-infiltrating immune cell signatures as well as immune checkpoint molecules in glioma. A nomogram model was developed for predicting the overall survival for patients with gliomas. Results: We found the intersection of 415 DEGs between gliomas and normal brain tissues, and identified that an eighteen calcium-related gene panel was significantly enriched in these DEGs. A calcium-related signature derived risk score was developed to divide patients into high- and low-risk groups. Low levels of calcium-related gene expression in high-risk score cases were accompanied with worse outcomes of patients. Calcium-related risk scores were significantly associated with characteristic clinical features, immune infiltrating signatures of tumor microenvironment, and exhausted T cell markers including programmed cell death 1 (PD-1), lymphocyte activating 3 (LAG3), and T cell membrane protein 3 (TIM-3), which contribute to an adverse therapeutic effect of immunotherapy. Calcium-related signature risk score was considered as an independent prognostic parameter to predict the of overall survival of patients with gliomas in nomogram model. Conclusion: Our study demonstrated that calcium signaling pathway is highly associated with immunosuppression of gliomas and overall survival of patients. Targeting the calcium signaling pathway might be a new strategy to reverse the immunosuppressive microenvironment of gliomas and improve the efficacy of glioma immunotherapy.