Impact of Y chromosome loss on the risk of Parkinson's disease and progression

Abstract

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.

Keywords: LOY; Onset; Parkinson's disease; Progression.

Fig. 1

Levels of LOY and risk for PD over time in the UK Biobank cohort. (a) The forest plot depicts the hazard ratios (HRs) for the association between LOY levels in blood cells and the risk of incident PD during the follow-up period, adjusted for potential confounders. The squares represent point estimates, with the sides of the square inversely proportional to the standard error of the estimates. The horizontal lines indicate 95% confidence interval (CI) of the estimates. (b) Covariate-adjusted survival curves of PD onset for males with LOY (magenta line) and non-LOY (light blue line) on a subset of participants aged over 50 at the time of sampling. The table below lists the number of males surviving free of PD and those who were diagnosed with PD at various time points following blood sampling. The P value was derived from a two-sided Wald test in the Cox proportional hazard analysis. PD-PRS, PD polygenic risk score.

Fig. 2

Longitudinal analysis of MDS-UPDRS III and MMSE scores in male patients with PD carrying LOY and non-LOY carriers. (a) Adjusted mean MDS-UPDRS III scores, calculated using the estimated fixed-effect parameters from the LMM analysis, are displayed over time. The scores are stratified based on the presence of the LOY (magenta for carriers, light blue for non-LOY carriers). (b) Adjusted mean MMSE scores, calculated using the estimated fixed-effect parameters from the LMM analysis, are displayed over time. The scores are stratified based on the presence of the LOY (magenta for carriers, light blue for non-LOY carriers). The shaded ribbons indicate ± standard error of the mean (s.e.m.) across time. Due to the lack of complete overlap in follow-up records for MDS-UPDRS III and MMSE across all patients, some patients underwent exclusive analysis for either MDS-UPDRS III or MMSE. The P value was calculated by the t-test using Satterthwaite's method in the LMM analysis.

Fig. 3

Brain functional connectivity maps comparing male patients with PD carrying LOY to non-LOY carriers. Significant decreases in brain functional connectivity were observed in LOY carriers (n = 12) compared to non-LOY carriers (n = 71) using the visual peripheral network (a), salience/ventral attention A network (b), limbic A network (c), and control C network (d) as seed. SFG, superior frontal gyrus; MidFG, middle frontal gyrus; PaCiG, paracingulate gyrus; sLOC, superior lateral occipital cortex; OP, occipital pole; iLOC, inferior lateral occipital cortex; toMTG, temporooccipital middle temporal gyrus; AG, angular gyrus; OFusG, occipital fusiform gyrus; L, left; R, right. Z indicates the position of the slice (z-coordinate).

Fig. 4

Characteristics of the postmortem single-cell transcriptome for LOY cells in male individuals with PD. (a) Summary of snRNA-seq profiling, covering 279 post-mortem brain samples across five brain regions from 60 individuals in the AMP-PD Project (DMNX, n = 55; GPI, n = 57; PMC, n = 57; PFC, n = 57; PVC, n = 53). The sample size of Braak stages is as follows: four control individuals (Braak stage = 0), four early-stage individuals (Braak stage = 1/2), 27 medium-stage individuals (Braak stage = 3/4), 17 late-stage individuals (Braak stage = 5/6), and eight individuals with no available Braak stage (Braak stage = NA). The pathological diagnoses include 45 PD cases and 15 non-PD cases. (b) Joint UMAP of 1·3 million cells across seven major cell classes including excitatory neurons (Exc), inhibitory neurons (Inh), oligodendrocytes (Oli), oligodendrocyte precursor cells (OPC), astrocytes (Ast), microglia/immune cells (Immune), and vascular and epithelial cells (Vast). (c) UMAPs of microglia/immune subtypes. (d) Distribution of LOY cells (blue) and non-LOY cells (pink) in microglia/immune subtypes. (e) Heatmap illustrating the temporal expression patterns of specific genes (Growth and Recession) identified through TDEseq analysis in the LOY-Mic P2RY12 cells. The upper heatmap demonstrates a subset of genes that exhibit a general trend of upregulation in LOY-Mic P2RY12 cells across different Braak stages and five brain regions (named Growth pattern). In contrast, the lower heatmap demonstrates a subset of genes that display a consistent trend of downregulation across different Braak stages and brain regions (named Recession pattern). Gene expression levels were log-transformed and standardised using z-scores for visualisation. (f) CMap analysis used the genes of Growth or recession patterns, which demonstrated the correlation of pattern-specific genes with drug resistance.