Background Genome-wide association studies (GWASs) in Parkinson's disease (PD) have increased the scope of biological knowledge about the disease over the past decade. We sought to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into disease etiology. Methods We performed the largest meta-GWAS of PD to date, involving the analysis of 7.8M SNPs in 37.7K cases, 18.6K UK Biobank proxy-cases (having a first degree relative with PD), and 1.4M controls. We carried out a meta-analysis of this GWAS data to nominate novel loci. We then evaluated heritable risk estimates and predictive models using this data. We also utilized large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type and biological pathway enrichments for the identified risk factors. Additionally we examined shared genetic risk between PD and other phenotypes of interest via genetic correlations followed by Mendelian randomization. Findings We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16-36% of the heritable risk of PD depending on prevalence. Integrating methylation and expression data within a Mendelian randomization framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested PD loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes, smoking status, and educational attainment. Mendelian randomization between cognitive performance and PD risk showed a robust association. Interpretation These data provide the most comprehensive understanding of the genetic architecture of PD to date by revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of this disease remains unidentified. Funding See supplemental materials (Text S2). lead to earlier detection and refined diagnostics, which may help improve clinical trials (4). The generation of copious amounts of public summary statistics created by this effort relating to both the GWAS and subsequent analyses of gene expression and methylation patterns may be of use to investigators planning follow-up functional studies in stem cells or other cellular screens, allowing them to prioritize targets more efficiently using our data as additional evidence. We hope our findings may have some downstream clinical impact in the future such as improved patient stratification for clinical trials and genetically informed drug targets.
The persistence of HIV-1 in virally suppressed infected individuals on highly active antiretroviral therapy (HAART) remains a major therapeutic problem. The use of cytokines has been envisioned as an additional therapeutic strategy to stimulate latent proviruses in these individuals. Immune activation therapy using IL-2 has shown some promise. In the present study, we found that IL-7 was significantly more effective at enhancing HIV-1 proviral reactivation than either IL-2 alone or IL-2 combined with phytohemagglutinin (PHA) in CD8-depleted PBMCs. IL-7 also showed a positive trend for inducing proviral reactivation from resting CD4 + T lymphocytes from HIV-1-infected patients on suppressive HAART. Moreover, the phylogenetic analyses of viral envelope gp120 genes from induced viruses indicated that distinct proviral quasispecies had been activated by IL-7, as compared with those activated by the PHA/IL-2 treatment. These studies thus demonstrate that different activators of proviral latency may perturb and potentially deplete only selected, specific portions of the proviral archive in virally suppressed individuals. The known immunomodulatory effects of IL-7 could be combined with its ability to stimulate HIV-1 replication from resting CD4 + T lymphocytes, in addition to other moieties, to potentially deplete HIV-1 reservoirs and lead to the rational design of immuneantiretroviral approaches.
This study demonstrates that multimodal MRI is able to discriminate patients with PD from those with MSA with high accuracy. The combination of different MR biomarkers could be a great tool in early stage of disease to help diagnosis. © 2018 International Parkinson and Movement Disorder Society.
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