Choroid Plexus Volume in Rural Chinese Older Adults: Distribution and Association With Cardiovascular Risk Factors and Cerebral Small Vessel Disease

Background The choroid plexus (CP) is involved in neurodegenerative diseases. However, the association of CP with cardiovascular risk factors and cerebral small vessel disease in older adults remains unclear. Methods and Results This population‐based study included 1263 participants (60 years and older) from the MIND‐China (Multimodal Interventions to Delay Dementia and Disability in Rural China) substudy (2018–2020), of which 111 individuals completed diffusion tensor imaging examination. CP volume was automatically segmented. White matter hyperintensities (WMHs), enlarged perivascular spaces (EPVS), cerebral microbleeds, and lacunes were assessed following the Standards for Reporting Vascular Changes on Neuroimaging 1. Peak width of skeletonized mean diffusivity and free water were derived from diffusion tensor imaging images. We used linear regression models to evaluate the association between CP volume and cardiovascular risk factors, WMH volumes, and diffusion tensor imaging metrics, and logistic regression models to examine the association between CP volume and EPVS, cerebral microbleeds, and lacunes. The CP volume increased with age (P<0.001). Men (β coefficient=0.47 [95% CI, 0.29–0.64]) and participants with diabetes (β coefficient=0.16 [95% CI, 0.01–0.31]) had larger CP volumes than women and individuals without diabetes, respectively (P<0.05). Greater CP volume was significantly associated with larger total and periventricular WMH volumes and moderate to severe EPVS in basal ganglia (P<0.05) but not with deep WMHs, EPVS in centrum semiovale, lacunes, or cerebral microbleeds. In the diffusion tensor imaging subsample, enlarged CP was significantly associated with higher peak width of skeletonized mean diffusivity and free water of periventricular and deep white matter (P<0.05). Conclusions An enlarged CP is associated with larger global and periventricular WMH volume and higher likelihoods of EPVS in basal ganglia and impaired white matter integrity, suggesting that an enlarged CP may represent a precursor of cerebral small vessel disease

Association of polygenic risk scores with Alzheimer’s diseaseand plasma biomarkers among Chinese older adults: Acommunity-based study

INTRODUCTION: We examined the associations of polygenic risk score (PRS) with Alzheimer's disease (AD) and plasma biomarkers in the Chinese population. METHODS: This population-based study used baseline data from MIND-China (2018; n = 4873) and follow-up data from dementia-free individuals (2014–2018; n = 2117). We measured AD-related plasma biomarkers in a subsample (n = 1256). Data were analyzed using logistic and Cox regression models. RESULTS: We developed PRS with (PRS APOE) and without (PRS non- APOE) apolipoprotein E (APOE) gene. In the longitudinal analysis, PRS APOE was associated with a multivariable-adjusted hazards ratio of 1.91 (95% CI = 1.13–3.23) for AD. PRS APOE in combination with demographics yielded discriminative (area under the curve [AUC]) and predictive(C-statistic) accuracy of 0.80 (95% confidence interval [CI] = 0.77–0.84) and 0.80 (0.77–0.82), respectively. PRS non- APOE showed an association with AD risk similar to PRS APOE. PRS APOE, but not PRS non- APOE, was associated with reduced plasma Aβ42/Aβ40 ratio and increased Neurofilament light chain (NfL) (p &lt; 0.05). DISCUSSION: The PRS with and without APOE gene, in combination with demographics, shows good discriminative and predictive ability for AD. The AD-related pathologies underlie AD risk associated with PRS APOE. Highlights: The PRS APOE and PRS non- APOE were associated with AD risk in the Chinese population. The PRS APOE and PRS non- APOE, in combination with demographics, showed good discriminative and predictive ability for AD. The AD-related pathologies underlie the AD risk associated with PRS APOE but not PRS non- APOE.</p

Drug repositioning for SARS-CoV-2 by Gaussian kernel similarity bilinear matrix factorization

Coronavirus disease 2019 (COVID-19), a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently spreading rapidly around the world. Since SARS-CoV-2 seriously threatens human life and health as well as the development of the world economy, it is very urgent to identify effective drugs against this virus. However, traditional methods to develop new drugs are costly and time-consuming, which makes drug repositioning a promising exploration direction for this purpose. In this study, we collected known antiviral drugs to form five virus-drug association datasets, and then explored drug repositioning for SARS-CoV-2 by Gaussian kernel similarity bilinear matrix factorization (VDA-GKSBMF). By the 5-fold cross-validation, we found that VDA-GKSBMF has an area under curve (AUC) value of 0.8851, 0.8594, 0.8807, 0.8824, and 0.8804, respectively, on the five datasets, which are higher than those of other state-of-art algorithms in four datasets. Based on known virus-drug association data, we used VDA-GKSBMF to prioritize the top-k candidate antiviral drugs that are most likely to be effective against SARS-CoV-2. We confirmed that the top-10 drugs can be molecularly docked with virus spikes protein/human ACE2 by AutoDock on five datasets. Among them, four antiviral drugs ribavirin, remdesivir, oseltamivir, and zidovudine have been under clinical trials or supported in recent literatures. The results suggest that VDA-GKSBMF is an effective algorithm for identifying potential antiviral drugs against SARS-CoV-2

Long-term exposure to ambient fine particulate components and leukocyte epigenome-wide DNA Methylation in older men: the Normative Aging Study

Background Epigenome-wide association studies of ambient fine particulate matter (PM2.5) have been reported. However, few have examined PM2.5 components (PMCs) and sources or included repeated measures. The lack of high-resolution exposure measurements is the key limitation. We hypothesized that significant changes in DNA methylation might vary by PMCs and the sources. Methods We predicted the annual average of 14 PMCs using novel high-resolution exposure models across the contiguous U.S., between 2000–2018. The resolution was 50 m × 50 m in the Greater Boston Area. We also identified PM2.5 sources using positive matrix factorization. We repeatedly collected blood samples and measured leukocyte DNAm with the Illumina HumanMethylation450K BeadChip in the Normative Aging Study. We then used median regression with subject-specific intercepts to estimate the associations between long-term (one-year) exposure to PMCs / PM2.5 sources and DNA methylation at individual cytosine-phosphate-guanine CpG sites. Significant probes were identified by the number of independent degrees of freedom approach, using the number of principal components explaining > 95% of the variation of the DNA methylation data. We also performed regional and pathway analyses to identify significant regions and pathways. Results We included 669 men with 1,178 visits between 2000–2013. The subjects had a mean age of 75 years. The identified probes, regions, and pathways varied by PMCs and their sources. For example, iron was associated with 6 probes and 6 regions, whereas nitrate was associated with 15 probes and 3 regions. The identified pathways from biomass burning, coal burning, and heavy fuel oil combustion sources were associated with cancer, inflammation, and cardiovascular diseases, whereas there were no pathways associated with all traffic. Conclusions Our findings showed that the effects of PM2.5 on DNAm varied by its PMCs and sources