DNA methylation differences in Alzheimer's disease (AD) have been reported. Here, we conducted a meta-analysis of more than 1000 prefrontal cortex brain samples to prioritize the most consistent ...methylation differences in multiple cohorts. Using a uniform analysis pipeline, we identified 3751 CpGs and 119 differentially methylated regions (DMRs) significantly associated with Braak stage. Our analysis identified differentially methylated genes such as MAMSTR, AGAP2, and AZU1. The most significant DMR identified is located on the MAMSTR gene, which encodes a cofactor that stimulates MEF2C. Notably, MEF2C cooperates with another transcription factor, PU.1, a central hub in the AD gene network. Our enrichment analysis highlighted the potential roles of the immune system and polycomb repressive complex 2 in pathological AD. These results may help facilitate future mechanistic and biomarker discovery studies in AD.
To better understand DNA methylation in Alzheimer's disease (AD) from both mechanistic and biomarker perspectives, we performed an epigenome-wide meta-analysis of blood DNA methylation in two large ...independent blood-based studies in AD, the ADNI and AIBL studies, and identified 5 CpGs, mapped to the SPIDR, CDH6 genes, and intergenic regions, that are significantly associated with AD diagnosis. A cross-tissue analysis that combined these blood DNA methylation datasets with four brain methylation datasets prioritized 97 CpGs and 10 genomic regions that are significantly associated with both AD neuropathology and AD diagnosis. An out-of-sample validation using the AddNeuroMed dataset showed the best performing logistic regression model includes age, sex, immune cell type proportions, and methylation risk score based on prioritized CpGs in cross-tissue analysis (AUC = 0.696, 95% CI: 0.616 - 0.770, P-value = 2.78 × 10
). Our study offers new insights into epigenetics in AD and provides a valuable resource for future AD biomarker discovery.
miRNAs were recently implicated in the pathogenesis of numerous diseases, including neurological disorders such as Parkinson's disease (PD). miRNAs are abundant in the nervous system, essential for ...efficient brain function and play important roles in neuronal patterning and cell specification. To further investigate their involvement in the etiology of PD, we conducted miRNA expression profiling in peripheral blood mononuclear cells (PBMCs) of 19 patients and 13 controls using microarrays. We found 18 miRNAs differentially expressed, and pathway analysis of 662 predicted target genes of 11 of these miRNAs revealed an over-representation in pathways previously linked to PD as well as novel pathways. To narrow down the genes for further investigations, we undertook a parallel approach using chromatin immunoprecipitation-sequencing (ChIP-seq) analysis to uncover genome-wide interactions of α-synuclein, a molecule with a central role in both monogenic and idiopathic PD. Convergence of ChIP-seq and miRNomics data highlighted the glycosphingolipid biosynthesis and the ubiquitin proteasome system as key players in PD. We then tested the association of target genes belonging to these pathways with PD risk, and identified nine SNPs in USP37 consistently associated with PD susceptibility in three genome-wide association studies (GWAS) datasets (0.46≤OR≤0.63) and highly significant in the meta-dataset (3.36×10⁻⁴<p <1.94×10⁻³). A SNP in ST8SIA4 was also highly associated with PD (p = 6.15×10⁻³) in the meta-dataset. These findings suggest that several miRNAs may act as regulators of both known and novel biological processes leading to idiopathic PD.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Only Apolipoprotein E polymorphisms have been consistently associated with the risk of late-onset Alzheimer disease (LOAD), but they represent only a minority of the underlying genetic effect. To ...identify additional LOAD risk loci, we performed a genome-wide association study (GWAS) on 492 LOAD cases and 498 cognitive controls using Illumina's HumanHap550 beadchip. An additional 238 cases and 220 controls were used as a validation data set for single-nucleotide polymorphisms (SNPs) that met genome-wide significance. To validate additional associated SNPs (p < 0.0001) and nominally associated candidate genes, we imputed SNPs from our GWAS using a previously published LOAD GWAS1 and the IMPUTE program. Association testing was performed with the Cochran-Armitage trend test and logistic regression, and genome-wide significance was determined with the False Discovery Rate-Beta Uniform Mixture method. Extensive quality-control methods were performed at both the sample and the SNP level. The GWAS confirmed the known APOE association and identified association with a 12q13 locus at genome-wide significance; the 12q13 locus was confirmed in our validation data set. Four additional highly associated signals (1q42, 4q28, 6q14, 19q13) were replicated with the use of the imputed data set, and six candidate genes had SNPs with nominal association in both the GWAS and the joint imputated data set. These results help to further define the genetic architecture of LOAD.
Alzheimer's disease (AD) is the most common late-onset neurodegenerative disorder. Identifying individuals at increased risk of developing AD is important for early intervention. Using data from the ...Alzheimer Disease Genetics Consortium, we constructed polygenic risk scores (PRSs) for AD and age-at-onset (AAO) of AD for the UK Biobank participants. We then built machine learning (ML) models for predicting development of AD, and explored feature importance among PRSs, conventional risk factors, and ICD-10 codes from electronic health records, a total of > 11,000 features using the UK Biobank dataset. We used eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP), which provided superior ML performance as well as aided ML model explanation. For participants age 40 and older, the area under the curve for AD was 0.88. For subjects of age 65 and older (late-onset AD), PRSs were the most important predictors. This is the first observation that PRSs constructed from the AD risk and AAO play more important roles than age in predicting AD. The ML model also identified important predictors from EHR, including urinary tract infection, syncope and collapse, chest pain, disorientation and hypercholesterolemia, for developing AD. Our ML model improved the accuracy of AD risk prediction by efficiently exploring numerous predictors and identified novel feature patterns.
DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research ...primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC v1.0 arrays. We conducted a comprehensive assessment of the EPIC v1.0 array probe reliability using 69 blood DNA samples, each measured twice, generated by the Alzheimer's Disease Neuroimaging Initiative study. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliability information for probes on the EPIC v1.0 array, will serve as a valuable resource for future DNAm studies.
Epigenome-wide association studies often detect many differentially methylated sites, and many are located in distal regulatory regions. To further prioritize these significant sites, there is a ...critical need to better understand the functional impact of CpG methylation. Recent studies demonstrated that CpG methylation-dependent transcriptional regulation is a widespread phenomenon. Here, we present MethReg, an R/Bioconductor package that analyzes matched DNA methylation and gene expression data, along with external transcription factor (TF) binding information, to evaluate, prioritize and annotate CpG sites with high regulatory potential. At these CpG sites, TF-target gene associations are often only present in a subset of samples with high (or low) methylation levels, so they can be missed by analyses that use all samples. Using colorectal cancer and Alzheimer's disease datasets, we show MethReg significantly enhances our understanding of the regulatory roles of DNA methylation in complex diseases.
Summary
Parkinson disease (PD) is a chronic neurodegenerative disorder with a cumulative prevalence of greater than one per thousand. To date three independent genome‐wide association studies (GWAS) ...have investigated the genetic susceptibility to PD. These studies implicated several genes as PD risk loci with strong, but not genome‐wide significant, associations.
In this study, we combined data from two previously published GWAS of Caucasian subjects with our GWAS of 604 cases and 619 controls for a joint analysis with a combined sample size of 1752 cases and 1745 controls. SNPs in SNCA (rs2736990, p‐value = 6.7 × 10−8; genome‐wide adjusted p = 0.0109, odds ratio (OR) = 1.29 95% CI: 1.17–1.42 G vs. A allele, population attributable risk percent (PAR%) = 12%) and the MAPT region (rs11012, p‐value = 5.6 × 10−8; genome‐wide adjusted p = 0.0079, OR = 0.70 95% CI: 0.62–0.79 T vs. C allele, PAR%= 8%) were genome‐wide significant. No other SNPs were genome‐wide significant in this analysis. This study confirms that SNCA and the MAPT region are major genes whose common variants are influencing risk of PD.
To evaluate the relationship between dry eye symptoms, non-ocular conditions and tear film parameters.
Cross-sectional study.
The study population consisted of patients who were seen in the Miami ...Veterans Affairs eye clinic. Patients filled out standardised questionnaires assessing dry eye symptoms (dry eye questionnaire 5 (DEQ5) and ocular surface disease index (OSDI)), non-ocular pain, depression and post-traumatic stress disorder (PTSD), and also underwent measurement of tear film parameters.
Correlations between dry eye symptoms and non-ocular conditions as compared with tear film parameters.
136 patients with a mean age of 65 (SD 11) years participated in the study. All correlations between the dry eye questionnaire scores (DEQ5 and OSDI) and (A) self-reported non-ocular pain measures (numerical rating scale and pain history), (B) depression and (C) PTSD were significant and moderate in strength (Pearson's coefficient 0.24 to 0.60, p<0.01 for all). All correlations between the dry eye questionnaires and tear film measures were weak (Pearson's coefficient -0.10 to 0.18) and most were not significant. Multivariable linear regression analyses revealed that PTSD and non-ocular pain more closely associated with dry eye symptoms than did tear film parameters. Specifically, non-ocular pain and PTSD accounted for approximately 36% of the variability in DEQ5 scores (R=0.60) and approximately 40% of variability in OSDI scores (R=0.64). Of note, none of the tear parameters remained significantly associated with dry eye symptoms in either model.
Dry eye symptoms more closely align to non-ocular pain, depression and PTSD than to tear film parameters.
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