Biology subjects

Leshchyk, A.

Publications and source records attributed to Leshchyk, A..

4 recordsLinked to original sources

bioRxiv2026

Genetic Modifiers of Cognitive Function: Novel Genetic Associations with Memory, Executive Function, and Attention in the Long Life Family Study

Cognitive performance is central to health and quality of life. Studying the factors that sustain performance may offer insights into maintaining cognitive function into advanced ages and may inform strategies to promote healthy cognitive aging. To identify single nucleotide polymorphisms (SNPs) underlying cognitive function, we performed genome-wide association studies (GWAS) of nine neuropsychological test scores capturing performance in three cognitive domains in 2,455 participants of the Long Life Family Study (LLFS). We identified 12 variants in seven tests and three domains that reached genome-wide significance (p < 5x10-). Three rare (minor allele frequency, European population MAF<0.01) protective, intronic variants, rs190287985 (CCSER1), rs75730801 (FHOD3), and rs552842447 (LINC00508), were uniquely associated with semantic fluency, phonemic fluency and number span forward, respectively. Two rare deleterious variants, rs556333682 and rs188304645, were associated with performance on the Hopkins Verbal Learning Test-Revised (HVLT-R) learning trials and lie in ischemia-related genes SH3TC1 and RPH3A. Another variant, rs180691759, associated with HVLT-R delayed recall, was proximal to RSPO3 and linked to decreased ECHDC1 expression, implicating ischemic and unexplained Ethylmalonic acid (EMA) pathways. We compared the results with GWASs of a general cognitive factor (GCF) and reaction time (RT) in the UK Biobank and meta-analysis results of the UK Biobank, CHARGE and COGENT by Davies et al. We found that rs535509651 associates with HVLT-R delayed recall in the LLFS and nominally associates (p<0.05) with GCF, and that rs10424537 associates with Immediate Logical Memory in the LLFS and nominally associates with RT. Furthermore, we identified 5 genome-wide significant loci in Davies et al. that reached loci adjusted significance in the LLFS (GCF p<0.05/128 and RT p<0.05/39). Each locus was associated with a single cognitive domain in the LLFS. We annotated the genome-wide significant results with quantitative trait loci (QTL) analyses of whole blood transcriptomic, serum metabolomic data, and gene set enrichment analyses (GSEA) using all nominally significant transcripts (p < 0.05/12). QTL analyses discovered 1 SNP-transcript (ECHDC1, p < 3 x 10-6), no SNP-lipid (p < 2 x 10-4), and no SNP-polar metabolite (p < 2 x 10-4) associations. Gene set enrichment analyses identified three pathways at FDR < 0.05. Our findings provide insight into the domain-specific genetic architecture of cognitive function.

genetics↗

bioRxiv2025

Increased Genetic Protection Against Alzheimer's Disease in Centenarians

We constructed a polygenic protective score specific to Alzheimers disease (AD PPS) based on the current literature among the participants enrolled in five studies of healthy aging and extreme longevity in the US, Europe, and Asia. This AD PPS did not include variants on Apolipoprotein E (APOE) gene. Comparisons of AD PPS in different data sets of healthy agers and centenarians showed that centenarians have stronger genetic protection against AD compared to individuals without familial longevity. The current study also shows evidence that this genetic protection increases with increasingly older ages in centenarians (centenarians who died before reaching age 105 years, semi-supercentenarians who reached age 105 to 109 years, and supercentenarians who reached age 110 years and older). However, the genetic protection was of modest size: the average increase in AD PPS was approximately one additional protective allele per 5 years of gained lifetime. Additionally, we show that the higher AD PPS was associated with better cognitive function and decreased mortality. Taken together, this analysis suggests that individuals who achieve the most extreme ages, on average, have the greatest protection against AD. This finding is robust to different genetic backgrounds with important implications for universal applicability of therapeutics that target this AD PPS.

genetics↗

bioRxiv2024

Identification of novel plasma proteomic biomarkers of Dupuytren Disease

Dupuytren Disease (DD) is a chronic progressive disease that can cause disabling hand deformities. The most common treatments have either high complication rates or high early recurrence rates. Dupuytren lacks a staging biomarker profile to inform the development of preventive therapeutics to improve long-term outcomes. This multi-omic study aimed to create a DD blood proteomic biomarker profile by comparing DD plasma with that of a healthy control group. We measured circulating collagen metabolism peptides and found normal Collagen I synthesis but impaired Collagen I degradation in DD. We measured 6995 serum protein aptamers and identified 68 proteins that showed statistically significant differences compared with the control group. We developed two Diagnostic Proteomic Risk Scores (DPRS) based on hypothesis-free and hypothesis-based analyses. In independent data, our hypothesis-free and hypothesis-based DPRS distinguished Dupuytren from control subjects with accuracies of 76.5% and 70.6%, respectively. Our hypothesis-based DPRS also distinguished DD subjects with different disease progression rates by age at their first corrective procedure (p=0.0018). This pilot study is the first to provide evidence to suggest that Collagen I accumulation in DD results from impaired degradation rather than increased collagen synthesis. It also describes novel DPRS that have potential use as diagnostic and staging biomarker panels for Dupuytren disease.

molecular biology↗

bioRxiv2020

Comprehensive generation, visualization, and reporting of quality control metrics for single-cell RNA sequencing data

Single-cell RNA sequencing (scRNA-seq) can be used to gain insights into cellular heterogeneity within complex tissues. However, a variety of technical artifacts can be present in scRNA-seq data and need to be assessed before downstream analyses can be performed. While several algorithms and tools have been developed to perform individual quality control (QC) tasks, they are scattered in different packages across several programming environments. Comprehensive pipelines to streamline the process of generating and visualizing QC metrics are lacking. To address this need, we built the SCTK-QC pipeline within the singleCellTK R package (https://github.com/compbiomed/singleCellTK). Features in this pipeline include the ability to import data from 11 different preprocessing tools or file formats, perform empty droplet detection with 2 different algorithms, generate standard quality control metrics such as number of UMIs per cell or the percentage of mitochondrial counts, predict doublets using 6 different algorithms, and estimate ambient RNA. QC data can be exported to R and/or Python objects used in popular down-stream workflows. Results are visualized in an easy-to-read HTML report. This pipeline can also be used by non-computational users with an interactive graphical user interface developed with R/Shiny. Overall, the SCTK-QC pipeline will streamline and standardize QC analysis for scRNA-seq data across a variety of different single-cell transcriptomic platforms and preprocessing tools.

bioinformatics↗