Biology subjects

Vishnyakova, O.

Publications and source records attributed to Vishnyakova, O..

3 recordsLinked to original sources

bioRxiv2026

A New Sparse Bayesian Quantile Neural Network-based Approach and Its Application to Discover Physiological Sweet Spots in the Canadian Longitudinal Study on Aging

Identifying physiological sweet spots (optimal ranges for homeostasis) is essential for precision medicine. However, traditional statistical methods often rely on globally linear or locally jagged models that struggle to capture the smooth, non-linear nature of biological regulation in high-dimensional data. We present the Quantile Feature Selection Network (Q-FSNet), a neural network-based framework that integrates quantile regression, feature selection, and uncertainty estimation to identify biomarkers with sweet spots. Unlike traditional methods, Q-FSNet learns continuous response curves without requiring pre-specified number of change points. We further introduce Quantile Dirichlet Network (Q-DirichNet), a fully Bayesian extension that utilizes Dirichlet priors to automate feature shrinkage. Using data from the Canadian Longitudinal Study on Aging, we identified 25 metabolites with distinct homeostatic ranges for which biological age acceleration is minimized. The metabolites with sweet spots for biological aging include some derived from diet or produced by the gut microbiome; this highlights their potential for knowledge translation and public health impact. Our results, corroborated by existing literature, demonstrate that these sparse neural network-based methods offer a scalable and interpretable tool for discovering metabolic signatures of healthy aging vs. dysregulation in large-scale omics research.

bioinformatics↗

bioRxiv2025

Epigenetic signature of heterogeneity in aging: Findings from the Canadian Longitudinal Study on Aging

Background: Human aging does not follow a single trajectory. Epigenetic changes offer insight into the heterogeneity in aging by reflecting the combined influence of genetic, environmental, and lifestyle factors on the timing and progression of age-related changes beyond what chronological age alone can explain. Recent studies in cancer and aging underscore the importance of methylation variability as a marker of biological dysregulation. Methods: We investigated the role of DNA methylation in aging heterogeneity by performing epigenome-wide differential methylation and variance association analyses in blood samples from 1,445 Canadians aged 45 to 85 from the Canadian Longitudinal Study on Aging. Results: We identified 448 differentially methylated regions and 488 differentially variable regions associated with health decline as measured by the health deficit accumulation Frailty Index, cognitive function, and physical function. These two classes of regions showed minimal overlap, with distinct gene coverage, suggesting that variability contributes a complementary signal to aging heterogeneity. Genes overlapped by differentially methylated regions were enriched for immune and inflammation-related pathways, whereas differentially variable regions highlighted additional localized, CpG-island-enriched signals shared across health domains, consistent with regionally structured rather than diffuse dysregulation. By integrating significant CpGs from both analyses, we constructed an epigenetic biomarker. The biomarker was associated with all-cause mortality and showed higher discrimination than biomarkers constructed from differential methylation or variability alone, with a similar pattern reproduced in the Baltimore Longitudinal Study of Aging. Conclusions: These findings suggest that DNA methylation variability may provide a complementary dimension of epigenetic aging and support further evaluation in larger cohorts with more mortality events.

genomics↗

bioRxiv2024

Advanced median-based genetic similarity analysis in Kazakh Tazy dogs: A novel approach for breed conformity assessment

The breed conformity evaluation is crucial for the preservation of the traits that characterise each dog breed. The use of genetic markers for this purpose provides a precision and objectivity that can surpass the reliability of phenotypic evaluations. In this study, we present a new simple algorithm for assessing breed conformity. The algorithm creates a similarity matrix based on genotypic data and then uses the median to calculate the percentage of genetic similarity that an individual has in relation to the genetic diversity of the breed. To validate the proposed algorithm, we applied it to the genotypic data of 18 microsatellites and 43,691 single nucleotide polymorphisms (SNPs) of the Kazakh Tazy dog, a breed of great cultural and historical importance to Kazakhstan that is now threatened with extinction due to crossbreeding. The algorithm showed a moderate correlation between the microsatellite and SNP genotyping methods, reflecting the different aspects of genetic similarity. In particular, the SNP-based evaluations agreed better with the expert judgements, highlighting their potential for accurate analysis of breed conformity. The proposed algorithm provides easily interpretable results, is flexible, adapts to different genetic markers and may provide an evaluation mechanism for breed conformity in situations where there is no reference population, incomplete pedigrees, unidentified meta-founders and high genetic diversity in the population. Author summaryOur research was initiated by the urgent concern for the possible extinction of the Kazakh Tazy dog, a breed with deep historical roots and cultural significance in Kazakhstan. Information at the DNA level may lead to faster genetic improvement of the breed than relying only on phenotypic data and pedigrees. Genotypic data can be processed to provide valuable insights into genetic diversity, relatedness and ancestry. However, existing methods do not provide a measure of percentage similarity that can be used to assess how closely a particular individual matches the typical genetic composition of the breed. These challenges have led us to propose an approach that overcomes the limitations of existing methods and allows genetic similarity to be assessed based on genotypes. It is based on a median-based approach to analyze genetic data and has been applied to microsatellite and SNP markers but can also be adapted to other genetic markers. This method provides results even in the absence of a defined reference population, complete pedigrees or identified meta-pedigrees and during high genetic diversity within a breed. It can provide breeders and researchers with a tool to maintain the genetic purity of unique breeds.

genomics↗