Developing "Aging Clocks" Based on Novel Allelic Polymorphisms

The aim of this study is to create an "aging clock" that accounts for novel allelic polymorphisms in full-genome sequencing results to determine biological age.

The .vcf files of 21 samples from a study investigating the role of individual genomic variants of brain morphogenesis factors in the development of cognitive impairment were used to examine the data structure. Full genome sequencing (GWAS) results in .vcf format will be used as raw data from our own study. Correlation analysis and machine learning methods will be applied to analyze the data. The following algorithm for data processing is proposed: preprocessing of raw data, comparison of found polymorphisms with known polymorphisms, establishment of correlation between found polymorphisms and known age-associated diseases, assessment of statistical significance of found new polymorphisms with age-associated parameters (using trained models), model selection, and "clock" validation.

In the process of algorithm development, the structure of .vcf files was studied in order to automate the search for new allelic polymorphisms in genes with known involvement in the development of age-associated diseases. Analysis of fullexome sequencing results from 21 samples identified several genomic variants (rs6265, rs4760, rs4758443, etc.) associated with impaired brain development and the occurrence of cognitive impairment and age-associated diseases according to the literature. Preliminary results of the analysis demonstrate that the proposed bioinformatics data processing method can potentially be used to estimate the biological age of the study sample; however, the small sample size does not allow us to establish the accuracy of the proposed analysis method. For this reason, an analysis of 5000 additional samples is planned to optimize the proposed "aging clock" algorithms and evaluate their accuracy.

Analysis of a larger sample of biological samples from patients with ageassociated diseases will make it possible to identify new allelic polymorphisms, which will further improve the accuracy of the "aging clock".

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