Immune and molecular aging signals in analog astronauts during the AMADEE-24 Mars analog mission: code and data for reproducing the results

This deposit contains the code and processed data needed to reproduce the analyses and figures associated with the revision of the manuscript "Longitudinal Immune and Molecular-Aging Signals in Analog Astronauts during the AMADEE-24 Mars Analog Mission: An Exploratory Study" (Lazaryan et al.; corresponding author A. Arakelyan), submitted to iScience (Cell Press). The study is a longitudinal molecular profiling of six analog astronauts sampled at up to five time points - before the mission (BM) and four time points across the uninterrupted 14-day AMADEE-24 Mars analog mission. Assays include bulk RNA-seq of peripheral blood mononuclear cells (PBMCs), genomic and cell-free telomere length measurement, and plasma cytokine and protein profiling. The accompanying analysis covers repeated-measures differential gene expression, immune-cell deconvolution, gene set variation analysis, self-organizing-map transcriptomic portraits, and transcriptomic aging-clock estimation. What is updated: This version now accommodates the reviewers' suggestions about the data analysis statistical framework. The differential expression analysis now uses a repeated-measures framework that blocks on participant identity (DESeq2, ~ AA + RIN + Timepoint), validated orthogonally with limma-voom and duplicateCorrelation, and supported by a composition-sensitivity analysis on CLR-transformed cell-type fractions. Enrichment analyses for inferred cell-type-specific transcriptomic programs now use an updated gene-set collection (MSigDB Hallmark, GO, Reactome, KEGG MEDICUS, and Blood Transcription Modules [Li, S. et al., 2014]). In addition to RNAAgeCalc for RNA age calculation, we used the BAGE model, specifically trained for PBMCs. Longitudinal outcomes such as telomere and aging-clock dynamics are modeled with linear mixed-effects models (lme4/lmerTest with emmeans contrasts), and within-participant associations are assessed with repeated-measures correlation (rmcorr).