Reihs, R. | bioRxiv Science

bioRxiv2025

Multi-modal atlas of lifestyle interventions reveals malleability of ageing-linked molecular features

Extending human healthspan requires understanding how lifestyle interventions impact molecular systems across tissues and time. Here, we present the TirolGESUND Lifestyle Atlas (ClinicalTrials.gov: NCT05678426), a longitudinal, multi-modal resource profiling 156 healthy women (aged 30-60 years) undergoing 6-month intermittent fasting (n=114) or smoking cessation (n=42) interventions. Participants were sampled up to four times across seven tissues and fluids, generating >3,450 biospecimens with harmonised DNA methylation, metabolomics, microbiome, and immune profiling, alongside skin histology, barrier measurements, and rich clinical metadata. We demonstrate the utility of this dataset through: (i) multi-omics-wide association studies linking traits to molecular features; (ii) integrative factor modelling revealing coordinated cross-tissue signatures; (iii) epigenetic-biomarker cross-omic associations, and (iv) CpG-level variance decomposition mapping stable, individual-specific, tissue-restricted, and intervention-responsive methylation patterns. We further show that ageing-linked features are selectively malleable: highly compliant intermittent fasting participants exhibited attenuated or even age-opposing molecular trajectories within six months. The atlas enables unprecedented within-cohort comparisons across omic layers and tissues, supporting discovery of context-dependent biomarkers, cross-system coordination, and intervention responsiveness. Data are available via an interactive portal, with sensitive data under controlled access (https://eutops.github.io/lifestyle-atlas/). This resource provides a foundation for exploring biomarker association and multi-tissue epigenetics, enabling hypothesis generation and benchmarking for systems biology and human healthspan research. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=186 HEIGHT=200 SRC="FIGDIR/small/673115v2_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@fec2d9org.highwire.dtl.DTLVardef@1aa5d13org.highwire.dtl.DTLVardef@1c4a6f2org.highwire.dtl.DTLVardef@1ac62fb_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIMulti-tissue multi-modal profiling of two clinically-relevant lifestyle interventions in 156 women aged 30-60 C_LIO_LIIntermittent fasting modifies ageing-linked molecular features in an age-opposing direction C_LIO_LICross-tissue epigenetic biomarker mapping links immunity, metabolism, and microbiome C_LIO_LITissue-specific epigenetic plasticity maps reveal candidate meQTLs, C_LIO_LIData sharing and interactive portal enable broad reuse for hypothesis generation and exploration C_LI

systems biology↗

bioRxiv2020

On the correlation between material-induced cell shape and phenotypical response of human mesenchymal stem cells

Learning rules by which cell shape impacts cell function would enable control of cell physiology and fate in medical applications, particularly, on the interface of cells and material of the implants. We defined the phenotypic response of human bone marrow-derived mesenchymal stem cells (hMSCs) to 2176 randomly generated surface topographies by probing basic functions such as migration, proliferation, protein synthesis, apoptosis, and differentiation using quantitative image analysis. Clustering the surfaces into 28 archetypical cell shapes, we found a very strict correlation between cell shape and physiological response and selected seven cell shapes to describe the molecular mechanism leading to phenotypic diversity. Transcriptomics analysis revealed a tight link between cell shape, molecular signatures, and phenotype. For instance, proliferation is strongly reduced in cells with limited spreading, resulting in down-regulation of genes involved in the G2/M cycle and subsequent quiescence, whereas cells with large filopodia are related to activation of early response genes and inhibition of the osteogenic process. Thus, we have started to unravel the open question of how cell function follows cell shape. This will allow designing implants that can actively regulate cellular, molecular signalling through cell shape. Here we are proposing an approach to tackle this question.

bioinformatics↗