Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2025.10.27.684890

Sex differences in thyroid aging and their implications in thyroid disorders: insights from gene regulatory networks

Saha, E.·Ben-Guebila, M.·Chen, C.·Fanfani, V.·Hoff-Shutta, K.·DeMeo, D.·Quackenbush, J.·Lopes-Ramos, C.
View original source ↗Export metadata ↓

Abstract

Thyroid disorders are more prevalent in females than males, with sex differences in disease risk varying by age, e.g. although risk of anaplastic thyroid carcinoma (ATC) increases with age for both sexes, females are diagnosed at younger ages than males. In contrast, Hashimotos thyroiditis (HT) is more common in ages 30-50, with females having higher risk. These patterns suggest that in thyroid, gene regulatory processes evolve with age in a sex-specific manner. To characterize these sex differences in thyroid aging, we estimated and analyzed individual-specific gene regulatory networks using BONOBO and PANDA algorithms. We found that regulatory patterns of pathways involved in cell proliferation, immune response, and metabolic processes vary nonlinearly with age, with sex-specific differences in direction and rate. Females show two inflection points around ages 40 and 60, when regulatory patterns show significant change for most pathways, consistent with changes in targeting by estrogen and androgen receptors. Investigating gene regulatory patterns in HT and ATC, we observed that disease-relevant immune and metabolic pathways changed with age in the same direction as they change in ATC. In contrast, in HT, disease-related regulatory patterns are in the opposite direction of aging. In age groups where HT is most diagnosed, regulatory patterns in females more closely resembled disease states than males, highlighting sex-biased regulations role in elevated disease risk in females. Our findings demonstrate immune response and metabolic processes are regulated in age- and sex-specific manner, potentially driving variation in disease risk, emphasizing the need for tailored screening and prevention strategies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/684890v3_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@cd93aeorg.highwire.dtl.DTLVardef@9a913aorg.highwire.dtl.DTLVardef@1b4a862org.highwire.dtl.DTLVardef@19adca8_HPS_FORMAT_FIGEXP M_FIG C_FIG

Explore related subjects

systems biologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Saha, E., Ben-Guebila, M., Chen, C., Fanfani, V., Hoff-Shutta, K., DeMeo, D., Quackenbush, J., Lopes-Ramos, C.. 2025-10-28. Sex differences in thyroid aging and their implications in thyroid disorders: insights from gene regulatory networks. https://doi.org/10.1101/2025.10.27.684890

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Dietary fibre responses emerge through host-dietary regime interplay: Apple pectin modulates immune reactivity in adult zebrafish

Dietary fibres are rarely consumed independently. Instead, they form part of an overall diet that includes dietary fibres from different sources, in varying amounts and consumed under different feeding patterns. Here, we tested how dietary regimes containing apple pectin, oat {beta}-glucan, or cellulose shaped the host. We analysed gut microbiome composition by 16S rRNA sequencing, measured brain and intestinal SCFA profiles by targeted metabolomics, and assessed immunomodulation by measuring gene expression systemically in the blood and locally in the spleen, as well as intestinal enzyme activity. The dietary intervention was conducted for 12 weeks on adult female and male zebrafish (Danio rerio). Our results show that the gut microbial composition can be relatively stable across different dietary fibre exposure patterns yet still vary significantly between the sexes. Additionally, the effect of sex on the gut microbiome may become more evident when dietary fibres are administered at high dosages, but intermittently. Dietary fibre regimes can alter intestinal short-chain fatty acid profiles more readily than brain profiles, which show a stronger sexually dimorphic response. Interestingly, apple pectin modulated the zebrafish immune response through interactions dependent on the overall regime, tissue, sex, and host immune status. Notably, tissue il1b gene expression differed depending on how apple pectin was administered and the host's physiological state. Collectively, our study emphasises the highly context-specific effects of dietary fibres, shaped by the dynamic interplay between the overall dietary regime and intertwined host factors.

systems biology↗
bioRxiv2026

A spin glass representation of hierarchical gene regulation and the partial resolution of frustration

Gene regulatory networks are directed and often contain loops. A loop can place competing demands on its genes, so that no expression state satisfies every regulatory interaction. In statistical physics such a conflict is called frustration. Existing spin-glass models of tissues assume symmetric regulation, and studies of frustration consider single cells. We develop a nonreciprocal multicellular Ising model that couples a directed regulatory network in each cell to random, symmetric signalling between neighbouring cells. We define intracellular and intercellular frustration densities, which count the unsatisfied interactions within a cell and with its neighbours. We study six exemplar nine-gene networks that share a downstream cascade and differ in an upstream three-gene motif. In isolated cells the motif sets the frustration. Negative feedback loops pass frustration around the loop, and their genes keep switching. The incoherent feedforward loop holds frustration at a single gene and freezes. When cells communicate, they form spatial clusters with shared expression profiles, and conflict between neighbours concentrates at cluster boundaries. Stronger coupling lowers intercellular frustration and raises intracellular frustration. Frustration is therefore resolved only in part: cells satisfy more of the couplings to their neighbours by satisfying fewer of their own regulatory interactions. Varying the coupling strength reveals a transition near the value at which the combined input of a cell's eight neighbours matches a single regulatory interaction. Below it, cells follow their own networks and the tissue fragments. Our framework links the structure of gene regulatory networks to the stability of gene expression in cells and tissues.

systems biology↗
bioRxiv2026

Co-transcriptomic network analysis of host-parasite interactions reveals genes underpinning parasite fitness

Interactions between parasites and their host organisms generate continuous variation in infection outcomes. Although dual transcriptome studies have demonstrated extensive molecular dialogues between interacting species, it is still unclear how natural variation in host and parasite gene regulatory networks and coordination between them contribute to diverse disease phenotypes. Here, we re-contextualized co-transcriptomes from recombinant inbred lines of the plant-parasitic root-knot nematode Meloidogyne hapla infecting Medicago truncatula host plants with relative measures of infection intensity as a proxy for parasite load. We used infection intensity to estimate interaction gradients on gene expression by calculating its covariance with transcript levels. Quantitative analyses of interaction gradients for host and parasite transcriptomes identified major differences in development-related transcriptional programs along the infection continuum. In addition, integrated network analyses connected host cell wall remodeling with parasite protein production and secretion. Silencing of candidate root-knot nematode genes reduced host galling and parasite reproductive fitness, providing experimental support for our network-derived predictions. Together, our findings present an integrated systems genetics framework connecting naturally occurring genetic variation to quantitative disease phenotypes.

systems biology↗