---
title: "Apoptosis-Related Genes WNT1 and S100A8 Link Inflammatory Bowel Disease and Osteoporosis"
id: "plos-one-1-apoptosis-related-genes-bridge-inflammatory-bowel-disease-and-osteoporosis-a"
canonical_url: "https://medichelpline.com/clinical-feed/plos-one-1-apoptosis-related-genes-bridge-inflammatory-bowel-disease-and-osteoporosis-a"
content_type: "clinical_feed_article"
specialty: "Gastroenterology"
source_name: "PLOS ONE (Medicine)"
source_url: "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002"
published_at: "2026-08-12T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Apoptosis-Related Genes WNT1 and S100A8 Link Inflammatory Bowel Disease and Osteoporosis
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/plos-one-1-apoptosis-related-genes-bridge-inflammatory-bowel-disease-and-osteoporosis-a
- **Specialty:** [Gastroenterology](https://medichelpline.com/clinical-feed/gastroenterology.md)
- **Primary Source:** PLOS ONE (Medicine)
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002)
- **Published At:** 2026-08-12T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- Inflammatory bowel disease (IBD) and osteoporosis (OP) frequently co-occur, with IBD potentially accelerating the development of OP. - Using GEO database gene expression data, differential gene expression and weighted gene co-expression network analysis (WGCNA) identified genes dysregulated in both conditions. - Intersection of differentially expressed genes with apoptosis-related genes highlighted key candidates involved in both diseases. - Machine learning (lasso regression) refined the candidate list to three key apoptosis-associated genes: MITF, S100A8, and WNT1. - Further validation showed that WNT1 and S100A8 are significantly upregulated in IBD and OP and have good diagnostic ability (AUC about 0.68–0.70). - WNT1 is enriched in cell cycle and neuroactive ligand receptor pathways, while S100A8 is involved in adaptive immune responses and inflammation. - Pearson correlation analyses linked WNT1 and S100A8 with distinct sets of genes related to immune and inflammatory processes. - These findings suggest **WNT1** and **S100A8** play critical roles bridging apoptosis mechanisms in IBD and OP, proposing them as potential diagnostic biomarkers and therapeutic targets. - The study provides new insights for clinical management and prevention strategies targeting shared molecular pathways in IBD-induced osteoporosis. - Further functional and clinical validation will be necessary to confirm these findings and develop targeted interventions.
## Clinical Analysis & Structured Key Points
[ Skip to main content ](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#main-content) Advertisement * [plos.org](https://plos.org/) * [Create account](https://community.plos.org/registration/new) * [Sign in](https://journals.plos.org/user/secure/login?page=%2Fplosone%2Farticle%3Fid%3D10.1371%2Fjournal.pone.0356002) * * About * Browse * Publish * [](https://journals.plos.org/plosone/ "PLOS One") * Search [advanced search](https://journals.plos.org/plosone/search) * [Browse Topics](https://journals.plos.org/plosone/subjectAreaBrowse) Browse Subject Areas ? Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click [here](https://github.com/PLOS/plos-thesaurus/blob/master/README.md "Link opens in new window"). [](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002) [](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002) * 0 [Save](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0356002#savedHeader) [Total Mendeley and Citeulike bookmarks.](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0356002#savedHeader) * 0 [Citation](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0356002#citedHeader) [Paper's citation count computed by Dimensions.](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0356002#citedHeader) * 8 [View](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0356002#viewedHeader) [PLOS views and downloads.](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0356002#viewedHeader) * 0 [Share](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0356002#discussedHeader) [Sum of Facebook, Twitter, Reddit and Wikipedia activity.](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0356002#discussedHeader) Open Access Peer-reviewed Research Article # Apoptosis-related genes bridge inflammatory bowel disease and osteoporosis: A bioinformatic analysis * Yue Su , Contributed equally to this work with: Yue Su, Xiaohui Luo Roles Data curation, Writing – original draft, Writing – review & editing Affiliation Anorectal Department, Wenshan Zhuang and Miao Autonomous Prefecture Hospital of Traditional Chinese Medicine, Wenshan Zhuang and Miao Autonomous Prefecture, Yunnan, China ⨯ * Xiaohui Luo , Contributed equally to this work with: Yue Su, Xiaohui Luo Roles Methodology, Software Affiliation Department of Orthopedics, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China ⨯ * Haitao Xu Roles Data curation, Writing – original draft, Writing – review & editing * E-mail: huihuiluo1997@163.com Affiliation Department of Orthopedics, The Affiliated Yongchuan Hospital of Chongqing Medical University, Chongqing, China [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0009-0004-1044-7970 ](https://orcid.org/0009-0004-1044-7970 "ORCID Registry") ⨯ # Apoptosis-related genes bridge inflammatory bowel disease and osteoporosis: A bioinformatic analysis * Yue Su, * Xiaohui Luo, * Haitao Xu ![PLOS](https://journals.plos.org/resource/img/logo-plos-full-color.svg) x * Published: August 12, 2026 * * [Article](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002) * [Authors](https://journals.plos.org/plosone/article/authors?id=10.1371/journal.pone.0356002) * [Metrics](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0356002) * [Comments](https://journals.plos.org/plosone/article/comments?id=10.1371/journal.pone.0356002) * [Media Coverage](http://plos.altmetric.com/details/doi/10.1371/journal.pone.0356002) * [Abstract](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#abstract0) * [Background](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#sec005) * [Methods](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#sec006) * [Result](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#sec014) * [Discussion](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#sec020) * [Conclusion](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#sec021) * [References](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#references) * [Reader Comments](https://journals.plos.org/plosone/article/comments?id=10.1371/journal.pone.0356002) * [Figures](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002) ## Abstract ### Background Inflammatory bowel disease (IBD) and osteoporosis (OP) often co-occur, with IBD accelerating OP onset, though the underlying mechanisms remain unclear. ### Methods Based on gene expression data from the GEO database, differential expression analysis was performed using the limma package to identify genes dysregulated in both IBD and OP. Weighted Gene Co-expression Network Analysis (WGCNA) was employed to explore the associations between genes and phenotypes. Candidate genes were obtained by intersecting differentially expressed genes with key WGCNA modules, followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. To further focus on apoptosis-related mechanisms, the candidate genes were intersected with an apoptosis-related gene set and refined using lasso regression. Core genes were identified through differential expression validation and receiver operating characteristic curve analysis. Subsequently, their potential functions and regulatory networks were explored via multidimensional analysis, gene set enrichment analysis, and Pearson correlation analysis. ### Results WNT1 and S100A8 are closely associated with the progression of both inflammatory bowel disease and osteoporosis. Gene Set Enrichment Analysis revealed that WNT1 is primarily enriched in cell cycle checkpoint signaling, chromosome organization, neuroactive ligand signaling, and neuroactive ligand–receptor interaction. In contrast, S100A8 is mainly enriched in adaptive immune response, adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily, inflammatory bowel disease, and leishmaniasis. Pearson correlation analysis showed that WNT1 is correlated with TSPAN32, POU3F3, NXPH3, EGFL7, LHX3, TNNI2, HMX1, FAM3A, IBTK, and ZNF747, while S100A8 is correlated with MMP3, SLC6A14, MMP10, S100A9, AQP9, S100A12, CXCL6, CXCR1, SLC38A4, and NCF2. ### Conclusions WNT1 and S100A8, which are associated with apoptosis, play critical roles in both inflammatory bowel disease and osteoporosis, providing new potential therapeutic targets and a theoretical basis for clinical diagnosis and treatment. ## Figures ![Fig 7](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0356002.g007) ![Fig 8](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0356002.g008) ![Fig 1](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0356002.g001) ![Fig 2](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0356002.g002) ![Fig 3](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0356002.g003) ![Fig 4](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0356002.g004) ![Fig 5](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0356002.g005) ![Fig 6](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0356002.g006) ![Fig 7](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0356002.g007) ![Fig 8](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0356002.g008) ![Fig 1](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0356002.g001) ![Fig 2](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0356002.g002) ![Fig 3](https://journals.plos.org/plosone/article/figure/image?size=inline&id=10.1371/journal.pone.0356002.g003) **Citation:** Su Y, Luo X, Xu H (2026) Apoptosis-related genes bridge inflammatory bowel disease and osteoporosis: A bioinformatic analysis. PLoS One 21(8): e0356002. https://doi.org/10.1371/journal.pone.0356002 **Editor:** Gary S. Stein, University of Vermont, UNITED STATES OF AMERICA **Received:** April 10, 2026; **Accepted:** July 28, 2026; **Published:** August 12, 2026 **Copyright:** © 2026 Su et al. This is an open access article distributed under the terms of the [Creative Commons Attribution License](http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. **Data Availability:** No data was generated by this study. The following existing data sources were used: GSE126124 and GSE56815 from GEO database available via . The list of apoptosis-related genes was acquired from the GeneCards website ( ). **Funding:** The author(s) received no specific funding for this work. **Competing interests:** The authors have declared that no competing interests exist. **Abbreviations:** OP, Osteoporosis; IBD, Inflammatory bowel disease; WGCNA, Weighted Gene Co-expression Network Analysis; DEGs, differentially expressed genes; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; ROC, receiver operating characteristic; AUC, area under the curve ## Background Osteoporosis(OP) is a common systemic metabolic bone disease characterized primarily by reduced bone mass and deterioration of bone microarchitecture, which leads to decreased bone strength and a significantly increased risk of fragility fractures [[1](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref001)]. According to a previous report, the prevalence of OP among the elderly population in China reaches 33.49%, meaning that one in every three elderly individuals is affected [[2](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref002)]. With the accelerated aging of the global population, the number of OP patients is expected to rise further in the future [[3](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref003)]. This trend not only increases the medical burden but also severely impacts patients’ quality of life [[4](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref004)]. The most common complication of OP is osteoporotic fracture, with a lifetime fracture risk of up to 40% for affected patients. Such fractures mainly include vertebral compression fractures and hip fragility fractures, with hip fragility fractures accounting for over 40% of cases. Moreover, the probability of refracture after vertebroplasty for vertebral compression fractures is nearly 20%. Fractures can lead to loss of mobility and independence, further reducing patients’ quality of life. Additionally, due to prolonged bed rest during hospitalization, osteoporotic fracture patients face a significantly elevated risk of complications such as pneumonia or thromboembolic events, which are associated with an excess mortality rate of up to 20% within 12 months. This further exacerbates the public health burden [[5](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref005)–[7](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref007)]. Therefore, in-depth research into the mechanisms underlying the development and progression of OP is of great importance for the prevention and treatment of this disease. Inflammatory bowel disease (IBD) is a chronic, heterogeneous inflammatory disorder of the intestines, primarily including Crohn’s disease and ulcerative colitis. Crohn’s disease can affect the entire gastrointestinal tract from the mouth to the anus, while ulcerative colitis lesions are mainly confined to the colon [[8](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref008)]. Its inflammatory features are chronic and relapsing, with clinical manifestations often including abdominal pain, weight loss, diarrhea, and other symptoms [[9](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref009),[10](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref010)]. Persistent inflammation may lead to complications such as intestinal strictures, fistula formation, weight loss, malnutrition, and even malignancy [[11](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref011)]. According to incomplete statistics, IBD affects approximately 1.5 million Americans and 2.2 million Europeans [[12](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref012),[13](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref013)], with a global prevalence estimated at 0.3% to 0.5% [[14](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref014)]. he etiology of IBD is complex, involving the interplay of multiple factors including genetics, environment, diet, immune responses, and neural regulation [[15](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref015)]. Due to its chronic and protracted course, patients often face increased treatment burdens, higher hospitalization rates, and significant impacts on their quality of life and social functioning [[12](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref012),[16](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref016)]. In the treatment of IBD, glucocorticoids play a crucial role. For example, oral systemic glucocorticoids such as prednisone and prednisolone have been used for over 60 years to alleviate symptoms of IBD. Second-generation glucocorticoids (e.g., budesonide and beclomethasone dipropionate), due to their stronger anti-inflammatory activity, significant first-pass effect (resulting in low systemic bioavailability), and higher affinity for glucocorticoid receptors, have now become an important option for the treatment of IBD [[17](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref017)]. However, excessive use of glucocorticoids can inhibit the proliferation and differentiation of osteoblasts while promoting the apoptosis of osteoblasts and osteocytes, thereby inducing or exacerbating OP [[18](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref018)–[22](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref022)]. The prevalence of OP is significantly higher in patients with IBD [[23](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref023)]. The shared driving mechanisms behind the burden of these two diseases involve the impact of both IBD itself and its therapeutic agents on bone metabolism. Therefore, IBD is one of the significant etiological factors for osteoporosis, and elucidating the common pathogenesis and related molecular targets linking IBD and OP is of great importance for clinical prevention and treatment. The aim of this study is to identify key genes commonly associated with both IBD and OP by integrating bioinformatics analytical approaches, thereby uncovering potential shared genetic mechanisms between the two diseases. This research seeks to provide a theoretical foundation for mitigating bone loss related to IBD and to offer novel potential targets for the prevention and treatment of OP in patients with IBD. ## Methods ### Sample source The data related to IBD and OP were both obtained from the GEO database. The expression matrix for IBD was derived from the GSE126124 dataset, from which tissue-related expression profiles were selected, including 21 normal tissues and 57 diseased tissues, with the platform type GPL6244. The expression matrix for OP was sourced from the GSE56815 dataset, which included 40 normal samples and 40 OP samples, using the platform GPL96. The list of apoptosis-related genes was acquired from the GeneCards website ( ), with data collection up to December 1, 2025. To identify genes more closely associated with the apoptosis process, genes with a relevance score ≥ 5 were selected for subsequent analysis. ### Differential analysis To analyze the differentially expressed genes in the GSE126124 and GSE56815 datasets, this study utilized the limma package in R for differential expression analysis. To ensure statistical significance of the identified genes, the screening threshold for differentially expressed genes was set at a p ) [[24](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356002#pone.0356002.ref024)]. ### Enrichment analysis Functional enrichment analysis for the intersecting genes of IBD and OP was performed using the Metascape platform ( ). This analysis included Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment to identify key biological processes, molecular functions, cellular component, and associated signaling pathways. The enriched terms were clustered based on functional similarity, from which the most significantly enriched and representative terms were selected. A statistical significance threshold of p < 0.05
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