{ "abstract": "Allostatic load (AL), a composite measure of multisystem dysregulation associated with chronic stress, has been linked to lung cancer risk. However, its joint effects with genetic susceptibility and the biological pathways underlying this relationship remain unclear. We conducted a prospective cohort study of 336,945 UK Biobank participants to assess associations between AL and lung cancer incidence and its histological subtypes. A polygenic risk score was constructed to evaluate the joint associations of AL and genetic susceptibility. We further assessed whether AL provided incremental risk stratification beyond established low-dose computed tomography (LDCT) screening eligibility frameworks and integrated plasma proteomic data using machine learning, enrichment, and mediation analyses. We found that higher AL was associated with an increased risk of lung cancer (per-unit HR = 1.073, 95% CI: 1.053–1.094; Low vs. Normal HR = 1.284, 95% CI: 1.065–1.547; High vs. Normal HR = 1.629, 95% CI: 1.347–1.971). Subtype analyses revealed the strongest effect for small-cell lung cancer (SCLC), with significant associations also observed for lung adenocarcinoma and squamous cell carcinoma. High AL combined with high genetic risk was associated with a 136.9% increased risk (HR = 2.369, 95% CI: 1.565–3.583), without evidence of interaction. AL provided additional risk discrimination beyond established LDCT screening eligibility criteria. Proteomic analyses identified 111 AL-associated proteins and 34 proteins with potential mediation signal, including HGF, RARRES2, and GDF15, implicating inflammatory, metabolic, and growth factor-related processes as biological correlates of the AL–lung cancer association. In conclusion, higher AL was independently associated with lung cancer risk, particularly SCLC. Integrative proteomic analyses provided exploratory evidence for biological pathways that may link cumulative physiological dysregulation to lung carcinogenesis. Incorporating AL, as a composite biomarker reflecting cumulative physiological burden, into risk models may improve risk stratification and help identify individuals at elevated risk. Author summary: Lung cancer remains the leading cause of cancer-related death worldwide. We investigated whether long-term physiological stress, quantified using a measure known as allostatic load that captures cumulative dysregulation across multiple body systems, is associated with the development of lung cancer. We also examined whether AL and inherited genetic susceptibility were jointly associated with lung cancer risk. Using data from a large prospective population cohort, we found that individuals with higher levels of physiological stress had a substantially greater risk of developing lung cancer. The association was particularly strong for small-cell lung cancer, an aggressive subtype. People with both high stress burden and high genetic risk experienced the highest incidence rates, although the two factors appeared to contribute independently. We also found that allostatic load provided additional risk stratification beyond existing low-dose CT screening eligibility criteria, suggesting that it may help identify high-risk individuals not fully captured by current screening rules. To explore potential biological explanations, we integrated large-scale plasma protein data and identified stress-related inflammatory and metabolic pathways that may connect chronic physiological dysregulation to lung carcinogenesis. Our findings suggest that long-term systemic stress, as captured by allostatic load, is associated with lung cancer development and may reflect cumulative biological and behavioral disadvantage. Incorporating stress-related biological measures into risk assessment may improve identification of high-risk individuals and inform prevention strategies.", "abstract_shown": true, "affiliations": [ "Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China", "GCP Center, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China", "Clinical Research Institut, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China", "Department of Respiratory and Critical Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine (Jiangsu Hospital of Traditional Chinese Medicine), Nanjing, China", "Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China", "Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, Jiangsu, China" ], "article_type": "Research Article", "arxiv": null, "author_total": 14, "authors": [ { "affs": [ 0 ], "name": "Fan Yang" }, { "affs": [ 1 ], "name": "Wei Wang" }, { "affs": [ 2 ], "name": "Fangyi Chen" }, { "affs": [ 3 ], "name": "Zhichao Wang" }, { "affs": [ 4 ], "name": "Yifan Wang" }, { "affs": [ 5 ], "name": "Tianchen Qi" }, { "name": "Zhazheng He" }, { "name": "Shuang Liang" }, { "name": "Qingyin Bu" }, { "name": "Xirui Qiu" }, { "name": "Dong Jiaqing" }, { "name": "Shuai Ren" }, { "name": "Juncheng Dai" }, { "name": "Xiaoxiao Wang" } ], "bibtex": "https://research.draconitic.com/paper/9jr9pv86pzbhj.bib", "cited_by": 0, "doi": "10.1371/journal.pdig.0001766", "fulltext_url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001766", "id": "9jr9pv86pzbhj", "issns": [ "2767-3170" ], "landing_url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001766", "language": "eng", "licence": "CC-BY", "licence_label": "CC BY", "licence_source": "article", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "metadata_licence": null, "native_subjects": [ [ "openalex", "2730|Lung Cancer Research Studies" ], [ "plos", "/Biology and life sciences/Genetics/Genetics of disease/Genetic predisposition" ], [ "plos", "/Biology and life sciences/Immunology/Immune response/Inflammation" ], [ "plos", "/Medicine and health sciences/Clinical medicine/Signs and symptoms/Inflammation" ], [ "plos", "/Medicine and health sciences/Diagnostic medicine/Cancer detection and diagnosis/Cancer screening" ], [ "plos", "/Medicine and health sciences/Epidemiology/Cancer epidemiology" ], [ "plos", "/Medicine and health sciences/Epidemiology/Medical risk factors/Cancer risk factors" ], [ "plos", "/Medicine and health sciences/Immunology/Immune response/Inflammation" ], [ "plos", "/Medicine and health sciences/Oncology/Cancer detection and diagnosis/Cancer screening" ], [ "plos", "/Medicine and health sciences/Oncology/Cancer risk factors" ], [ "plos", "/Medicine and health sciences/Oncology/Cancers and neoplasms/Lung and intrathoracic tumors" ], [ "plos", "/Medicine and health sciences/Oncology/Cancers and neoplasms/Lung and intrathoracic tumors/Non-small cell lung cancer" ], [ "plos", "/Medicine and health sciences/Oncology/Cancers and neoplasms/Lung and intrathoracic tumors/Small cell lung cancer" ] ], "openalex": "W7221764241", "pdf_url": "https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0001766&type=printable", "pmcid": "PMC13667778", "pmid": null, "published": "2026-10-01", "publisher": "Public Library of Science", "ris": "https://research.draconitic.com/paper/9jr9pv86pzbhj.ris", "sources": [ { "first_seen": "2026-10-30T12:17:23Z", "native_id": "10.1371/journal.pdig.0001766", "source": "plos", "url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001766" }, { "first_seen": "2026-10-30T12:17:35Z", "native_id": "PMC:PMC13667778", "source": "europepmc", "url": "https://europepmc.org/article/PMC/PMC13667778" } ], "subjects": [ { "field": "medicine", "origin": "plos:oncology", "subfield": "oncology" } ], "title": "Allostatic load, genetic susceptibility, and lung cancer risk: Evidence from a prospective cohort and integrative proteomic analyses", "title_text": "Allostatic load, genetic susceptibility, and lung cancer risk: Evidence from a prospective cohort and integrative proteomic analyses", "type": "peer-reviewed", "updated_at": "2026-10-30T12:17:35Z", "url": "https://research.draconitic.com/paper/9jr9pv86pzbhj", "venue": "PLOS Digital Health", "versions": [] }