Allostatic load, genetic susceptibility, and lung cancer risk: Evidence from a prospective cohort and integrative proteomic analyses

@article{yang2026allostatic,
  title = {{Allostatic load, genetic susceptibility, and lung cancer risk: Evidence from a prospective cohort and integrative proteomic analyses}},
  author = {Fan Yang and Wei Wang and Fangyi Chen and Zhichao Wang and Yifan Wang and Tianchen Qi and Zhazheng He and Shuang Liang and Qingyin Bu and Xirui Qiu and Dong Jiaqing and Shuai Ren and Juncheng Dai and Xiaoxiao Wang},
  journal = {PLOS Digital Health},
  year = {2026},
  month = oct,
  doi = {10.1371/journal.pdig.0001766},
  url = {https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001766},
  note = {CC BY},
}

TY  - JOUR
TI  - Allostatic load, genetic susceptibility, and lung cancer risk: Evidence from a prospective cohort and integrative proteomic analyses
AU  - Fan Yang
AU  - Wei Wang
AU  - Fangyi Chen
AU  - Zhichao Wang
AU  - Yifan Wang
AU  - Tianchen Qi
AU  - Zhazheng He
AU  - Shuang Liang
AU  - Qingyin Bu
AU  - Xirui Qiu
AU  - Dong Jiaqing
AU  - Shuai Ren
AU  - Juncheng Dai
AU  - Xiaoxiao Wang
PY  - 2026
DA  - 2026/10/01
JO  - PLOS Digital Health
DO  - 10.1371/journal.pdig.0001766
UR  - https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001766
AB  - 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.
SN  - 2767-3170
ER  -