Marc J Gunter | PubMed Health

PubMed2026

Proteomics of multimorbidity progression across cardiometabolic diseases and cancer in a multinational cohort.

BACKGROUND: Multimorbidity, defined here as the co-occurrence of cardiovascular disease (CVD), type 2 diabetes (T2D), and/or cancer is a major public health challenge. However, its underlying biological mechanisms remain unclear, limiting progress toward identifying shared interventional targets. METHODS: We applied large-scale plasma proteomics (SomaScan 7k; 7,289 aptamers) in 13,270 European Prospective Investigation into Cancer and Nutrition (EPIC) participants to identify protein signatures of multimorbidity. We modelled multimorbidity progression as sequential disease transitions, i.e., from the disease-free state at baseline to a first disease and from the first disease to a second disease. Using weighted multivariable Cox regression, we estimated hazard ratios (HR) and 95% confidence intervals (CI) for risk of cancer, CVD, and T2D. Risk associations were replicated using Olink proteomics in UK Biobank (N = 44,567). RESULTS: We identified 422 aptamers associated with more than one disease (FDR-corrected P < 0.05), e.g., 265 aptamers were shared between CVD and T2D. Thirty-eight aptamers were associated with multimorbidity progression. Among these, 27 aptamers showed consistent positive associations across sequential disease transitions, including SEMA6A (disease-free to cancer HR: 1.14; 95% CI 1.05, 1.23; cancer to T2D HR: 2.61; 95% CI 1.76, 3.80). Four aptamers showed consistent inverse associations, including NLGN1 (disease-free to T2D HR: 0.72; 95% CI 0.61, 0.84; T2D to cancer HR: 0.57; 95% CI 0.43, 0.75). Nineteen of the identified proteins were also measured in UK Biobank, with broadly consistent associations. CONCLUSIONS: This study identifies candidate proteins that may indicate molecular pathways to multimorbidity of cardiometabolic diseases and cancer. Future studies should evaluate the causal roles of these proteins for targeted interventions and risk stratification.

Humans↗

PubMed2026

Plasma signals of lung tumor promotion for molecular cancer prevention.

Predicting lung cancer risk would enhance prevention trials. Although the Canakinumab Anti-inflammatory Thrombosis Outcome Study (CANTOS) trial demonstrated reduced lung cancer incidence with interleukin (IL)-1β inhibition, the high number needed to treat (NNT) to prevent lung cancer limits its use in unselected populations. Using machine learning, we identified a 14-protein plasma signature predicting lung cancer more than 5 years before diagnosis. The signature, validated across eight cohorts, was elevated in current smokers and individuals exposed to particulate matter (PM) and linked to lung myeloid and alveolar cells. In epidermal growth factor receptor (EGFR)-driven lung adenocarcinoma, diverse epithelial lineages converged on a keratin8+/claudin4+ alveolar transitional state (KAC), whose transcriptional programs correlated with signature emergence. Components of the signature were induced by PM, oncogenic EGFR, or IL-1β, whereas IL-1β inhibition restrained PM-driven KAC expansion and early tumorigenesis. In CANTOS, the signature identified individuals who seemed to benefit more from anti-IL-1β therapy, lowering the NNT threshold and nominating circulating signals of tumor promotion for prevention.

Humans↗

PubMed2025

Insulinemic and inflammatory dietary patterns and colorectal cancer risk: a dietary data harmonization study of one million participants in the Consortium of Metabolomics Studies (COMETS).

BACKGROUND: Inflammatory and insulinemic dietary patterns have been associated with colorectal cancer (CRC) risk, but generalizability across diverse populations with heterogeneous food supplies and dietary behaviors has not been established. OBJECTIVES: We harmonized disparate dietary and covariate data on a large scale to compute the reverse Empirical Dietary Index for Hyperinsulinemia (rEDIH), reverse Empirical Dietary Inflammatory Pattern (rEDIP), and Healthy Eating Index (HEI)-2015 scores, and tested their associations with CRC risk. METHODS: We leveraged data among 501,892 women and 407,390 men from 6 cohorts across the United States (NIH-AARP, Multi-Ethnic Study of Atherosclerosis, Prostate, Lung, Colorectal, and Ovarian, SCCS) and Europe (EPIC, ATBC) with varying sociodemographic characteristics, participating in the Consortium of Metabolomics Studies. We harmonized nomenclature and nutritional information of >800 unique food items across cohorts. We used multivariable-adjusted Cox regression, adjusting for demographic, clinical, and lifestyle factors, to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between the dietary indices and CRC risk per cohort, then meta-analyzed the estimates. RESULTS: During a median follow-up of 14.9 y, 16,525 incident CRC cases were diagnosed. Participants in the highest quintile of rEDIH (low-insulinemic diet) had an 18% reduced risk of CRC (HR: 0.82; 95% CI: 0.78, 0.86) compared with those in the lowest quintile. For the same comparison, similar risk reductions were observed for rEDIP (anti-inflammatory diet) (HR: 0.84; 95% CI: 0.80, 0.89) and HEI-2015 (overall dietary quality) (HR: 0.80; 95% CI: 0.76, 0.85). Heterogeneity between cohorts in the meta-analyzed estimates was low for rEDIH (I2 = 22.3%) compared with rEDIP (I2 = 62.5%) and HEI-2015 (I2=83.9%). CONCLUSIONS: Using carefully harmonized data from nearly 1 million individuals in the United States and Europe, we observed significant CRC risk reduction with habitual intake of low-insulinemic and anti-inflammatory dietary patterns, comparable with higher overall dietary quality. Study findings underscore the utility of these dietary patterns for global cancer prevention efforts.

Humans↗

PubMed2025

Genetic risk factors modulate the association between physical activity and colorectal cancer.

BACKGROUND: Physical activity (PA) is an established protective factor for colorectal cancer (CRC), but it is unclear if genetic variants modify this effect. To investigate this possibility, we conducted a genome-wide gene-PA interaction analysis. METHODS: Using logistic regression and two-step and joint tests, we analyzed interactions between common genetic variants across the genome and PA in relation to CRC risk. Self-reported PA levels were categorized as active (≥ 8.75 MET-h/wk) vs. inactive (< 8.75 MET-h/wk) and as study- and sex-specific quartiles of activity. RESULTS: PA had an overall protective effect on CRC (OR [active vs. inactive] = 0.85; 95%CI = 0.81-0.90). The two-step GxE method identified an interaction between rs4779584, an intergenic variant near the GREM1 and SCG5 genes, and PA for CRC risk (p-interaction = 2.6×10- 8). Stratification by genotype at this locus showed a significant reduction in CRC risk by 20% in active vs. inactive participants with the CC genotype (OR = 0.80; 95%CI = 0.75-0.85), but no significant PA-CRC association among CT or TT carriers. When PA was modeled as quartiles, the 1-d.f. GxE test identified that rs56906466, an intergenic variant near the KCNG1 gene, modified the association between PA and CRC (p-interaction = 3.5×10- 8). Stratification at this locus showed that increase in PA (highest vs. lowest quartile) was associated with a lower CRC risk solely among TT carriers (OR = 0.77; 95%CI = 0.72-0.82). CONCLUSIONS: In summary, we identified two genetic variants that modified the association between PA and CRC risk. One of them, related to GREM1 and SCG5, suggests that the bone morphogenetic protein (BMP)-related, inflammatory, and/or insulin signaling pathways may be associated with the protective influence of PA on colorectal carcinogenesis.

GWAS↗

PubMed2025

Redefining ALS: Large-scale proteomic profiling reveals a prolonged pre-diagnostic phase with immune, muscular, metabolic, and brain involvement.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic phase, especially for the common non-monogenic form. METHODS: We leveraged the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with up to 30 years of follow-up to identify incident ALS cases across five European countries. Pre-diagnostic plasma samples from initially healthy participants underwent high-throughput proteomic profiling (7,285 protein markers, SomaScan). Cox proportional hazards models based on 4,567 participants (including 172 incident ALS cases) were used to identify protein biomarkers associated with future ALS diagnosis. Top results were indirectly validated in two independent case-control studies of prevalent ALS (n=417 ALS, 852 controls). Functional annotation included cross-disease comparisons, gene set and tissue enrichment testing, organ-specific proteomic clocks, and the application of large-language models (LLM). FINDINGS: Five proteins (SECTM1, CA3, THAP4, KLHL41, SLC26A7) were identified as significant pre-diagnostic ALS biomarkers (FDR=0.05), detectable approximately two decades before diagnosis. Of these, all except SECTM1 were indirectly validated in independent cohorts of prevalent ALS cases, supporting their clinical significance. Additionally, 22 nominally significant (p<0.05) pre-diagnostic biomarkers were FDR-significant in prevalent ALS with consistent effect directions. Cross-disease comparisons with pre-diagnostic Parkinson's and Alzheimer's disease suggested a largely specific pre-diagnostic ALS biomarker signature. Gene ontology and tissue enrichment highlighted early involvement of immune, muscle, metabolic, and digestive processes. Furthermore, analyses of proteomic clocks revealed accelerated aging in brain-cognition, immune, and muscle tissues before clinical diagnosis. Druggability and LLM analyses revealed possible therapeutic targets and novel strategies, emphasizing translational relevance. INTERPRETATION: Our study provides first evidence of ultra-early molecular changes in common ALS up to two decades prior to clinical onset, mainly affecting immune, muscle, metabolic, digestive, and cognitive systems. Our study nominates several compelling candidates for risk stratification studies and novel therapeutic targets for early intervention. FUNDING: Clinical Research in ALS and Related Disorders for Therapeutic Development (CreATe) Consortium, Cure Alzheimer's Fund, Michael J Fox Foundation, Interdisciplinary Centre for Clinical Research, University Münster.

Journal Article↗

PubMed2025

Redefining ALS: Large-scale proteomic profiling reveals a prolonged pre-diagnostic phase with immune, muscular, metabolic, and brain involvement.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic phase, especially for the common non-monogenic form. METHODS: We leveraged the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with up to 30 years of follow-up to identify incident ALS cases across five European countries. Pre-diagnostic plasma samples from initially healthy participants underwent high-throughput proteomic profiling (7,285 protein markers, SomaScan). Cox proportional hazards models based on 4,567 participants (including 172 incident ALS cases) were used to identify protein biomarkers associated with future ALS diagnosis. Top results were indirectly validated in two independent case-control studies of prevalent ALS (n=417 ALS, 852 controls). Functional annotation included cross-disease comparisons, gene set and tissue enrichment testing, organ-specific proteomic clocks, and the application of large-language models (LLM). FINDINGS: Five proteins (SECTM1, CA3, THAP4, KLHL41, SLC26A7) were identified as significant pre-diagnostic ALS biomarkers (FDR=0.05), detectable approximately two decades before diagnosis. Of these, all except SECTM1 were indirectly validated in independent cohorts of prevalent ALS cases, supporting their clinical significance. Additionally, 22 nominally significant (p<0.05) pre-diagnostic biomarkers were FDR-significant in prevalent ALS with consistent effect directions. Cross-disease comparisons with pre-diagnostic Parkinson's and Alzheimer's disease suggested a largely specific pre-diagnostic ALS biomarker signature. Gene ontology and tissue enrichment highlighted early involvement of immune, muscle, metabolic, and digestive processes. Furthermore, analyses of proteomic clocks revealed accelerated aging in brain-cognition, immune, and muscle tissues before clinical diagnosis. Druggability and LLM analyses revealed possible therapeutic targets and novel strategies, emphasizing translational relevance. INTERPRETATION: Our study provides first evidence of ultra-early molecular changes in common ALS up to two decades prior to clinical onset, mainly affecting immune, muscle, metabolic, digestive, and cognitive systems. Our study nominates several compelling candidates for risk stratification studies and novel therapeutic targets for early intervention. FUNDING: Clinical Research in ALS and Related Disorders for Therapeutic Development (CreATe) Consortium, Cure Alzheimer's Fund, Michael J Fox Foundation, Interdisciplinary Centre for Clinical Research, University Münster.

Journal Article↗