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Biomedical subjects

P Martijn Kolijn

Publications and source records attributed to P Martijn Kolijn.

5 recordsLinked to original sources

Immune Markers and Risk of Pancreatic Cancer in the European EPIC Cohort.

The immune system is a major driver in pancreatic cancer development. Several prospective cohort studies have found associations for single immune system-derived proteins such as IL6 or CRP, but results are inconclusive, and Omics-based research is scarce. Hence, we aimed to investigate associations of a comprehensive protein panel with the risk of pancreatic cancer. Within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, 92 immune proteins were measured in baseline blood samples of 406 incident pancreatic cancer cases and 406 sex- and age-matched controls, using the Olink Immuno-Oncology panel. Multivariable adjusted conditional logistic regression was used to estimate odds ratios (OR, 95% CI) for protein levels in association with pancreatic cancer risk. Eight biomarkers were associated with pancreatic cancer risk (MMP12, LAMP3, CD28, IL-6, IL-12, FASLG, PD-L2, and PDCD1) but only MMP12 was significantly associated after multivariable adjustments for confounders and the seven proteins, with OR = 1.56 (95% CI: 1.20-2.03) for a doubling in protein concentration. After correction for multiple testing, none of the proteins were associated with risk. Restricting analyses to cases diagnosed within the first 4 years and 4-8 years after recruitment resulted in OR of 1.89 (95% CI: 1.28-2.80) and 1.37 (95% CI: 1.01-1.86) for MMP12, respectively. Higher levels of MMP12 were associated with pancreatic cancer risk specifically in those diagnosed shortly after recruitment, while other immune-related factors were not associated with risk. Further cohort studies are needed to confirm our initial findings.

Humans

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

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 M&#xfc;nster.

Journal Article

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 M&#xfc;nster.

Journal Article

A viral clonality evenness score to predict progression to adult T-cell leukaemia in asymptomatic carriers of human T-lymphotropic virus type 1 in Japan: a retrospective longitudinal cohort study.

BACKGROUND: Adult T-cell leukaemia/lymphoma (ATL) is a highly aggressive T-cell malignancy that occurs in approximately 2-7% of individuals with human T-lymphotropic virus type 1 (HTLV-1), after decades of asymptomatic infection. To address the urgent need for predictive biomarkers to identify asymptomatic carriers of HTLV-1 at high risk of progression to ATL, we aimed to evaluate viral clonality sequencing as a potential tool for risk stratification. METHODS: This retrospective longitudinal cohort study involved HTLV-1 carriers enrolled in the Joint Study on Predisposing Factors of ATL Development, a nationwide cohort study initiated in Japan in 2002. Participants were selected from this cohort on the basis of their baseline proviral load at the time of enrolment as an asymptomatic carrier, length of follow-up, and clinical outcome. The cohort was subdivided into three subgroups: the first comprising HTLV-1 carriers who developed ATL, the second comprising carriers with high proviral load (&#x2265;4%) who did not progress to ATL, and the third comprising carriers with low proviral load (<4%) who did not progress to ATL. DNA extracted from peripheral blood mononuclear cells collected at enrolment and at least one follow-up visit was analysed by HTLV-1 clonality sequencing and the proviral load was quantified. We calculated a viral clonality evenness (VCE) score, based on the Shannon Evenness Index, to quantify the uniformity of the clonal distribution of samples, for which 0 represents a perfectly monoclonal architecture and 1 indicates a completely polyclonal landscape. We then estimated the performance of proviral load thresholds and VCE scoring to classify the risk of progression to ATL using the area under the receiver operating characteristic curve (AUC), the accuracy, and Matthews correlation coefficient. VCEs were compared between participant subgroups with the Wilcoxon rank sum test. FINDINGS: 56 participants followed up by JSPFAD between Feb 6, 2003, and July 19, 2022, were included in this study: 17 who progressed to ATL (mean follow-up 8&#xb7;3 years [SD 4&#xb7;0]), 18 who had a high proviral load and did not progress to ATL (9&#xb7;7 years [3&#xb7;4]), and 21 who had a low proviral load and did not progress to ATL (7&#xb7;5 years [3&#xb7;0]). Clonality sequencing of samples from 39 participants who did not progress to ATL revealed hundreds to thousands of HTLV-1 integration sites at both timepoints, corresponding to multiple clones of low and uniform abundance, and these participants had high VCE scores (&#x2265;0&#xb7;694) at baseline. By contrast, most participants (14 of 17) who progressed to ATL had a single predominant clone or two to four predominant clones at both timepoints, and lower VCE scores (<0&#xb7;694) at baseline than those who did not progress (p<0&#xb7;0001). AUCs were very similar for proviral load thresholds (91 [95% CI 80-98]) and VCE scoring (91 [78-100]), although when using methods that give equal weight to every individual, VCE scoring outperformed proviral load thresholds in predicting progression to ATL (accuracy: proviral load 0&#xb7;76 [95% CI 0&#xb7;76-0&#xb7;77], VCE scoring 1&#xb7;00 [0&#xb7;99-1&#xb7;00]; Matthews correlation coefficient: proviral load 0&#xb7;23 [95% CI 0&#xb7;19-0&#xb7;24], VCE scoring 0&#xb7;91 [0&#xb7;80-1&#xb7;00]). Prediction based on VCE scoring indicated no false positives, compared with 20% when using proviral load, although VCE scoring yields a greater number of false negatives (0&#xb7;3% vs 0&#xb7;1%). INTERPRETATION: The implementation of VCE scoring in clinical practice could inform early pre-emptive therapeutic interventions, exclusively targeting individuals with HTLV-1 at high risk and aiming to prevent progression to aggressive, treatment-refractory disease. Further validation, including independent confirmation of the performance of VCE scoring in multiple populations and the characterisation of its temporal dynamics, will be crucial to determine its clinical utility and potential integration into care pathways. FUNDING: Association Jules Bordet, FNRS-T&#xe9;l&#xe9;vie, FCC, WALInnov, FLF, JSPS-KAKENHI, and CoBiA.

Humans