Search PubMedSearch

PubMed · 42501826

The Association of Diabetes-Related Dietary Patterns with Pancreatic Cancer Risk in the European Prospective Investigation into Cancer and Nutrition Study.

Abstract

BACKGROUND: Pancreatic cancer is relatively rare but remains one of the most lethal tumors. Identifying modifiable risk factors is a crucial step to reduce disease burden. Evidence suggests a potential role of type 2 diabetes mellitus in its pathogenesis. OBJECTIVES: The objective of this study is to examine the association between dietary patterns related to diabetes and pancreatic cancer risk in a European population. METHODS: A total of 367,395 participants from the European Prospective Investigation into Cancer and Nutrition study were included. After a median follow-up of 14.9 y, 926 incident cases were identified. The Diabetes Risk Reduction Diet (DRRD), the Empirical Dietary Index for Hyperinsulinemia (EDIH), and the Empirical Dietary Index for Insulin Resistance (EDIR) were estimated from food frequency questionnaires at recruitment. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between dietary patterns and pancreatic cancer were calculated using multivariable Cox proportional hazards regression models, adjusted for relevant confounders. RESULTS: Adherence to DRRD showed no association with risk of pancreatic cancer (HRT3vsT1: 0.94; 95% CI: 0.79, 1.12). Higher adherence to EDIH was associated with a borderline 19% increased pancreatic cancer risk (HRT3vsT1: 1.19; 95% CI: 0.99, 1.44). No significant associations were observed in relation to EDIR. No heterogeneity was observed among the subgroups. CONCLUSIONS: Higher adherence to a hyperinsulinemic dietary pattern may contribute to risk of developing pancreatic cancer in our population. Further research is warranted to elucidate the potential role of dietary factors in cancer risk prevention.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Luisa Torres-Laiton, Weronika Balcerzak, Raul Zamora-Ros, Alba Gasque, Calogero Saieva, Claire Cadeau, Dagfinn Aune, Franziska Jannasch, Laia Peruchet-Noray, Léa Bouteille, Maria Teresa Giraudo, Matthias B Schulze, Mattias Johansson, Natalia Cabrera Castro, Renée T Fortner, Rosario Tumino, Salvatore Panico, Thérèse Truong, Verena Katzke, Marta Crous-Bou. 2026-07-25. The Association of Diabetes-Related Dietary Patterns with Pancreatic Cancer Risk in the European Prospective Investigation into Cancer and Nutrition Study.. https://doi.org/10.1016/j.tjnut.2026.101755

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans