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Epidemiology

Associations of diabetes, circulating protein biomarkers, and risk of pancreatic cancer

British Journal of Cancer volume 130, pages 504–510 (2024)Cite this article

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Abstract

Background

Type 2 diabetes (T2D) is associated with higher risk of pancreatic cancer (PC), but the underlying mechanisms are not fully understood.

Methods

We conducted a case-subcohort study involving 610 PC cases and 623 subcohort participants with 92 protein biomarkers measured in baseline plasma samples. Genetically-instrumented T2D was derived using 86 single-nucleotide polymorphisms (SNPs), including insulin resistance (IR) SNPs.

Results

In observational analyses of 623 subcohort participants (mean age, 52 years; 61% women), T2D was positively associated with 13 proteins (SD difference: IL6: 0.52 [0.23–0.81]; IL10: 0.41 [0.12–0.70]), of which 8 were nominally associated with incident PC. The 8 proteins potentially mediated 36.9% (18.7–75.0%) of the association between T2D and PC. In MR, no associations were observed for genetically-determined T2D with proteins, but there were positive associations of genetically-determined IR with IL6 and IL10 (SD difference: 1.23 [0.05–2.41] and 1.28 [0.31–2.24]). In two-sample MR, fasting insulin was associated with both IL6 and PC, but no association was observed between IL6 and PC.

Conclusions

Proteomics were likely to explain the association between T2D and PC, but were not causal mediators. Elevated fasting insulin driven by insulin resistance might explain the associations of T2D, proteomics, and PC.

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Fig. 1: Associations of T2D, proteomics, and PC.
Fig. 2: Observational and genetic associations of T2D, IL6, and PC.
Fig. 3: Flow diagram.

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Data availability

CKB investigators are committed to sharing this important resource with the wider scientific community, so that the potential value of the CKB resource can be maximized. Open access to the CKB resource has begun in a phased approach. To facilitate the process a Data Access Committee (see http://www.ckbiobank.org/site/Data+Access) has been established, comprising not only senior CKB scientists but also external experts in related fields. For any external data access requests, an outline proposal defining the purpose of the investigation, the data/samples required and the time-scale for the analysis needs to be completed and submitted for review by the study executive committee. The access request review will assess the scientific merit of the proposal to ensure that research questions are legitimate and that there is no duplication of effort. Only proposals complying with the activities listed in the participant’s original consent and with the study’s ethical approval will be considered. To facilitate future collaboration and streamline data sharing and access, a detailed policy document on data access and a related IT platform has been developed and made available on the study web site (www.ckbiobank.org). The policy reflects the principles of the data access policies promoted by the study funders, as well as certain specific conditions already agreed with the original funder (the Kadoorie Foundation) and Chinese government. Information on access to the CKB resource is actively disseminated through workshops, seminars and conference presentations, in published articles, and through the study website. To date over 250 researchers have registered through our data sharing system and over 100 datasets have been securely delivered to open access users and collaborators using this facility.

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Acknowledgements

The chief acknowledgment is to the participants, the project staff, and the China National Centre for Disease Control and Prevention (CDC) and its regional offices for access to death and disease registries. The Chinese National Health Insurance scheme provides electronic linkage to all hospital admission data.

Funding

This work was supported by National Natural Science Foundation of China (82304223, 82192901, 82192904, 82192900). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, 088158/Z/09/Z), grants (2016YFC0900500) from the National Key R&D Program of China, National Natural Science Foundation of China (81390540, 91846303, 81941018), and Chinese Ministry of Science and Technology (2011BAI09B01). Dr Pang acknowledges support from the Peking University Medicine Fund of Fostering Young Scholars’ Scientific & Technological Innovation (BMU2022RCZX022), the Fundamental Research Funds for the Central Universities, and the Peking University Start-up Grant (BMU2022PY014). The proteomics analysis was funded by NDPH Pump Priming Award, Pancreatic Cancer UK (A102016RIFProfZChen), and Cancer Research UK Oxford Centre (C552/A17720). The funders had no role in the study design, data collection, data analysis and interpretation, writing of the report, or the decision to submit the article for publication.

Author information

Author notes

  1. These authors contributed equally: Liming Li, Zhengming Chen, Christiana Kartsonaki.

Authors and Affiliations

  1. Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, 100191, Beijing, China

    Yuanjie Pang, Jun Lv, Ting Wu, Canqing Yu & Liming Li

  2. Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China

    Yuanjie Pang, Jun Lv, Canqing Yu & Liming Li

  3. Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China

    Jun Lv, Canqing Yu & Liming Li

  4. National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Beijing, China

    Yu Guo

  5. Fuwai Hospital, Chinese Academy of Medical Sciences, 167 Beilishi Road, Xicheng District, 100037, Beijing, China

    Yu Guo

  6. Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, Roosevelt Drive, University of Oxford, Oxford, UK

    Yiping Chen, Ling Yang, Iona Y. Millwood, Robin G. Walters, Xiaoming Yang, Rebecca Stevens, Robert Clarke, Zhengming Chen & Christiana Kartsonaki

  7. Medical Research Council Population Health Research Unit (MRC PHRU) at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK

    Yiping Chen, Ling Yang, Iona Y. Millwood, Robin G. Walters, Zhengming Chen & Christiana Kartsonaki

  8. National Center for Food Safety Risk Assessment, 37 Guangqu Road, 100021, Beijing, China

    Junshi Chen

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Contributions

YP, LL, ZC, and CK had full access to the data. YP and CK conducted data analysis and are responsible for accuracy of the results and the decision to submit for publication. All authors were involved in study design, conduct, long-term follow-up, review and coding of disease events, interpretation of the results, or writing the report. All authors approved the final version of the manuscript. YP is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

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Correspondence to Yuanjie Pang or Liming Li.

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Pang, Y., Lv, J., Wu, T. et al. Associations of diabetes, circulating protein biomarkers, and risk of pancreatic cancer. Br J Cancer 130, 504–510 (2024). https://doi.org/10.1038/s41416-023-02533-2

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