Annual Meeting of the NCI Cohort Consortium (Abstract Submission): Submission #10

Lightning Talks Abstract
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Presenter's First Name: : Ting
Presenter's Last Name:: Zhang
Title (eg: professor, assistant professor, chair, etc):: postdoctoral fellow
Degree(s): PhD
Contact Email:: ting.zhang3@nih.gov
Organization:: National Cancer Institute
Project Title:: Blood proteomic profiles and pancreatic ductal adenocarcinoma risk – A Mendelian randomization and observational analysis
Additional Authors:
1. First Name: Ting
   Last Name: Zhang
   Degree(s): Ph.D. MPH
   Organization: National Cancer Institute
2. First Name: Devika
   Last Name: Godbole
   Degree(s): MS
   Organization: National Cancer Institute
3. First Name: Ziqiao
   Last Name: Wang
   Degree(s): Ph.D.
   Organization: Johns Hopkins Bloomberg School of Public Health
4. First Name: Xiaoyu
   Last Name: Wang
   Degree(s): MS
   Organization: National Cancer Institute
5. First Name: Jia
   Last Name: Liu
   Degree(s): Ph.D.
   Organization: National Cancer Institute
6. First Name: Chirayu
   Last Name: Mohindroo
   Degree(s): MBBS
   Organization: National Cancer Institute
7. First Name: Shilpa
   Last Name: Katta
   Degree(s): MS
   Organization: National Cancer Institute
8. First Name: Shengchao
   Middle Initial: A.
   Last Name: Li
   Degree(s): MS
   Organization: National Cancer Institute
9. First Name: Jiahui
   Last Name: Wang
   Degree(s): MS
   Organization: National Cancer Institute
10. First Name: PanScan
    Middle Initial: and
    Last Name: PanC4 Consortium
    Organization: National Cancer Institute
11. First Name: Brian
    Middle Initial: M.
    Last Name: Wolpin
    Degree(s): M.D., MPH
    Organization: Dana-Farber Cancer Institute
12. First Name: Harvey
    Middle Initial: A.
    Last Name: Risch
    Degree(s): M.D., Ph.D.
    Organization: Yale School of Public Health
13. First Name: Laufey
    Middle Initial: T.
    Last Name: Amundadottir
    Degree(s): Ph.D.
    Organization: National Cancer Institute
14. First Name: Alison
    Middle Initial: P.
    Last Name: Klein
    Degree(s): Ph.D., MHS
    Organization: Johns Hopkins Bloomberg School of Public Health
15. First Name: Vernon
    Middle Initial: A.
    Last Name: Burk
    Degree(s): MPH
    Organization: Johns Hopkins Bloomberg School of Public Health
16. First Name: Nilanjan
    Last Name: Chatterjee
    Degree(s): Ph.D., MS
    Organization: Johns Hopkins Bloomberg School of Public Health
17. First Name: Kai
    Last Name: Yu
    Degree(s): Ph.D.
    Organization: National Cancer Institute
18. First Name: Elizabeth
    Middle Initial: A.
    Last Name: Platz
    Degree(s): ScD, MPH
    Organization: Johns Hopkins Bloomberg School of Public Health
19. First Name: Diptavo
    Last Name: Dutta
    Degree(s): Ph.D.
    Organization: National Cancer Institute
20. First Name: Haoyu
    Last Name: Zhang
    Degree(s): Ph.D.
    Organization: National Cancer Institute
21. First Name: Rachael
    Middle Initial: Z.
    Last Name: Stolzenberg-Solomon
    Degree(s): PhD, MPH, RD
    Organization: National Cancer Institute

Abstract::
Background: Proteomic biomarkers hold promises for early detection and etiologic insights into pancreatic ductal adenocarcinoma (PDAC). We investigated associations between genetically predicted plasma proteins and PDAC risk using Mendelian randomization (MR) and assessed identified proteins with incident PDAC in two prospective cohorts.  
Methods: We conducted proteome-wide MR by applying cis-acting protein quantitative trait loci (pQTLs, P<5×10-8) identified from genome-wide association studies of plasma proteins in the UK Biobank (UKB, n=34,557; 2923 proteins) and deCODE (n=35,559; 4719 proteins), respectively, to summary statistics from a PDAC GWAS meta-analysis of PanScan1–3/PanC4/FinnGen (10,244 cases, 360,535 controls of European ancestry). We validated the top MR-identified proteomic-PDAC associations using Cox proportional hazards models within UKB (n=52,551, 133 cases) and Atherosclerosis Risk in Communities (ARIC) study (n=9476; 88 cases) cohorts and combined using fixed-effect meta-analysis.
Results: The proteome-wide MR identified 44 proteins significantly associated with PDAC risk after Bonferroni correction (PUKB<2.7×10-5 or PdeCODE <3.0×10-5), of which 17 were cross-validated in both datasets (P<0.05). Of the 44, eight proteins were previously identified, including ABO, CTRB1, B4GALT1, REG1A, FUT3, AMY2A, AMY2B, and NCF1 (OR=0.80–1.27 per standard deviation increment). The remaining 36 proteins were newly identified. In prospective analyses, higher plasma ABO and ITIH3 were associated with incident PDAC in UKB-ARIC meta-analysis (HR=1.19 and 1.20 respectively). 
Conclusion/Discussion: We identified multiple genetically predicted plasma proteins associated with PDAC risk, among which associations for measured plasma ABO and ITIH3 were further validated using in two prospective cohorts. These proteins highlight promising candidates for future investigations as PDAC prevention targets.