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Principal Investigator
Rachael Stolzenberg-Solomon
PH.D, R.D., M.P.H.
Position Title
Senior Investigator
About this CDAS Project
PLCO (Learn more about this study)
Project ID
Initial CDAS Request Approval
Mar 27, 2024
Covariate data for new set of controls for GWAS studies
We are requesting covariate data from cases and controls from DUP-30. We used previously genotyped controls for PanScan3 (EEMS-2006-0306, addendum 3) which are biased for both exposures and genotype. Most of the previously genotyped controls for EEMS-2006-0306, addendum 3, were male smokers (because part of a lung cancer GWAS) from PLCO and often the results for PanScan3 are different compared to the other GWAS phases. Therefore we are requesting the two unbiased set of controls which was created previously for PLCO-277, DUP 30, and DUP-72. We feel that this previously created set would require less resources to assemble for us.

We would like to obtain covariate data from the cases and controls selected for DUP-30 with flags for cases and controls sets (random and matched). We would also like the PLCO study ids so that we can merge the data with the GWAS data that we have in hand (DUPS 72) and check for potential overlap with the PLCO data that we have for PanScan1 and PanScan3. In addition to the basic information (age @ diagnosis; age when selected as matched control, age @ collection or baseline; 1st cancer site; sex; study name; and study PID), history of diabetes (yes, no, missing), baseline BMI, smoking (never, current, former, packyears, missing) alcohol use (grams per day), BMI at age 20, HEI-2015, and family history of pancreatic cancer. The later were included with PLCO-277 and DUP-30.

We feel that it would save time and resources to use the set that was already created.

It remains largely unknown the causal genes and molecular mechanisms for pancreatic ductal adenocarcinoma (PDAC) risk. We request covariate data for DUPS 72 to conduct Mendelian Randomization (MR) studies of hypothesized exposures and PDAC. The PanScan1-3 and PanC4 study populations are unique in their large number of pancreatic cancer cases and GWAS data. We aim to examine the associations between hypothesized exposures and PDAC risk by using two-sample MR using genotype and summary level statistics from PanScan1-3 and PanC4. We will use single-nucleotide polymorphisms (SNPs) that are associated with hypothesized exposures of interest at genome-wide significance identified from other sources as instrumental variables and apply them to summary-level GWAS statistics of PDAC within PanScan1-3 and PanC4 GWAS studies. We will generate MR estimates by using inverse variance weighting (IVW) and other MR methods. We will also conduct cis-MR analysis by focusing on variants within/near a known protein-encoding gene to characterize the effect of the protein on PDAC. For PDAC-associated snps, we will perform Bayesian colocalization analyses to investigate shared causal genetic variants and PDAC. This proposal will provide novel insights into PDAC etiology and could have implications for prevention or therapeutic approaches. The research will be used to learn about, prevent or treat cancer. We intent to publish or otherwise broadly share any findings from this research with the scientific community.


Haoyu Zhang (
Ting Zhang (
Xing Hua (
Kai Yu