Add like
Add dislike
Add to saved papers

Fine mapping in TERT-CLPTM1L region identified three independent lung cancer susceptibility signals: A large-scale multi-ethnic population study.

Genome-wide association studies (GWAS) and fine mapping studies have identified multiple lung cancer susceptibility variants in TERT-CLPTM1L region. However, it is still unclear about the relationship between these risk variants and the independent lung cancer risk signals in this region. Therefore, we evaluated the independent susceptibility signals for lung cancer and explored the potential functional variants in this region. Sequential conditional analysis was used to detect the independent susceptibility loci based on four lung cancer GWAS datasets with 12 843 lung cases and 12 639 controls. Comprehensively functional annotations were performed for each independent signal. Three independent susceptibility signals were identified in multi-ethnic population. For the first signal, rs2736100 showed the most significant association with lung cancer risk (C > A, OR = 0.82, 95%CI: 0.79-0.85, P = 1.98 × 10-25 ). Rs36019446 was the top-ranked site (A > G, OR = 0.88, 95%CI: 0.84-0.92, P = 1.74 × 10-9 ) in the second signal. For the third signal, rs326048 was the leading SNP (A > G, OR = 0.91, 95%CI: 0.87-0.95, P = 1.38 × 10-5 ). The following subgroup analysis found the same three loci among Asian population. Further, we compared the difference between various subgroup populations. Functional annotations revealed that rs2736100, rs27996 (r2  = 0.85 with rs36019446) and rs326049 (r2  = 0.73 with rs326048) could be potential functional variants in these three risk signals, respectively. In conclusion, although multiple variants have been found associated with lung cancer risk in TERT-CLPTM1L region, our findings indicated that there are three independent lung cancer susceptibility signals in this region.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app