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Updated: Mar 14, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
A population-specific correlation between ADIPOQ rs2241766 and rs 1501299 and colorectal cancer risk: a meta-analysis
Lin Ye1, Guobin Wang2, Yong Tang2
1Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, HuaZhong University of Science and Technology, 1277 JieFang Avenue, Wuhan, 430022, China. ylwhuhhust@hust.edu.cn.
Aims:
Many epidemiological studies have investigated the correlation between adiponectin, C1Q and collagen domain containing (ADIPOQ) single nucleotide polymorphisms (SNPs) and risk of colorectal cancer (CRC). Although conflicting results have been reported, there was dispute regarding two SNPs (rs2241766 T/G and rs1501299 G/T). Therefore, we conducted a meta-analysis to systematically assess the associations and try to find the reasons for the dispute.
Methods:
We searched PubMed, the Cochrane Library, Elsevier, Wiley Online Library, China National Knowledge Infrastructure, WanFang data and Chongqing VIP to search for all eligible case-control studies published up to January 2015. Effect sizes of odds ratios (OR) and 95 % confidence intervals (95 % CI) were calculated using a fixed- or random-effect model.
Results:
Ten case-control studies including 4377 cases and 5584 controls were selected. A significant difference was observed in Chinese (OR 0.76; 95 % CI 0.68, 0.85; P < 0.001) and Ashkenazi Jewish populations (OR 0.79; 95 % CI 0.63, 0.99; P = 0.04) for rs2241766 with dominant model (TT vs TG + GG). A significant difference was observed in the Chinese population (OR 1.23; 95 % CI 1.11, 1.37; P < 0.001) for rs1501299 with dominant model (TT vs TG + GG). In addition, intake of red meat showed a synergistic effect between ADIPOQ gene and risk of colorectal cancer (CRC).
Conclusions:
ADIPOQ SNPs rs2241766 T/G and rs 1501299 G/T have a population-specific correlation with risk of CRC. However, small sample studies may increase reporting bias, particularly if the total number of studies included in the analysis is small.
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