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Meta-Analysis
. 2015 Dec 1:5:17369.
doi: 10.1038/srep17369.

Meta-analysis of genome-wide association studies identifies common susceptibility polymorphisms for colorectal and endometrial cancer near SH2B3 and TSHZ1

Timothy H T Cheng  1 , Deborah Thompson  2 , Jodie Painter  3 , Tracy O'Mara  3 , Maggie Gorman  1 , Lynn Martin  1 , Claire Palles  1 , Angela Jones  1 , Daniel D Buchanan  4   5 , Aung Ko Win  5 , John Hopper  5 , Mark Jenkins  5 , Noralane M Lindor  6 , Polly A Newcomb  7 , Steve Gallinger  8 , David Conti  9 , Fred Schumacher  9 , Graham Casey  9 , Graham G Giles  5   10   11 , Paul Pharoah  2   12 , Julian Peto  13 , Angela Cox  14 , Anthony Swerdlow  15 , Fergus Couch  16   17 , Julie M Cunningham  16 , Ellen L Goode  17 , Stacey J Winham  17 , Diether Lambrechts  18 , Peter Fasching  19   20 , Barbara Burwinkel  21   22 , Hermann Brenner  22   21 , Hiltrud Brauch  22   21 , Jenny Chang-Claude  21 , Helga B Salvesen  23 , Vessela Kristensen  24 , Hatef Darabi  25 , Jingmei Li  25 , Tao Liu  25 , Annika Lindblom  25 , Per Hall  26 , Magdalena Echeverry de Polanco  27 , Monica Sans  28 , Angel Carracedo  29 , Sergi Castellvi-Bel  30 , Augusto Rojas-Martinez  31 , Samuel Aguiar Jnr  32 , Manuel R Teixeira  33 , Alison M Dunning  12 , Joe Dennis  2 , Geoffrey Otton  34 , Tony Proietto  34 , Elizabeth Holliday  35 , John Attia  35 , Katie Ashton  35 , Rodney J Scott  35 , Mark McEvoy  36 , Sean C Dowdy  37 , Brooke L Fridley  38 , Henrica M J Werner  39 , Jone Trovik  39 , Tormund S Njolstad  39 , Emma Tham  25 , Miriam Mints  40 , Ingo Runnebaum  41 , Peter Hillemanns  42 , Thilo Dörk  43 , Frederic Amant  44 , Stefanie Schrauwen  18 , Alexander Hein  20 , Matthias W Beckmann  20 , Arif Ekici  45 , Kamila Czene  26 , Alfons Meindl  46 , Manjeet K Bolla  2 , Kyriaki Michailidou  2 , Jonathan P Tyrer  12 , Qin Wang  2 , Shahana Ahmed  12 , Catherine S Healey  12 , Mitul Shah  12 , Daniela Annibali  47 , Jeroen Depreeuw  47 , Nada A Al-Tassan  48 , Rebecca Harris  49 , Brian F Meyer  48 , Nicola Whiffin  50 , Fay J Hosking  50 , Ben Kinnersley  50 , Susan M Farrington  51 , Maria Timofeeva  51 , Albert Tenesa  52 , Harry Campbell  53 , Robert W Haile  54 , Shirley Hodgson  55 , Luis Carvajal-Carmona  56 , Jeremy P Cheadle  49 , Douglas Easton  2   12 , Malcolm Dunlop  51 , Richard Houlston  50 , Amanda Spurdle  3 , Ian Tomlinson  1   57
Affiliations
Meta-Analysis

Meta-analysis of genome-wide association studies identifies common susceptibility polymorphisms for colorectal and endometrial cancer near SH2B3 and TSHZ1

Timothy H T Cheng et al. Sci Rep. .

Abstract

High-risk mutations in several genes predispose to both colorectal cancer (CRC) and endometrial cancer (EC). We therefore hypothesised that some lower-risk genetic variants might also predispose to both CRC and EC. Using CRC and EC genome-wide association series, totalling 13,265 cancer cases and 40,245 controls, we found that the protective allele [G] at one previously-identified CRC polymorphism, rs2736100 near TERT, was associated with EC risk (odds ratio (OR) = 1.08, P = 0.000167); this polymorphism influences the risk of several other cancers. A further CRC polymorphism near TERC also showed evidence of association with EC (OR = 0.92; P = 0.03). Overall, however, there was no good evidence that the set of CRC polymorphisms was associated with EC risk, and neither of two previously-reported EC polymorphisms was associated with CRC risk. A combined analysis revealed one genome-wide significant polymorphism, rs3184504, on chromosome 12q24 (OR = 1.10, P = 7.23 × 10(-9)) with shared effects on CRC and EC risk. This polymorphism, a missense variant in the gene SH2B3, is also associated with haematological and autoimmune disorders, suggesting that it influences cancer risk through the immune response. Another polymorphism, rs12970291 near gene TSHZ1, was associated with both CRC and EC (OR = 1.26, P = 4.82 × 10(-8)), with the alleles showing opposite effects on the risks of the two cancers.

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Figures

Figure 1
Figure 1. Forest plot showing association between cancer risk and rs3184504 genotype in each data set.
Studies are shown in order of EC GWAS, EC iCOGS and CRC GWAS (Table 1). Black squares represent the point estimate of the odds ratio and have areas proportional to study size. Lines represent 95% confidence intervals. The diamond shows the summary statistic. The overall heterogeneity statistic is shown. There is also no evidence of heterogeneity between the pooled CRC and pooled EC studies (details not shown).
Figure 2
Figure 2. Regional association plot for region around rs3184504.
Plots are produced in LocusZoom and show the most strongly associated SNP, rs3184504 (purple diamond). rs7137828, intron of ATXN2, is the SNP with the second lowest P value. The primary aim of this analysis is to compare association signals among SNPs in the region. Therefore, the data are derived from a meta-analysis of genotyped or high-quality imputed SNPs in the GWAS data sets, and because imputation quality was more variable in iCOGS than in the GWAS data, the iCOGS samples are not included.
Figure 3
Figure 3. Forest plot showing association between cancer risk and rs12970291 genotype in each data set.
Legend is as for Fig. 1.
Figure 4
Figure 4. Regional association plot for region around rs12970291.
Legend is as for Fig. 2, except as follows. The most strongly associated SNP from the full discovery meta-analysis (rs12970291, purple diamond) is not the most strongly associated in the GWAS data sets. The most strongly associated SNP, rs35185115, lies about 30kb downstream of TSHZ1, but this SNP imputed poorly in iCOGS and was therefore assessed in fewer samples in the discovery meta-analysis than rs12970291, which was directly genotyped in iCOGS.
See this image and copyright information in PMC

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