Background Serrated polyposis syndrome (SPS) is a clinical entity characterised by large and/ormultiple serrated polyps throughout the colon and increased risk for colorectal cancer (CRC). The basis for SPS genetic predisposition is largely unknown. Common, low-penetrance genetic variants have been consistently associated with CRC susceptibility, however, their role in SPS genetic predisposition has not been yet explored.
Objective The aim of this study was to evaluate if common, low-penetrance genetic variants for CRC risk are also implicated in SPS genetic susceptibility.
Methods A case-control study was performed in 219 SPS patients and 548 asymptomatic controls analysing 65 CRC susceptibility variants. A risk prediction model for SPS predisposition was developed.
Results Statistically significant associations with SPS were found for seven genetic variants (rs4779584-GREM1, rs16892766-EIF3H, rs3217810-CCND2, rs992157-PNKD1/TMBIM1, rs704017-ZMIZ1, rs11196172-TCF7L2, rs6061231-LAMA5). The GREM1 risk allele was remarkably over-represented in SPS cases compared with controls (OR=1.573, 1.21–2.04, p value=0.0006). A fourfold increase in SPS risk was observed when comparing subjects within the highest decile of variants (≥65) with those in the first decile (≤50).
Conclusions Genetic variants for CRC risk are also involved in SPS susceptibility, being the most relevant ones rs4779584-GREM1, rs16892766-EIF3H and rs3217810-CCND2.
- serrated polyposis syndrome
- colorectal cancer
- genetic association study
- low-penetrance genetic variant
- genetic predisposition to disease
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Statistics from Altmetric.com
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.
- serrated polyposis syndrome
- colorectal cancer
- genetic association study
- low-penetrance genetic variant
- genetic predisposition to disease
Colorectal cancer (CRC) is currently one of the most common neoplasms in developed countries, and it represents the second most fatal malignancy after lung cancer.1 This neoplasm is developed from different precursor lesions, including conventional adenomas and serrated polyps. This heterogeneity drives the progression to carcinoma through distinct pathways.2 While most CRC progress through the adenoma–carcinoma sequence, serrated polyps, previously known as hyperplastic polyps, are also considered precursor lesions with an alternative pathway to CRC.3 The term serrated polyp refers to a lesion with a serrated or ‘sawtooth’ appearance of the colonic crypts at microscopy. On the other hand, the risk of developing CRC is influenced by both environmental and genetic factors. Part of this germline CRC predisposition is already known including both rare, high-penetrance and common, low-penetrance genetic variants.4 Genome-wide association studies (GWAS) have been conducted since 2007 and have identified ~130 common, low-penetrance genetic variants associated with CRC risk.5
Interestingly, prior studies have evaluated the association between GWAS-identified SNPs linked to CRC susceptibility and polyp subtypes, including adenomas, serrated polyps and advanced/non-advanced polyps but not the association with serrated polyposis syndrome (SPS).6–9
SPS is a condition characterised by the development of large and/or multiple serrated polyps throughout the colon and increased risk for CRC. The prevalence of CRC in patients with SPS has been estimated to range between 15% and 35%.3 10 In order to help in identifying this clinical entity, the WHO established in 2010 the following criteria defining SPS as the presence of (I) at least five serrated polyps proximal to the sigmoid colon, of which two measure at least 10 mm in diameter and/or (II) any number of serrated polyps occurring proximal to the sigmoid colon in an individual who has a first-degree relative with SPS and/or (III) more than 20 serrated polyps spread throughout the colon.11 Despite recent developments in sequencing technologies, the genetic aetiology of SPS remains largely unknown. The only proposed gene for germline SPS predisposition is RNF43, which would explain a small proportion of SPS cases.12–15
Keeping in mind that serrated polyps are considered CRC precursor lesions and considering that SPS confers a relatively high risk for CRC, the current study aims to test if common, low-penetrance genetic variants for CRC risk are also involved in the predisposition to SPS.
Materials and methods
Our study comprised 219 Spanish patients ascertained in high-risk clinics for CRC that fulfilled the SPS clinical criteria.11 They included 130 men (59.36%) and 89 women (40.63%) aged between 20–78 (mean age 54.62±11.08 years old). Presence of conventional adenomas in SPS patients was frequent (around 70%). We also included 548 asymptomatic controls from the Barcelona CRC screening programme with a positive faecal immunochemical test but a negative colonoscopy showing no relevant findings related to CRC risk. The control group included 269 men (49.08%) and 279 women (50.92%), aged between 50–69 (mean age 59.49±5.57 years old). Cases and controls included in this study were negative for a family history of hereditary or familial CRC or adenomatous polyposis (ie, ≥2 first-degree relatives with CRC/adenomatous polyposis or one first-degree relative diagnosed before the age of 60). DNA was obtained from frozen peripheral blood by standard extraction procedures for all samples. RNF43 mutations were excluded in the cases cohort. Mutations in other high-penetrance CRC genes such as MUTYH could not be ruled out although their contribution may be considered scarce since cases did not present a relevant family history for hereditary or familial CRC or adenomatous polyposis. Written informed consent was obtained from all individuals.
SNP genotyping and quality control
Sixty-five SNPs previously associated with CRC susceptibility were selected and genotyped in all available DNA samples. SNPs were selected from previous GWAS published before mid-2017 (www.ebi.ac.uk/gwas/, GWAS Catalogue). Genotyping was performed with the Biomark 96.96 Genotyping dynamic array (Fluidigm, San Francisco, CA, USA) and TaqMan assays (Thermo Fisher Scientific, Waltham, MA, USA). Data quality was assessed using the Fluidigm SNP Genotyping Analysis and PLINK softwares. Samples and SNPs with genotyping success rate below 90% were removed from subsequent analyses (including rs7229639, rs3764482). One SNP was monomorphic and was also eliminated (rs10904849). In order to further test for genotyping quality, five samples were duplicated and genotype concordance was 100%. Deviation of the genotype frequencies in the controls from those expected under Hardy-Weinberg equilibrium (HWE) was assessed by the χ2 test (1df). Each SNP was in HWE (p value >0.01) in controls (data not shown), thereby excluding the possibility of genotyping artefacts and any hidden population stratification. After quality filtering, the final available dataset comprised 741 samples (215 cases and 526 controls) and 62 SNPs. The overall genotyping success rate in the remaining individuals was 99.07%.
Logistic regression analysis was used to evaluate the association between each SNP and SPS risk under an additive model. The total number of risk alleles was calculated for all samples and coded as 0, 1 or 2 for each SNP assuming an additive genetic effect. Two-sided t-test was applied to compare the mean number of risk alleles between cases and controls. Furthermore, an additive genetic risk score (GRS) was developed by using a general linear model to assess for genetic susceptibility. GRS was defined as the count of risk alleles across all available SNPs. An unweighted GRS was preferred. A weighted genetic risk score was also tested, using the originally published log-ORs as weights. Since the results were essentially the same, and the weights may be biassed due to the winner’s course effect, we opted to use the unweighted score. All statistical tests were two-sided, and p values <0.05 were considered statistically significant. All analyses were performed using PLINK v1.09 (V.3.4.1). Bonferroni correction was used for multiple testing adjustment (α adjusted=0.05/62=8.06×10−4).
Association tests for individual SNPs
A total of 215 SPS patients and 526 controls were successfully genotyped for 62 SNPs previously linked with genetic susceptibility to CRC. First, the frequency of CRC risk alleles between SPS cases and controls was compared and those significantly enriched in the SPS cohort were detected. Results are shown in table 1. Seven CRC SNPs showed statistically significant associations with SPS (rs992157, rs16892766, rs704017, rs11196172, rs3217810, 4779584, rs6061231) and these genetic associations were in the same direction as previously reported for CRC susceptibility. Despite being not significant, most remaining SNPs (42/52), showed ORs in the same directions as those previously described in the literature for CRC susceptibility.
Genetic risk score model
The presence of higher number of CRC risk alleles in the SPS cohort when compared with controls was also evaluated. The distribution of risk by allele number for the 62 genotyped SNPs is displayed in figure 1, both for cases and controls. The distribution of risk alleles followed a normal distribution in both SPS cases and controls with a shift towards a higher number of risk alleles in affected individuals consistent with a cumulative impact of CRC risk alleles on SPS predisposition. The mean number of risk alleles in control individuals was 56.20 compared with 57.46 in SPS cases and there was a statistically significant difference in the mean number of risk alleles between SPS cases and controls (difference: −1.26; two-sided t-test p value=0.0016).
Next, a GRS was calculated for SPS cases and controls when carrying an increasing number of CRC risk alleles. The median number of risk alleles in controls, 56, was considered as reference. SPS cases and controls were grouped considering subjects carrying ≤45 risk alleles and ≥65 alleles, because of the small number of subjects at these extremes. The risk score was higher in the SPS group compared with the control cohort (OR=1.05, 95% CI 1.02 to 1.09, p value=0.0019). We observed that there was a twofold increase in SPS risk for subjects in the highest quintile of risk alleles (≥62) compared with those in the first quintile (≤53) (OR=2.16, 95% CI 1.29 to 3.63, p=0.0034). Additionally, a fourfold increase in SPS risk was detected for subjects in the highest decile of risk alleles (≥65), compared with those in the first decile (≤50) (OR=4.24, 95% CI 1.76 to 10.21, p value=0.0013). As shown in figure 1, the increase in risk per allele was linear, indicating the independent additive contribution of each allele to SPS risk.
The association of 65 common, low-penetrance CRC susceptibility variants in SPS development was assessed in a cohort of 768 samples (219 SPS cases and 548 controls) in order to check if common, low-penetrance genetic variants for CRC risk were also involved in SPS genetic susceptibility. Our results showed statistically significant association of seven CRC genetic variants with SPS (rs992157, rs16892766, rs704017, rs11196172, rs3217810, rs4779584 and rs6061231).
Among the detected SPS genetic associations, the most significant corresponded to rs4779584. The T risk allele frequency was remarkably higher in SPS cases (25%) than in controls (17%) (OR=1.573, 1.21 to 2.04, p value=0.0006). This association remained statistically significant even after multiple testing corrections. This SNP maps to chromosomal region 15q13.3, is intergenic and lies between SCG5 and GREM1. It was previously suggested that this variant captures two independent association signals represented by rs16969681 and rs11632715 upstream of GREM1.16 The rs16969681 variant lies upstream of GREM1 and is close to a regulatory element that acts as an allele-specific GREM1 enhancer. The rs16969681 risk allele differentially binds with a higher affinity the intestine-specific transcription factor CDX2 and the Wnt effector TCF7L2 producing a stronger GREM1 expression and promoting tumourigenesis.17 Noteworthy, a 40 kb duplication upstream of this gene was previously linked with increased GREM1 expression in individuals with hereditary mixed polyposis.18 This clinical entity shows some overlap with SPS since patients develop polyps of multiple and mixed morphologies including serrated lesions, Peutz-Jeghers polyps, juvenile polyps, conventional adenomas and CRC (OMIM # 601228). Moreover, this genetic variant had been linked with serrated polyps in previous studies.7 9
Additionally, our results show that rs16892766 at 8q23.3 is associated with SPS susceptibility. Previous fine mapping in this region and functional analysis identified rs16888589 as the potential effector of this association through increasing the expression of EIF3H, promoting carcinogenesis.19 Besides, we also detected an association with SPS for rs3217810 at 12p13.32 located in the intron of CCND2, a cyclin involved in cell cycle G1/S transition.20 Both SNPs had been previously linked with serrated polyps.9
Further novel associations with SPS were also detected in our cohort for rs992157 (2q35, PNKD/TMBIM1), rs704017 (10q22.3, ZMIZ1), rs11196172 (10q25.2, TCF7L2) and rs6061231 (20q13.33, LAMA5). Interestingly, rs11196172 was previously associated with a higher TCF7L2 expression.21 As previously commented, high levels of activated TCF7L2 increase GREM1 expression. Therefore, the rs11196172 risk allele may also have an impact on GREM1 expression. It is also important to highlight that the 20q13.33 region harbouring LAMA5 may be suggested as relevant for SPS susceptibility since two variants from that locus showed either a significant (rs6061231) or borderline significant association (rs4925386).
Regarding the results of our polygenic risk model, the distribution of CRC risk alleles follows a normal distribution in both SPS cases and controls, with a shift towards a higher allele number in SPS cases. These results show an enrichment of CRC susceptibility variants in the SPS cohort, therefore suggesting those variants may play a role in mediating CRC risk through serrated lesions and SPS predisposition. A similar study from our group identified CRC risk variants related to advanced adenoma, implying that part of CRC risk is mediated through susceptibility to this other polyp type.8
It should be noted that this study corresponds to the first analysis of common, low-penetrance CRC risk variants in a SPS cohort. However, we are aware that our results are preliminary and this study has several limitations including limited sample size, lack of environmental data or no replication in an independent SPS cohort. Therefore, further studies are needed to confirm our findings. On the other hand, specific GWAS for SPS susceptibility or serrated polyps are needed to further characterise more precisely the germline predisposition architecture of this clinical entity.
In summary, our study suggests that some CRC risk genetic variants could also be involved in SPS susceptibility. The rs4779584 variant, near GREM1, seems to be the most important effector of the common, low-penetrance SPS susceptibility identified so far. Likewise, rs16892766, and rs3217810 could be relevant since they have been identified linked to serrated lesions in previous studies. There are potential implications of our study in the near future. CRC SNPs predisposing to SPS and new SPS SNPs could be used to identify a subgroup of individuals with increased disease risk and modulate population-based CRC-prevention measures.
We are sincerely grateful to the patients, the Barcelona CRC screening program, the Functional Genomics and the Biobank core facilities of IDIBAPS Hospital Clínic, Biobanco Vasco para la Investigación/O+ehun-Hospital Donostia, the Genetics Unit at the Hospital Universitario de Móstoles and the Hereditary Cancer Program of the Catalan Institute of Oncology. The work was carried out (in part) at the Esther Koplowitz Centre, Barcelona.
Correction notice This article has been corrected since it was published Online First. The name of author Miriam Cuatrecasas has been corrected.
Contributors CA-C, VM and SC-B planned the study. CA-C, YSdL, MD-G, JM, SC, LB, LM, JJL, TO, MC and SC-B conducted the study. CA-C, YSdL, MD-G, JM, SC, LB, LM, JJL, TO, MC, ADdB, LB, JC, DR-A, FB, CR-P, LV, VM and SC-B collected data. CA-C, YSdL, AC, GC, VM and SC-B interpreted data. CA-C and SC-B drafted the manuscript. The final draft of the manuscript was approved by all authors.
Funding CA-C, JM and JJL were supported by a contract from CIBEREHD. YSdL was supported by a fellowship (LCF/BQ/DI18/11660058) from 'la Caixa' Foundation (ID 100010434) funded EU Horizon 2020 Programme (Marie Skłodowska-Curie grant agreement no. 713673). LB was supported by a Juan de la Cierva postdoctoral contract (FJCI-2017-32593) and MD-G by a contract from Agència de Gestió d’Ajuts Universitaris i de Recerca, AGAUR, (Generalitat de Catalunya, 2018FI_B1_00213). CIBEREHD, CIBERER, CIBERESP and CIBERONC are funded by the Instituto de Salud Carlos III. This research was supported by grants from Fondo de Investigación Sanitaria/FEDER (14/00613, 16/00766, 17/00509, 17/00878), Fundación Científica de la Asociación Española contra el Cáncer (GCB13131592CAST), Spanish Ministry of Science, Innovation and Universities, co-funded by FEDER funds, (SAF2016-80888-R), PERIS (SLT002/16/00398, SLT002/16/0037, Generalitat de Catalunya), CERCA Programme (Generalitat de Catalunya) and Agència de Gestió d'Ajuts Universitaris i de Recerca (Generalitat de Catalunya, GRPRE 2017SGR21, GRC 2017SGR653, 2017SGR1282, 2017SGR723). This article is based upon work from COST Action CA17118, supported by European Cooperation in Science and Technology (COST). www.cost.eu.
Competing interests None declared.
Patient consent for publication Not required.
Ethics approval This study was approved by the corresponding institutional ethics committees.
Provenance and peer review Not commissioned; externally peer reviewed.