Prediction of Colorectal Cancer Risk Using a Genetic Risk Score: The Korean Cancer Prevention Study-II (KCPS-II)

Validation of a Genetic-Enhanced Risk Prediction Model for Colorectal Cancer in a Large Community-Based Cohort

BACKGROUND

Polygenic risk scores (PRS) which summarize individuals' genetic risk profile may enhance targeted colorectal cancer screening. A critical step towards clinical implementation is rigorous external validations in large community-based cohorts. This study externally validated a PRS-enhanced colorectal cancer risk model comprising 140 known colorectal cancer loci to provide a comprehensive assessment on prediction performance.

METHODS

The model was developed using 20,338 individuals and externally validated in a community-based cohort (n = 85,221). We validated predicted 5-year absolute colorectal cancer risk, including calibration using expected-to-observed case ratios (E/O) and calibration plots, and discriminatory accuracy using time-dependent AUC. The PRS-related improvement in AUC, sensitivity and specificity were assessed in individuals of age 45 to 74 years (screening-eligible age group) and 40 to 49 years with no endoscopy history (younger-age group).

RESULTS

In European-ancestral individuals, the predicted 5-year risk calibrated well [E/O = 1.01; 95% confidence interval (CI), 0.91-1.13] and had high discriminatory accuracy (AUC = 0.73; 95% CI, 0.71-0.76). Adding the PRS to a model with age, sex, family and endoscopy history improved the 5-year AUC by 0.06 (P < 0.001) and 0.14 (P = 0.05) in the screening-eligible age and younger-age groups, respectively. Using a risk-threshold of 5-year SEER colorectal cancer incidence rate at age 50 years, adding the PRS had a similar sensitivity but improved the specificity by 11% (P < 0.001) in the screening-eligible age group. In the younger-age group it improved the sensitivity by 27% (P = 0.04) with similar specificity.

CONCLUSIONS

The proposed PRS-enhanced model provides a well-calibrated 5-year colorectal cancer risk prediction and improves discriminatory accuracy in the external cohort.

IMPACT

The proposed model has potential utility in risk-stratified colorectal cancer prevention.

Variation of Positive Predictive Values of Fecal Immunochemical Tests by Polygenic Risk Score in a Large Screening Cohort

INTRODUCTION

Prevalence of colorectal neoplasms varies by polygenic risk scores (PRS). We aimed to assess to what extent a PRS might be relevant for defining personalized cutoff values for fecal immunochemical tests (FITs) in colorectal cancer screening.

METHODS

Among 5,306 participants of screening colonoscopy who provided a stool sample for a quantitative FIT (Ridascreen Hemoglobin or FOB Gold) before colonoscopy, a PRS was determined, based on the number of risk alleles in 140 single nucleotide polymorphisms. Subjects were classified into low, medium, and high genetic risk of colorectal neoplasms according to PRS tertiles. We calculated positive predictive values (PPVs) and numbers needed to scope (NNS) to detect 1 advanced neoplasm (AN) by the risk group, and cutoff variation needed to achieve comparable PPVs across risk groups in the samples tested with Ridascreen (N = 1,271) and FOB Gold (N = 4,035) independently, using cutoffs yielding 85%, 90%, or 95% specificity.

RESULTS

Performance of both FITs was very similar within each PRS group. For a given cutoff, PPVs were consistently higher by 11%-15% units in the high-risk PRS group compared with the low-risk group (all P values < 0.05). Correspondingly, NNS to detect 1 advanced neoplasm varied from 2 (high PRS, high cutoff) to 5 (low PRS, low cutoff). Conversely, very different FIT cutoffs would be needed to ensure comparable PPVs across PRS groups.

DISCUSSION

PPVs and NNS of FITs varied widely across people with high and low genetic risk score. Further research should evaluate the relevance of these differences for personalized colorectal cancer screening.

Polygenic risk prediction models for colorectal cancer: a systematic review

BACKGROUND

Risk prediction models incorporating single nucleotide polymorphisms (SNPs) could lead to individualized prevention of colorectal cancer (CRC). However, the added value of incorporating SNPs into models with only traditional risk factors is still not clear. Hence, our primary aim was to summarize literature on risk prediction models including genetic variants for CRC, while our secondary aim was to evaluate the improvement of discriminatory accuracy when adding SNPs to a prediction model with only traditional risk factors.

METHODS

We conducted a systematic review on prediction models incorporating multiple SNPs for CRC risk prediction. We tested whether a significant trend in the increase of Area Under Curve (AUC) according to the number of SNPs could be observed, and estimated the correlation between AUC improvement and number of SNPs. We estimated pooled AUC improvement for SNP-enhanced models compared with non-SNP-enhanced models using random effects meta-analysis, and conducted meta-regression to investigate the association of specific factors with AUC improvement.

RESULTS

We included 33 studies, 78.79% using genetic risk scores to combine genetic data. We found no significant trend in AUC improvement according to the number of SNPs (p for trend = 0.774), and no correlation between the number of SNPs and AUC improvement (p = 0.695). Pooled AUC improvement was 0.040 (95% CI: 0.035, 0.045), and the number of cases in the study and the AUC of the starting model were inversely associated with AUC improvement obtained when adding SNPs to a prediction model. In addition, models constructed in Asian individuals achieved better AUC improvement with the incorporation of SNPs compared with those developed among individuals of European ancestry.

CONCLUSIONS

Though not conclusive, our results provide insights on factors influencing discriminatory accuracy of SNP-enhanced models. Genetic variants might be useful to inform stratified CRC screening in the future, but further research is needed.

Polygenic risk score across distinct colorectal cancer screening outcomes: from premalignant polyps to colorectal cancer

BACKGROUND

Different risk-based colorectal cancer (CRC) screening strategies, such as the use of polygenic risk scores (PRS), have been evaluated to improve effectiveness of these programs. However, few studies have previously assessed its usefulness in a fecal immunochemical test (FIT)-based screening study.

METHODS

A PRS of 133 single nucleotide polymorphisms was assessed for 3619 participants: population controls, screening controls, low-risk lesions (LRL), intermediate-risk (IRL), high-risk (HRL), CRC screening program cases, and clinically diagnosed CRC cases. The PRS was compared between the subset of cases (n = 648; IRL+HRL+CRC) and controls (n = 956; controls+LRL) recruited within a FIT-based screening program. Positive predictive values (PPV), negative predictive values (NPV), and the area under the receiver operating characteristic curve (aROC) were estimated using cross-validation.

RESULTS

The overall PRS range was 110-156. PRS values increased along the CRC tumorigenesis pathway (Mann-Kendall P value 0.007). Within the screening subset, the PRS ranged 110-151 and was associated with higher risk-lesions and CRC risk (OR_D10vsD1 1.92, 95% CI 1.22-3.03). The cross-validated aROC of the PRS for cases and controls was 0.56 (95% CI 0.53-0.59). Discrimination was equal when restricted to positive FIT (aROC 0.56), but lower among negative FIT (aROC 0.55). The overall PPV among positive FIT was 0.48. PPV were dependent on the number of risk alleles for positive FIT (PPVp10-p90 0.48-0.57).

CONCLUSIONS

PRS plays an important role along the CRC tumorigenesis pathway; however, in practice, its utility to stratify the general population or as a second test after a FIT positive result is still doubtful. Currently, PRS is not able to safely stratify the general population since the improvement on PPV values is scarce.

Prediction of colorectal cancer risk based on profiling with common genetic variants

Increasing numbers of common genetic variants associated with colorectal cancer (CRC) have been identified. Our study aimed to determine whether risk prediction based on common genetic variants might enable stratification for CRC risk. Meta-analysis of 11 genome-wide association studies comprising 16 871 cases and 26 328 controls was performed to capture CRC susceptibility variants. Genetic prediction models with several candidate polygenic risk scores (PRSs) were generated from Scottish CRC case-control studies (6478 cases and 11 043 controls) and the score with the best performance was then tested in UK Biobank (UKBB) (4800 cases and 20 287 controls). A weighted PRS of 116 CRC single nucleotide polymorphisms (wPRS116 ) was found with the best predictive performance, reporting a c-statistics of 0.60 and an odds ratio (OR) of 1.46 (95% confidence interval [CI] = 1.41-1.50, per SD increase) in Scottish data set. The predictive performance of this wPRS116 was consistently validated in UKBB data set with c-statistics of 0.61 and an OR of 1.49 (95% CI = 1.44-1.54, per SD increase). Modeling the levels of PRS with age and sex in the general UK population shows that employing genetic risk profiling can achieve a moderate degree of risk discrimination that could be helpful to identify a subpopulation with higher CRC risk due to genetic susceptibility.

The emerging field of polygenic risk scores and perspective for use in clinical care

Genetic testing is used widely for diagnostic, carrier and predictive testing in monogenic diseases. Until recently, there were no genetic testing options available for multifactorial complex diseases like heart disease, diabetes and cancer. Genome-wide association studies (GWAS) have been invaluable in identifying single-nucleotide polymorphisms (SNPs) associated with increased or decreased risk for hundreds of complex disorders. For a given disease, SNPs can be combined to generate a cumulative estimation of risk known as a polygenic risk score (PRS). After years of research, PRSs are increasingly used in clinical settings. In this article, we will review the literature on how both genome-wide and restricted PRSs are developed and the relative merit of each. The validation and evaluation of PRSs will also be discussed, including the recognition that PRS validity is intrinsically linked to the methodological and analytical approach of the foundation GWAS together with the ethnic characteristics of that cohort. Specifically, population differences may affect imputation accuracy, risk magnitude and direction. Even as PRSs are being introduced into clinical practice, there is a push to combine them with clinical and demographic risk factors to develop a holistic disease risk. The existing evidence regarding the clinical utility of PRSs is considered across four different domains: informing population screening programs, guiding therapeutic interventions, refining risk for families at high risk, and facilitating diagnosis and predicting prognostic outcomes. The evidence for clinical utility in relation to five well-studied disorders is summarized. The potential ethical, legal and social implications are also highlighted.

Single-nucleotide polymorphisms based genetic risk score in the prediction of pancreatic cancer risk

BACKGROUND

Disease-related single nucleotide polymorphisms (SNPs) based genetic risk score (GRS) has been proven to provide independent inherited risk other than family history in multiple cancer types.

AIM

To evaluate the potential of GRS in the prediction of pancreatic cancer risk.

METHODS

In this case-control study (254 cases and 1200 controls), we aimed to evaluate the association between GRS and pancreatic ductal adenocarcinoma (PDAC) risk in the Chinese population. The GRS was calculated based on the genotype information of 18 PDAC-related SNPs for each study subject (personal genotyping information of the SNPs) and was weighted by external odd ratios (ORs).

RESULTS

GRS was significantly different in cases and controls (1.96 ± 3.84 in PDACs vs 1.09 ± 0.94 in controls, P < 0.0001). Logistic regression revealed GRS to be associated with PDAC risk [OR = 1.23, 95% confidence interval (CI): 1.13-1.34, P < 0.0001]. GRS remained significantly associated with PDAC (OR = 1.36, 95%CI: 1.06-1.74, P = 0.015) after adjusting for age and sex. Further analysis revealed an association of increased risk for PDAC with higher GRS. Compared with low GRS (< 1.0), subjects with high GRS (2.0) were 99% more likely to have PDAC (OR: 1.99, 95%CI: 1.30-3.04, P = 0.002). Participants with intermediate GRS (1.0-1.9) were 39% more likely to have PDAC (OR: 1.39, 95%CI: 1.03-1.84, P = 0.031). A positive trend was observed (P trend = 0.0006).

CONCLUSION

GRS based on PDAC-associated SNPs could provide independent information on PDAC risk and may be used to predict a high risk PDAC population.

External Validation of Risk Prediction Models Incorporating Common Genetic Variants for Incident Colorectal Cancer Using UK Biobank

The aim of this study was to compare and externally validate risk scores developed to predict incident colorectal cancer that include common genetic variants (SNPs), with or without established lifestyle/environmental (questionnaire-based/classical/phenotypic) risk factors. We externally validated 23 risk models from a previous systematic review in 443,888 participants ages 37 to 73 from the UK Biobank cohort who had 6-year prospective follow-up, no prior history of colorectal cancer, and data for incidence of colorectal cancer through linkage to national cancer registries. There were 2,679 (0.6%) cases of incident colorectal cancer. We assessed model discrimination using the area under the operating characteristic curve (AUC) and relative risk calibration. The AUC of models including only SNPs increased with the number of included SNPs and was similar in men and women: the model by Huyghe with 120 SNPs had the highest AUC of 0.62 [95% confidence interval (CI), 0.59-0.64] in women and 0.64 (95% CI, 0.61-0.66) in men. Adding phenotypic risk factors without age improved discrimination in men but not in women. Adding phenotypic risk factors and age increased discrimination in all cases (P < 0.05), with the best performing models including SNPs, phenotypic risk factors, and age having AUCs between 0.64 and 0.67 in women and 0.67 and 0.71 in men. Relative risk calibration varied substantially across the models. Among middle-aged people in the UK, existing polygenic risk scores discriminate moderately well between those who do and do not develop colorectal cancer over 6 years. Consideration should be given to exploring the feasibility of incorporating genetic and lifestyle/environmental information in any future stratified colorectal cancer screening program.

The U-shaped association between body mass index and gastric cancer risk in the Helicobacter pylori Biomarker Cohort Consortium: A nested case-control study from eight East Asian cohort studies

The association between body mass index (BMI) and noncardia gastric cancer (NCGC) risk remains controversial. The purpose of our study was to examine the association of BMI with NCGC risk with consideration of Helicobacter pylori (HP) biomarkers. This international nested case-control study, composed of 1,591 incident NCGC cases and 1,953 matched controls, was established from eight cohorts in China, Japan and Korea, where the majority of NCGCs are diagnosed worldwide. HP antibody biomarkers were measured in blood collected at cohort enrollment by multiplex serology. The NCGC risk according to baseline BMI was estimated using logistic regression to produce odds ratios (ORs) and 95% confidence intervals (CIs). We found a U-shaped association between BMI category and NCGC risk. Compared to those with reference BMI (22.6-25.0 kg/m² ), those with lower and higher BMI had an increased NCGC risk (BMI <18.5 kg/m² , OR = 1.56, 95% CI = 1.04-2.34; BMI >27.5 kg/m² , OR = 1.48, 95% CI = 1.15-1.91; adjusted for age, sex and smoking). The U-shaped association was persistent among subjects with HP infection and high-risk biomarkers (HP+ CagA+: BMI <18.5 kg/m² , OR = 1.60, 95% CI = 1.00-2.55; BMI >27.5 kg/m² , OR = 1.59, 95% CI = 1.21-2.11; and Omp+ HP0305+: BMI <18.5 kg/m² , OR = 1.88, 95% CI = 1.04-3.42; BMI >27.5 kg/m² , OR = 1.70, 95% CI = 1.20-2.42, respectively). Our study provides evidence of significantly increased NCGC risk among individuals with low or high BMI, including in subjects with high-risk HP biomarkers (HP+ CagA+, Omp+ HP0305+) in the high-risk area of East Asia.

Risk Prediction Models for Colorectal Cancer Incorporating Common Genetic Variants: A Systematic Review

Colorectal cancer screening reduces colorectal cancer incidence and mortality. Risk models based on phenotypic variables have relatively good discrimination in external validation and may improve efficiency of screening. Models incorporating genetic variables may perform better. In this review, we updated our previous review by searching Medline and EMBASE from the end date of that review (January 2014) to February 2019 to identify models incorporating at least one SNP and applicable to asymptomatic individuals in the general population. We identified 23 new models, giving a total of 29. Of those in which the SNP selection was on the basis of published genome-wide association studies, in external or split-sample validation the AUROC was 0.56 to 0.57 for models that included SNPs alone, 0.61 to 0.63 for SNPs in combination with other risk factors, and 0.56 to 0.70 when age was included. Calibration was only reported for four. The addition of SNPs to other risk factors increases discrimination by 0.01 to 0.06. Public health modeling studies suggest that, if determined by risk models, the range of starting ages for screening would be several years greater than using family history alone. Further validation and calibration studies are needed alongside modeling studies to assess the population-level impact of introducing genetic risk-based screening programs.

Quantitative risk of positive family history in developing colorectal cancer: A meta-analysis

BACKGROUND

Positive family history is a risk factor for development of colorectal cancer. Despite numerous studies on the topic, the absolute risk in patients with a positive family history remains unclear and therefore studies are lacking to validate non-invasive screening methods in individuals with positive family history.

AIM

To quantify the risk of colorectal cancer in individuals with a positive family history.

METHODS

A comprehensive electronic literature search was performed using PubMed from January 1955 until November 2017, EMBASE from 1947 until 2018, and Cochrane Library without date restrictions. Two independent reviewers conducted study selection, data extraction and quality assessment. A meta-analysis of Mantel-Haenzel relative risks was performed using the random effects model. Newcastle-Ottawa scale was used to score the quality of selected papers. Funnel plot and Egger’s regression test was performed to detect publication bias. Subgroup analysis was performed comparing Asian and non-Asian studies. Sensitivity analyses were performed to rule out the effect of the timing of the study, overall quality, the main outcome and the effect of each individual study in overall result.

RESULTS

Forty-six out of 3390 studies, including 906981 patients were included in the final analysis. 41 of the included studies were case-control and 5 were cohort. A positive family history of colorectal cancer in first-degree relatives was associated with significantly increased risk of colorectal cancer with a relative risk of 1.87 (95%CI: 1.68-2.09; P < 0.00001). Cochrane Q test was significant (P < 0.00001, I² = 90%). Egger’s regression test showed asymmetry in the funnel plot and therefore the Trim and Fill method was used which confirmed the validity of the results. There was no difference between Asian versus non-Asian studies. Results remained robust in sensitivity analyses.

CONCLUSION

Individuals with a positive family history of colorectal cancer are 1.87 times more likely to develop colorectal cancer. Screening guidelines should pay specific attention to individuals with positive family history and further studies need to be done on validating current screening methods or developing new modalities in this high-risk population.

A Propensity Score-adjusted Analysis of the Effects of Ubiquitin E3 Ligase Copy Number Variation in Peripheral Blood Leukocytes on Colorectal Cancer Risk

Background: The ubiquitin ligases E3 (E3s) plays a key role in the specific protein degradation in many carcinogenic biological processes. Colorectal cancer (CRC) development may be affected by the copy number variation (CNV) of E3s. Prior studies may have underestimated the impact of potential confounding factors' effects on the association between gene CNV and CRC risk, and CRC risk predictive model integrating gene CNV patterns is lacking. Our research sought to assess the genes CNVs of MDM2, SKP2, FBXW7, β-TRCP, and NEDD4-1 and CRC risk by using propensity score (PS) adjustment and developing models that integrate CNV patterns for CRC risk predictions.

Methods: This study comprising 1036 participants used traditional regression and different PS techniques to adjust the confounding factors to evaluate the relationships between five gene CNVs and CRC risk, and to establish a CRC risk predictive model. The AUC was applied to evaluate the effect of the model. The categorical net reclassification improvement (NRI) and the integrated discrimination improvement (IDI) were analyzed to evaluate the discriminatory accuracy improvement among the models.

Results: Compared to variable adjustment, the odds ratios (ORs) tended to be conservative and accurate with narrow confidence intervals (CIs) after PS adjustment. After PS adjustment, MDM2 amplification was related to increased CRC risk (Amp-pattern: OR = 8.684, 95% CI: 1.213-62.155, P = 0.031), whereas SKP2 deletion and the (del+amp) genotype were associated with reduced CRC risk (Del-pattern: OR = 0.323, 95% CI: 0.106-0.979, P = 0.046; Var-pattern: OR = 0.339, 95% CI: 0.135-0.854, P = 0.024). The predictive model integrating the gene CNV pattern could correctly reclassify 1.7% of the subjects.

Conclusions: MDM2 amplification and SKP2 CNVs are associated with increased and decreased CRC risk, respectively; abnormal CNV-integrated model is more precise for predicting CRC risk. Further studies are needed to verify these encouraging outcomes.

A five-gene based risk score with high prognostic value in colorectal cancer

Colorectal cancer (CRC) is one of the most frequently occurring malignancies worldwide. The outcomes of patients with similar clinical symptoms or at similar pathological stages remain unpredictable. This inherent clinical diversity is most likely due to the genetic heterogeneity. The present study aimed to create a predicting tool to evaluate patient survival based on genetic profile. Firstly, three Gene Expression Omnibus (GEO) datasets (GSE9348, GSE44076 and GSE44861) were utilized to identify and validate differentially expressed genes (DEGs) in CRC. The GSE14333 dataset containing survival information was then introduced in order to screen and verify prognosis-associated genes. Of the 66 DEGs, the present study screened out 46 biomarkers closely associated to patient overall survival. By Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, it was demonstrated that these genes participated in multiple biological processes which were highly associated with cancer proliferation, drug-resistance and metastasis, thus further affecting patient survival. The five most important genes, MET proto-oncogene, receptor tyrosine kinase, carboxypeptidase M, serine hydroxymethyltransferase 2, guanylate cyclase activator 2B and sodium voltage-gated channel a subunit 9 were selected by a random survival forests algorithm, and were further made up to a linear risk score formula by multivariable cox regression. Finally, the present study tested and verified this risk score within three independent GEO datasets (GSE14333, GSE17536 and GSE29621), and observed that patients with a high risk score had a lower overall survival (P<0.05). Furthermore, this risk score was the most significant compared with other predicting factors including age and American Joint Committee on Cancer stage, in the model, and was able to predict patient survival independently and directly. The findings suggest that this survival associated DEGs-based risk score is a powerful and accurate prognostic tool and is promisingly implemented in a clinical setting.

Evaluation of genetic variants in association with colorectal cancer risk and survival in Asians

Genome-wide association studies (GWAS) have identified over 40 genetic loci associated with colorectal cancer (CRC) risk. The association of single nucleotide polymorphisms (SNPs) at these loci with CRC risk and survival has not been adequately evaluated in East Asians. GWAS-identified CRC risk variants were used to construct weighted genetic risk scores (GRSs). We evaluated these GRSs in association with CRC risk in 3,303 CRC cases and 3,553 controls using logistic regression models. Associations with overall and CRC-specific survival were assessed in 731 CRC patients using Cox regression models. The association between the GRSs (overall and Asian-specific) and CRC risk was approximately twofold (highest vs. lowest quintile), and the shape of the dose-response was linear (ptrend  = 1.24 × 10-13 and 3.02 × 10-14 for overall GRS and Asian-specific GRS, respectively). The association of the GRS with CRC risk was stronger among those with a family history of CRC (pinteraction  = 0.007). Asian-specific GRS using previously reported survival SNPs increased risk for mortality and the shape of the dose-response was linear for CRC-specific and all-cause mortality (ptrend  = 0.01 and 0.006, respectively). Furthermore, the minor alleles of rs6983267 and rs1957636 were associated with worse CRC-specific and overall survival. We show that GRSs constructed using GWAS-identified common variants are strongly associated with CRC risk in Asians. We confirm previous findings for the possible association between some SNPs with survival, and provide evidence for two additional CRC risk variants that may be related to CRC survival.

Risk Model for Colorectal Cancer in Spanish Population Using Environmental and Genetic Factors: Results from the MCC-Spain study

Colorectal cancer (CRC) screening of the average risk population is only indicated according to age. We aim to elaborate a model to stratify the risk of CRC by incorporating environmental data and single nucleotide polymorphisms (SNP). The MCC-Spain case-control study included 1336 CRC cases and 2744 controls. Subjects were interviewed on lifestyle factors, family and medical history. Twenty-one CRC susceptibility SNPs were genotyped. The environmental risk model, which included alcohol consumption, obesity, physical activity, red meat and vegetable consumption, and nonsteroidal anti-inflammatory drug use, contributed to CRC with an average per factor OR of 1.36 (95% CI 1.27 to 1.45). Family history of CRC contributed an OR of 2.25 (95% CI 1.87 to 2.72), and each additional SNP contributed an OR of 1.07 (95% CI 1.04 to 1.10). The risk of subjects with more than 25 risk alleles (5^th quintile) was 82% higher (OR 1.82, 95% CI 1.11 to 2.98) than subjects with less than 19 alleles (1^st quintile). This risk model, with an AUROC curve of 0.63 (95% CI 0.60 to 0.66), could be useful to stratify individuals. Environmental factors had more weight than the genetic score, which should be considered to encourage patients to achieve a healthier lifestyle.

Association between serum concentrations of persistent organic pollutants and smoking in Koreans: A cross-sectional study

Background

Studies on the associations between persistent organic pollutants (POPs) and smoking according to gender and smoking amount (cigarettes/day) are limited, and the results regarding the relationship between POPs and smoking are not completely consistent across studies.

Objectives

The smoking rate in Korea is one of the highest among the Organization for Economic Cooperation and Development (OECD) countries. We investigated the association between serum concentrations of POPs and cigarette smoking in Koreans by smoking status (never-smoker/ever-smoker) and smoking amount (cigarettes/day) according to gender.

Methods

Serum concentrations of 32 polychlorinated biphenyls (PCBs) and 19 organochlorine pesticides (OCPs) were measured in 401 participants (232 men and 169 women) who received health examinations during the Korean Cancer Prevention Study-II. We compared POP levels in ever-smokers and never-smokers and conducted multivariate logistic regression analyses to identify associations between POPs and smoking.

Results

Among women, the concentrations of PCB 156, PCB 167, and PCB 180 were significantly higher in ever-smokers than in never-smokers. After adjustments for age, body mass index, gamma-glutamyl transpeptidase, and alcohol intake, serum PCB 157 concentration was positively associated with male ever-smokers (OR 2.26; 95% CI, 1.01–5.04). In addition, trans-nonachlordane in OCPs as well as PCBs was significantly positively related with female ever-smokers (OR 3.21; 95% CI, 1.04–9.86). We found that subjects who smoked fewer than 15 cigarettes/day had a higher risk of having high POP concentrations than never-smokers.

Conclusions

These results indicate that smoking may be associated with human serum POPs levels.

Genetic variation rs7930 in the miR-4273-5p target site is associated with a risk of colorectal cancer

PURPOSE

MicroRNAs (miRNAs) are noncoding RNAs that play roles as tumor suppressors or oncogenes by regulating the expression of target genes via binding to seed-match sequences. Polymorphisms in the miRNA-binding site of a target gene can alter miRNA binding and potentially affect the risk of cancer. The objective of this study was to identify single-nucleotide polymorphisms (SNPs) in miRNA-binding sites and assess their involvement in the risk of colorectal cancer (CRC).

MATERIALS AND METHODS

SNPs in the 3' untranslated regions of genes were selected and assessed for their effects on CRC risk in Korean population using participants in Korean Cancer Prevention Study-II. A detailed study was carried out with the SNP rs7930 in the 3' untranslated region of the translocase of outer mitochondrial membrane 20 (TOMM20) gene. A case-control study (1,545 controls and 620 CRC cases) was conducted to analyze the relationship between polymorphism at rs7930 and the risk of CRC. An interacting miRNA was predicted using web-based software programs, and its interaction with rs7930 in CRC cell lines was investigated by using a luciferase assay.

RESULTS

Individuals carrying the rs7930 AG genotype (G allele) had a 1.721-fold increased risk for CRC in comparison with those with the AA genotype (A allele). The miRNA miR-4273-5p was found to specifically interact with the A allele of rs7930 and to suppress the expression of the target gene (TOMM20) in CRC cell lines.

CONCLUSION

rs7930 is an independent genetic risk factor for CRC susceptibility. Our study suggests a mechanism of how this SNP contributes to CRC carcinogenesis.

Fruit and vegetable consumption, Helicobacter pylori antibodies, and gastric cancer risk: A pooled analysis of prospective studies in China, Japan, and Korea

Epidemiological findings on the association between fruit and vegetable consumption and gastric cancer risk remain inconsistent. The present analysis included 810 prospectively ascertained non-cardia gastric cancer cases and 1,160 matched controls from the Helicobacter pylori Biomarker Cohort Consortium, which collected blood samples, demographic, lifestyle, and dietary data at baseline. Conditional logistic regression adjusting for total energy intake, smoking, and H. pylori status, was applied to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for gastric cancer risk across cohort- and sex-specific quartiles of fruit and vegetable intake. Increasing fruit intake was associated with decreasing risk of non-cardia gastric cancer (OR = 0.71, 95% CI: 0.52-0.95, p trend = 0.02). Compared to low-fruit consumers infected with CagA-positive H. pylori, high-fruit consumers without evidence of H. pylori antibodies had the lowest odds for gastric cancer incidence (OR = 0.12, 95% CI: 0.06-0.25), whereby the inverse association with high-fruit consumption was attenuated among individuals infected with CagA-positive H. pylori (OR = 0.82, 95% CI: 0.66-1.03). To note, the small number of H. pylori negative individuals does influence this finding. We observed a weaker, nondose-response suggestion of an inverse association of vegetable intake with non-cardia gastric cancer risk. High fruit intake may play a role in decreasing risk of non-cardia gastric cancer in Asia.

Helicobacter pylori blood biomarker for gastric cancer risk in East Asia

BACKGROUND

Incidence and mortality rates for gastric cancer, the fifth most commonly diagnosed and third most deadly cancer worldwide, are highest in East Asia. We sought to identify gastric cancer risk biomarkers among eight prospective studies from China, Japan and Korea.

METHODS

This pooled nested case-control study included 1608 incident non-cardia gastric cancer cases and 1958 matched controls. Pre-diagnostic antibody levels to 15 Helicobacter pylori proteins were assessed using multiplex serology. Conditional logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

Sero-positivity to 10 H. pylori antigens (Omp, CagA, VacA, HcpC, HP 0305, GroEL, NapA, HyuA, Cad, HpaA) was associated with a 1.29- to 3.26-fold increase in odds of gastric cancer. Omp and HP 0305 consistently remained associated with gastric cancer risk after mutually adjusting for all other markers. Sero-positivity to both Omp and HP 0305 was associated with an over 4-fold increase in gastric cancer incidence (OR, 4.09; 95% CI 3.26-5.13). When limited to only those who are CagA+ H. pylori+, Omp/HP 0305 sero-positivity remained strongly associated with an over 3-fold increase in the odds of gastric cancer (OR, 3.34; 95% CI 2.27-4.91). The results were highly consistent among the cohorts.

CONCLUSIONS

We have confirmed new H. pylori biomarkers that are strongly associated with gastric cancer risk, even among those infected with the known H. pylori virulence factor CagA. These results may help to design cost-efficient prevention strategies to reduce gastric cancer incidence in East Asia.

A comparison of genomic profiles of complex diseases under different models

Background

Various approaches are being used to predict individual risk to polygenic diseases from data provided by genome-wide association studies. As there are substantial differences between the diseases investigated, the data sets used and the way they are tested, it is difficult to assess which models are more suitable for this task.

Results

We compared different approaches for seven complex diseases provided by the Wellcome Trust Case Control Consortium (WTCCC) under a within-study validation approach. Risk models were inferred using a variety of learning machines and assumptions about the underlying genetic model, including a haplotype-based approach with different haplotype lengths and different thresholds in association levels to choose loci as part of the predictive model. In accordance with previous work, our results generally showed low accuracy considering disease heritability and population prevalence. However, the boosting algorithm returned a predictive area under the ROC curve (AUC) of 0.8805 for Type 1 diabetes (T1D) and 0.8087 for rheumatoid arthritis, both clearly over the AUC obtained by other approaches and over 0.75, which is the minimum required for a disease to be successfully tested on a sample at risk, which means that boosting is a promising approach. Its good performance seems to be related to its robustness to redundant data, as in the case of genome-wide data sets due to linkage disequilibrium.

Conclusions

In view of our results, the boosting approach may be suitable for modeling individual predisposition to Type 1 diabetes and rheumatoid arthritis based on genome-wide data and should be considered for more in-depth research.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-015-0157-2) contains supplementary material, which is available to authorized users.

Targeted screening for colorectal cancer in high-risk individuals

The idea of targeted screening for colorectal cancer based on risk profiles originates from its benefits to improve detection yield and optimize screening efficiency. Clinically, it allows individuals to be more aware of their own risk and make informed decisions on screening choice. From a public health perspective, the implementation of risk stratification strategies may better justify utilization of colonoscopic resources, and facilitate resource-planning in the formulation of population-based screening programmes. There are several at-risk groups who should receive earlier screening, and colonoscopy is more preferred. This review summarizes the currently recommended CRC screening strategies among subjects with different risk factors, and introduces existing risk scoring systems. Additional genetic, epidemiological, and clinical parameters may be needed to enhance their performance to risk-stratify screening participants. Future research studies should refine these scoring systems, and explore the adaptability, feasibility, acceptability, and user-friendliness of their use in clinical practice among different population groups.

Risk Prediction Models for Colorectal Cancer: A Systematic Review

Colorectal cancer is the second leading cause of cancer-related death in Europe and the United States. Survival is strongly related to stage at diagnosis and population-based screening reduces colorectal cancer incidence and mortality. Stratifying the population by risk offers the potential to improve the efficiency of screening. In this systematic review we searched Medline, EMBASE, and the Cochrane Library for primary research studies reporting or validating models to predict future risk of primary colorectal cancer for asymptomatic individuals. A total of 12,808 papers were identified from the literature search and nine through citation searching. Fifty-two risk models were included. Where reported (n = 37), half the models had acceptable-to-good discrimination (the area under the receiver operating characteristic curve, AUROC >0.7) in the derivation sample. Calibration was less commonly assessed (n = 21), but overall acceptable. In external validation studies, 10 models showed acceptable discrimination (AUROC 0.71-0.78). These include two with only three variables (age, gender, and BMI; age, gender, and family history of colorectal cancer). A small number of prediction models developed from case-control studies of genetic biomarkers also show some promise but require further external validation using population-based samples. Further research should focus on the feasibility and impact of incorporating such models into stratified screening programmes.

Gene-gene interaction analysis identifies a new genetic risk factor for colorectal cancer

BACKGROUND

Adiponectin levels have been shown to be associated with colorectal cancer (CRC). Furthermore, a newly identified adiponectin receptor, T-cadherin, has been associated with plasma adiponectin levels. Therefore, we investigated the potential for a genetic association between T-cadherin and CRC risk.

RESULT

We conducted a case-control study using the Korean Cancer Prevention study-II cohort, which is composed of 325 CRC patients and 977 normal individuals. Study results revealed that rs3865188 in the 5' flanking region of the T-cadherin gene (CDH13) was significantly associated with CRC (p = 0.0474). The odds ratio (OR) for the TT genotype as compared to the TA + AA genotype was 1.577 (p = 0.0144). In addition, the interaction between CDH13 and the adiponectin gene (APN) for CRC risk was investigated using a logistic regression analysis. Among six APN single nucleotide polymorphisms (rs182052, rs17366568, rs2241767, rs3821799, rs3774261, and rs6773957), an interaction with the rs3865188 was found for four (rs2241767, rs3821799, rs3774261, and rs6773957). The group with combined genotypes of TT for rs3865188 and GG for rs377426 displayed the highest risk for CRC development as compared to those with the other genotype combinations. The OR for the TT/GG genotype as compared to the AA/AA genotype was 4.108 (p = 0.004). Furthermore, the plasma adiponectin level showed a correlation with the gene-gene interaction, and the group with the highest risk for CRC had the lowest adiponectin level (median, 4.8 μg/mL for the TT/GG genotype vs.7.835 μg/mL for the AA/AA genotype, p = 0.0017).

CONCLUSIONS

The present study identified a new genetic factor for CRC risk and an interaction between CDH13 and APN in CRC risk. These genetic factors may be useful for predicting CRC risk.

A model to determine colorectal cancer risk using common genetic susceptibility loci

BACKGROUND & AIMS

Risk for colorectal cancer (CRC) can be greatly reduced through screening. To aid in the development of screening strategies, we refined models designed to determine risk of CRC by incorporating information from common genetic susceptibility loci.

METHODS

By using data collected from more than 12,000 participants in 6 studies performed from 1990 through 2011 in the United States and Germany, we developed risk determination models based on sex, age, family history, genetic risk score (number of risk alleles carried at 27 validated common CRC susceptibility loci), and history of endoscopic examinations. The model was validated using data collected from approximately 1800 participants in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, conducted from 1993 through 2001 in the United States.

RESULTS

We identified a CRC genetic risk score that independently predicted which patients in the training set would develop CRC. Compared with determination of risk based only on family history, adding the genetic risk score increased the discriminatory accuracy from 0.51 to 0.59 (P = .0028) for men and from 0.52 to 0.56 (P = .14) for women. We calculated age- and sex-specific 10-year CRC absolute risk estimates based on the number of risk alleles, family history, and history of endoscopic examinations. A model that included a genetic risk score better determined the recommended starting age for screening in subjects with and without family histories of CRC. The starting age for high-risk men (family history of CRC and genetic risk score, 90%) was 42 years, and for low-risk men (no family history of CRC and genetic risk score, 10%) was 52 years. For men with no family history and a high genetic risk score (90%), the starting age would be 47 years; this is an intermediate value that is 5 years earlier than it would be for men with a genetic risk score of 10%. Similar trends were observed in women.

CONCLUSIONS

By incorporating information on CRC risk alleles, we created a model to determine the risk for CRC more accurately. This model might be used to develop screening and prevention strategies.

A colorectal cancer prediction model using traditional and genetic risk scores in Koreans

Background

Genome-wide association studies have identified numerous single nucleotide polymorphisms (SNPs) as associated with colorectal cancer (CRC) risk in populations of European descent. However, their utility for predicting risk to CRC in Asians remains unknown. A case-cohort study (random sub-cohort N = 1,685) from the Korean Cancer Prevention Study-II (KCPS-II) (N = 145,842) was used. Twenty-three SNPs identified in previous 47 studies were genotyped on the KCPS-II sub-cohort members. A genetic risk score (GRS) was calculated by summing the number of risk alleles over all SNPs. Prediction models with or without GRS were evaluated in terms of the area under the receiver operating characteristic curve (AUROC) and the continuous net reclassification index (NRI).

Results

Seven of 23 SNPs showed significant association with CRC and rectal cancer in Koreans, but not with colon cancer alone. AUROCs (95% CI) for traditional risk score (TRS) alone and TRS plus GRS were 0.73 (0.69–0.78) and 0.74 (0.70–0.78) for CRC, and 0.71 (0.65–0.77) and 0.74 (0.68–0.79) for rectal cancer, respectively. The NRI (95% CI) for a prediction model with GRS compared to the model with TRS alone was 0.17 (-0.05-0.37) for CRC and 0.41 (0.10–0.68) for rectal cancer alone.

Conclusion

Our results indicate genetic variants may be useful for predicting risk to CRC in the Koreans, especially risk for rectal cancer alone. Moreover, this study suggests effective prediction models for colon and rectal cancer should be developed separately.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0207-y) contains supplementary material, which is available to authorized users.

Association between serum levels of adiponectin and polychlorinated biphenyls in Korean men and women

Persistent organic pollutants (POPs) are endocrine-disrupting chemicals associated with metabolic syndrome and type 2 diabetes. In humans, little is known about their potential role on obesity. Adiponectin augments the effects of insulin on glucose homeostasis. The expression of adiponectin is reduced in obesity, insulin resistance, and type 2 diabetes. The aim of this study is to reveal whether accumulation of the POPs, especially polychlorinated biphenyls (PCBs), is associated with serum levels of adiponectin in Koreans. This cross-sectional study includes 98 Koreans (49 men and 49 women). Serum levels of marker PCBs (PCB 28, 52, 101, 138, 153, and 180) were measured by Agilent 7890GC-micro-ECD (Gas chromatography-micro-electron capture detector). Total adiponectin levels were quantified by enzyme-linked immunosorbent assay. We defined high (≥Median) and low (<Median) body mass index (BMI) groups by using median value of BMI (24.6 kg/m2 for men; 23.0 kg/m2 for women). PCB28, PCB138, and PCB153 were significantly negatively associated with adiponectin levels (β-coefficients=-0.00741 for PCB28; -0.00438 for PCB138; -0.00406 for PCB153). When we divided subjects by sex, PCB28 and PCB153 were inversely associated with adiponectin in women. In the high BMI group (≥Median), PCB153 showed the significant negative associations with adiponectin levels (P<0.05). However, these associations were not seen in the low BMI group. In conclusion, we found negative associations between PCBs and adiponectin. This cross-sectional study could provide support for the hypothesis that POPs exposure might contribute to type 2 diabetes as well as obesity.

A novel colorectal cancer risk locus at 4q32.2 identified from an international genome-wide association study

Only a fraction of colorectal cancer heritability is explained by known risk-conferring genetic variation. This study was designed to identify novel risk alleles in Europeans. We conducted a genome-wide association study (GWAS) meta-analysis of colorectal cancer in participants from a population-based case-control study in Israel (n = 1616 cases, 1329 controls) and a consortium study from the Colon Cancer Family Registry (n = 1977 cases, 999 controls). We used a two-stage (discovery-replication) GWAS design, followed by a joint meta-analysis. A combined analysis identified a novel susceptibility locus that reached genome-wide significance on chromosome 4q32.2 [rs35509282, risk allele = A (minor allele frequency = 0.09); odds ratio (OR) per risk allele = 1.53; P value = 8.2 × 10(-9); nearest gene = FSTL5]. The direction of the association was consistent across studies. In addition, we confirmed that 14 of 29 previously identified susceptibility variants were significantly associated with risk of colorectal cancer in this study. Genetic variation on chromosome 4q32.2 is significantly associated with risk of colorectal cancer in Ashkenazi Jews and Europeans in this study.

Development and application of chronic disease risk prediction models

Currently, non-communicable chronic diseases are a major cause of morbidity and mortality worldwide, and a large proportion of chronic diseases are preventable through risk factor management. However, the prevention efficacy at the individual level is not yet satisfactory. Chronic disease prediction models have been developed to assist physicians and individuals in clinical decision-making. A chronic disease prediction model assesses multiple risk factors together and estimates an absolute disease risk for the individual. Accurate prediction of an individual's future risk for a certain disease enables the comparison of benefits and risks of treatment, the costs of alternative prevention strategies, and selection of the most efficient strategy for the individual. A large number of chronic disease prediction models, especially targeting cardiovascular diseases and cancers, have been suggested, and some of them have been adopted in the clinical practice guidelines and recommendations of many countries. Although few chronic disease prediction tools have been suggested in the Korean population, their clinical utility is not as high as expected. This article reviews methodologies that are commonly used for developing and evaluating a chronic disease prediction model and discusses the current status of chronic disease prediction in Korea.