Genome-wide Modeling of Polygenic Risk Score in Colorectal Cancer Risk.

Accurate colorectal cancer (CRC) risk prediction models are critical for identifying individuals at low and high risk of developing CRC, as they can then be offered targeted screening and interventions to address their risks of developing disease (if they are in a high-risk group) and avoid unnecessary screening and interventions (if they are in a low-risk group). As it is likely that thousands of genetic variants contribute to CRC risk, it is clinically important to investigate whether these genetic variants can be used jointly for CRC risk prediction. In this paper, we derived and compared different approaches to generating predictive polygenic risk scores (PRS) from genome-wide association studies (GWASs) including 55,105 CRC-affected case subjects and 65,079 control subjects of European ancestry. We built the PRS in three ways, using (1) 140 previously identified and validated CRC loci; (2) SNP selection based on linkage disequilibrium (LD) clumping followed by machine-learning approaches; and (3) LDpred, a Bayesian approach for genome-wide risk prediction. We tested the PRS in an independent cohort of 101,987 individuals with 1,699 CRC-affected case subjects. The discriminatory accuracy, calculated by the age- and sex-adjusted area under the receiver operating characteristics curve (AUC), was highest for the LDpred-derived PRS (AUC = 0.654) including nearly 1.2 M genetic variants (the proportion of causal genetic variants for CRC assumed to be 0.003), whereas the PRS of the 140 known variants identified from GWASs had the lowest AUC (AUC = 0.629). Based on the LDpred-derived PRS, we are able to identify 30% of individuals without a family history as having risk for CRC similar to those with a family history of CRC, whereas the PRS based on known GWAS variants identified only top 10% as having a similar relative risk. About 90% of these individuals have no family history and would have been considered average risk under current screening guidelines, but might benefit from earlier screening. The developed PRS offers a way for risk-stratified CRC screening and other targeted interventions.

Calibration of polygenic risk scores is required prior to clinical implementation: results of three common cancers in UKB.

BACKGROUND: SNP-based polygenic risk scores have recently been adopted in the clinic for risk assessment of some common diseases. Their validity is supported by a consistent trend between their percentile rank and disease risk in populations. However, for clinical use at the individual level, the reliability of score values is necessary considering they are directly used to calculate remaining lifetime risk. OBJECTIVES: We assessed the reliability of polygenic score values to estimate prostate cancer (PCa), breast cancer (BCa) and colorectal cancer (CRC) risk in three incident cohorts from the UK Biobank (n>500 000). METHODS: Cancer-specific Genetic Risk Score (GRS), a well-established population-standardised polygenic risk score, was calculated. RESULTS: A systematic bias was found between estimated risks (GRS values) and observed risks; ß (95% CI) was 0.67 (0.58-0.76), 0.74 (0.65-0.84) and 0.82 (0.75-0.89), respectively, for PCa, BCa and CRC, all significantly lower than 1.00 (perfect calibration), p<0.001. After applying a correction factor derived from a training data set, the ß for corrected GRS values in an independent testing data set were 1.09 (1.05-1.13), 1.00 (0.88-1.12) and 1.08 (0.96-1.21), respectively, for PCa, BCa and CRC. CONCLUSION: Assessing the calibration of polygenic risk scores is necessary and feasible to ensure their reliability prior to clinical implementation.

Associations between Genetic Variants and Blood Biomarkers of One-Carbon Metabolism in Postmenopausal Women from the Women's Health Initiative Observational Study.

BACKGROUND: Genetic variation in one-carbon metabolism may affect nutrient concentrations and biological functions. However, data on genetic variants associated with blood biomarkers of one-carbon metabolism in US postmenopausal women are limited, and whether these associations were affected by the nationwide folic acid (FA) fortification program is unclear. OBJECTIVES: We investigated associations between genetic variants and biomarkers of one-carbon metabolism using data from the Women's Health Initiative Observational Study. METHODS: In 1573 non-Hispanic White (NHW) and 282 Black/African American, American Indian/Alaska Native, Asian/Pacific Islander, and Hispanic/Latino women aged 50-79 y, 288 nonsynonymous and tagging single-nucleotide variants (SNVs) were genotyped. RBC folate, plasma folate, pyridoxal-5'-phosphate (PLP), vitamin B-12, homocysteine, and cysteine concentrations were determined in 12-h fasting blood. Multivariable linear regression tested associations per variant allele and for an aggregated genetic risk score. Effect modifications before, during, and after nationwide FA fortification were examined. RESULTS: After correction for multiple comparisons, among NHW women, 5,10-methylenetetrahydrofolate reductase (MTHFR) rs1801133 (677C→T) variant T was associated with lower plasma folate (-13.0%; 95% CI: -17.3%, -8.6%) and higher plasma homocysteine (3.5%; 95% CI: 1.7%, 5.3%) concentrations. Other associations for nonsynonymous SNVs included DNMT3A rs11695471 (T→A) with plasma PLP; EHMT2 rs535586 (G→A), TCN2 rs1131603 (L349S A→G), and TCN2 rs35838082 (R188W G→A) with plasma vitamin B-12; CBS rs2851391 (G→A) with plasma homocysteine; and MTHFD1 rs2236224 (G→A) and rs2236225 (R653Q G→A) with plasma cysteine. The influence of FA fortification on the associations was limited. Highest compared with lowest quartiles of aggregated genetic risk scores from SNVs in MTHFR and MTRR were associated with 14.8% to 18.9% lower RBC folate concentrations. Gene-biomarker associations were similar in women of other races/ethnicities. CONCLUSIONS: Our findings on genetic variants associated with several one-carbon metabolism biomarkers may help elucidate mechanisms of maintaining B vitamin status in postmenopausal women.

Genetic architectures of proximal and distal colorectal cancer are partly distinct.

OBJECTIVE: An understanding of the etiologic heterogeneity of colorectal cancer (CRC) is critical for improving precision prevention, including individualized screening recommendations and the discovery of novel drug targets and repurposable drug candidates for chemoprevention. Known differences in molecular characteristics and environmental risk factors among tumors arising in different locations of the colorectum suggest partly distinct mechanisms of carcinogenesis. The extent to which the contribution of inherited genetic risk factors for CRC differs by anatomical subsite of the primary tumor has not been examined. DESIGN: To identify new anatomical subsite-specific risk loci, we performed genome-wide association study (GWAS) meta-analyses including data of 48 214 CRC cases and 64 159 controls of European ancestry. We characterised effect heterogeneity at CRC risk loci using multinomial modelling. RESULTS: We identified 13 loci that reached genome-wide significance (p<5×10-8) and that were not reported by previous GWASs for overall CRC risk. Multiple lines of evidence support candidate genes at several of these loci. We detected substantial heterogeneity between anatomical subsites. Just over half (61) of 109 known and new risk variants showed no evidence for heterogeneity. In contrast, 22 variants showed association with distal CRC (including rectal cancer), but no evidence for association or an attenuated association with proximal CRC. For two loci, there was strong evidence for effects confined to proximal colon cancer. CONCLUSION: Genetic architectures of proximal and distal CRC are partly distinct. Studies of risk factors and mechanisms of carcinogenesis, and precision prevention strategies should take into consideration the anatomical subsite of the tumour.

Cumulative Burden of Colorectal Cancer-Associated Genetic Variants Is More Strongly Associated With Early-Onset vs Late-Onset Cancer.

BACKGROUND & AIMS: Early-onset colorectal cancer (CRC, in persons younger than 50 years old) is increasing in incidence; yet, in the absence of a family history of CRC, this population lacks harmonized recommendations for prevention. We aimed to determine whether a polygenic risk score (PRS) developed from 95 CRC-associated common genetic risk variants was associated with risk for early-onset CRC. METHODS: We studied risk for CRC associated with a weighted PRS in 12,197 participants younger than 50 years old vs 95,865 participants 50 years or older. PRS was calculated based on single nucleotide polymorphisms associated with CRC in a large-scale genome-wide association study as of January 2019. Participants were pooled from 3 large consortia that provided clinical and genotyping data: the Colon Cancer Family Registry, the Colorectal Transdisciplinary Study, and the Genetics and Epidemiology of Colorectal Cancer Consortium and were all of genetically defined European descent. Findings were replicated in an independent cohort of 72,573 participants. RESULTS: Overall associations with CRC per standard deviation of PRS were significant for early-onset cancer, and were stronger compared with late-onset cancer (P for interaction = .01); when we compared the highest PRS quartile with the lowest, risk increased 3.7-fold for early-onset CRC (95% CI 3.28-4.24) vs 2.9-fold for late-onset CRC (95% CI 2.80-3.04). This association was strongest for participants without a first-degree family history of CRC (P for interaction = 5.61 × 10-5). When we compared the highest with the lowest quartiles in this group, risk increased 4.3-fold for early-onset CRC (95% CI 3.61-5.01) vs 2.9-fold for late-onset CRC (95% CI 2.70-3.00). Sensitivity analyses were consistent with these findings. CONCLUSIONS: In an analysis of associations with CRC per standard deviation of PRS, we found the cumulative burden of CRC-associated common genetic variants to associate with early-onset cancer, and to be more strongly associated with early-onset than late-onset cancer, particularly in the absence of CRC family history. Analyses of PRS, along with environmental and lifestyle risk factors, might identify younger individuals who would benefit from preventive measures.

Broad- and narrow-sense validity performance of three polygenic risk score methods for prostate cancer risk assessment.

BACKGROUND: Several polygenic risk score (PRS) methods are available for measuring the cumulative effect of multiple risk-associated single nucleotide polymorphisms (SNPs). Their performance in predicting risk at the individual level has not been well studied. METHODS: We compared the performance of three PRS methods for prostate cancer risk assessment in a clinical trial cohort, including genetic risk score (GRS), pruning and thresholding (P + T), and linkage disequilibrium prediction (LDpred). Performance was evaluated for score deciles (broad-sense validity) and score values (narrow-sense validity). RESULTS: A training process was required to identify the best P + T model (397 SNPs) and LDpred model (3 011 362 SNPs). In contrast, GRS was directly calculated based on 110 established risk-associated SNPs. For broad-sense validity in the testing population, higher deciles were significantly associated with higher observed risk; Ptrend was 7.40 × 10-11 , 7.64 × 10-13 , and 7.51 × 10-10 for GRS, P + T, and LDpred, respectively. For narrow-sense validity, the calibration slope (1 is best) was 1.03, 0.77, and 0.87, and mean bias score (0 is best) was 0.09, 0.21, and 0.10 for GRS, P + T, and LDpred, respectively. CONCLUSIONS: The performance of GRS was better than P + T and LDpred. Fewer and well-established SNPs of GRS also make it more feasible and interpretable for genetic testing at the individual level.

Associations between Plasma Choline Metabolites and Genetic Polymorphisms in One-Carbon Metabolism in Postmenopausal Women: The Women's Health Initiative Observational Study.

BACKGROUND: Choline plays an integral role in one-carbon metabolism in the body, but it is unclear whether genetic polymorphisms are associated with variations in plasma choline and its metabolites. OBJECTIVES: This study aimed to evaluate the association of genetic variants in choline and one-carbon metabolism with plasma choline and its metabolites. METHODS: We analyzed data from 1423 postmenopausal women in a case-control study nested within the Women's Health Initiative Observational Study. Plasma concentrations of choline, betaine, dimethylglycine (DMG), and trimethylamine N-oxide were determined in 12-h fasting blood samples collected at baseline (1993-1998). Candidate and tagging single-nucleotide polymorphisms (SNPs) were genotyped in betaine-homocysteine S-methyltransferase (BHMT), BHMT2, 5,10-methylenetetrahydrofolate reductase (MTHFR), methylenetetrahydrofolate dehydrogenase (NADP+ dependent 1) (MTHFD1), 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR), and 5-methyltetrahydrofolate-homocysteine methyltransferase reductase (MTRR). Linear regression was used to derive percentage difference in plasma concentrations per variant allele, adjusting for confounders, including B-vitamin biomarkers. Potential effect modification by plasma vitamin B-12, vitamin B-6, and folate concentrations and folic-acid fortification periods was examined. RESULTS: The candidate SNP BHMT R239Q (rs3733890) was associated with lower concentrations of plasma betaine and DMG concentrations (-4.00% and -6.75% per variant allele, respectively; both nominal P < 0.05). Another candidate SNP, BHMT2 rs626105 A>G, was associated with higher plasma DMG concentration (13.0%; P < 0.0001). Several tagSNPs in these 2 genes were associated with plasma concentrations after correction for multiple comparisons. Vitamin B-12 status was a significant effect modifier of the association between the genetic variant BHMT2 rs626105 A>G and plasma DMG concentration. CONCLUSIONS: Genetic variations in metabolic enzymes were associated with plasma concentrations of choline and its metabolites. Our findings contribute to the knowledge on the variation in blood nutrient concentrations in postmenopausal women.

Concept and benchmarks for assessing narrow-sense validity of genetic risk score values.

BACKGROUND: While higher genetic risk score (GRS) has been statistically associated with increased disease risk (broad-sense validity), the concept and tools for assessing the validity of reported GRS values from tests (narrow-sense validity) are underdeveloped. METHODS: We propose two benchmarks for assessing the narrow-sense validity of GRS. The baseline benchmark requires that the mean GRS value in a general population approximates 1.0. The calibration benchmark assesses the agreement between observed risks and estimated risks (GRS values). We assessed benchmark performance for three prostate cancer (PCa) GRS tests, derived from three SNP panels with increasing stringency of selection criteria, in a PCa chemoprevention trial where 714 of 3225 men were diagnosed with PCa during the 4-year follow-up. RESULTS: GRS from Panels 1, 2, and 3 were all statistically associated with PCa risk; P = 5.58 × 10-3 , P = 1 × 10-3 , and P = 1.5 × 10-13 , respectively (broad-sense validity). For narrow-sense validity, the mean GRS value among men without PCa was 1.33, 1.09, and 0.98 for Panels 1, 2, and 3, respectively (baseline benchmark). For assessing the calibration benchmark, observed risks were calculated for seven groups of men with GRS values <0.3, 0.3-0.79, 0.8-1.19, 1.2-1.49, 1.5-1.99, 2-2.99, and ≥3. The calibration slope (higher is better) was 0.15, 0.12, and 0.60, and the bias score (lower is better) between the observed risks and GRS values was 0.08, 0.08, and 0.02 for Panels 1, 2, and 3, respectively. CONCLUSION: Performance differed considerably among GRS tests. We recommend that all GRS tests be evaluated using the two benchmarks before clinical implementation for individual risk assessment.

Genome-Wide Interaction Analyses between Genetic Variants and Alcohol Consumption and Smoking for Risk of Colorectal Cancer.

Genome-wide association studies (GWAS) have identified many genetic susceptibility loci for colorectal cancer (CRC). However, variants in these loci explain only a small proportion of familial aggregation, and there are likely additional variants that are associated with CRC susceptibility. Genome-wide studies of gene-environment interactions may identify variants that are not detected in GWAS of marginal gene effects. To study this, we conducted a genome-wide analysis for interaction between genetic variants and alcohol consumption and cigarette smoking using data from the Colon Cancer Family Registry (CCFR) and the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). Interactions were tested using logistic regression. We identified interaction between CRC risk and alcohol consumption and variants in the 9q22.32/HIATL1 (Pinteraction = 1.76×10-8; permuted p-value 3.51x10-8) region. Compared to non-/occasional drinking light to moderate alcohol consumption was associated with a lower risk of colorectal cancer among individuals with rs9409565 CT genotype (OR, 0.82 [95% CI, 0.74-0.91]; P = 2.1×10-4) and TT genotypes (OR,0.62 [95% CI, 0.51-0.75]; P = 1.3×10-6) but not associated among those with the CC genotype (p = 0.059). No genome-wide statistically significant interactions were observed for smoking. If replicated our suggestive finding of a genome-wide significant interaction between genetic variants and alcohol consumption might contribute to understanding colorectal cancer etiology and identifying subpopulations with differential susceptibility to the effect of alcohol on CRC risk.

Genome-wide diet-gene interaction analyses for risk of colorectal cancer.

Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet interactions, as well as our recently developed Cocktail method that involves a screening step based on marginal associations and gene-diet correlations and a testing step for multiplicative interactions, while correcting for multiple testing using weighted hypothesis testing. Per quartile increment in the intake of red and processed meat were associated with statistically significant increased risks of colorectal cancer and vegetable, fruit and fiber intake with lower risks. From the case-control analysis, we detected a significant interaction between rs4143094 (10p14/near GATA3) and processed meat consumption (OR = 1.17; p = 8.7E-09), which was consistently observed across studies (p heterogeneity = 0.78). The risk of colorectal cancer associated with processed meat was increased among individuals with the rs4143094-TG and -TT genotypes (OR = 1.20 and OR = 1.39, respectively) and null among those with the GG genotype (OR = 1.03). Our results identify a novel gene-diet interaction with processed meat for colorectal cancer, highlighting that diet may modify the effect of genetic variants on disease risk, which may have important implications for prevention.

Common genetic variation and survival after colorectal cancer diagnosis: a genome-wide analysis.

Genome-wide association studies have identified several germline single nucleotide polymorphisms (SNPs) significantly associated with colorectal cancer (CRC) incidence. Common germline genetic variation may also be related to CRC survival. We used a discovery-based approach to identify SNPs related to survival outcomes after CRC diagnosis. Genome-wide genotyping arrays were conducted for 3494 individuals with invasive CRC enrolled in six prospective cohort studies (median study-specific follow-up = 4.2-8.1 years). In pooled analyses, we used Cox regression to assess SNP-specific associations with CRC-specific and overall survival, with additional analyses stratified by stage at diagnosis. Top findings were followed-up in independent studies. A P value threshold of P < 5×10(-8) in analyses combining discovery and follow-up studies was required for genome-wide significance. Among individuals with distant-metastatic CRC, several SNPs at 6p12.1, nearest the ELOVL5 gene, were statistically significantly associated with poorer survival, with the strongest associations noted for rs209489 [hazard ratio (HR) = 1.8, P = 7.6×10(-10) and HR = 1.8, P = 3.7×10(-9) for CRC-specific and overall survival, respectively). No SNPs were statistically significantly associated with survival among all cases combined or in cases without distant-metastases. SNPs in 6p12.1/ELOVL5 were associated with survival outcomes in individuals with distant-metastatic CRC, and merit further follow-up for functional significance. Findings from this genome-wide association study highlight the potential importance of genetic variation in CRC prognosis and provide clues to genomic regions of potential interest.

GWASeq: targeted re-sequencing follow up to GWAS.

BACKGROUND: For the last decade the conceptual framework of the Genome-Wide Association Study (GWAS) has dominated the investigation of human disease and other complex traits. While GWAS have been successful in identifying a large number of variants associated with various phenotypes, the overall amount of heritability explained by these variants remains small. This raises the question of how best to follow up on a GWAS, localize causal variants accounting for GWAS hits, and as a consequence explain more of the so-called "missing" heritability. Advances in high throughput sequencing technologies now allow for the efficient and cost-effective collection of vast amounts of fine-scale genomic data to complement GWAS. RESULTS: We investigate these issues using a colon cancer dataset. After QC, our data consisted of 1993 cases, 899 controls. Using marginal tests of associations, we identify 10 variants distributed among six targeted regions that are significantly associated with colorectal cancer, with eight of the variants being novel to this study. Additionally, we perform so-called 'SNP-set' tests of association and identify two sets of variants that implicate both common and rare variants in the etiology of colorectal cancer. CONCLUSIONS: Here we present a large-scale targeted re-sequencing resource focusing on genomic regions implicated in colorectal cancer susceptibility previously identified in several GWAS, which aims to 1) provide fine-scale targeted sequencing data for fine-mapping and 2) provide data resources to address methodological questions regarding the design of sequencing-based follow-up studies to GWAS. Additionally, we show that this strategy successfully identifies novel variants associated with colorectal cancer susceptibility and can implicate both common and rare variants.

Estimating the heritability of colorectal cancer.

A sizable fraction of colorectal cancer (CRC) is expected to be explained by heritable factors, with heritability estimates ranging from 12 to 35% twin and family studies. Genome-wide association studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) associated with CRC risk. Although it has been shown that these CRC susceptibility SNPs only explain a small proportion of the genetic risk, it is not clear how much of the heritability these SNPs explain and how much is left to be detected by other, yet to be identified, common SNPs. Therefore, we estimated the heritability of CRC under different scenarios using Genome-Wide Complex Trait Analysis in the Genetics and Epidemiology of Colorectal Cancer Consortium including 8025 cases and 10 814 controls. We estimated that the heritability explained by known common CRC SNPs identified in GWAS was 0.65% (95% CI:0.3-1%; P = 1.11 × 10-16), whereas the heritability explained by all common SNPs was at least 7.42% (95% CI: 4.71-10.12%; P = 8.13 × 10(-8)), suggesting that many common variants associated with CRC risk remain to be detected. Comparing the heritability explained by the common variants with that from twin and family studies, a fraction of the heritability may be explained by other genetic variants, such as rare variants. In addition, our analysis showed that the gene × smoking interaction explained a significant proportion of the CRC variance (P = 1.26 × 10(-2)). In summary, our results suggest that known CRC SNPs only explain a small proportion of the heritability and more common SNPs have yet to be identified.

CYP24A1 variant modifies the association between use of oestrogen plus progestogen therapy and colorectal cancer risk.

BACKGROUND: Menopausal hormone therapy (MHT) use has been consistently associated with a decreased risk of colorectal cancer (CRC) in women. Our aim was to use a genome-wide gene-environment interaction analysis to identify genetic modifiers of CRC risk associated with use of MHT. METHODS: We included 10 835 postmenopausal women (5419 cases and 5416 controls) from 10 studies. We evaluated use of any MHT, oestrogen-only (E-only) and combined oestrogen-progestogen (E+P) hormone preparations. To test for multiplicative interactions, we applied the empirical Bayes (EB) test as well as the Wald test in conventional case-control logistic regression as primary tests. The Cocktail test was used as secondary test. RESULTS: The EB test identified a significant interaction between rs964293 at 20q13.2/CYP24A1 and E+P (interaction OR (95% CIs)=0.61 (0.52-0.72), P=4.8 × 10(-9)). The secondary analysis also identified this interaction (Cocktail test OR=0.64 (0.52-0.78), P=1.2 × 10(-5) (alpha threshold=3.1 × 10(-4)). The ORs for association between E+P and CRC risk by rs964293 genotype were as follows: C/C, 0.96 (0.61-1.50); A/C, 0.61 (0.39-0.95) and A/A, 0.40 (0.22-0.73), respectively. CONCLUSIONS: Our results indicate that rs964293 modifies the association between E+P and CRC risk. The variant is located near CYP24A1, which encodes an enzyme involved in vitamin D metabolism. This novel finding offers additional insight into downstream pathways of CRC etiopathogenesis.

Generalization and dilution of association results from European GWAS in populations of non-European ancestry: the PAGE study.

The vast majority of genome-wide association study (GWAS) findings reported to date are from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic associations described will generalize to populations of diverse ancestry. The Population Architecture Using Genomics and Epidemiology (PAGE) study is a consortium of multi-ancestry, population-based studies formed with the objective of refining our understanding of the genetic architecture of common traits emerging from GWAS. In the present analysis of five common diseases and traits, including body mass index, type 2 diabetes, and lipid levels, we compare direction and magnitude of effects for GWAS-identified variants in multiple non-EA populations against EA findings. We demonstrate that, in all populations analyzed, a significant majority of GWAS-identified variants have allelic associations in the same direction as in EA, with none showing a statistically significant effect in the opposite direction, after adjustment for multiple testing. However, 25% of tagSNPs identified in EA GWAS have significantly different effect sizes in at least one non-EA population, and these differential effects were most frequent in African Americans where all differential effects were diluted toward the null. We demonstrate that differential LD between tagSNPs and functional variants within populations contributes significantly to dilute effect sizes in this population. Although most variants identified from GWAS in EA populations generalize to all non-EA populations assessed, genetic models derived from GWAS findings in EA may generate spurious results in non-EA populations due to differential effect sizes. Regardless of the origin of the differential effects, caution should be exercised in applying any genetic risk prediction model based on tagSNPs outside of the ancestry group in which it was derived. Models based directly on functional variation may generalize more robustly, but the identification of functional variants remains challenging.

Trans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained.

Genome-wide association studies (GWAS) have identified ~100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1 × 10(-4) in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies.

Identification of a common variant with potential pleiotropic effect on risk of inflammatory bowel disease and colorectal cancer.

Although genome-wide association studies (GWAS) have separately identified many genetic susceptibility loci for ulcerative colitis (UC), Crohn's disease (CD) and colorectal cancer (CRC), there has been no large-scale examination for pleiotropy, or shared genetic susceptibility, for these conditions. We used logistic regression modeling to examine the associations of 181 UC and CD susceptibility variants previously identified by GWAS with risk of CRC using data from the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry. We also examined associations of significant variants with clinical and molecular characteristics in a subset of the studies. Among 11794 CRC cases and 14190 controls, rs11676348, the susceptibility single nucleotide polymorphism (SNP) for UC, was significantly associated with reduced risk of CRC (P = 7E-05). The multivariate-adjusted odds ratio of CRC with each copy of the T allele was 0.93 (95% CI 0.89-0.96). The association of the SNP with risk of CRC differed according to mucinous histological features (P heterogeneity = 0.008). In addition, the (T) allele was associated with lower risk of tumors with Crohn's-like reaction but not tumors without such immune infiltrate (P heterogeneity = 0.02) and microsatellite instability-high (MSI-high) but not microsatellite stable or MSI-low tumors (P heterogeneity = 0.03). The minor allele (T) in SNP rs11676348, located downstream from CXCR2 that has been implicated in CRC progression, is associated with a lower risk of CRC, particularly tumors with a mucinous component, Crohn's-like reaction and MSI-high. Our findings offer the promise of risk stratification of inflammatory bowel disease patients for complications such as CRC.

Folate-mediated one-carbon metabolism genes and interactions with nutritional factors on colorectal cancer risk: Women's Health Initiative Observational Study.

BACKGROUND: Investigations of folate-mediated one-carbon metabolism (FOCM) genes and gene-nutrient interactions with respect to colorectal cancer (CRC) risk are limited to candidate polymorphisms and dietary folate. This study comprehensively investigated associations between genetic variants in FOCM and CRC risk and whether the FOCM nutrient status modified these associations. METHODS: Two hundred eighty-eight candidate and tagging single-nucleotide polymorphisms (SNPs) in 30 FOCM genes were genotyped for 821 incident CRC case-control matched pairs in the Women's Health Initiative Observational Study cohort. FOCM biomarkers (red blood cell [RBC] folate, plasma folate, pyridoxal-5'-phosphate [PLP], vitamin B12, and homocysteine) and self-reported alcohol consumption were measured at the baseline. Conditional logistic regression was implemented; effect modification was examined on the basis of known enzyme-nutrient relations. RESULTS: Statistically significant associations were observed between CRC risk and functionally defined candidate SNPs of methylenetetrahydrofolate dehydrogenase 1 (MTHFD1; K134R), 5-methyltetrahydrofolate-homocysteine methyltransferase reductase (MTRR; P450R), and PR domain containing 2 with ZNF domain (PRDM2; S450N) and a literature candidate SNP of thymidylate synthase (TYMS; g.676789A>T; nominal P < .05). In addition, suggestive associations were noted for tagging SNPs in cystathionine-ß-synthase (CBS), dihydrofolate reductase (DHFR), DNA (cytosine-5-)-methyltransferase 3ß (DNMT3B), methionine adenosyltransferase I α (MAT1A), MTHFD1, and MTRR (nominal P < .05; adjusted P, not significant). Significant interactions between nutrient biomarkers and candidate polymorphisms were observed for 1) plasma/RBC folate and folate hydrolase 1 (FOLH1), paraoxonase 1 (PON1), transcobalamin II (TCN2), DNMT1, and DNMT3B; 2) plasma PLP and TYMS TS3; 3) plasma B12 and betaine-homocysteine S-methyltransferase 2 (BHMT2); and 4) homocysteine and methylenetetrahydrofolate reductase (MTHFR) and alanyl-transfer RNA synthetase (AARS). CONCLUSIONS: Genetic variants in FOCM genes are associated with CRC risk among postmenopausal women. FOCM nutrients continue to emerge as effect modifiers of genetic influences on CRC risk.

Associations of prostate cancer risk variants with disease aggressiveness: results of the NCI-SPORE Genetics Working Group analysis of 18,343 cases.

Genetic studies have identified single nucleotide polymorphisms (SNPs) associated with the risk of prostate cancer (PC). It remains unclear whether such genetic variants are associated with disease aggressiveness. The NCI-SPORE Genetics Working Group retrospectively collected clinicopathologic information and genotype data for 36 SNPs which at the time had been validated to be associated with PC risk from 25,674 cases with PC. Cases were grouped according to race, Gleason score (Gleason ≤ 6, 7, ≥ 8) and aggressiveness (non-aggressive, intermediate, and aggressive disease). Statistical analyses were used to compare the frequency of the SNPs between different disease cohorts. After adjusting for multiple testing, only PC-risk SNP rs2735839 (G) was significantly and inversely associated with aggressive (OR = 0.77; 95 % CI 0.69-0.87) and high-grade disease (OR = 0.77; 95 % CI 0.68-0.86) in European men. Similar associations with aggressive (OR = 0.72; 95 % CI 0.58-0.89) and high-grade disease (OR = 0.69; 95 % CI 0.54-0.87) were documented in African-American subjects. The G allele of rs2735839 was associated with disease aggressiveness even at low PSA levels (<4.0 ng/mL) in both European and African-American men. Our results provide further support that a PC-risk SNP rs2735839 near the KLK3 gene on chromosome 19q13 may be associated with aggressive and high-grade PC. Future prospectively designed, case-case GWAS are needed to identify additional SNPs associated with PC aggressiveness.