Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol L−1, p=3.4×10−12), T2D risk (OR[95%CI]=0.86[0.76-0.96], p=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose−1, p=0.048), but higher 2-h glucose (β=0.16±0.05 mmol L−1, p=4.3×10−4). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8×10−6) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol L−1, p=1.3×10−8). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
It has been hypothesized that predominance of the 2-hydroxylation estrogen metabolism pathway over the 16α-hydroxylation pathway may be inversely associated with breast cancer risk.
We examined the associations of invasive breast cancer risk with circulating 2-OHE1, 16α-OHE1, and the 2-OHE1:16α-OHE1 ratio in a case-control study of postmenopausal women nested within two prospective cohorts: the New York University Women’s Health Study (NYUWHS) and the Northern Sweden Mammary Screening Cohort (NSMSC), with adjustment for circulating levels of estrone, and additional analyses by tumor estrogen receptor (ER) status. Levels of 2-OHE1 and 16α-OHE1 were measured using ESTRAMET 2/16 assay in stored serum or plasma samples from 499 incident breast cancer cases and 499 controls, who were matched on cohort, age, and date of blood donation.
Overall, no significant associations were observed between breast cancer risk and circulating levels of 2-OHE1, 16α-OHE1, or their ratio in either cohort and in combined analyses. For 2-OHE1, there was evidence of heterogeneity by ER status in models adjusting for estrone (p ≤ 0.03). We observed a protective association of 2-OHE1 with ER+ breast cancer (multivariate-adjusted OR for a doubling of 2-OHE1 = 0.67 (95% CI = 0.48–0.94, p = 0.02).
In this study, higher levels of 2-OHE1 were associated with reduced risk of ER+ breast cancer in postmenopausal women after adjustment for circulating estrone.
These results suggest that taking into account the levels of parent estrogens and estrogen receptor status is important in studies of estrogen metabolites and breast cancer.
Estrogen metabolism; breast cancer; postmenopausal; estrogen receptor; prospective cohorts
Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist–hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006–0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.
Intake of the mainly plant derived n-3 polyunsaturated fatty acid (PUFA) α-linolenic acid (ALA) has been associated with lower risk of coronary heart disease (CHD). However, the results have been inconsistent. Therefore, the objective of this study was to examine the association between ALA consumption and risk of CHD. Potential effect modification by long-chain n-3 PUFA (n-3 LCPUFA) was also investigated. Data from eight American and European prospective cohort studies including 148,675 women and 80,368 men were used. The outcome measure was incident CHD (CHD event and death). During follow-up of 4-10 years, 4,493 CHD events and 1,751 CHD deaths occurred. Among men we found an inverse association (not significant) between intake of ALA and CHD event and death. For each additional gram of ALA, there was a 15% lower risk of CHD events (HR: 0.85; 95% CI: 0.72, 1.01) and a 23% lower risk of CHD deaths (HR: 0.77; 95% CI 0.58, 1.01). We found no consistent associations among women. No effect modification by intake of n-3 LCPUFA was found.
Alpha-linolenic acid; coronary heart disease; epidemiology
Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=−0.09±0.01 mmol l−1, P=3.4 × 10−12), T2D risk (OR[95%CI]=0.86[0.76–0.96], P=0.010), early insulin secretion (β=−0.07±0.035 pmolinsulin mmolglucose−1, P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l−1, P=4.3 × 10−4). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10−6) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l−1, P=1.3 × 10−8). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
Both rare and common variants contribute to the aetiology of complex traits such as type 2 diabetes (T2D). Here, the authors examine the effect of coding variation on glycaemic traits and T2D, and identify low-frequency variation in GLP1R significantly associated with these traits.
The etiology of renal cell carcinoma (RCC) is only partially understood, but a metabolic component appears likely. We investigated biomarkers of one-carbon metabolism and RCC onset and survival.
The European Prospective Investigation into Cancer and Nutrition (EPIC) recruited 385747 participants with blood samples between 1992 and 2000, and this analysis included 556 RCC case-control pairs. A subsequent replication study included 144 case-control pairs nested within the Melbourne Collaborative Cohort Study (MCCS). Plasma concentrations of vitamin B2, vitamin B6, folate, vitamin B12, methionine and homocysteine were measured in prediagnostic samples and evaluated with respect to RCC risk using conditional and unconditional logistic regression models, and to all-cause mortality in RCC cases using Cox regression models. All statistical tests were two-sided.
EPIC participants with higher plasma concentrations of vitamin B6 had lower risk of RCC, the odds ratio comparing the 4th and 1st quartiles (OR4vs1) being 0.40 95% confidence interval [CI] = 0.28 to 0.57, P
trend < .001. We found similar results after adjusting for potential confounders (adjusted P
trend < .001). In survival analysis, the hazard ratio for all-cause mortality in RCC cases when comparing the 4th and 1st quartiles (HR4vs1) of vitamin B6 was 0.57 (95% CI = 0.37 to 0.87, P
trend < .001).
Subsequent replication of these associations within the MCCS yielded very similar results for both RCC risk (OR4vs1 = 0.47, 95% CI = 0.23 to 0.99, P
trend = .07) and all-cause mortality (HR4vs1 = 0.56, 95% CI = 0.27 to 1.17, P
trend = .02). No association was evident for the other measured biomarkers.
Study participants with higher circulating concentrations of vitamin B6 had lower risk of RCC and improved survival following diagnosis in two independent cohorts.
A major challenge in cancer epidemiologic studies, especially those of rare cancers, is observing enough cases. To address this, researchers often join forces by bringing multiple studies together to achieve large sample sizes, allowing for increased power in hypothesis testing, and improved efficiency in effect estimation. Combining studies, however, renders the analysis difficult owing to the presence of heterogeneity in the pooled data. In this article, motivated by a collaborative nested case–control (NCC) study of ovarian cancer in three cohorts from United States, Sweden, and Italy, we investigate the use of penalty regularized partial likelihood estimation in the context of pooled NCC studies to achieve two goals. First, we propose an adaptive group lasso (gLASSO) penalized approach to simultaneously identify important variables and estimate their effects. Second, we propose a composite agLASSO penalized approach to identify variables with heterogeneous effects. Both methods are readily implemented with the group coordinate gradient decent algorithm and shown to enjoy the oracle property. We conduct simulation studies to evaluate the performance of our proposed approaches in finite samples under various heterogeneity settings, and apply them to the pooled ovarian cancer study.
Cox's proportional hazards model; Group penalty; Heterogeneity; Nested case–control sampling; Ovarian cancer; Pooled studies; Shrinkage estimation
The evidence of a relation between folate intake and one-carbon metabolism (OCM) with pancreatic cancer (PanCa) is inconsistent. In this study, the association between genes and single-nucleotide polymorphisms (SNPs) related to OCM and PanCa was assessed.
Using biochemical knowledge of the OCM pathway, we identified thirty-seven genes and 834 SNPs to examine in association with PanCa. Our study included 1,408 cases and 1,463 controls nested within twelve cohorts (PanScan). The ten SNPs and five genes with lowest p values (<0.02) were followed up in 2,323 cases and 2,340 controls from eight case-control studies (PanC4) that participated in PanScan2. The correlation of SNPs with metabolite levels was assessed for 649 controls from the European Prospective Investigation into Cancer and Nutrition.
When both stages were combined, we observed suggestive associations with PanCa for rs10887710 (MAT1A) (OR 1.13, 95%CI 1.04-1.23), rs1552462 (SYT9) (OR 1.27, 95%CI 1.02-1.59), and rs7074891 (CUBN) (OR 1.91, 95%CI 1.12-3.26). After correcting for multiple comparisons, no significant associations were observed in either the first or second stage. The three suggested SNPs showed no correlations with one-carbon biomarkers.
This is the largest genetic study to date to examine the relation between germline variations in OCM-related genes polymorphisms and the risk of PanCa. Suggestive evidence for an association between polymorphisms and PanCa was observed among the cohort-nested studies, but this did not replicate in the case-control studies. Our results do not strongly support the hypothesis that genes related to OCM play a role in pancreatic carcinogenesis.
Pancreatic cancer; One-carbon metabolism; Polymorphisms; Biomarkers; Epidemiology
Human papillomavirus type 16 (HPV16) infection is causing an increasing number of oropharyngeal cancers in the United States and Europe. The aim of our study was to investigate whether HPV antibodies are associated with head and neck cancer risk when measured in prediagnostic sera.
We identified 638 participants with incident head and neck cancers (patients; 180 oral cancers, 135 oropharynx cancers, and 247 hypopharynx/larynx cancers) and 300 patients with esophageal cancers as well as 1,599 comparable controls from within the European Prospective Investigation Into Cancer and Nutrition cohort. Prediagnostic plasma samples from patients (collected, on average, 6 years before diagnosis) and control participants were analyzed for antibodies against multiple proteins of HPV16 as well as HPV6, HPV11, HPV18, HPV31, HPV33, HPV45, and HPV52. Odds ratios (ORs) of cancer and 95% CIs were calculated, adjusting for potential confounders. All-cause mortality was evaluated among patients using Cox proportional hazards regression.
HPV16 E6 seropositivity was present in prediagnostic samples for 34.8% of patients with oropharyngeal cancer and 0.6% of controls (OR, 274; 95% CI, 110 to 681) but was not associated with other cancer sites. The increased risk of oropharyngeal cancer among HPV16 E6 seropositive participants was independent of time between blood collection and diagnosis and was observed more than 10 years before diagnosis. The all-cause mortality ratio among patients with oropharyngeal cancer was 0.30 (95% CI, 0.13 to 0.67), for patients who were HPV16 E6 seropositive compared with seronegative.
HPV16 E6 seropositivity was present more than 10 years before diagnosis of oropharyngeal cancers.
Recent genome-wide meta-analyses identified 157 loci associated with cross-sectional lipid traits. Here we tested whether these loci associate (singly and in trait-specific genetic risk scores [GRS]) with longitudinal changes in total cholesterol (TC) and triglyceride (TG) levels in a population-based prospective cohort from Northern Sweden (the GLACIER Study). We sought replication in a southern Swedish cohort (the MDC Study; N = 2,943). GLACIER Study participants (N = 6,064) were genotyped with the MetaboChip array. Up to 3,495 participants had 10-yr follow-up data available in the GLACIER Study. The TC- and TG-specific GRSs were strongly associated with change in lipid levels (β = 0.02 mmol/l per effect allele per decade follow-up, P = 2.0×10−11 for TC; β = 0.02 mmol/l per effect allele per decade follow-up, P = 5.0×10−5 for TG). In individual SNP analysis, one TC locus, apolipoprotein E (APOE) rs4420638 (β = 0.12 mmol/l per effect allele per decade follow-up, P = 2.0×10−5), and two TG loci, tribbles pseudokinase 1 (TRIB1) rs2954029 (β = 0.09 mmol/l per effect allele per decade follow-up, P = 5.1×10−4) and apolipoprotein A-I (APOA1) rs6589564 (β = 0.31 mmol/l per effect allele per decade follow-up, P = 1.4×10−8), remained significantly associated with longitudinal changes for the respective traits after correction for multiple testing. An additional 12 loci were nominally associated with TC or TG changes. In replication analyses, the APOE rs4420638, TRIB1 rs2954029, and APOA1 rs6589564 associations were confirmed (P≤0.001). In summary, trait-specific GRSs are robustly associated with 10-yr changes in lipid levels and three individual SNPs were strongly associated with 10-yr changes in lipid levels.
Although large cross-sectional studies have proven highly successful in identifying gene variants related to lipid levels and other cardiometabolic traits, very few examples of well-designed longitudinal studies exist where associations between genotypes and long-term changes in lipids have been assessed. Here we undertook analyses in the GLACIER Study to determine whether the 157 previously identified lipid-associated genes variants associate with changes in blood lipid levels over 10-yr follow-up. We identified a variant in APOE that is robustly associated with total cholesterol change and two variants in TRIB1 and APOA1 respectively that are robustly associated with triglyceride change. We replicated these findings in a second Swedish cohort (the MDC Study). The identified genes had previously been associated with cardiovascular traits such as myocardial infarction or coronary heart disease; hence, these novel lipid associations provide additional insight into the pathogenesis of atherosclerotic heart and large vessel disease. By incorporating all 157 established variants into gene scores, we also observed strong associations with 10-yr lipid changes, illustrating the polygenic nature of blood lipid deterioration.
Familial cancer can be used to leverage genetic association studies. Recent genome-wide association studies have reported independent associations between seven single nucleotide polymorphisms (SNPs) and risk of glioma. The aim of this study was to investigate whether glioma cases with a positive family history of brain tumours, defined as having at least one first or second degree relative with a history of brain tumour, are associated with known glioma risk loci. 1431 glioma cases and 2868 cancer-free controls were identified from four case-control studies and two prospective cohorts from USA, Sweden, and Denmark and genotyped for seven SNPs previously reported to be associated with glioma risk in case-control designed studies. Odds ratios were calculated by unconditional logistic regression. In analyses including glioma cases with a family history of brain tumours (n=104) and control subjects free of glioma at baseline, three out of seven SNPs were associated with glioma risk; rs2736100 (5p15.33, TERT), rs4977756 (9p21.3, CDKN2A-CDKN2B), and rs6010620 (20q13.33, RTEL1). After Bonferroni correction for multiple comparisons, only one marker was statistically significantly associated with glioma risk, rs6010620 (ORtrend for the minor (A) allele, 0.39; 95% CI, 0.25–0.61; Bonferroni adjusted ptrend, 1.7×10−4). In conclusion, as previously shown for glioma regardless of family history of brain tumours, rs6010620 (RTEL1) was associated with an increased risk of glioma when restricting to cases with family history of brain tumours. These findings require confirmation in further studies with a larger number of glioma cases with a family history of brain tumours.
Glioma; brain tumours; genome-wide association study; single nucleotide polymorphism
Low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, and total cholesterol are heritable, modifiable, risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,578 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5×10−8, including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian, and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipids are often associated with cardiovascular and metabolic traits including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio, and body mass index. Our results illustrate the value of genetic data from individuals of diverse ancestries and provide insights into biological mechanisms regulating blood lipids to guide future genetic, biological, and therapeutic research.
Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiologic studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P<5×10−8 for each) to examine the role of triglycerides on risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglycerides, and show that the direction and magnitude of both are factors in determining CAD risk. Second, we consider loci with only a strong magnitude of association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol, a polymorphism's strength of effect on triglycerides is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
Obesity is associated with an increased risk of esophageal adenocarcinoma (EAC) and a decreased risk of esophageal squamous cell carcinoma (ESCC). However, little is known about the risk of EAC and ESCC related to other metabolic risk factors. We aimed to examine the risk of EAC and ESCC in relation to metabolic risk factors, separately and combined in a prospective cohort study.
The Metabolic Syndrome and Cancer cohort includes prospective cohorts in Austria, Norway and Sweden, with blood pressure, lipids, glucose and BMI available from 578 700 individuals. Relative risk (RR) for EAC and ESCC was calculated using Cox’s proportional hazards analysis for metabolic risk factors categorized into quintiles and transformed into z-scores. The standardized sum of all z-scores was used as a composite score for the metabolic syndrome (MetS).
In total, 324 histologically verified cases of esophageal cancer were identified (114 EAC, 184 ESCC and 26 with other histology). BMI was associated with an increased risk of EAC (RR 7.34 (95% confidence interval, 2.88-18.7) top versus bottom quintile) and negatively associated with the risk of ESCC (RR 0.38 (0.23-0.62)). The mean value of systolic and diastolic blood pressure (mid blood pressure) was associated with the risk of ESCC (RR 1.77 (1.37-2.29)). The composite MetS score was associated with the risk of EAC (RR 1.56 (1.19-2.05) per one unit increase of z-score) but not ESCC.
In accordance with previous studies, high BMI was associated with an increased risk of EAC and a decreased risk of ESCC. An association between high blood pressure and risk of ESCC was observed but alcohol consumption is a potential confounding factor that we were not able to adjust for in the analysis. The MetS was associated with EAC but not ESCC. However this association was largely driven by the strong association between BMI and EAC. We hypothesize that this association is more likely to be explained by factors directly related to obesity than the metabolic state of the MetS, considering that no other metabolic factor than BMI was associated with EAC.
Esophageal cancer; Esophageal adenocarcinoma; Esophageal squamous cell carcinoma; Obesity; Hypertension
Diabetes is a suspected risk factor for pancreatic cancer, but questions remain about whether it is a risk factor or a result of the disease. This study prospectively examined the association between diabetes and the risk of pancreatic adenocarcinoma in pooled data from the NCI pancreatic cancer cohort consortium (PanScan).
The pooled data included 1,621 pancreatic adenocarcinoma cases and 1,719 matched controls from twelve cohorts using a nested case–control study design. Subjects who were diagnosed with diabetes near the time (<2 years) of pancreatic cancer diagnosis were excluded from all analyses. All analyses were adjusted for age, race, gender, study, alcohol use, smoking, BMI, and family history of pancreatic cancer.
Self-reported diabetes was associated with a forty percent increased risk of pancreatic cancer (OR = 1.40, 95 % CI: 1.07, 1.84). The association differed by duration of diabetes; risk was highest for those with a duration of 2–8 years (OR = 1.79, 95 % CI: 1.25, 2.55); there was no association for those with 9+ years of diabetes (OR = 1.02, 95 % CI: 0.68, 1.52).
These findings provide support for a relationship between diabetes and pancreatic cancer risk. The absence of association in those with the longest duration of diabetes may reflect hypoinsulinemia and warrants further investigation.
Diabetes; Risk factor; Cohort consortium; Pancreatic cancer
Survival of patients with pancreatic adenocarcinoma is limited and few prognostic factors are known. We conducted a two-stage genome-wide association study (GWAS) to identify germline variants associated with survival in patients with pancreatic adenocarcinoma.
We analyzed overall survival in relation to single nucleotide polymorphisms (SNPs) among 1,005 patients from two large GWAS datasets, PanScan I and ChinaPC. Cox proportional hazards regression was used in an additive genetic model with adjustment for age, sex, clinical stage and the top four principal components of population stratification. The first stage included 642 cases of European ancestry (PanScan), from which the top SNPs (P≤10−5) were advanced to a joint analysis with 363 additional patients from China (ChinaPC).
In the first stage of cases of European descent, the top-ranked loci were at chromosomes 11p15.4, 18p11.21, and 1p36.13, tagged by rs12362504 (P=1.63×10−7), rs981621 (P=1.65×10−7), and rs16861827 (P=3.75×10−7), respectively. One-hundred thirty-one SNPs with P ≤ 10−5 were advanced to a joint analysis with cases from the ChinaPC study. In the joint analysis, the top-ranked SNP was rs10500715 (minor allele frequency, 0.37; P=1.72×10−7) on chromosome 11p15.4, which is intronic to the SET binding factor 2 (SBF2) gene. The hazard ratio (95% CI) for death was 0.74 (0.66–0.84) in PanScan I, 0.79 (0.65–0.97) in ChinaPC, and 0.76 (0.68–0.84) in the joint analysis.
Germline genetic variation in the SBF2 locus was associated with overall survival in patients with pancreatic adenocarcinoma of European and Asian ancestry. This association should be investigated in additional large patient cohorts.
Pancreatic cancer; GWAS; single nucleotide polymorphism; SET binding factor 2
Carotenoids, micronutrients in fruits and vegetables, may reduce breast cancer risk. Most, but not all, past studies of circulating carotenoids and breast cancer have found an inverse association with at least one carotenoid, although the specific carotenoid has varied across studies.
We conducted a pooled analysis of eight cohort studies comprising more than 80% of the world’s published prospective data on plasma or serum carotenoids and breast cancer, including 3055 case subjects and 3956 matched control subjects. To account for laboratory differences and examine population differences across studies, we recalibrated participant carotenoid levels to a common standard by reassaying 20 plasma or serum samples from each cohort together at the same laboratory. Using conditional logistic regression, adjusting for several breast cancer risk factors, we calculated relative risks (RRs) and 95% confidence intervals (CIs) using quintiles defined among the control subjects from all studies. All P values are two-sided.
Statistically significant inverse associations with breast cancer were observed for α-carotene (top vs bottom quintile RR = 0.87, 95% CI = 0.71 to 1.05, Ptrend = .04), β-carotene (RR = 0.83, 95% CI = 0.70 to 0.98, Ptrend = .02), lutein+zeaxanthin (RR = 0.84, 95% CI = 0.70 to 1.01, Ptrend = .05), lycopene (RR = 0.78, 95% CI = 0.62 to 0.99, Ptrend = .02), and total carotenoids (RR = 0.81, 95% CI = 0.68 to 0.96, Ptrend = .01). β-Cryptoxanthin was not statistically significantly associated with risk. Tests for heterogeneity across studies were not statistically significant. For several carotenoids, associations appeared stronger for estrogen receptor negative (ER−) than for ER+ tumors (eg, β-carotene: ER−: top vs bottom quintile RR = 0.52, 95% CI = 0.36 to 0.77, Ptrend = .001; ER+: RR = 0.83, 95% CI = 0.66 to 1.04, Ptrend = .06; Pheterogeneity = .01).
This comprehensive prospective analysis suggests women with higher circulating levels of α-carotene, β-carotene, lutein+zeaxanthin, lycopene, and total carotenoids may be at reduced risk of breast cancer.
Whole-grain foods and cereal dietary fiber intake is associated with lower body weight. This may partly result from lower energy utilization of high-fiber diets.
In the present study, the impact on ileal excretion of energy and macronutrients in response to a rye bread high-fiber diet compared to a refined wheat low-fiber diet was investigated. Furthermore, the effect of meal frequency on apparent absorption of nutrients was studied for the first time.
Ten participants that had undergone ileostomy consumed standardized iso-caloric diets, including low-fiber wheat bread (20 g dietary fiber per day) for 2 weeks followed by high-fiber rye bread (52 g dietary fiber per day) for 2 weeks. The diets were consumed in an ordinary (three meals per day) and a nibbling (seven meals per day) meal frequency in a cross-over design. Ileal effluents were collected during 24 h at the third day of each of the four dietary periods and analyzed for gross energy and nutrient contents.
The results showed that intake of rye bread high-fiber diet compared to the refined wheat low-fiber diet caused an increase in ileal excretion of energy and macronutrients. The effect was independent of meal frequency. This suggests that a high intake of rye may result in lower availability of macronutrients for small intestinal digestion and absorption. A regular intake of rye may therefore have implications for weight management.
rye bread; refined wheat; meal frequency; ileal excretion; ileostomy
To assess the association between height and risk of cancer and cancer death.
The metabolic syndrome and cancer project is a prospective pooled cohort study of 585,928 participants from seven cohorts in Austria, Norway, and Sweden. Hazard ratios (HRs) and 95 % confidence intervals (CIs) for cancer incidence and death were estimated in height categories and per 5-cm increment for each cancer site using Cox proportional hazards model.
During a mean follow-up of 12.7 years (SD = 7.2), 38,862 participants were diagnosed with cancer and 13,547 participants died of cancer. Increased height (per 5-cm increment) was associated with an increased overall cancer risk in women, HR 1.07 (95 % CI 1.06–1.09), and in men, HR 1.04 (95 % CI 1.03–1.06). The highest HR was seen for malignant melanoma in women, HR 1.17 (95 % CI 1.11–1.24), and in men HR 1.12 (95 % CI 1.08–1.19). Height was also associated with increased risk of cancer death in women, HR 1.03 (95 % CI 1.01–1.16), and in men, HR 1.03 (95 % CI 1.01–1.05). The highest HR was observed for breast cancer death in postmenopausal women (>60 years), HR 1.10 (95 % CI 1.00–1.21), and death from renal cell carcinoma in men, HR 1.18 (95 % CI 1.07–1.30). All these associations were independent of body mass index.
Height was associated with risk of cancer and cancer death indicating that factors related to height such as hormonal and genetic factors stimulate both cancer development and progression.
Body stature; Body height; Epidemiology; Cancer risk; Cohort study
The role of estrogen and progesterone in the development of endometrial cancer is well documented. Few studies have examined the association of genetic variants in sex hormone-related genes with endometrial cancer risk.
We conducted a case-control study nested within three cohorts to examine the association of endometrial cancer risk with polymorphisms in hormone-related genes among 391 cases (92% postmenopausal at diagnosis) and 712 individually-matched controls. We also examined the association of these polymorphisms with circulating levels of sex hormones and SHBG in a cross-sectional analysis including 596 healthy postmenopausal women at blood donation (controls from this nested case-control study and from a nested case-control study of breast cancer in one of the three cohorts).
Adjusting for endometrial cancer risk factors, the A allele of rs4775936 in CYP19 was significantly associated (ORper allele = 1.22, 95% CI = 1.01–1.47, ptrend = 0.04), while the T allele of rs10046 was marginally associated with increased risk of endometrial cancer (ORper allele = 1.20, 95% CI = 0.99 – 1.45, ptrend = 0.06). PGR rs1042838 was also marginally associated with risk (ORper allele = 1.25, 95% CI = 0.96–1.61, ptrend = 0.09). No significant association was found for the other polymorphisms, i.e. CYP1B1 rs1800440 and rs1056836, UGT1A1 rs8175347, SHBG rs6259 and ESR1 rs2234693. Rs8175347 was significantly associated with postmenopausal levels of estradiol, free estradiol and estrone and rs6259 with SHBG and estradiol.
Our findings support an association between genetic variants in CYP19, and possibly PGR, and risk of endometrial cancer.
endometrial cancer; estrogen; sex hormone-binding globulin; progesterone receptor; single nucleotide polymorphism
We developed an absolute risk model to identify individuals in the general population at elevated risk of pancreatic cancer.
Patients and Methods
Using data on 3,349 cases and 3,654 controls from the PanScan Consortium, we developed a relative risk model for men and women of European ancestry based on non-genetic and genetic risk factors for pancreatic cancer. We estimated absolute risks based on these relative risks and population incidence rates.
Our risk model included current smoking (multivariable adjusted odds ratio (OR) and 95% confidence interval: 2.20 [1.84–2.62]), heavy alcohol use (>3 drinks/day) (OR: 1.45 [1.19–1.76]), obesity (body mass index >30 kg/m2) (OR: 1.26 [1.09–1.45]), diabetes >3 years (nested case-control OR: 1.57 [1.13–2.18], case-control OR: 1.80 [1.40–2.32]), family history of pancreatic cancer (OR: 1.60 [1.20–2.12]), non-O ABO genotype (AO vs. OO genotype) (OR: 1.23 [1.10–1.37]) to (BB vs. OO genotype) (OR 1.58 [0.97–2.59]), rs3790844(chr1q32.1) (OR: 1.29 [1.19–1.40]), rs401681(5p15.33) (OR: 1.18 [1.10–1.26]) and rs9543325(13q22.1) (OR: 1.27 [1.18–1.36]). The areas under the ROC curve for risk models including only non-genetic factors, only genetic factors, and both non-genetic and genetic factors were 58%, 57% and 61%, respectively. We estimate that fewer than 3/1,000 U.S. non-Hispanic whites have more than a 5% predicted lifetime absolute risk.
Although absolute risk modeling using established risk factors may help to identify a group of individuals at higher than average risk of pancreatic cancer, the immediate clinical utility of our model is limited. However, a risk model can increase awareness of the various risk factors for pancreatic cancer, including modifiable behaviors.
Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age2, sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (Pinteraction = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, Pinteraction = 0.014 vs. n = 71,611, Pinteraction = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (Pinteraction = 0.003) and the SEC16B rs10913469 (Pinteraction = 0.025) variants showed evidence of SNP × physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal.
We undertook analyses in 111,421 adults of European descent to examine whether physical activity diminishes the genetic risk of obesity predisposed by 12 single nucleotide polymorphisms, as previously reported in a study of 20,000 UK adults (Li et al, PLoS Med. 2010). Although the study by Li et al is widely cited, the original report has not been replicated to our knowledge. Therefore, we sought to confirm or refute the original study's findings in a combined analysis of 111,421 adults. Our analyses yielded a statistically significant interaction effect (Pinteraction = 0.015), confirming the original study's results; we also identified an interaction between the FTO locus and physical activity (Pinteraction = 0.003), verifying previous analyses (Kilpelainen et al, PLoS Med., 2010), and we detected a novel interaction between the SEC16B locus and physical activity (Pinteraction = 0.025). We also examined the power constraints of interaction analyses, thereby demonstrating that sources of within- and between-study heterogeneity and the manner in which data are treated can inhibit the detection of interaction effects in meta-analyses that combine many cohorts with varying characteristics. This suggests that combining many small studies that have measured environmental exposures differently may be relatively inefficient for the detection of gene × environment interactions.
Sex hormones play a key role in the development of breast cancer. Certain polymorphic variants (SNPs and repeat polymorphisms) in hormone-related genes are associated with sex hormone levels. However, the relationship observed between these genetic variants and breast cancer risk has been inconsistent. We conducted a case-control study nested within two prospective cohorts to assess the relationship between specific genetic variants in hormone-related genes and breast cancer risk. In total, 1164 cases and 2111 individually-matched controls were included in the study. We did not observe an association between potential functional genetic polymorphisms in the estrogen pathway, SHBG rs6259, ESR1 rs2234693, CYP19 rs10046 and rs4775936, and UGT1A1 rs8175347, or the progesterone pathway, PGR rs1042838, with the risk of breast cancer. Our results suggest that these genetic variants do not have a strong effect on breast cancer risk.
Four loci have been associated with pancreatic cancer through genome-wide association studies (GWAS). Pathway-based analysis of GWAS data is a complementary approach to identify groups of genes or biological pathways enriched with disease-associated single-nucleotide polymorphisms (SNPs) whose individual effect sizes may be too small to be detected by standard single-locus methods. We used the adaptive rank truncated product method in a pathway-based analysis of GWAS data from 3851 pancreatic cancer cases and 3934 control participants pooled from 12 cohort studies and 8 case–control studies (PanScan). We compiled 23 biological pathways hypothesized to be relevant to pancreatic cancer and observed a nominal association between pancreatic cancer and five pathways (P < 0.05), i.e. pancreatic development, Helicobacter pylori lacto/neolacto, hedgehog, Th1/Th2 immune response and apoptosis (P = 2.0 × 10−6, 1.6 × 10−5, 0.0019, 0.019 and 0.023, respectively). After excluding previously identified genes from the original GWAS in three pathways (NR5A2, ABO and SHH), the pancreatic development pathway remained significant (P = 8.3 × 10−5), whereas the others did not. The most significant genes (P < 0.01) in the five pathways were NR5A2, HNF1A, HNF4G and PDX1 for pancreatic development; ABO for H.
pylori lacto/neolacto; SHH for hedgehog; TGFBR2 and CCL18 for Th1/Th2 immune response and MAPK8 and BCL2L11 for apoptosis. Our results provide a link between inherited variation in genes important for pancreatic development and cancer and show that pathway-based approaches to analysis of GWAS data can yield important insights into the collective role of genetic risk variants in cancer.
Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10−8), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
Men and women differ substantially regarding height, weight, and body fat. Interestingly, previous work detecting genetic effects for waist-to-hip ratio, to assess body fat distribution, has found that many of these showed sex-differences. However, systematic searches for sex-differences in genetic effects have not yet been conducted. Therefore, we undertook a genome-wide search for sexually dimorphic genetic effects for anthropometric traits including 133,723 individuals in a large meta-analysis and followed promising variants in further 137,052 individuals, including a total of 94 studies. We identified seven loci with significant sex-difference including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were significant in women, but not in men. Of interest is that sex-difference was only observed for waist phenotypes, but not for height or body-mass-index. We found no evidence for sex-differences with opposite effect direction for men and women. The PPARG locus is of specific interest due to its link to diabetes genetics and therapy. Our findings demonstrate the importance of investigating sex differences, which may lead to a better understanding of disease mechanisms with a potential relevance to treatment options.