Inflammatory potential of the diet and risk of colorectal cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) study

Pro-inflammatory diets are associated with risk of developing colorectal cancer (CRC), however inconsistencies exist in subsite- and sex-specific associations. The relationship between CRC and combined lifestyle-related factors that contribute towards a low-grade inflammatory profile has not yet been explored. We examined the association between the dietary inflammatory potential and an inflammatory profile and CRC risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. This cohort included 476,160 participants followed-up of 14 years and 5,991 incident CRC cases (3,897 colon and 2,094 rectal tumours). Dietary inflammatory potential was estimated using an Inflammatory Score of the Diet (ISD). An Inflammatory Profile Score (IPS) was constructed, incorporating the ISD, physical activity level and abdominal obesity. The associations between the ISD and CRC and IPS and CRC were assessed using multivariable regression models. More pro- inflammatory diets were related to a higher CRC risk, particularly for colon cancer; Hazar Ratio (HR) for highest versus lowest ISD quartile was 1.15 (95% confidence interval (CI) 1.04-1.27) for CRC, 1.24 (95% CI 1.09-1.41) for colon cancer and 0.99 (95% CI 0.83-1.17) for rectal cancer. Associations were more pronounced in men and not significant in women. The IPS was associated with CRC risk, particularly colon cancer among men; HRs for the highest versus lowest IPS were 1.62 (95% CI 1.31- 2.01) for colon cancer overall and 2.11 (95% CI 1.50-2.97) for colon cancer in men. This study shows that more pro-inflammatory diets and a more inflammatory profile are associated with higher risk of CRC, principally colon cancer and in men. This article is protected by copyright. All rights reserved

Interaction between genes and macronutrient intake on the risk of developing type 2 diabetes: systematic review and findings from (EPIC)-InterAct

Background: Gene-diet interactions have been reported to contribute to the development of type 2 diabetes (T2D). However, to our knowledge, few examples have been consistently replicated to date. Objective: We aimed to identify existing evidence for gene-macronutrient interactions and T2D and to examine the reported interactions in a large-scale study. Design: We systematically reviewed studies reporting gene-macronutrient interactions and T2D. We searched the MEDLINE, Human Genome Epidemiology Network, and WHO International Clinical Trials Registry Platform electronic databases to identify studies published up to October 2015. Eligibility criteria included assessment of macronutrient quantity (e.g., total carbohydrate) or indicators of quality (e.g., dietary fiber) by use of self-report or objective biomarkers of intake. Interactions identified in the review were subsequently examined in the EPIC (European Prospective Investigation into Cancer)-InterAct case-cohort study (n = 21,148, with 9403 T2D cases; 8 European countries). Prentice-weighted Cox regression was used to estimate country-specific HRs, 95% CIs, and P-interaction values, which were then pooled by random-effects meta-analysis. A primary model was fitted by using the same covariates as reported in the published studies, and a second model adjusted for additional covariates and estimated the effects of isocaloric macronutrient substitution. Results: Thirteen observational studies met the eligibility criteria (n < 1700 cases). Eight unique interactions were reported to be significant between macronutrients [carbohydrate, fat, saturated fat, dietary fiber, and glycemic load derived from self-report of dietary intake and circulating n–3 (ω-3) polyunsaturated fatty acids] and genetic variants in or near transcription factor 7–like 2 (TCF7L2), gastric inhibitory polypeptide receptor (GIPR), caveolin 2 (CAV2), and peptidase D (PEPD) (P-interaction < 0.05). We found no evidence of interaction when we tried to replicate previously reported interactions. In addition, no interactions were detected in models with additional covariates. Conclusions: Eight gene-macronutrient interactions were identified for the risk of T2D from the literature. These interactions were not replicated in the EPIC-InterAct study, which mirrored the analyses undertaken in the original reports. Our findings highlight the importance of independent replication of reported interactions

Circulating concentrations of vitamin D in relation to pancreatic cancer risk in European populations

Evidence from in vivo, in vitro and ecological studies are suggestive of a protective effect of vitamin D against pancreatic cancer (PC). However, this has not been confirmed by analytical epidemiological studies. We aimed to examine the association between pre-diagnostic circulating vitamin D concentrations and PC incidence in European populations. We conducted a pooled nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Nord-Trøndelag Health Study's second survey (HUNT2) cohorts. In total, 738 primary incident PC cases (EPIC n = 626; HUNT2 n = 112; median follow-up = 6.9 years) were matched to 738 controls. Vitamin D [25(OH)D2 and 25(OH)D3 combined] concentrations were determined using isotope-dilution liquid chromatography-tandem mass spectrometry. Conditional logistic regression models with adjustments for body mass index and smoking habits were used to estimate incidence rate ratios (IRRs) and 95% confidence intervals (95%CI). Compared with a reference category of >50 to 75 nmol/L vitamin D, the IRRs (95% CIs) were 0.71 (0.42–1.20); 0.94 (0.72–1.22); 1.12 (0.82–1.53) and 1.26 (0.79–2.01) for clinically pre-defined categories of ≤25; >25 to 50; >75 to 100; and >100 nmol/L vitamin D, respectively (p for trend = 0.09). Corresponding analyses by quintiles of season-standardized vitamin D concentrations also did not reveal associations with PC risk (p for trend = 0.23). Although these findings among participants from the largest combination of European cohort studies to date show increasing effect estimates of PC risk with increasing pre-diagnostic concentrations of vitamin D, they are not statistically significant

Interaction between genes and macronutrient intake on the risk of developing type 2 diabetes: systematic review and findings from EPIC-InterAct

Background: Gene-diet interactions have been reported to contribute to the development of type 2 diabetes (T2D). However, to our knowledge, few examples have been consistently replicated to date. Objective: We aimed to identify existing evidence for genemacronutrient interactions and T2D and to examine the reported interactions in a large-scale study. Design: We systematically reviewed studies reporting genemacronutrient interactions and T2D. We searched the MEDLINE, Human Genome Epidemiology Network, and WHO International Clinical Trials Registry Platform electronic databases to identify studies published up to October 2015. Eligibility criteria included assessment of macronutrient quantity (e.g., total carbohydrate) or indicators of quality (e.g., dietary fiber) by use of self-report or objective biomarkers of intake. Interactions identified in the review were subsequently examined in the EPIC (European Prospective Investigation into Cancer)-InterAct case-cohort study (n = 21,148, with 9403 T2D cases; 8 European countries). Prentice-weighted Cox regression was used to estimate country-specific HRs, 95% CIs, and P-interaction values, which were then pooled by random-effects meta-analysis. A primary model was fitted by using the same covariates as reported in the published studies, and a second model adjusted for additional covariates and estimated the effects of isocaloric macronutrient substitution. Results: Thirteen observational studies met the eligibility criteria (n , 1700 cases). Eight unique interactions were reported to be significant between macronutrients [carbohydrate, fat, saturated fat, dietary fiber, and glycemic load derived from self-report of dietary intake and circulating n–3 (v-3) polyunsaturated fatty acids] and genetic variants in or near transcription factor 7–like 2 (TCF7L2), gastric inhibitory polypeptide receptor (GIPR), caveolin 2 (CAV2), and peptidase D (PEPD) (P-interaction , 0.05). We found no evidence of interaction when we tried to replicate previously reported interactions. In addition, no interactions were detected in models with additional covariates. Conclusions: Eight gene-macronutrient interactions were identified for the risk of T2D from the literature. These interactions were not replicated in the EPIC-InterAct study, which mirrored the analyses undertaken in the original reports. Our findings highlight the importance of independent replication of reported interactions.Funding for the InterAct project was provided by the EU FP6 programme (grant number LSHM_CT_2006_037197). In addition, InterAct investigators acknowledge funding from the following agencies: Medical Research Council Epidemiology Unit MC_UU_12015/1 and MC_UU_12015/5, and Medical Research Council Human Nutrition Research MC_UP_A090_1006 and Cambridge Lipidomics Biomarker Research Initiative G0800783. IS, JWJB and YTvdS: Verification of diabetes cases was additionally funded by NL Agency grant IGE05012 and an Incentive Grant from the Board of the UMC Utrecht (The Netherlands; HBBdM, AMWS and DLvdA: Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); German Federal Ministry of Education and Research (BMBF) and the State of Brandenburg to the German Center for Diabetes Research (DZD); FLC: Cancer Research UK C8221/A19170 and C570/A16491 and Medical Research Council MR/M012190/1; PWF: Swedish Research Council, Novo Nordisk, Swedish Heart Lung Foundation, Swedish Diabetes Association; JH, KO and AT: Danish Cancer Society; RK: Deutsche Krebshilfe; SP: Associazione Italiana per la Ricerca sul Cancro; JRQ: Asturias Regional Government; MT: Health Research Fund (FIS) of the Spanish Ministry of Health; Navarre Regional Government; the CIBER en Epidemiología y Salud Pública (CIBERESP), Spain; Murcia Regional Government (Nº 6236); RT: AIRE-ONLUS Ragusa, AVIS-Ragusa, Sicilian Regional Government; Red Temática de Investigación Cooperativa en Cáncer of the Instituto de Salud Carlos III (ISCIII RTICC RD12/0036/0018), cofounded by FEDER funds/European Regional Development Fund (ERDF); German Cancer Aid, German Ministry of Research (BMBF); Compagnia di San Paolo; Imperial College Biomedical Research Centre

Associations between dietary inflammatory scores and biomarkers of inflammation in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort

Background Since the first version of the dietary inflammatory index (DII®) developed in the past decade, several other versions have been developed. However, to date no study has attempted to compare these versions with respect to their associations with biomarkers of inflammation. Objective We aimed to investigate the relationship between four dietary inflammatory scores [DII, two energy-adjusted derivatives (E-DII and E-DIIr), and the Inflammatory Score of the Diet (ISD)], and circulating levels of several inflammatory markers and adipokines. Methods This study included 17 637 participants from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with at least one marker of inflammation measured in blood. Associations between the four scores and C-reactive protein (CRP), interleukin (IL)6, IL10, IL1RA, tumor necrosis factor-α (TNFα), soluble tumor necrosis factor receptor-1 (sTNFR1), sTNFR2, leptin, soluble leptin receptor (sLeptin R), adiponectin, and High Molecular Weight (HMW) adiponectin were evaluated using multivariable linear regressions adjusted for potential confounders. Results Positive associations were observed between the four dietary inflammatory scores and levels of CRP, IL6, sTNFR1, sTNFR2 and leptin. However, only the DII and the ISD were positively associated with IL1RA levels and only the DII and the E-DIIr were positively associated with TNFα levels. The proportion of variance of each biomarker explained by the scores was lower than 2%, which was equivalent to the variance explained by smoking status but much lower than that explained by body mass index. Conclusions Our results suggest that the four dietary inflammatory scores were associated with some biomarkers of inflammation and could be used to assess the inflammatory potential of diet in European adults but are not sufficient to capture the inflammatory status of an individual. These findings can help to better understand the inflammatory potential of diet, but they need to be replicated in studies with repeated dietary measurements

Corneal confocal microscopy detects a reduction in corneal endothelial cells and nerve fibres in patients with acute ischemic stroke

YesEndothelial dysfunction and damage underlie cerebrovascular disease and ischemic stroke. We undertook corneal confocal microscopy (CCM) to quantify corneal endothelial cell and nerve morphology in 146 patients with an acute ischemic stroke and 18 age-matched healthy control participants. Corneal endothelial cell density was lower (P<0.001) and endothelial cell area (P<0.001) and perimeter (P<0.001) were higher, whilst corneal nerve fbre density (P<0.001), corneal nerve branch density (P<0.001) and corneal nerve fbre length (P=0.001) were lower in patients with acute ischemic stroke compared to controls. Corneal endothelial cell density, cell area and cell perimeter correlated with corneal nerve fber density (P=0.033, P=0.014, P=0.011) and length (P=0.017, P=0.013, P=0.008), respectively. Multiple linear regression analysis showed a signifcant independent association between corneal endothelial cell density, area and perimeter with acute ischemic stroke and triglycerides. CCM is a rapid non-invasive ophthalmic imaging technique, which could be used to identify patients at risk of acute ischemic stroke.Qatar National Research Fund Grant BMRP2003865

CA19‐9 and apolipoprotein‐A2 isoforms as detection markers for pancreatic cancer: a prospective evaluation

Recently, we identified unique processing patterns of apolipoprotein A2 (ApoA2) in patients with pancreatic cancer. Our study provides a first prospective evaluation of an ApoA2 isoform (“ApoA2‐ATQ/AT”), alone and in combination with carbohydrate antigen 19–9 (CA19‐9), as an early detection biomarker for pancreatic cancer. We performed ELISA measurements of CA19‐9 and ApoA2‐ATQ/AT in 156 patients with pancreatic cancer and 217 matched controls within the European EPIC cohort, using plasma samples collected up to 60 months prior to diagnosis. The detection discrimination statistics were calculated for risk scores by strata of lag‐time. For CA19‐9, in univariate marker analyses, C‐statistics to distinguish future pancreatic cancer patients from cancer‐free individuals were 0.80 for plasma taken ≤6 months before diagnosis, and 0.71 for >6–18 months; for ApoA2‐ATQ/AT, C‐statistics were 0.62, and 0.65, respectively. Joint models based on ApoA2‐ATQ/AT plus CA19‐9 significantly improved discrimination within >6–18 months (C = 0.74 vs. 0.71 for CA19‐9 alone, p = 0.022) and ≤ 18 months (C = 0.75 vs. 0.74, p = 0.022). At 98% specificity, and for lag times of ≤6, >6–18 or ≤ 18 months, sensitivities were 57%, 36% and 43% for CA19‐9 combined with ApoA2‐ATQ/AT, respectively, vs. 50%, 29% and 36% for CA19‐9 alone. Compared to CA19‐9 alone, the combination of CA19‐9 and ApoA2‐ATQ/AT may improve detection of pancreatic cancer up to 18 months prior to diagnosis under usual care, and may provide a useful first measure for pancreatic cancer detection prior to imaging

CA19‐9 and apolipoprotein‐A2 isoforms as detection markers for pancreatic cancer: a prospective evaluation

Recently, we identified unique processing patterns of apolipoprotein A2 (ApoA2) in patients with pancreatic cancer. Our study provides a first prospective evaluation of an ApoA2 isoform (“ApoA2‐ATQ/AT”), alone and in combination with carbohydrate antigen 19–9 (CA19‐9), as an early detection biomarker for pancreatic cancer. We performed ELISA measurements of CA19‐9 and ApoA2‐ATQ/AT in 156 patients with pancreatic cancer and 217 matched controls within the European EPIC cohort, using plasma samples collected up to 60 months prior to diagnosis. The detection discrimination statistics were calculated for risk scores by strata of lag‐time. For CA19‐9, in univariate marker analyses, C‐statistics to distinguish future pancreatic cancer patients from cancer‐free individuals were 0.80 for plasma taken ≤6 months before diagnosis, and 0.71 for &gt;6–18 months; for ApoA2‐ATQ/AT, C‐statistics were 0.62, and 0.65, respectively. Joint models based on ApoA2‐ATQ/AT plus CA19‐9 significantly improved discrimination within &gt;6–18 months (C = 0.74 vs. 0.71 for CA19‐9 alone, p = 0.022) and ≤ 18 months (C = 0.75 vs. 0.74, p = 0.022). At 98% specificity, and for lag times of ≤6, &gt;6–18 or ≤ 18 months, sensitivities were 57%, 36% and 43% for CA19‐9 combined with ApoA2‐ATQ/AT, respectively, vs. 50%, 29% and 36% for CA19‐9 alone. Compared to CA19‐9 alone, the combination of CA19‐9 and ApoA2‐ATQ/AT may improve detection of pancreatic cancer up to 18 months prior to diagnosis under usual care, and may provide a useful first measure for pancreatic cancer detection prior to imaging