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Background : European vaccine effectiveness (VE) studies initiated and funded by the European Centre for Disease Prevention and Control (ECDC) and the European Commission (I-MOVE-COVID-19) include 38 hospitals across 13 European countries. Using a test-negative case–control design, we aimed to measure VE against hospitalisation due to COVID-19 in vaccination target group(s) overall and by vaccine product. Methods : Between 28 December 2020 and 06 June 2021, we recruited patients hospitalised with severe acute respiratory illness (SARI ; ECDC case definition). Cases were SARI patients, laboratory-confirmed SARS-CoV-2 positive by RT-PCR within 24 hrs of admission or within the previous 2 weeks. Controls were SARI patients who were RT-PCR negative for SARSCoV-2 at admission. We pooled available data received from 34 hospitals in eight countries, and estimated VE in those aged ≥65 years using logistic regression, adjusting for study site (as fixed effect), swab date, age and chronic condition. Results : We included 1, 670 SARI patients (1, 095 cases, 575 controls). Seventynine cases (7%) and 244 controls (42%) were vaccinated ; 73% (235/323) with Pfizer–BioNTech vaccine. Adjusted VE (aVE) for one and two doses of Pfizer–BioNTech was 69% (95%CI: 44–82) and 93% (95%CI: 85– 97), respectively (sample size was too small to estimate aVE by other vaccine products). For one dose of Pfizer–BioNTech, aVE was 73% (95%CI: 49– 86) in those aged 65–79 years and 64% (30–82) in those ≥80 years. For two doses in these age-groups, aVE was 97% (95%CI: 86–99) and 85% (95%CI: 66–94), respectively. Conclusions : Our results suggest good protection against severe COVID-19 conferred by one and two doses of Pfizer–BioNTech vaccine in adults ≥65 years.

Emerging evidence suggests that a metabolic profile associated with obesity may be a more relevant risk factor for some cancers than adiposity per se. Basal metabolic rate (BMR) is an indicator of overall body metabolism and may be a proxy for the impact of a specific metabolic profile on cancer risk. Therefore, we investigated the association of predicted BMR with incidence of 13 obesity-related cancers in the European Prospective Investigation into Cancer and Nutrition (EPIC). BMR at baseline was calculated using the WHO/FAO/UNU equations and the relationships between BMR and cancer risk were investigated using multivariable Cox proportional hazards regression models. A total of 141,295 men and 317,613 women, with a mean follow-up of 14 years were included in the analysis. Overall, higher BMR was associated with a greater risk for most cancers that have been linked with obesity. However, among normal weight participants, higher BMR was associated with elevated risks of esophageal adenocarcinoma (hazard ratio per 1-standard deviation change in BMR [HR1-SD]: 2.46; 95% CI 1.20; 5.03) and distal colon cancer (HR1-SD: 1.33; 95% CI 1.001; 1.77) among men and with proximal colon (HR1-SD: 1.16; 95% CI 1.01; 1.35), pancreatic (HR1-SD: 1.37; 95% CI 1.13; 1.66), thyroid (HR1-SD: 1.65; 95% CI 1.33; 2.05), postmenopausal breast (HR1-SD: 1.17; 95% CI 1.11; 1.22) and endometrial (HR1-SD: 1.20; 95% CI 1.03; 1.40) cancers in women. These results indicate that higher BMR may be an indicator of a metabolic phenotype associated with risk of certain cancer types, and may be a useful predictor of cancer risk independent of body fatness. © 2019 International Agency for Research on Cancer (IARC/WHO); licensed by UICC

Purpose: Advanced glycation end products (AGEs) can be formed in foods by the reaction of reducing sugars with proteins, and have been shown to induce insulin resistance and obesity in experimental studies. We examined the association between dietary AGEs intake and changes in body weight in adults over an average of 5 years of follow-up. Methods: A total of 255,170 participants aged 25–70 years were recruited in ten European countries (1992–2000) in the PANACEA study (Physical Activity, Nutrition, Alcohol, Cessation of smoking, Eating out of home in relation to Anthropometry), a sub-cohort of the EPIC (European Prospective Investigation into Cancer and Nutrition). Body weight was measured at recruitment and self-reported between 2 and 11 years later depending on the study center. A reference database for AGEs was used containing UPLC–MS/MS-measured Nε-(carboxymethyl)-lysine (CML), Nε-(1-carboxyethyl)-lysine (CEL), and Nδ-(5-hydro-5-methyl-4-imidazolon-2-yl)-ornithine (MG-H1) in 200 common European foods. This reference database was matched to foods and decomposed recipes obtained from country-specific validated dietary questionnaires in EPIC and intake levels of CEL, CML, and MG-H1 were estimated. Associations between dietary AGEs intake and body weight change were estimated separately for each of the three AGEs using multilevel mixed linear regression models with center as random effect and dietary AGEs intake and relevant confounders as fixed effects. Results: A one-SD increment in CEL intake was associated with 0.111 kg (95% CI 0.087–0.135) additional weight gain over 5 years. The corresponding additional weight gain for CML and MG-H1 was 0.065 kg (0.041–0.089) and 0.034 kg (0.012, 0.057), respectively. The top six food groups contributing to AGEs intake, with varying proportions across the AGEs, were cereals/cereal products, meat/processed meat, cakes/biscuits, dairy, sugar and confectionary, and fish/shellfish. Conclusion: In this study of European adults, higher intakes of AGEs were associated with marginally greater weight gain over an average of 5 years of follow-up. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

Background: High carbohydrate intake raises blood triglycerides, glucose, and insulin; reduces HDLs; and may increase risk of coronary heart disease (CHD). Epidemiological studies indicate that high dietary glycemic index (GI) and glycemic load (GL) are associated with increased CHD risk. Objectives: The aim of this study was to determine whether dietary GI, GL, and available carbohydrates are associated with CHD risk in both sexes. Methods: This large prospective study-the European Prospective Investigation into Cancer and Nutrition-consisted of 338,325 participants who completed a dietary questionnaire. HRs with 95% CIs for a CHD event, in relation to intake of GI, GL, and carbohydrates, were estimated using covariate-adjusted Cox proportional hazard models. Results: After 12.8 y (median), 6378 participants had experienced a CHD event. High GL was associated with greater CHD risk [HR 1.16 (95% CI: 1.02, 1.31) highest vs. lowest quintile, p-trend 0.035; HR 1.18 (95% CI: 1.07, 1.29) per 50 g/day of GL intake]. The association between GL and CHD risk was evident in subjects with BMI (in kg/m2) =25 [HR: 1.22 (95% CI: 1.11, 1.35) per 50 g/d] but not in those with BMI

Source at https://doi.org/10.18632/aging.101900. Differences in health status by socioeconomic position (SEP) tend to be more evident at older ages, suggesting the involvement of a biological mechanism responsive to the accumulation of deleterious exposures across the lifespan. DNA methylation (DNAm) has been proposed as a biomarker of biological aging that conserves memory of endogenous and exogenous stress during life. We examined the association of education level, as an indicator of SEP, and lifestyle-related variables with four biomarkers of age-dependent DNAm dysregulation: the total number of stochastic epigenetic mutations (SEMs) and three epigenetic clocks (Horvath, Hannum and Levine), in 18 cohorts spanning 12 countries. The four biological aging biomarkers were associated with education and different sets of risk factors independently, and the magnitude of the effects differed depending on the biomarker and the predictor. On average, the effect of low education on epigenetic aging was comparable with those of other lifestyle-related risk factors (obesity, alcohol intake), with the exception of smoking, which had a significantly stronger effect. Our study shows that low education is an independent predictor of accelerated biological (epigenetic) aging and that epigenetic clocks appear to be good candidates for disentangling the biological pathways underlying social inequalities in healthy aging and longevity.

Background: There is uncertainty about the relevance of animal foods to the pathogenesis of ischemic heart disease (IHD). We examined meat, fish, dairy products, and eggs and risk for IHD in the pan-European EPIC cohort (European Prospective Investigation Into Cancer and Nutrition). Methods: In this prospective study of 409 885 men and women in 9 European countries, diet was assessed with validated questionnaires and calibrated with 24-hour recalls. Lipids and blood pressure were measured in a subsample. During a mean of 12.6 years of follow-up, 7198 participants had a myocardial infarction or died of IHD. The relationships of animal foods with risk were examined with Cox regression with adjustment for other animal foods and relevant covariates. Results: The hazard ratio (HR) for IHD was 1.19 (95% CI, 1.06-1.33) for a 100-g/d increment in intake of red and processed meat, and this remained significant after exclusion of the first 4 years of follow-up (HR, 1.25 [95% CI, 1.09-1.42]). Risk was inversely associated with intakes of yogurt (HR, 0.93 [95% CI, 0.89-0.98] per 100-g/d increment), cheese (HR, 0.92 [95% CI, 0.86-0.98] per 30-g/d increment), and eggs (HR, 0.93 [95% CI, 0.88-0.99] per 20-g/d increment); the associations with yogurt and eggs were attenuated and nonsignificant after exclusion of the first 4 years of follow-up. Risk was not significantly associated with intakes of poultry, fish, or milk. In analyses modeling dietary substitutions, replacement of 100 kcal/d from red and processed meat with 100 kcal/d from fatty fish, yogurt, cheese, or eggs was associated with ≈20% lower risk of IHD. Consumption of red and processed meat was positively associated with serum non-high-density lipoprotein cholesterol concentration and systolic blood pressure, and consumption of cheese was inversely associated with serum non-high-density lipoprotein cholesterol. Conclusions: Risk for IHD was positively associated with consumption of red and processed meat and inversely associated with consumption of yogurt, cheese, and eggs, although the associations with yogurt and eggs may be influenced by reverse causation bias. It is not clear whether the associations with red and processed meat and cheese reflect causality, but they were consistent with the associations of these foods with plasma non-high-density lipoprotein cholesterol and for red and processed meat with systolic blood pressure, which could mediate such effects. © 2018 American Heart Association, Inc.

Importance: Soft drinks are frequently consumed, but whether this consumption is associated with mortality risk is unknown and has been understudied in European populations to date. Objective: To examine the association between total, sugar-sweetened, and artificially sweetened soft drink consumption and subsequent total and cause-specific mortality. Design, Setting, and Participants: This population-based cohort study involved participants (n = 451743 of the full cohort) in the European Prospective Investigation into Cancer and Nutrition (EPIC), an ongoing, large multinational cohort of people from 10 European countries (Denmark, France, Germany, Greece, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom), with participants recruited between January 1, 1992, and December 31, 2000. Excluded participants were those who reported cancer, heart disease, stroke, or diabetes at baseline; those with implausible dietary intake data; and those with missing soft drink consumption or follow-up information. Data analyses were performed from February 1, 2018, to October 1, 2018. Exposure: Consumption of total, sugar-sweetened, and artificially sweetened soft drinks. Main Outcomes and Measures: Total mortality and cause-specific mortality. Hazard ratios (HRs) and 95% CIs were estimated using multivariable Cox proportional hazards regression models adjusted for other mortality risk factors. Results: In total, 521 330 individuals were enrolled. Of this total, 451743 (86.7%) were included in the study, with a mean (SD) age of 50.8 (9.8) years and with 321081 women (71.1%). During a mean (range) follow-up of 16.4 (11.1 in Greece to 19.2 in France) years, 41693 deaths occurred. Higher all-cause mortality was found among participants who consumed 2 or more glasses per day (vs consumers of

BACKGROUND: Social inequalities in the prevalence of childhood overweight and obesity are well-established, but less is known about when the social gradient first emerges and how it evolves across childhood and adolescence.OBJECTIVE: This study examines maternal education differentials in children's body mass trajectories in infancy, childhood and adolescence using data from four contemporary European child cohorts.METHODS: Prospective data on children's body mass index (BMI) were obtained from four cohort studies-Generation XXI (G21-Portugal), Growing Up in Ireland (GUI) infant and child cohorts, and the Millennium Cohort Study (MCS-UK)-involving a total sample of 41,399 children and 120,140 observations. Children's BMI trajectories were modelled by maternal education level using mixed-effect models.RESULTS: Maternal educational inequalities in children's BMI were evident as early as three years of age. Children from lower maternal educational backgrounds were characterised by accelerated BMI growth, and the extent of the disparity was such that boys from primary-educated backgrounds measured 0.42 kg/m2 (95% CI 0.24, 0.60) heavier at 7 years of age in G21, 0.90 kg/m2 (95% CI 0.60, 1.19) heavier at 13 years of age in GUI and 0.75 kg/m2 (95% CI 0.52, 0.97) heavier in MCS at 14 years of age. The corresponding figures for girls were 0.71 kg/m2 (95% CI 0.50, 0.91), 1.31 kg/m2 (95% CI 1.00, 1.62) and 0.76 kg/m2 (95% CI 0.53, 1.00) in G21, GUI and MCS, respectively.CONCLUSIONS: Maternal education is a strong predictor of BMI across European nations. Socio-economic differentials emerge early and widen across childhood, highlighting the need for early intervention.

Background Chronic inflammation plays a critical role in the pathogenesis of the 2 major types of gastric cancer. Several foods, nutrients, and nonnutrient food components seem to be involved in the regulation of chronic inflammation. Objective We assessed the association between the inflammatory potential of the diet and the risk of gastric carcinoma, overall and for the 2 major subsites: cardia cancers and noncardia cancers. Design A total of 476,160 subjects (30% men, 70% women) from the European Investigation into Cancer and Nutrition (EPIC) study were followed for 14 y, during which 913 incident cases of gastric carcinoma were identified, including 236 located in the cardia, 341 in the distal part of the stomach (noncardia), and 336 with overlapping or unknown tumor site. The dietary inflammatory potential was assessed by means of an inflammatory score of the diet (ISD), calculated with the use of 28 dietary components and their corresponding inflammatory scores. The association between the ISD and gastric cancer risk was estimated by HRs and 95% CIs calculated by multivariate Cox regression models adjusted for confounders. Results The inflammatory potential of the diet was associated with an increased risk of gastric cancer. The HR (95% CI) for each increase in 1 SD of the ISD were 1.25 (1.12, 1.39) for all gastric cancers, 1.30 (1.06, 1.59) for cardia cancers, and 1.07 (0.89, 1.28) for noncardia cancers. The corresponding values for the highest compared with the lowest quartiles of the ISD were 1.66 (1.26, 2.20), 1.94 (1.14, 3.30), and 1.07 (0.70, 1.70), respectively. Conclusions Our results suggest that low-grade chronic inflammation induced by the diet may be associated with gastric cancer risk. This pattern seems to be more consistent for gastric carcinomas located in the cardia than for those located in the distal stomach. This study is listed on the ISRCTN registry as ISRCTN12136108. © 2018 American Society for Nutrition. All rights reserved.

Purpose: There is inconsistent evidence regarding the relationship between higher intake of nuts, being an energy-dense food, and weight gain. We investigated the relationship between nut intake and changes in weight over 5 years. Methods: This study includes 373,293 men and women, 25–70 years old, recruited between 1992 and 2000 from 10 European countries in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Habitual intake of nuts including peanuts, together defined as nut intake, was estimated from country-specific validated dietary questionnaires. Body weight was measured at recruitment and self-reported 5 years later. The association between nut intake and body weight change was estimated using multilevel mixed linear regression models with center/country as random effect and nut intake and relevant confounders as fixed effects. The relative risk (RR) of becoming overweight or obese after 5 years was investigated using multivariate Poisson regressions stratified according to baseline body mass index (BMI). Results: On average, study participants gained 2.1 kg (SD 5.0 kg) over 5 years. Compared to non-consumers, subjects in the highest quartile of nut intake had less weight gain over 5 years (−0.07 kg; 95% CI −0.12 to −0.02) (P trend = 0.025) and had 5% lower risk of becoming overweight (RR 0.95; 95% CI 0.92–0.98) or obese (RR 0.95; 95% CI 0.90–0.99) (both P trend

Background Whether and how n-3 and n-6 polyunsaturated fatty acids (PUFAs) are related to type 2 diabetes (T2D) is debated. Objectively measured plasma PUFAs can help to clarify these associations. Methods and Findings Plasma phospholipid PUFAs were measured by gas chromatography among 12,132 incident T2D cases and 15,919 subcohort participants in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct study across eight European countries. Country-specific hazard ratios (HRs) were estimated using Prentice-weighted Cox regression and pooled by random-effects meta-analysis. We also systematically reviewed published prospective studies on circulating PUFAs and T2D risk and pooled the quantitative evidence for comparison with results from EPIC-InterAct. In EPIC-InterAct, among long-chain n-3 PUFAs, α-linolenic acid (ALA) was inversely associated with T2D (HR per standard deviation [SD] 0.93; 95% CI 0.88–0.98), but eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) were not significantly associated. Among n-6 PUFAs, linoleic acid (LA) (0.80; 95% CI 0.77–0.83) and eicosadienoic acid (EDA) (0.89; 95% CI 0.85–0.94) were inversely related, and arachidonic acid (AA) was not significantly associated, while significant positive associations were observed with γ-linolenic acid (GLA), dihomo-GLA, docosatetraenoic acid (DTA), and docosapentaenoic acid (n6-DPA), with HRs between 1.13 to 1.46 per SD. These findings from EPIC-InterAct were broadly similar to comparative findings from summary estimates from up to nine studies including between 71 to 2,499 T2D cases. Limitations included potential residual confounding and the inability to distinguish between dietary and metabolic influences on plasma phospholipid PUFAs. Conclusions These large-scale findings suggest an important inverse association of circulating plant-origin n-3 PUFA (ALA) but no convincing association of marine-derived n3 PUFAs (EPA and DHA) with T2D. Moreover, they highlight that the most abundant n6-PUFA (LA) is inversely associated with T2D. The detection of associations with previously less well-investigated PUFAs points to the importance of considering individual fatty acids rather than focusing on fatty acid class., Using a large European cohort, Nita Forouhi and colleagues investigate the association between the concentration of polyunsaturated fatty acids measured in plasma and risk of developing type 2 diabetes., Author Summary Why Was This Study Done? Most dietary guidelines recommend the consumption of polyunsaturated fatty acids for cardiovascular health, but it is unclear whether or how n-3 and n-6 types of polyunsaturated fatty acids are related to type 2 diabetes. Health concerns have been raised previously about a diet high in linoleic acid (n-6 fatty acid), but its association with type 2 diabetes is unclear. Major limitations in previous studies have included the error-prone subjective assessment of the habitual consumption of polyunsaturated fatty acids when dietary intakes were evaluated and a small number of type 2 diabetes cases (n = 71 to 673) when objective biomarkers of polyunsaturated fatty acids were measured. What Did the Researchers Do and Find? We measured circulating individual polyunsaturated fatty acids in the blood samples of individuals within a large study from across eight countries of Europe among a reference sample of 15,919 individuals as well as 12,132 individuals who subsequently developed diabetes. Individuals were followed up for an average of approximately 10 y. We investigated the association between individual polyunsaturated fatty acids and the risk of future type 2 diabetes using statistical analyses that accounted for factors that could be potential alternative explanations for any observed associations. We found that higher levels of blood alpha-linolenic acid, a plant-origin n-3 fatty acid, and n-6 linoleic acid, the most abundant type of polyunsaturated fatty acid, were associated with a lower risk of future type 2 diabetes. In contrast, higher levels of four other minor individual n-6 fatty acids were associated with higher type 2 diabetes risk, while the blood marine-origin n-3 fatty acids were not associated with future diabetes. What Do These Findings Mean? Our findings show that it is important to consider individual circulating polyunsaturated fatty acids for association with type 2 diabetes risk, rather than placing emphasis on the class of circulating polyunsaturated fatty acids. We found that blood n-6 linoleic acid, the most abundant polyunsaturated fatty acid, is inversely associated with type 2 diabetes. We found no evidence that blood total n-6 polyunsaturated fatty acids may elevate the risk of type 2 diabetes, but several individual minor blood n-6 polyunsaturated fatty acids were associated with increased type 2 diabetes risk, highlighting the importance of polyunsaturated fatty acid metabolism in the development of type 2 diabetes.

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.

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 countryspecific 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.