Interaction between genes and macronutrient intake on the risk of developing type 2 diabetes: systematic review and findings from European Prospective Investigation into Cancer (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.

Association of dietary protein and dairy intakes and change in renal function: results from the population-based longitudinal Doetinchem cohort study.

BACKGROUND: Evidence has suggested that protein from dairy may be less detrimental to renal health than protein from nondairy products. However, to our knowledge, no previous studies have used cystatin C-based measures of the estimated glomerular filtration rate (eGFR). OBJECTIVE: We investigated the associations of sources of protein and dairy with the change in the eGFR in persons with a normal or mildly decreased eGFR. DESIGN: We included 3798 participants, aged 26-65 y, from the Doetinchem Cohort study who were examined ≥3 times 5 y apart. Intakes of protein and dairy and subtypes of protein and dairy were assessed at each round. With the use of the Chronic Kidney Disease Epidemiology Collaboration equation, the eGFR was estimated from cystatin C with all available samples per participant examined in one assay run. Generalized estimating equation models, which were adjusted for lifestyle, biological, and other dietary factors (monounsaturated fat, polyunsaturated fat, phosphorus, magnesium, calcium, and vitamin D) were performed. RESULTS: The mean baseline eGFR in the total cohort and in subjects with a mildly decreased eGFR (≥1 eGFR of 60-90 mL · min-1 · 1.73 m-2 during follow-up; n = 1326) was 108.6 and 95.2 mL · min-1 · 1.73 m-2, and the mean annual decline in both groups was 1.01 and 1.34 mL · min-1 · 1.73 m-2, respectively. Intakes of total, vegetable, animal, and nondairy protein, dairy protein, cheese, total dairy, high-fat dairy, and fermented dairy were not associated with eGFR changes. In individuals with a mildly decreased eGFR, higher consumption of milk, milk products, and low-fat dairy was associated with less annual decline in the eGFR (P-trend = 0.003). These associations were partially explained by dietary components of dairy (monounsaturated fat, polyunsaturated fat, phosphorus, magnesium, calcium, and vitamin D; P-trend < 0.04). CONCLUSIONS: Higher low-fat dairy consumption, but not sources of protein, is associated with less annual decline in the eGFR, particularly in individuals with a mildly decreased eGFR. These associations are partly attributable to other major components of dairy. Confirmation of these results will improve our ability to understand the role of dairy consumption in the prevention of renal dysfunction.

Association Between Low-Density Lipoprotein Cholesterol-Lowering Genetic Variants and Risk of Type 2 Diabetes: A Meta-analysis.

Importance: Low-density lipoprotein cholesterol (LDL-C)-lowering alleles in or near NPC1L1 or HMGCR, encoding the respective molecular targets of ezetimibe and statins, have previously been used as proxies to study the efficacy of these lipid-lowering drugs. Alleles near HMGCR are associated with a higher risk of type 2 diabetes, similar to the increased incidence of new-onset diabetes associated with statin treatment in randomized clinical trials. It is unknown whether alleles near NPC1L1 are associated with the risk of type 2 diabetes. Objective: To investigate whether LDL-C-lowering alleles in or near NPC1L1 and other genes encoding current or prospective molecular targets of lipid-lowering therapy (ie, HMGCR, PCSK9, ABCG5/G8, LDLR) are associated with the risk of type 2 diabetes. Design, Setting, and Participants: The associations with type 2 diabetes and coronary artery disease of LDL-C-lowering genetic variants were investigated in meta-analyses of genetic association studies. Meta-analyses included 50 775 individuals with type 2 diabetes and 270 269 controls and 60 801 individuals with coronary artery disease and 123 504 controls. Data collection took place in Europe and the United States between 1991 and 2016. Exposures: Low-density lipoprotein cholesterol-lowering alleles in or near NPC1L1, HMGCR, PCSK9, ABCG5/G8, and LDLR. Main Outcomes and Measures: Odds ratios (ORs) for type 2 diabetes and coronary artery disease. Results: Low-density lipoprotein cholesterol-lowering genetic variants at NPC1L1 were inversely associated with coronary artery disease (OR for a genetically predicted 1-mmol/L [38.7-mg/dL] reduction in LDL-C of 0.61 [95% CI, 0.42-0.88]; P = .008) and directly associated with type 2 diabetes (OR for a genetically predicted 1-mmol/L reduction in LDL-C of 2.42 [95% CI, 1.70-3.43]; P < .001). For PCSK9 genetic variants, the OR for type 2 diabetes per 1-mmol/L genetically predicted reduction in LDL-C was 1.19 (95% CI, 1.02-1.38; P = .03). For a given reduction in LDL-C, genetic variants were associated with a similar reduction in coronary artery disease risk (I2 = 0% for heterogeneity in genetic associations; P = .93). However, associations with type 2 diabetes were heterogeneous (I2 = 77.2%; P = .002), indicating gene-specific associations with metabolic risk of LDL-C-lowering alleles. Conclusions and Relevance: In this meta-analysis, exposure to LDL-C-lowering genetic variants in or near NPC1L1 and other genes was associated with a higher risk of type 2 diabetes. These data provide insights into potential adverse effects of LDL-C-lowering therapy.

Coffee and tea consumption in relation to estimated glomerular filtration rate: results from the population-based longitudinal Doetinchem Cohort Study.

BACKGROUND: Although coffee consumption and tea consumption have been linked to diabetes, the relation with kidney function is less clear and is underresearched. OBJECTIVE: We investigated the prospective associations of coffee and tea consumption with estimated glomerular filtration rate (eGFR). DESIGN: We included 4722 participants aged 26-65 y from the Doetinchem Cohort Study who were examined every 5 y for 15 y. Coffee and tea consumption (in cups/d) were assessed at each round. eGFR was assessed by using the Chronic Kidney Disease Epidemiology Collaboration equation based on both plasma creatinine and cystatin C. We determined the association between categories of coffee and tea intake and 1) eGFR and 2) subsequent annual changes in eGFR by using generalized estimating equation analyses. RESULTS: Baseline mean ± SD eGFR was 108.0 ± 14.7 mL · min(-1) · 1.73 m(-2) Tea consumption was not associated with eGFR. Those individuals who drank >6 cups coffee/d had a 1.33 (95% CI: 0.24, 2.43) mL · min(-1) · 1.73 m(-2) higher eGFR than those who drank <1 cup/d (P-trend = 0.02). This association was most apparent among those with a median age of ≥46 y at baseline, with eGFR being 2.47 (95% CI: 0.42, 4.51) mL · min(-1) · 1.73 m(-2) higher in participants drinking >6 cups/d compared with <1 cup/d (P-trend = 0.02). Adjustment for biological risk factors and coffee constituents did not attenuate the associations. Neither coffee nor tea consumption was associated with changes in eGFR. CONCLUSIONS: Coffee consumption was associated with a slightly higher eGFR, particularly in those aged ≥46 y. The absence of an association with eGFR changes suggests that the higher eGFR among coffee consumers is unlikely to be a result of glomerular hyperfiltration. Therefore, low to moderate coffee consumption is not expected to be a concern for kidney health in the general population.

Common genetic variants highlight the role of insulin resistance and body fat distribution in type 2 diabetes, independent of obesity.

We aimed to validate genetic variants as instruments for insulin resistance and secretion, to characterize their association with intermediate phenotypes, and to investigate their role in type 2 diabetes (T2D) risk among normal-weight, overweight, and obese individuals. We investigated the association of genetic scores with euglycemic-hyperinsulinemic clamp- and oral glucose tolerance test-based measures of insulin resistance and secretion and a range of metabolic measures in up to 18,565 individuals. We also studied their association with T2D risk among normal-weight, overweight, and obese individuals in up to 8,124 incident T2D cases. The insulin resistance score was associated with lower insulin sensitivity measured by M/I value (ß in SDs per allele [95% CI], -0.03 [-0.04, -0.01]; P = 0.004). This score was associated with lower BMI (-0.01 [-0.01, -0.0]; P = 0.02) and gluteofemoral fat mass (-0.03 [-0.05, -0.02; P = 1.4 × 10(-6)) and with higher alanine transaminase (0.02 [0.01, 0.03]; P = 0.002) and γ-glutamyl transferase (0.02 [0.01, 0.03]; P = 0.001). While the secretion score had a stronger association with T2D in leaner individuals (Pinteraction = 0.001), we saw no difference in the association of the insulin resistance score with T2D among BMI or waist strata (Pinteraction > 0.31). While insulin resistance is often considered secondary to obesity, the association of the insulin resistance score with lower BMI and adiposity and with incident T2D even among individuals of normal weight highlights the role of insulin resistance and ectopic fat distribution in T2D, independently of body size.