TCF7L2 polymorphisms and inflammatory markers before and after treatment with fenofibrate

<p>Abstract</p> <p>Background</p> <p>Inflammation is implicated in causing diabetes. We tested whether transcription factor 7 like-2 (TCF7L2) gene polymorphisms (rs12255372 and rs7903146), consistently associated with type 2 diabetes, are associated with plasma concentrations of inflammatory markers before and after three weeks of daily treatment with fenofibrate.</p> <p>Methods</p> <p>Men and women in the Genetics of Lipid-Lowering Drugs and Diet Network study (n = 1025, age 49 ± 16 y) were included. All participants suspended use of lipid-lowering drugs for three weeks and were then given 160 mg/day of fenofibrate for three weeks. Inflammatory markers and lipids were measured before and after fenofibrate. ANOVA was used to test for differences across TCF7L2 genotypes.</p> <p>Results</p> <p>Under the additive or dominant model, there were no significant differences (<it>P </it>> 0.05) in the concentrations of inflammatory markers (hsCRP, IL-2, IL-6, TNF-α and MCP-1) across TCF7L2 genotypes in the period before or after treatment. For both rs12255372 and rs7903146, homozygote T-allele carriers had significantly higher (<it>P </it>< 0.05) post-fenofibrate concentrations of MCP-1 in the recessive model. No other significant associations were detected.</p> <p>Conclusion</p> <p>Overall these data show no association between TCF7L2 polymorphisms and the inflammatory markers suggesting that the effects of TCF7L2 on diabetes may not be via inflammation.</p

Validity of a self-administered food frequency questionnaire (FFQ) and its generalizability to the estimation of dietary folate intake in Japan

BACKGROUND: In an epidemiological study, it is essential to test the validity of the food frequency questionnaire (FFQ) for its ability to estimate dietary intake. The objectives of our study were to 1) validate a FFQ for estimating folate intake, and to identify the foods that contribute to inter-individual variation of folate intake in the Japanese population. METHODS: Validity of the FFQ was evaluated using 28-day weighed dietary records (DRs) as gold standard in the two groups independently. In the group for which the FFQ was developed, validity was evaluated by Spearman's correlation coefficients (CCs), and linear regression analysis was used to identify foods with large inter-individual variation. The cumulative mean intake of these foods was compared with total intake estimated by the DR. The external validity of the FFQ and intake from foods on the same list were evaluated in the other group to verify generalizability. Subjects were a subsample from the Japan Public Health Center-based prospective Study who volunteered to participate in the FFQ validation study. RESULTS: CCs for the internal validity of the FFQ were 0.49 for men and 0.29 and women, while CCs for external validity were 0.33 for men and 0.42 for women. CCs for cumulative folate intake from 33 foods selected by regression analysis were also applicable to an external population. CONCLUSION: Our FFQ was valid for and generalizable to the estimation of folate intake. Foods identified as predictors of inter-individual variation in folate intake were also generalizable in Japanese populations. The FFQ with 138 foods was valid for the estimation of folate intake, while that with 33 foods might be useful for estimating inter-individual variation and ranking of individual folate intake

Measurement error adjustment in essential fatty acid intake from a food frequency questionnaire: alternative approaches and methods

<p>Abstract</p> <p>Background</p> <p>We aimed at assessing the degree of measurement error in essential fatty acid intakes from a food frequency questionnaire and the impact of correcting for such an error on precision and bias of odds ratios in logistic models. To assess these impacts, and for illustrative purposes, alternative approaches and methods were used with the binary outcome of cognitive decline in verbal fluency.</p> <p>Methods</p> <p>Using the Atherosclerosis Risk in Communities (ARIC) study, we conducted a sensitivity analysis. The error-prone exposure – visit 1 fatty acid intake (1987–89) – was available for 7,814 subjects 50 years or older at baseline with complete data on cognitive decline between visits 2 (1990–92) and 4 (1996–98). Our binary outcome of interest was clinically significant decline in verbal fluency. Point estimates and 95% confidence intervals were compared between naïve and measurement-error adjusted odds ratios of decline with every SD increase in fatty acid intake as % of energy. Two approaches were explored for adjustment: (A) External validation against biomarkers (plasma fatty acids in cholesteryl esters and phospholipids) and (B) Internal repeat measurements at visits 2 and 3. The main difference between the two is that Approach B makes a stronger assumption regarding lack of error correlations in the structural model. Additionally, we compared results from regression calibration (RCAL) to those from simulation extrapolation (SIMEX). Finally, using structural equations modeling, we estimated attenuation factors associated with each dietary exposure to assess degree of measurement error in a bivariate scenario for regression calibration of logistic regression model.</p> <p>Results and conclusion</p> <p>Attenuation factors for Approach A were smaller than B, suggesting a larger amount of measurement error in the dietary exposure. Replicate measures (Approach B) unlike concentration biomarkers (Approach A) may lead to imprecise odds ratios due to larger standard errors. Using SIMEX rather than RCAL models tends to preserve precision of odds ratios. We found in many cases that bias in naïve odds ratios was towards the null. RCAL tended to correct for a larger amount of effect bias than SIMEX, particularly for Approach A.</p

A prospective cohort study of dietary patterns of non-western migrants in the Netherlands in relation to risk factors for cardiovascular diseases: HELIUS-Dietary Patterns

<p>Abstract</p> <p>Background</p> <p>In Western countries the prevalence of cardiovascular disease (CVD) is often higher in non-Western migrants as compared to the host population. Diet is an important modifiable determinant of CVD. Increasingly, dietary patterns rather than single nutrients are the focus of research in an attempt to account for the complexity of nutrient interactions in foods. Research on dietary patterns in non-Western migrants is limited and may be hampered by a lack of validated instruments that can be used to assess the habitual diet of non-western migrants in large scale epidemiological studies. The ultimate aims of this study are to (1) understand whether differences in dietary patterns explain differences in CVD risk between ethnic groups, by developing and validating ethnic-specific Food Frequency Questionnaires (FFQs), and (2) to investigate the determinants of these dietary patterns. This paper outlines the design and methods used in the HELIUS-Dietary Patterns study and describes a systematic approach to overcome difficulties in the assessment and analysis of dietary intake data in ethnically diverse populations.</p> <p>Methods/Design</p> <p>The HELIUS-Dietary Patterns study is embedded in the HELIUS study, a Dutch multi-ethnic cohort study. After developing ethnic-specific FFQs, we will gather data on the habitual intake of 5000 participants (18-70 years old) of ethnic Dutch, Surinamese of African and of South Asian origin, Turkish or Moroccan origin. Dietary patterns will be derived using factor analysis, but we will also evaluate diet quality using hypothesis-driven approaches. The relation between dietary patterns and CVD risk factors will be analysed using multiple linear regression analysis. Potential underlying determinants of dietary patterns like migration history, acculturation, socio-economic factors and lifestyle, will be considered.</p> <p>Discussion</p> <p>This study will allow us to investigate the contribution of the dietary patterns on CVD risk factors in a multi-ethnic population. Inclusion of five ethnic groups residing in one setting makes this study highly innovative as confounding by local environment characteristics is limited. Heterogeneity in the study population will provide variance in dietary patterns which is a great advantage when studying the link between diet and disease.</p

Genetic Effects at Pleiotropic Loci Are Context-Dependent with Consequences for the Maintenance of Genetic Variation in Populations

Context-dependent genetic effects, including genotype-by-environment and genotype-by-sex interactions, are a potential mechanism by which genetic variation of complex traits is maintained in populations. Pleiotropic genetic effects are also thought to play an important role in evolution, reflecting functional and developmental relationships among traits. We examine context-dependent genetic effects at pleiotropic loci associated with normal variation in multiple metabolic syndrome (MetS) components (obesity, dyslipidemia, and diabetes-related traits). MetS prevalence is increasing in Western societies and, while environmental in origin, presents substantial variation in individual response. We identify 23 pleiotropic MetS quantitative trait loci (QTL) in an F16 advanced intercross between the LG/J and SM/J inbred mouse strains (Wustl:LG,SM-G16; n = 1002). Half of each family was fed a high-fat diet and half fed a low-fat diet; and additive, dominance, and parent-of-origin imprinting genotypic effects were examined in animals partitioned into sex, diet, and sex-by-diet cohorts. We examine the context-dependency of the underlying additive, dominance, and imprinting genetic effects of the traits associated with these pleiotropic QTL. Further, we examine sequence polymorphisms (SNPs) between LG/J and SM/J as well as differential expression of positional candidate genes in these regions. We show that genetic associations are different in different sex, diet, and sex-by-diet settings. We also show that over- or underdominance and ecological cross-over interactions for single phenotypes may not be common, however multidimensional synthetic phenotypes at loci with pleiotropic effects can produce situations that favor the maintenance of genetic variation in populations. Our findings have important implications for evolution and the notion of personalized medicine

Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations : A transethnic genome-wide meta-analysis

Background Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes. Methods & findings Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04-1.06, per HbA1c-raising allele, p = 3 x 10-29); whereas GS-E was not (OR = 1.00, 95% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11%) was associated with an absolute decrease in HbA1c of 0.81%-units (95% CI 0.66-0.96) per allele in hemizygous men, and 0.68%-units (95% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2% (N = 0.65 million, 95% CI0.55-0.74) of African American adults with T2Dto remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants. Conclusions As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.Peer reviewe

Evidence on the magnitude of the economic, health and population effects of palm cooking oil consumption: an integrated modelling approach with Thailand as a case study

BACKGROUND: Palm oil’s high yields, consequent low cost and highly versatile properties as a cooking oil and food ingredient have resulted in its thorough infiltration of the food sector in some countries. Longitudinal studies have associated palm oil’s high saturated fatty acid content with non-communicable disease, but neither the economic or disease burdens have been assessed previously. // METHODS: This novel palm oil-focussed disease burden assessment employs a fully integrated health, macroeconomic and demographic Computable General Equilibrium Model for Thailand with nine regional (urban/rural) households. Nutritional changes from food consumption are endogenously translated into health (myocardial infarction (MI) and stroke) and population outcomes and are fed back into the macroeconomic model as health and caregiver-related productive labour supply effects and healthcare costs to generate holistic 2016–2035 burden estimates. Model scenarios mirror the replacement of palm cooking oil with other dietary oils and are compared with simulated total Thai health and macroeconomic burdens for MI and stroke. // RESULTS: Replacing consumption of palm cooking oil with other dietary oils could reduce MI/stroke incident cases by 8280/2639 and cumulative deaths by 4683/894 over 20 years, removing approximately 0.5% of the total Thai burden of MI/stroke. This palm cooking oil replacement would reduce consumption shares of saturated/monounsaturated fatty acids in Thai household consumption by 6.5%/3% and increase polyunsaturated fatty acid consumption shares by 14%, yielding a 1.74% decrease in the population-wide total-to-HDL cholesterol ratio after 20 years. The macroeconomic burden that would be removed is US$308mn, approximately 0.44% of the total burden of MI/stroke on Thailand’s economy or 0.003% of cumulative 20-year GDP. Bangkok and Central region households benefit most from removal of disease burdens. // CONCLUSIONS: Simulations indicate that consumption of palm cooking oil, rather than other dietary oils, imposes a negative health burden (MI and stroke) and associated economic burden on a high consuming country, such as Thailand. Integrated sectoral model frameworks to assess these burdens are possible, and burden estimates from our simulated direct replacement of palm cooking oil indicate that using these frameworks both for broader analyses of dietary palm oil use and total burden analyses of other diseases may also be beneficial