Dietary patterns, genetic risk, and incidence of obesity: Application of reduced rank regression in 11,735 adults from the UK Biobank study

Role of Planetary Health Diet in the association between genetic susceptibility to obesity and anthropometric measures in adults

BACKGROUND/OBJECTIVE

The roles of overall diet quality in linking genetic background with anthropometric measures are unclear, particularly regarding the recently developed Planetary Health Diet (PHD). This study aims to determine if the PHD mediates or moderates the relationship between genetic susceptibility to obesity and anthropometric measures.

SUBJECTS/METHODS

The study involved 2942 individuals from a Finnish population-based cohort (54% women, mean age 53 (SD ± 13) years). Habitual diet was assessed using a validated 130-item food frequency questionnaire, and the PHD Score (total score range 0-13 points) was adapted for Finnish food culture to evaluate diet quality. Genetic susceptibility to obesity was evaluated with a polygenic risk score (PRS) based on one million single nucleotide polymorphisms associated with body mass index (BMI). Baseline anthropometrics included weight, height, waist circumference (WC), and body fat percentage, with changes in these measures tracked over 7 years. A five-step multiple linear regression model and multivariable logistic regression with interaction terms were used to assess the mediating and moderating effects of the PHD. These analyses were also replicated in another Finnish cohort study (2 834 participants).

RESULTS

PRS for BMI was positively associated with baseline BMI and changes in anthropometric measures, except waist circumference (p = 0.12). Significant associations were observed for baseline BMI and WC (p < 0.001), changes in BMI and WC (p = 0.01), and body fat percentage change (p = 0.05). However, the PHD (average score 3.8 points) did not mediate or moderate these relationships. These findings were consistent in the replication cohort.

CONCLUSION

Diet quality assessed with the PHD did not mediate or moderate the associations between genetic susceptibility to obesity and anthropometric measures. This lack of effect may be partly due to low adherence to the PHD and the older age of participants ( > 50 years) at baseline.

Interactions between Polygenic Risk of Obesity and Dietary Factors on Anthropometric Outcomes: A Systematic Review and Meta-Analysis of Observational Studies

BACKGROUND

Diet is an important determinant of health and may moderate genetic susceptibility to obesity, but meta-analyses of available evidence are lacking.

OBJECTIVES

This study aimed to systematically review and meta-analyze evidence on the moderating effect of diet on genetic susceptibility to obesity, assessed with polygenic risk scores (PRS).

METHODS

A systematic search was conducted using MEDLINE, EMBASE, Web of Science, and the Cochrane Library to retrieve observational studies that examined PRS-diet interactions on obesity-related outcomes. Dietary exposures of interest included diet quality/dietary patterns and consumption of specific food and beverage groups. Random-effects meta-analyses were performed for pooled PRS- healthy eating index (HEI) interaction coefficients on body mass index (BMI) (on the basis of data from 4 cohort studies) and waist circumference (WC) (on the basis of data from 3 cohort studies).

RESULTS

Out of 36 retrieved studies, 78% were conducted among European samples. Twelve out of 21 articles examining dietary indices/patterns, and 16 out of 21 articles examining food/beverage groups observed some significant PRS-diet interactions. However, within many articles, findings are inconsistent when testing different combinations of obesity PRS-dietary factors and outcomes. Nevertheless, higher HEI scores and adherence to plant-based dietary patterns emerged as the more prominent diet quality/patterns that moderated genetic susceptibility to obesity, whereas higher consumption of fruits and vegetables, and lower consumption of fried foods and sugar-sweetened beverages emerged as individual food/beverage moderators. Results from the meta-analysis suggest that a higher HEI attenuates genetic susceptibility on BMI (pooled PRS∗HEI coefficient: -0.08; 95% confidence interval (CI): -0.15, 0.00; P = 0.0392) and WC (-0.37; 95% CI: -0.60, -0.15; P = 0.0013).

CONCLUSIONS

Current observational evidence suggests a moderating role of overall diet quality in polygenic risk of obesity. Future research should aim to identify genetic loci that interact with dietary exposures on anthropometric outcomes and conduct analyses among diverse ethnic groups.

TRIAL REGISTRATION NUMBER

This study was registered at the International Prospective Register of Systematic Reviews as CRD42022312289.

Gene co-expression network analysis for porcine intramuscular fatty acid composition

In pigs, meat quality depends markedly on the fatty acid (FA) content and composition of the intramuscular fat, which is partly determined by the gene expression in this tissue. The aim of this work was to identify the link between muscle gene expression and its FA composition. In an (Iberian × Duroc) × Duroc backcrossed pig population, we identified modules of co-expressed genes, and correlation analyses were performed for each of them versus the phenotypes, finding four relevant modules. Two of the modules were positively correlated with saturated FAs (SFAs) and monounsaturated FAs (MUFAs), while negatively correlated with polyunsaturated FAs (PUFAs) and the omega-6/omega-3 ratio. The gene-enrichment analysis showed that these modules had over-representation of pathways related with the biosynthesis of unsaturated FAs, the Peroxisome proliferator-activated receptor signalling pathway and FA elongation. The two other relevant modules were positively correlated with PUFA and the n-6/n-3 ratio, but negatively correlated with SFA and MUFA. In this case, they had an over-representation of pathways related with fatty and amino acid degradation, and with oxidative phosphorylation. Using a graphical Gaussian model, we inferred a network of connections between the genes within each module. The first module had 52 genes with 87 connections, and the most connected genes were ADIPOQ, which is related with FA oxidation, and ELOVL6 and FABP4, both involved in FA metabolism. The second module showed 196 genes connected by 263 edges, being FN1 and MAP3K11 the most connected genes. On the other hand, the third module had 161 genes connected by 251 edges and ATG13 was the top neighbouring gene, while the fourth module had 224 genes and 655 connections, and its most connected genes were related with mitochondrial pathways. Overall, this work successfully identified relevant muscle gene networks and modules linked with FA composition, providing further insights on how the physiology of the pigs influences FA composition.

Associations of Dietary Cholesterol Consumption With Incident Diabetes and Cardiovascular Disease: The Role of Genetic Variability in Cholesterol Absorption and Disease Predisposition

OBJECTIVE

Whether genetic susceptibility to disease and dietary cholesterol (DC) absorption contribute to inconsistent associations of DC consumption with diabetes and cardiovascular disease (CVD) remains unclear.

RESEARCH DESIGN AND METHODS

DC consumption was assessed by repeated 24-h dietary recalls in the UK Biobank. A polygenetic risk score (PRS) for DC absorption was constructed using genetic variants in the Niemann-Pick C1-Like 1 and ATP Binding Cassettes G5 and G8 genes. PRSs for diabetes, coronary artery disease, and stroke were also created. The associations of DC consumption with incident diabetes (n = 96,826) and CVD (n = 94,536) in the overall sample and by PRS subgroups were evaluated using adjusted Cox models.

RESULTS

Each additional 300 mg/day of DC consumption was associated with incident diabetes (hazard ratio [HR], 1.17 [95% CI, 1.07-1.27]) and CVD (HR, 1.09 [95% CI, 1.03-1.17]), but further adjusting for BMI nullified these associations (HR for diabetes, 0.99 [95% CI, 0.90-1.09]; HR for CVD, 1.04 [95% CI, 0.98-1.12]). Genetic susceptibility to the diseases did not modify these associations (P for interaction ≥0.06). The DC-CVD association appeared to be stronger in people with greater genetic susceptibility to cholesterol absorption assessed by the non-high-density lipoprotein cholesterol-related PRS (P for interaction = 0.04), but the stratum-level association estimates were not statistically significant.

CONCLUSIONS

DC consumption was not associated with incident diabetes and CVD, after adjusting for BMI, in the overall sample and in subgroups stratified by genetic predisposition to cholesterol absorption and the diseases. Nevertheless, whether genetic predisposition to cholesterol absorption modifies the DC-CVD association requires further investigation.

Relationship between trajectories of dietary iron intake and risk of type 2 diabetes mellitus: evidence from a prospective cohort study

BACKGROUND

The association between dietary iron intake and the risk of type 2 diabetes mellitus (T2DM) remains inconsistent. In this study, we aimed to investigate the relationship between trajectories of dietary iron intake and risk of T2DM.

METHODS

This study comprised a total of 61,115 participants without a prior T2DM from the UK Biobank database. We used the group-based trajectory model (GBTM) to identify different dietary iron intake trajectories. Cox proportional hazards models were used to evaluate the relationship between trajectories of dietary iron intake and risk of T2DM.

RESULTS

During a mean follow-up of 4.8 years, a total of 677 T2DM events were observed. Four trajectory groups of dietary iron intake were characterized by the GBTM: trajectory group 1 (with a mean dietary iron intake of 10.9 mg/day), 2 (12.3 mg/day), 3 (14.1 mg/day) and 4 (17.6 mg/day). Trajectory group 3 was significantly associated with a 38% decreased risk of T2DM when compared with trajectory group 1 (hazard ratio [HR] = 0.62, 95% confidence interval [CI]: 0.49-0.79), while group 4 was significantly related with a 30% risk reduction (HR = 0.70, 95% CI: 0.54-0.91). Significant effect modifications by obesity (p = 0.04) and history of cardiovascular disease (p < 0.01) were found to the relationship between trajectories of dietary iron intake and the risk of T2DM.

CONCLUSIONS

We found that trajectories of dietary iron intake were significantly associated with the risk of T2DM, where the lowest T2DM risk was observed in trajectory group 3 with a mean iron intake of 14.1 mg/day. These findings may highlight the importance of adequate dietary iron intake to the T2DM prevention from a public health perspective. Further studies to assess the relationship between dietary iron intake and risk of T2DM are needed, as well as intervention studies to mitigate the risks of T2DM associated with dietary iron changes.

Precision Nutrition to Improve Risk Factors of Obesity and Type 2 Diabetes

PURPOSE OF REVIEW

Existing dietary and lifestyle interventions and recommendations, to improve the risk factors of obesity and type 2 diabetes with the target to mitigate this double global epidemic, have produced inconsistent results due to interpersonal variabilities in response to these conventional approaches, and inaccuracies in dietary assessment methods. Precision nutrition, an emerging strategy, tailors an individual's key characteristics such as diet, phenotype, genotype, metabolic biomarkers, and gut microbiome for personalized dietary recommendations to optimize dietary response and health. Precision nutrition is suggested to be an alternative and potentially more effective strategy to improve dietary intake and prevention of obesity and chronic diseases. The purpose of this narrative review is to synthesize the current research and examine the state of the science regarding the effect of precision nutrition in improving the risk factors of obesity and type 2 diabetes.

RECENT FINDINGS

The results of the research review indicate to a large extent significant evidence supporting the effectiveness of precision nutrition in improving the risk factors of obesity and type 2 diabetes. Deeper insights and further rigorous research into the diet-phenotype-genotype and interactions of other components of precision nutrition may enable this innovative approach to be adapted in health care and public health to the special needs of individuals. Precision nutrition provides the strategy to make individualized dietary recommendations by integrating genetic, phenotypic, nutritional, lifestyle, medical, social, and other pertinent characteristics about individuals, as a means to address the challenges of generalized dietary recommendations. The evidence presented in this review shows that precision nutrition markedly improves risk factors of obesity and type 2 diabetes, particularly behavior change.

Novel approach to investigate the association between type 2 diabetes risk and dietary fats in a dietary pattern context: a scoping review

The effect of dietary fat on type 2 diabetes (T2D) risk is unclear. A posteriori dietary pattern methods have been increasingly used to investigate how dietary fats impact T2D risk. However, the diverse nutrients, foods and dietary patterns reported in these studies requires examination to better understand the role of dietary fats. This scoping review aimed to systematically search and synthesize the literature regarding the association between dietary patterns characterized by dietary fats and T2D risk using reduced rank regression. Medline and Embase were searched for cross-sectional, cohort or case-control studies published in English. Of the included studies (n = 8), five high-fat dietary patterns, mostly high in SFA, were associated with higher T2D risk or fasting glucose, insulin and Homeostasis Model Assessment (HOMA) levels. These were mostly low-fiber (n = 5) and high energy-density (n = 3) dietary patterns characterized by low fruit and vegetables intake, reduced fat dairy products and higher processed meats and butter intake. Findings from this review suggest that a posteriori dietary patterns high in SFA that increase T2D risk are often accompanied by lower fruits, vegetables and other fiber-rich foods intake. Therefore, healthy dietary fats consumption for T2D prevention should be encouraged as part of a healthful dietary pattern.

Cross-sectional associations of dietary patterns characterized by fat type with markers of cardiometabolic health

BACKGROUND AND AIMS

Individual dietary fats can differentially impact on cardiometabolic health. However, their impact within a dietary pattern is not well understood, and warrants comparison with diet quality scores with a dietary fat focus. The aim of this study was to investigate cross-sectional associations between a posteriori dietary patterns characterized by fat type and cardiometabolic health markers, and compare these with two diet quality scores.

METHODS AND RESULTS

UK Biobank adults with ≥two 24-h dietary assessments and data on cardiometabolic health were included (n = 24 553; mean age: 55.9 y). A posteriori dietary patterns (DP1; DP2) were generated through reduced rank regression (response variables: SFA, MUFA, PUFA). Mediterranean Diet Score (MDS) and Dietary Approaches to Stop Hypertension (DASH) dietary patterns were created. Multiple linear regression analyses were used to investigate associations between standardized dietary patterns and cardiometabolic health (total cholesterol, HDL-C, LDL-C and VLDL-C cholesterol, triglycerides, C-reactive protein [CRP], glycated hemoglobin [HbA1c]). DP1, positively correlated with SFAs, MUFAs and PUFAs, characterized by higher nuts, seeds and vegetables intake and lower fruits and low-fat yoghurt intake, was associated with lower HDL-C (β: -0.07; 95% CI: -0.10, -0.03) and triglycerides (-0.17; -0.23, -0.10) and higher LDL-C (0.07; 0.01,0.12), CRP (0.01; 0.01, 0.03) and HbA1c (0.16; 0.11,0.21). DP2, positively correlated with SFAs, negatively correlated with PUFAs, characterized by higher butter and high-fat cheese intake and lower nuts, seeds and vegetable intake, was associated with higher total cholesterol (0.10; 0.01, 0.21), VLDL-C (0.05; 0.02, 0.07), triglycerides (0.07; 0.01, 0.13), CRP (0.03; 0.02, 0,04) and HbA1c (0.06; 0.01, 0.11). Higher adherence to MDS and DASH was associated with favorable cardiometabolic health markers concentration.

CONCLUSIONS

Irrespective of the method used, dietary patterns that encourage healthy fat consumption were associated with favorable cardiometabolic health biomarkers. This study strengthens the evidence for incorporation of dietary fat type into policy and practice guidelines for CVD prevention.