Genome-wide association study of osteoporosis identifies genetic risk and interactions with DASH diet and sugar sweetened beverages in a Hispanic cohort of older adults

BACKGROUND

Osteoporosis (OP) and low bone mass can be debilitating and costly conditions if not acted on quickly. This disease is also difficult to diagnose as symptoms develop unnoticed until fracture occurs. Therefore, gaining understanding of the genetic risk associated with these conditions could be beneficial for healthcare professionals in early detection and prevention.

METHODS

The Boston Puerto Rican Osteoporosis (BPROS) study, an ancillary study to the Boston Puerto Rican Health Study (BPRHS), collected information regarding bone and bone health. All bone measurements were taken during regular BPROS visits using dual-energy x-ray absorptiometry. Osteoporosis was defined as T-score ≤ -2.5 (2.5 SD or more below peak bone mass). Dietary variables were collected at the second wave of the BPRHS via food frequency questionnaire. We conducted genome-wide associations with bone outcomes including bone mineral density (BMD) and OP for 978 participants. We also examined interactions with dietary quality on the relationships between genotype and bone outcomes. We further tested if candidate genetic variants described in previous GWAS on OP and BMD contribute to OP risk in this population.

RESULTS

Four variants were associated with OP: rs114829316 (IQCJ), rs76603051, rs12214684 (MCHR2), and rs77303493 (RIN2), and two variants with BMD of lumbar spine (rs11855618, CGNL1) and hip (rs73480593, NTRK2), reaching the genome-wide significance threshold of P ≤ 5E-08. In a gene-diet interaction analysis, we found that one SNP showed a significant interaction with the overall DASH score, and 7 SNPs with sugar-sweeten beverages, a major contributor to the DASH score.

CONCLUSION

This study identifies new genetic markers related to osteoporosis and BMD in older Hispanic adults. Additionally, we uncovered unique genetic markers that interact with dietary quality, specifically sugar-sweetened beverages, in relation to bone health. These findings may be useful to guide early detection and preventative care.

Corrigendum: APOE4 allele-specific associations between diet, multimodal biomarkers, and cognition among Puerto Rican adults in Massachusetts

[This corrects the article DOI: 10.3389/fnagi.2023.1285333.].

Therapeutic potential of plant-derived extracellular vesicles as nanocarriers for exogenous miRNAs

Cell-to-cell communication strategies include extracellular vesicles (EVs) in plants and animals. The bioactive molecules in a diet rich in vegetables and fruits are associated with disease-preventive effects. Plant-derived EVs (PDEVs) are biogenetically and morphologically comparable to mammalian EVs and transport bioactive molecules, including miRNAs. However, the biological functions of PDEVs are not fully understood, and standard isolation protocols are lacking. Here, PDEVs were isolated from four foods with a combination of ultracentrifugation and size exclusion chromatography, and evaluated as vehicles for enhanced transport of synthetic miRNAs. In addition, the role of food-derived EVs as carriers of dietary (poly)phenols and other secondary metabolites was investigated. EVs from broccoli, pomegranate, apple, and orange were efficiently isolated and characterized. In all four sources, 4 miRNA families were present in tissues and EVs. miRNAs present in broccoli and fruit-derived EVs showed a reduced RNase degradation and were ferried inside exposed cells. EVs transfected with a combination of ath-miR159a, ath-miR162a-3p, ath-miR166b-3p, and ath-miR396b-5p showed toxic effects on human cells, as did natural broccoli EVs alone. PDEVs transport trace amounts of phytochemicals, including flavonoids, anthocyanidins, phenolic acids, or glucosinolates. Thus, PDEVs can act as nanocarriers for functional miRNAs that could be used in RNA-based therapy.

APOE4 allele-specific associations between diet, multimodal biomarkers, and cognition among Puerto Rican adults in Massachusetts

Background

Apolipoprotein E (APOE) is the strongest genetic risk factor for sporadic Alzheimer's Disease (AD), and the ε4 allele (APOE4) may interact with lifestyle factors that relate to brain structural changes, underlying the increased risk of AD. However, the exact role of APOE4 in mediating interactions between the peripheral circulatory system and the central nervous system, and how it may link to brain and cognitive aging requires further elucidation. In this analysis, we investigated the association between APOE4 carrier status and multimodal biomarkers (diet, blood markers, clinical diagnosis, brain structure, and cognition) in the context of gene-environment interactions.

Methods

Participants were older adults from a longitudinal observational study, the Boston Puerto Rican Health Study (BPRHS), who self-identified as of Puerto Rican descent. Demographics, APOE genotype, diet, blood, and clinical data were collected at baseline and at approximately 12th year, with the addition of multimodal brain magnetic resonance imaging (MRI) (T1-weighted and diffusion) and cognitive testing acquired at 12-year. Measures were compared between APOE4 carriers and non-carriers, and associations between multimodal variables were examined using correlation and multivariate network analyses within each group.

Results

A total of 156 BPRHS participants (mean age at imaging = 68 years, 77% female, mean follow-up 12.7 years) with complete multimodal data were included in the current analysis. APOE4 carriers (n = 43) showed reduced medial temporal lobe (MTL) white matter (WM) microstructural integrity and lower mini-mental state examination (MMSE) score than non-carriers (n = 113). This pattern was consistent with an independent sample from the Alzheimer's Disease Neuroimaging Initiative (ADNI) of n = 283 non-Hispanic White adults without dementia (mean age = 75, 40% female). Within BPRHS, carriers showed distinct connectivity patterns between multimodal biomarkers, characterized by stronger direct network connections between baseline diet/blood markers with 12-year blood/clinical measures, and between blood markers (especially lipids and cytokines) and WM. Cardiovascular burden (i.e., hypertension and diabetes status) was associated with WM integrity for both carriers and non-carriers.

Conclusion

APOE4 carrier status affects interactions between dietary factors, multimodal blood biomarkers, and MTL WM integrity across ~12 years of follow-up, which may reflect increased peripheral-central systems crosstalk following blood-brain barrier breakdown in carriers.

The Personalized Nutrition Study (POINTS): evaluation of a genetically informed weight loss approach, a Randomized Clinical Trial

Weight loss (WL) differences between isocaloric high-carbohydrate and high-fat diets are generally small; however, individual WL varies within diet groups. Genotype patterns may modify diet effects, with carbohydrate-responsive genotypes losing more weight on high-carbohydrate diets (and vice versa for fat-responsive genotypes). We investigated whether 12-week WL (kg, primary outcome) differs between genotype-concordant and genotype-discordant diets. In this 12-week single-center WL trial, 145 participants with overweight/obesity were identified a priori as fat-responders or carbohydrate-responders based on their combined genotypes at ten genetic variants and randomized to a high-fat (n = 73) or high-carbohydrate diet (n = 72), yielding 4 groups: (1) fat-responders receiving high-fat diet, (2) fat-responders receiving high-carbohydrate diet, (3) carbohydrate-responders receiving high-fat diet, (4) carbohydrate-responders receiving high-carbohydrate diet. Dietitians delivered the WL intervention via 12 weekly diet-specific small group sessions. Outcome assessors were blind to diet assignment and genotype patterns. We included 122 participants (54.4 [SD:13.2] years, BMI 34.9 [SD:5.1] kg/m2, 84% women) in the analyses. Twelve-week WL did not differ between the genotype-concordant (-5.3 kg [SD:1.0]) and genotype-discordant diets (-4.8 kg [SD:1.1]; adjusted difference: -0.6 kg [95% CI: -2.1,0.9], p = 0.50). With the current ability to genotype participants as fat- or carbohydrate-responders, evidence does not support greater WL on genotype-concordant diets. ClinicalTrials identifier: NCT04145466.

Changes in quantity plant-based protein intake on type 2 diabetes remission in coronary heart disease patients: from the CORDIOPREV study

PURPOSE

Diabetes remission is a phenomenon described in the context of drastic weight loss due to bariatric surgery or low-calorie diets. Evidence suggests that increasing the intake of plant protein could reduce the risk of type 2 diabetes. We sought for association between changes in plant protein intake in the context of 2 healthy diets without weight loss nor glucose-lowering medication, and diabetes remission in coronary heart disease patients from the CORDIOPREV study.

METHODS

Newly diagnosed type 2 diabetes participants without glucose-lowering treatment were randomized to consume a Mediterranean or a low-fat diet. Type 2 diabetes remission was assessed with a median follow-up of 60 months according to the ADA recommendation. Information on patient's dietary intake was collected using food-frequency questionnaires. At first year of intervention, 177 patients were classified according to changes in plant protein consumption into those who increased or decreased its intake, in order to perform an observational analysis on the association between protein intake and diabetes remission.

RESULTS

Cox regression showed that patients increasing plant protein intake were more likely to remit from diabetes than those who decreased its intake (HR = 1.71(1.05-2.77)). The remission occurred mainly at first and second year of follow-up with diminished number of patients achieving remission in the third year onwards. The increase in plant protein was associated with lower intake of animal protein, cholesterol, saturated fatty acids, and fat, and with higher intake of whole grains, fibre, carbohydrates, legumes, and tree nuts.

CONCLUSION

These results support the need to increase protein intake of vegetal origin as dietary therapy to reverse type 2 diabetes in the context of healthy diets without weight loss.

Omega-3 fatty acids and individual variability in plasma triglyceride response: A mini-review

Cardiovascular disease (CVD) is a leading cause of death worldwide. Supplementation with the marine omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) is associated with lower CVD risk. However, results from randomized controlled trials that examine the effect of omega-3 supplementation on CVD risk are inconsistent. This risk-reducing effect may be mediated by reducing inflammation, oxidative stress and serum triglyceride (TG) levels. However, not all individuals respond by reducing TG levels after omega-3 supplementation. This inter-individual variability in TG response to omega-3 supplementation is not fully understood. Hence, we aim to review the evidence for how interactions between omega-3 fatty acid supplementation and genetic variants, epigenetic and gene expression profiling, gut microbiota and habitual intake of omega-3 fatty acids can explain why the TG response differs between individuals. This may contribute to understanding the current controversies and play a role in defining future personalized guidelines to prevent CVD.

The impact of alcoholic drinks and dietary factors on epigenetic markers associated with triglyceride levels

Background: Many epigenetic loci have been associated with plasma triglyceride (TG) levels, but epigenetic connections between those loci and dietary exposures are largely unknown. This study aimed to characterize the epigenetic links between diet, lifestyle, and TG. Methods: We first conducted an epigenome-wide association study (EWAS) for TG in the Framingham Heart Study Offspring population (FHS, n = 2,264). We then examined relationships between dietary and lifestyle-related variables, collected four times in 13 years, and differential DNA methylation sites (DMSs) associated with the last TG measures. Third, we conducted a mediation analysis to evaluate the causal relationships between diet-related variables and TG. Finally, we replicated three steps to validate identified DMSs associated with alcohol and carbohydrate intake in the Genetics of Lipid-Lowering Drugs and Diet Network (GOLDN) study (n = 993). Results: In the FHS, the EWAS revealed 28 TG-associated DMSs at 19 gene regions. We identified 102 unique associations between these DMSs and one or more dietary and lifestyle-related variables. Alcohol and carbohydrate intake showed the most significant and consistent associations with 11 TG-associated DMSs. Mediation analyses demonstrated that alcohol and carbohydrate intake independently affect TG via DMSs as mediators. Higher alcohol intake was associated with lower methylation at seven DMSs and higher TG. In contrast, increased carbohydrate intake was associated with higher DNA methylation at two DMSs (CPT1A and SLC7A11) and lower TG. Validation in the GOLDN further supports the findings. Conclusion: Our findings imply that TG-associated DMSs reflect dietary intakes, particularly alcoholic drinks, which could affect the current cardiometabolic risk via epigenetic changes. This study illustrates a new method to map epigenetic signatures of environmental factors for disease risk. Identification of epigenetic markers of dietary intake can provide insight into an individual's risk of cardiovascular disease and support the application of precision nutrition. Clinical Trial Registration: www.ClinicalTrials.gov, the Framingham Heart Study (FHS), NCT00005121; the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN), NCT01023750.

Metabolomic profiling in dogs with dilated cardiomyopathy eating non-traditional or traditional diets and in healthy controls

Dilated cardiomyopathy (DCM), caused by genetic and environmental factors, usually progresses to heart failure, a major cause of death in elderly people. A diet-associated form of DCM was recently identified in pet dogs eating non-traditional (NT) diets. To identify potential dietary causes, we analyzed metabolomic signatures and gene set/pathway enrichment in (1) all dogs based on disease, diet, and their interactions and (2) dogs with DCM based on diet. Metabolomic analysis was performed in 38 dogs with DCM eating NT diets (DCM-NT), 8 dogs with DCM eating traditional diets, 12 healthy controls eating NT diets, and 17 healthy controls eating traditional diets. Overall, 153 and 63 metabolites differed significantly between dogs with DCM versus healthy controls and dogs eating NT versus traditional diets, respectively, with 12 metabolites overlapping both analyses. Protein-protein interaction networks and gene set enrichment analysis identified 105 significant pathways and gene sets including aging-related pathways (e.g., nuclear factor-kappa B, oxidative damage, inflammation). Seventeen metabolites differed significantly in dogs with DCM eating NT versus traditional diets (e.g., fatty acids, amino acids, legume biomarkers), suggesting different mechanisms for primary versus diet-associated DCM. Our multifaceted metabolomic assessment of DCM in dogs highlighted diet's role in some forms of DCM.

Research gaps and opportunities in precision nutrition: an NIH workshop report

Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.

One-year longitudinal association between changes in dietary choline or betaine intake and cardiometabolic variables in the PREvención con DIeta MEDiterránea-Plus (PREDIMED-Plus) trial

BACKGROUND

Choline and betaine intakes have been related to cardiovascular health.

OBJECTIVES

We aimed to explore the relation between 1-y changes in dietary intake of choline or betaine and 1-y changes in cardiometabolic and renal function traits within the frame of the PREDIMED (PREvención con DIeta MEDiterránea)-Plus trial.

METHODS

We used baseline and 1-y follow-up data from 5613 participants (48.2% female and 51.8% male; mean ± SD age: 65.01 ± 4.91 y) to assess cardiometabolic traits, and 3367 participants to assess renal function, of the Spanish PREDIMED-Plus trial. Participants met ≥3 criteria of metabolic syndrome and had overweight or obesity [BMI (in kg/m2) ≥27 and ≤40]. These criteria were similar to those of the PREDIMED parent study. Dietary intakes of choline and betaine were estimated from the FFQ.

RESULTS

The greatest 1-y increase in dietary choline or betaine intake (quartile 4) was associated with improved serum glucose concentrations (-3.39 and -2.72 mg/dL for choline and betaine, respectively) and HbA1c levels (-0.10% for quartile 4 of either choline or betaine intake increase). Other significant changes associated with the greatest increase in choline or betaine intake were reduced body weight (-2.93 and -2.78 kg, respectively), BMI (-1.05 and -0.99, respectively), waist circumference (-3.37 and -3.26 cm, respectively), total cholesterol (-4.74 and -4.52 mg/dL, respectively), and LDL cholesterol (-4.30 and -4.16 mg/dL, respectively). Urine creatinine was reduced in quartile 4 of 1-y increase in choline or betaine intake (-5.42 and -5.74 mg/dL, respectively).

CONCLUSIONS

Increases in dietary choline or betaine intakes were longitudinally related to improvements in cardiometabolic parameters. Markers of renal function were also slightly improved, and they require further investigation.This trial was registered at https://www.isrctn.com/ as ISRCTN89898870.

Anti-COVID-19 measures threaten our healthy body weight: Changes in sleep and external synchronizers of circadian clocks during confinement

BACKGROUND & AIMS

Emergency measures in the face of the recent COVID-19 pandemic have been different among countries, although most have opted for confinement and restrictions on social contact. These measures have generated lifestyle changes with potential effects on individuals' health. The disturbances in daily routines due to confinement and remote work have impacted circadian rhythms and energy balance; however, the consequences of these disruptions have not been studied in depth. The objective was to evaluate the impact of 12-week confinement on body weight, considering changes in several external synchronizers of the biological clock.

METHODS

The participants, 521 university students (16-35 years), responded to 52 questions oriented to determine light exposure, sleep patterns, sedentary lifestyle, and eating times.

RESULTS

We found a reduction in sunlight exposure and sleep duration, an increment in sedentarism and screen exposure, and a delay in the timing of the main meals and sleep in the whole cohort. These behavioral changes were associated with a twofold increase in obesity. Subjects who increased their sedentary hours and shortened their sleep to a higher degree were those who gained more bodyweight. The most influential factors in body weight variation during confinement were sleep duration, physical activity (sedentarism), and light (timing of screen exposure). The mediation model explained 6% of the total body weight variation.

CONCLUSIONS

Results support a significant impact of confinement on several external synchronizers of the biological clock and on body weight. Health-related recommendations during the pandemic must include behavioral recommendations to mitigate the adverse effects on the biological clock.

APOE Genotypes Modulate Inflammation Independently of Their Effect on Lipid Metabolism

The association between APOE genotypes and cardiovascular disease (CVD) is partially mediated by LDL-cholesterol concentration but persists after adjusting for lipid levels and other cardiovascular risk factors. Data from the Aragon Workers Health Study (AWHS) (n = 4159) and the Lipid Unit at the Hospital Universitario Miguel Servet (HUMS) (n = 3705) were used to investigate the relationship between C-reactive protein (CRP) levels and APOE genotype. Lipoprotein particle and GlycA concentrations were analyzed in a subsample from AWHS. APOE genotyping was carried out by the Sanger method in both cohorts. APOE4 carriers had significantly lower levels of CRP than APOE3 carriers. Furthermore, APOE4 carriers had cholesterol-enriched LDL particles compared to APOE2 carriers. APOE4 carriers also had higher concentrations of small, medium, and large LDL particles. CRP levels were not associated with lipoprotein particle number, size, or composition. GlycA levels were not associated with APOE genotypes. However, GlycA levels were significantly associated with the size and the amount of cholesterol contained in HDL, VLDL, and LDL particles. APOE genotype influences CRP concentration regardless of lipid profile. APOE2 carriers showed the highest CRP levels, followed by APOE3 and APOE4. A more atherogenic lipid profile, but not inflammatory markers could partly explain the higher CVD risk observed in APOE4 carriers.

TMAO Upregulates Members of the miR-17/92 Cluster and Impacts Targets Associated with Atherosclerosis

Atherosclerosis is a hallmark of cardiovascular disease, and lifestyle strongly impacts its onset and progression. Nutrients have been shown to regulate the miR-17/92 cluster, with a role in endothelial function and atherosclerosis. Choline, betaine, and L-carnitine, found in animal foods, are metabolized into trimethylamine (TMA) by the gut microbiota. TMA is then oxidized to TMAO, which has been associated with atherosclerosis. Our aim was to investigate whether TMAO modulates the expression of the miR-17/92 cluster, along with the impact of this modulation on the expression of target genes related to atherosclerosis and inflammation. We treated HepG-2 cells, THP-1 cells, murine liver organoids, and human peripheral mononuclear cells with 6 µM of TMAO at different timepoints. TMAO increased the expression of all analyzed members of the cluster, except for miR-20a-5p in murine liver organoids and primary human macrophages. Genes and protein levels of SERPINE1 and IL-12A increased. Both have been associated with atherosclerosis and cardiovascular disease (CDVD) and are indirectly modulated by the miR-17-92 cluster. We concluded that TMAO modulates the expression of the miR-17/92 cluster and that such modulation could promote inflammation through IL-12A and blood clotting through SERPINE1 expression, which could ultimately promote atherosclerosis and CVD.

Poor self-reported sleep is associated with risk factors for cardiovascular disease: A cross-sectional analysis in half a million adults

BACKGROUND

Sleep is known to affect cardiovascular health, but some controversy exists on the independent association between different sleep characteristics (duration, restfulness, difficulties falling asleep) and specific risk factors for cardiovascular disease (CVD). We aimed to assess the association between self-reported sleep characteristics and the likelihood of major CVD risk factors.

METHODS

Totally, 521,364 Spanish workers (32% female, 44 ± 9 years [18-64]) insured by an occupational risk prevention company participated in this nationwide cross-sectional study. Participants' sleep was considered 'poor' if they reported having ≥1 of the following conditions: excessively short (<6 h/d) or long (>9 h/d) sleep, unrestful sleep, or difficulties to fall asleep. We assessed the independent association between aforementioned sleep characteristics and the prevalence of hypertension, diabetes, hypercholesterolaemia, obesity and physical inactivity.

RESULTS

Poor sleep (reported by 33% of participants) was associated with a higher likelihood of presenting all CVD risk factors individually, particularly physical inactivity (which prevalence was ~3-fold higher in the poor sleep group compared with participants reporting no sleep abnormality). In separate analyses, all the different sleep characteristics were associated with the likelihood of ≥2 CVD risk factors. Participants with optimal sleep, normal sleep duration, no difficulties falling sleep and restful sleep showed a lower total CVD risk score than their peers with poor sleep, short sleep duration, difficulties falling sleep and unrestful sleep, respectively (all p < .001).

CONCLUSIONS

Poor sleep was associated with a higher likelihood of presenting major CVD risk factors. These findings might support the importance of monitoring and improving sleep patterns for primary CVD prevention.

Integrative development of a short screening questionnaire of highly processed food consumption (sQ-HPF)

BACKGROUND

Recent lifestyle changes include increased consumption of highly processed foods (HPF), which has been associated with an increased risk of non-communicable diseases (NCDs). However, nutritional information relies on the estimation of HPF consumption from food-frequency questionnaires (FFQ) that are not explicitly developed for this purpose. We aimed to develop a short screening questionnaire of HPF consumption (sQ-HPF) that integrates criteria from the existing food classification systems.

METHODS

Data from 4400 participants (48.1% female and 51.9% male, 64.9 ± 4.9 years) of the Spanish PREDIMED-Plus ("PREvention with MEDiterranean DIet") trial were used for this analysis. Items from the FFQ were classified according to four main food processing-based classification systems (NOVA, IARC, IFIC and UNC). Participants were classified into tertiles of HPF consumption according to each system. Using binomial logistic regression, food groups associated with agreement in the highest tertile for at least two classification systems were chosen as items for the questionnaire. ROC analysis was used to determine cut-off points for the frequency of consumption of each item, from which a score was calculated. Internal consistency of the questionnaire was assessed through exploratory factor analysis (EFA) and Cronbach's analysis, and agreement with the four classifications was assessed with weighted kappa coefficients.

RESULTS

Regression analysis identified 14 food groups (items) associated with high HPF consumption for at least two classification systems. EFA showed that items were representative contributors of a single underlying factor, the "HPF dietary pattern" (factor loadings around 0.2). We constructed a questionnaire asking about the frequency of consumption of those items. The threshold frequency of consumption was selected using ROC analysis. Comparison of the four classification systems and the sQ-HPF showed a fair to high agreement. Significant changes in lifestyle characteristics were detected across tertiles of the sQ-HPF score. Longitudinal changes in HPF consumption were also detected by the sQ-HPF, concordantly with existing classification systems.

CONCLUSIONS

We developed a practical tool to measure HPF consumption, the sQ-HPF. This may be a valuable instrument to study its relationship with NCDs.

TRIAL REGISTRATION

Retrospectively registered at the International Standard Randomized Controlled Trial Registry ( ISRCTN89898870 ) on July 24, 2014.

Using Machine Learning to Predict Obesity Based on Genome-Wide and Epigenome-Wide Gene-Gene and Gene-Diet Interactions

Obesity is associated with many chronic diseases that impair healthy aging and is governed by genetic, epigenetic, and environmental factors and their complex interactions. This study aimed to develop a model that predicts an individual's risk of obesity by better characterizing these complex relations and interactions focusing on dietary factors. For this purpose, we conducted a combined genome-wide and epigenome-wide scan for body mass index (BMI) and up to three-way interactions among 402,793 single nucleotide polymorphisms (SNPs), 415,202 DNA methylation sites (DMSs), and 397 dietary and lifestyle factors using the generalized multifactor dimensionality reduction (GMDR) method. The training set consisted of 1,573 participants in exam 8 of the Framingham Offspring Study (FOS) cohort. After identifying genetic, epigenetic, and dietary factors that passed statistical significance, we applied machine learning (ML) algorithms to predict participants' obesity status in the test set, taken as a subset of independent samples (n = 394) from the same cohort. The quality and accuracy of prediction models were evaluated using the area under the receiver operating characteristic curve (ROC-AUC). GMDR identified 213 SNPs, 530 DMSs, and 49 dietary and lifestyle factors as significant predictors of obesity. Comparing several ML algorithms, we found that the stochastic gradient boosting model provided the best prediction accuracy for obesity with an overall accuracy of 70%, with ROC-AUC of 0.72 in test set samples. Top predictors of the best-fit model were 21 SNPs, 230 DMSs in genes such as CPT1A, ABCG1, SLC7A11, RNF145, and SREBF1, and 26 dietary factors, including processed meat, diet soda, French fries, high-fat dairy, artificial sweeteners, alcohol intake, and specific nutrients and food components, such as calcium and flavonols. In conclusion, we developed an integrated approach with ML to predict obesity using omics and dietary data. This extends our knowledge of the drivers of obesity, which can inform precision nutrition strategies for the prevention and treatment of obesity. Clinical Trial Registration: [www.ClinicalTrials.gov], the Framingham Heart Study (FHS), [NCT00005121].

Proximal and distal effects of genetic susceptibility to multiple sclerosis on the T cell epigenome

Identifying the effects of genetic variation on the epigenome in disease-relevant cell types can help advance our understanding of the first molecular contributions of genetic susceptibility to disease onset. Here, we establish a genome-wide map of DNA methylation quantitative trait loci in CD4⁺ T-cells isolated from multiple sclerosis patients. Utilizing this map in a colocalization analysis, we identify 19 loci where the same haplotype drives both multiple sclerosis susceptibility and local DNA methylation. We also identify two distant methylation effects of multiple sclerosis susceptibility loci: a chromosome 16 locus affects PRDM8 methylation (a chromosome 4 region not previously associated with multiple sclerosis), and the aggregate effect of multiple sclerosis-associated variants in the major histocompatibility complex influences DNA methylation near PRKCA (chromosome 17). Overall, we present a new resource for a key cell type in inflammatory disease research and uncover new gene targets for the study of predisposition to multiple sclerosis.

Trimethylamine n-Oxide (TMAO) Modulates the Expression of Cardiovascular Disease-Related microRNAs and Their Targets

Diet is a well-known risk factor of cardiovascular diseases (CVDs). Some microRNAs (miRNAs) have been described to regulate molecular pathways related to CVDs. Diet can modulate miRNAs and their target genes. Choline, betaine, and l-carnitine, nutrients found in animal products, are metabolized into trimethylamine n-oxide (TMAO), which has been associated with CVD risk. The aim of this study was to investigate TMAO regulation of CVD-related miRNAs and their target genes in cellular models of liver and macrophages. We treated HEPG-2, THP-1, mouse liver organoids, and primary human macrophages with 6 µM TMAO at different timepoints (4, 8, and 24 h for HEPG-2 and mouse liver organoids, 12 and 24 h for THP-1, and 12 h for primary human macrophages) and analyzed the expression of a selected panel of CVD-related miRNAs and their target genes and proteins by real-time PCR and Western blot, respectively. HEPG-2 cells were transfected with anti-miR-30c and syn-miR-30c. TMAO increased the expression of miR-21-5p and miR-30c-5p. PER2, a target gene of both, decreased its expression with TMAO in HEPG-2 and mice liver organoids but increased its mRNA expression with syn-miR-30c. We concluded that TMAO modulates the expression of miRNAs related to CVDs, and that such modulation affects their target genes.

Individual Postprandial Glycemic Responses to Diet in n-of-1 Trials: Westlake N-of-1 Trials for Macronutrient Intake (WE-MACNUTR)

BACKGROUND

The role of different types and quantities of macronutrients on human health has been controversial, and the individual response to dietary macronutrient intake needs more investigation.

OBJECTIVES

We aimed to use an 'n-of-1' study design to investigate the individual variability in postprandial glycemic response when eating diets with different macronutrient distributions among apparently healthy adults.

METHODS

Thirty apparently healthy young Chinese adults (women, 68%) aged between 22 and 34 y, with BMI between 17.2 and 31.9 kg/m2, were provided with high-fat, low-carbohydrate (HF-LC, 60-70% fat, 15-25% carbohydrate, 15% protein, of total energy) and low-fat, high-carbohydrate (LF-HC, 10-20% fat, 65-75% carbohydrate, 15% protein) diets, for 6 d wearing continuous glucose monitoring systems, respectively, in a randomized sequence, interspersed by a 6-d wash-out period. Three cycles were conducted. The primary outcomes were the differences of maximum postprandial glucose (MPG), mean amplitude of glycemic excursions (MAGE), and AUC24 between intervention periods of LF-HC and HF-LC diets. A Bayesian model was used to predict responders with the posterior probability of any 1 of the 3 outcomes reaching a clinically meaningful difference.

RESULTS

Twenty-eight participants were included in the analysis. Posterior probability of reaching a clinically meaningful difference of MPG (0.167 mmol/L), MAGE (0.072 mmol/L), and AUC24 (13.889 mmol/L·h) between LF-HC and HF-LC diets varied among participants, and those with posterior probability >80% were identified as high-carbohydrate responders (n = 9) or high-fat responders (n = 6). Analyses of the Bayesian-aggregated n-of-1 trials among all participants showed a relatively low posterior probability of reaching a clinically meaningful difference of the 3 outcomes between LF-HC and HF-LC diets.

CONCLUSIONS

N-of-1 trials are feasible to characterize personal response to dietary intervention in young Chinese adults.

A Catalog of Natural Products Occurring in Watermelon-Citrullus lanatus

Sweet dessert watermelon (Citrullus lanatus) is one of the most important vegetable crops consumed throughout the world. The chemical composition of watermelon provides both high nutritional value and various health benefits. The present manuscript introduces a catalog of 1,679 small molecules occurring in the watermelon and their cheminformatics analysis for diverse features. In this catalog, the phytochemicals are associated with the literature describing their presence in the watermelon plant, and when possible, concentration values in various plant parts (flesh, seeds, leaves, roots, rind). Also cataloged are the chemical classes, molecular weight and formula, chemical structure, and certain physical and chemical properties for each phytochemical. In our view, knowing precisely what is in what we eat, as this catalog does for watermelon, supports both the rationale for certain controlled feeding studies in the field of precision nutrition, and plant breeding efforts for the development of new varieties with enhanced concentrations of specific phytochemicals. Additionally, improved and comprehensive collections of natural products accessible to the public will be especially useful to researchers in nutrition, cheminformatics, bioinformatics, and drug development, among other disciplines.

Associations of network-derived metabolite clusters with prevalent type 2 diabetes among adults of Puerto Rican descent

INTRODUCTION

We investigated whether network analysis revealed clusters of coregulated metabolites associated with prevalent type 2 diabetes (T2D) among Puerto Rican adults.

RESEARCH DESIGN AND METHODS

We used liquid chromatography-mass spectrometry to measure fasting plasma metabolites (>600) among participants aged 40-75 years in the Boston Puerto Rican Health Study (BPRHS; discovery) and San Juan Overweight Adult Longitudinal Study (SOALS; replication), with (n=357; n=77) and without (n=322; n=934) T2D, respectively. Among BPRHS participants, we used unsupervised partial correlation network-based methods to identify and calculate metabolite cluster scores. Logistic regression was used to assess cross-sectional associations between metabolite clusters and prevalent T2D at the baseline blood draw in the BPRHS, and significant associations were replicated in SOALS. Inverse-variance weighted random-effect meta-analysis was used to combine cohort-specific estimates.

RESULTS

Six metabolite clusters were significantly associated with prevalent T2D in the BPRHS and replicated in SOALS (false discovery rate (FDR) <0.05). In a meta-analysis of the two cohorts, the OR and 95% CI (per 1 SD increase in cluster score) for prevalent T2D were as follows for clusters characterized primarily by glucose transport (0.21 (0.16 to 0.30); FDR <0.0001), sphingolipids (0.40 (0.29 to 0.53); FDR <0.0001), acyl cholines (0.35 (0.22 to 0.56); FDR <0.0001), sugar metabolism (2.28 (1.68 to 3.09); FDR <0.0001), branched-chain and aromatic amino acids (2.22 (1.60 to 3.08); FDR <0.0001), and fatty acid biosynthesis (1.54 (1.29 to 1.85); FDR <0.0001). Three additional clusters characterized by amino acid metabolism, cell membrane components, and aromatic amino acid metabolism displayed significant associations with prevalent T2D in the BPRHS, but these associations were not replicated in SOALS.

CONCLUSIONS

Among Puerto Rican adults, we identified several known and novel metabolite clusters that associated with prevalent T2D.

Use of Different Food Classification Systems to Assess the Association between Ultra-Processed Food Consumption and Cardiometabolic Health in an Elderly Population with Metabolic Syndrome (PREDIMED-Plus Cohort)

The association between ultra-processed food (UPF) and risk of cardiometabolic disorders is an ongoing concern. Different food processing-based classification systems have originated discrepancies in the conclusions among studies. To test whether the association between UPF consumption and cardiometabolic markers changes with the classification system, we used baseline data from 5636 participants (48.5% female and 51.5% male, mean age 65.1 ± 4.9) of the PREDIMED-Plus (“PREvention with MEDiterranean DIet”) trial. Subjects presented with overweight or obesity and met at least three metabolic syndrome (MetS) criteria. Food consumption was classified using a 143-item food frequency questionnaire according to four food processing-based classifications: NOVA, International Agency for Research on Cancer (IARC), International Food Information Council (IFIC) and University of North Carolina (UNC). Mean changes in nutritional and cardiometabolic markers were assessed according to quintiles of UPF consumption for each system. The association between UPF consumption and cardiometabolic markers was assessed using linear regression analysis. The concordance of the different classifications was assessed with intra-class correlation coefficients (ICC3, overall = 0.51). The highest UPF consumption was obtained with the IARC classification (45.9%) and the lowest with NOVA (7.9%). Subjects with high UPF consumption showed a poor dietary profile. We detected a direct association between UPF consumption and BMI (p = 0.001) when using the NOVA system, and with systolic (p = 0.018) and diastolic (p = 0.042) blood pressure when using the UNC system. Food classification methodologies markedly influenced the association between UPF consumption and cardiometabolic risk markers.

Genetics of Sleep and Insights into Its Relationship with Obesity

Considerable recent advancements in elucidating the genetic architecture of sleep traits and sleep disorders may provide insight into the relationship between sleep and obesity. Despite the considerable involvement of the circadian clock in sleep and metabolism, few shared genes, including FTO, were implicated in genome-wide association studies (GWASs) of sleep and obesity. Polygenic scores composed of signals from GWASs of sleep traits show largely null associations with obesity, suggesting lead variants are unique to sleep. Modest genome-wide genetic correlations are observed between many sleep traits and obesity and are largest for snoring.Notably, U-shaped positive genetic correlations with body mass index (BMI) exist for both short and long sleep durations. Findings from Mendelian randomization suggest robust causal effects of insomnia on higher BMI and, conversely, of higher BMI on snoring and daytime sleepiness. Bidirectional effects between sleep duration and daytime napping with obesity may also exist. Limited gene-sleep interaction studies suggest that achieving favorable sleep, as part of a healthy lifestyle, may attenuate genetic predisposition to obesity, but whether these improvements produce clinically meaningful reductions in obesity risk remains unclear. Investigations of the genetic link between sleep and obesity for sleep disorders other than insomnia and in populations of non-European ancestry are currently limited. Expected final online publication date for the Annual Review of Nutrition, Volume 41 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Gene-Diet Interactions in Colorectal Cancer: Survey Design, Instruments, Participants and Descriptive Data of a Case-Control Study in the Basque Country

Epidemiologic studies have revealed inconsistent evidence of gene-diet interaction in relation to colorectal cancer (CRC). The aim of this study was to analyze them in a sample of cases and controls from the population-based bowel cancer screening program of the Osakidetza/Basque Health Service. This study analyzed dietetic, genetic, demographic, socioeconomic factors and lifestyles. In the present manuscript, the survey design, sampling, instruments, measurements and related quality management were presented. Moreover, we analyze differences between cases and controls in some data, especially those related to diet. The participants were 308 cases and 308 age- and sex-matched subjects as controls. Cases were more likely than controls to have overweight/obesity (67.5% vs. 58.1%, p < 0.05), a lower intake of vitamin B₂ (0.86 ± 0.23 vs. 0.92 ± 0.23 mg/1000 kcal, p < 0.01) and calcium:phosphorus ratio (0.62 ± 0.12 vs. 0.65 ± 0.13, p < 0.01). A higher proportion of cases than controls did not meet the Nutritional Objectives for saturated fatty acids (85.7% vs. 67.5%, p < 0.001) or cholesterol (35.4% vs. 25.0%, p < 0.01). In conclusion, the present study provides valuable data for analyzing the complexity of gene-diet interaction in relation to CRC. The results presented here suggest that overweight/obesity and a high intake of certain dietary components, especially saturated fatty acids and cholesterol, are more frequent in cases than in controls.

Impact of Phenol-Enriched Virgin Olive Oils on the Postprandial Levels of Circulating microRNAs Related to Cardiovascular Disease

SCOPE

We investigate the postprandial modulation of cardiovascular-related microRNAs elicited by extra virgin olive oil (EVOOs) containing different levels of their own polyphenols.

METHODS AND RESULTS

It is randomized, postprandial, parallel, double-blind study. Twelve healthy participants consumed 30 mL of EVOO containing low (L-EVOO; 250 mg total phenols kg-1 of oil), medium (M-EVOO; 500 mg total phenols kg-1 of oil), and high (H-EVOO; 750 mg total phenols kg-1 of oil) enriched EVOOs. Postprandial plasma microRNAs levels are analyzed by real-time quantitative PCR. The results show that L-EVOO intake is associated with decreased let-7e-5p and miR-328a-3p levels and increased miR-17-5p and miR-20a-5p, concentrations. M-EVOO decreases plasma let-7e-5p and increases miR-17-5p, miR-20a-5p, and miR-192-5p levels. Finally, H-EVOO decreases let-7e-5p, miR-10a-5p, miR-21-5p, and miR-26b-5p levels.

CONCLUSION

During the postprandial state, the levels of let-7e-5p decrease with EVOO regardless of polyphenol content suggesting a general response to the fatty acid composition of EVOO or/and the presence of at least 250 mg polyphenol kg-1 olive oil. Moreover, the miR-17-92 cluster increases by low and medium polyphenol content suggesting a role in fatty acid metabolism and nutrient sensing. Thus, postprandial modulation of circulating microRNAs levels could be a potential mechanism for the cardiovascular benefits associated with EVOO intake.

DNA methylation and incident cardiovascular disease

PURPOSE OF REVIEW

DNA methylation is an epigenetic mark that reflects both genetic and environmental influences over the life course and has the potential to be a robust biomarker for cardiovascular disease (CVD) risk. However, standard association studies linking DNA methylation and CVD are susceptible to reverse causation and may not directly translate into useful biomarkers of future disease. Studies of incident CVD represent a crucial tool for improving this evidence base.

RECENT FINDINGS

Recent investigations have started to provide links between DNA methylation and incident CVD. Epigenome-wide association studies have suggested individual genetic loci in which differential methylation exists prior to disease onset, while multivariate predictive modeling approaches have made progress towards realizing the potential for DNA methylation as a predictive biomarker of CVD risk. Meanwhile, complementary analysis strategies such as Mendelian randomization have provided clues as to the causality of these epigenomic associations.

SUMMARY

Taken together, this wave of studies provides the basis for a better understanding of CVD pathophysiology and the development of more confident biomarkers of CVD risk.

Epigenomic Assessment of Cardiovascular Disease Risk and Interactions With Traditional Risk Metrics

Background Epigenome-wide association studies for cardiometabolic risk factors have discovered multiple loci associated with incident cardiovascular disease (CVD). However, few studies have sought to directly optimize a predictor of CVD risk. Furthermore, it is challenging to train multivariate models across multiple studies in the presence of study- or batch effects. Methods and Results Here, we analyzed existing DNA methylation data collected using the Illumina HumanMethylation450 microarray to create a predictor of CVD risk across 3 cohorts: Women's Health Initiative, Framingham Heart Study Offspring Cohort, and Lothian Birth Cohorts. We trained Cox proportional hazards-based elastic net regressions for incident CVD separately in each cohort and used a recently introduced cross-study learning approach to integrate these individual scores into an ensemble predictor. The methylation-based risk score was associated with CVD time-to-event in a held-out fraction of the Framingham data set (hazard ratio per SD=1.28, 95% CI, 1.10-1.50) and predicted myocardial infarction status in the independent REGICOR (Girona Heart Registry) data set (odds ratio per SD=2.14, 95% CI, 1.58-2.89). These associations remained after adjustment for traditional cardiovascular risk factors and were similar to those from elastic net models trained on a directly merged data set. Additionally, we investigated interactions between the methylation-based risk score and both genetic and biochemical CVD risk, showing preliminary evidence of an enhanced performance in those with less traditional risk factor elevation. Conclusions This investigation provides proof-of-concept for a genome-wide, CVD-specific epigenomic risk score and suggests that DNA methylation data may enable the discovery of high-risk individuals who would be missed by alternative risk metrics.

A gene-diet interaction-based score predicts response to dietary fat in the Women's Health Initiative

BACKGROUND

Although diet response prediction for cardiometabolic risk factors (CRFs) has been demonstrated using single genetic variants and main-effect genetic risk scores, little investigation has gone into the development of genome-wide diet response scores.

OBJECTIVE

We sought to leverage the multistudy setup of the Women's Health Initiative cohort to generate and test genetic scores for the response of 6 CRFs (BMI, systolic blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, and fasting glucose) to dietary fat.

METHODS

A genome-wide interaction study was undertaken for each CRF in women (n ∼ 9000) not participating in the dietary modification (DM) trial, which focused on the reduction of dietary fat. Genetic scores based on these analyses were developed using a pruning-and-thresholding approach and tested for the prediction of 1-y CRF changes as well as long-term chronic disease development in DM trial participants (n ∼ 5000).

RESULTS

Only 1 of these genetic scores, for LDL cholesterol, predicted changes in the associated CRF. This 1760-variant score explained 3.7% (95% CI: 0.09, 11.9) of the variance in 1-y LDL cholesterol changes in the intervention arm but was unassociated with changes in the control arm. In contrast, a main-effect genetic risk score for LDL cholesterol was not useful for predicting dietary fat response. Further investigation of this score with respect to downstream disease outcomes revealed suggestive differential associations across DM trial arms, especially with respect to coronary heart disease and stroke subtypes.

CONCLUSIONS

These results lay the foundation for the combination of many genome-wide gene-diet interactions for diet response prediction while highlighting the need for further research and larger samples in order to achieve robust biomarkers for use in personalized nutrition.

NutriGenomeDB: a nutrigenomics exploratory and analytical platform

Habitual consumption of certain foods has shown beneficial and protective effects against multiple chronic diseases. However, it is not clear by which molecular mechanisms they may exert their beneficial effects. Multiple -omic experiments available in public databases have generated gene expression data following the treatment of human cells with different food nutrients and bioactive compounds. Exploration of such data in an integrative manner offers excellent possibilities for gaining insights into the molecular effects of food compounds and bioactive molecules at the cellular level. Here we present NutriGenomeDB, a web-based application that hosts manually curated gene sets defined from gene expression signatures, after differential expression analysis of nutrigenomics experiments performed on human cells available in the Gene Expression Omnibus (GEO) repository. Through its web interface, users can explore gene expression data with interactive visualizations. In addition, external gene signatures can be connected with nutrigenomics gene sets using a gene pattern-matching algorithm. We further demonstrate how the application can capture the primary molecular mechanisms of a drug used to treat hypertension and thus connect its mode of action with hosted food compounds.

Epigenome-wide association study reveals a molecular signature of response to phylloquinone (vitamin K1) supplementation

Evidence suggests there are roles for vitamin K in various chronic disease outcomes, but population-level diet and supplement recommendations are difficult to determine due to high levels of variability in measures of status and response to intake compared to other nutrients. In this preliminary investigation, a blood-based epigenome-wide association study (EWAS) comparing responders and non-responders to phylloquinone (vitamin K1) supplementation (NCT00183001) was undertaken in order to better understand the molecular underpinnings of this observed variability. Responders (n = 24) and non-responders (n = 24) were identified in a prior 3-year phylloquinone supplementation trial based on their changes in plasma phylloquinone concentrations. Differential DNA methylation was identified in multiple regions with previously unknown relationships to phylloquinone absorption and metabolism, such as at the TMEM263 locus. A hypothesis-driven analysis of lipid-related genes highlighted a site in the NPC1L1 gene, supplementing existing evidence for its role in phylloquinone absorption. Furthermore, an EWAS for baseline plasma phylloquinone concentrations revealed a strong correlation between the epigenomic signatures of phylloquinone baseline status and response to supplementation. This work can guide future epigenomic research on vitamin K and contributes to the development of more personalized dietary recommendations for vitamin K.

Perspective: Dietary Biomarkers of Intake and Exposure-Exploration with Omics Approaches

While conventional nutrition research has yielded biomarkers such as doubly labeled water for energy metabolism and 24-h urinary nitrogen for protein intake, a critical need exists for additional, equally robust biomarkers that allow for objective assessment of specific food intake and dietary exposure. Recent advances in high-throughput MS combined with improved metabolomics techniques and bioinformatic tools provide new opportunities for dietary biomarker development. In September 2018, the NIH organized a 2-d workshop to engage nutrition and omics researchers and explore the potential of multiomics approaches in nutritional biomarker research. The current Perspective summarizes key gaps and challenges identified, as well as the recommendations from the workshop that could serve as a guide for scientists interested in dietary biomarkers research. Topics addressed included study designs for biomarker development, analytical and bioinformatic considerations, and integration of dietary biomarkers with other omics techniques. Several clear needs were identified, including larger controlled feeding studies, testing a variety of foods and dietary patterns across diverse populations, improved reporting standards to support study replication, more chemical standards covering a broader range of food constituents and human metabolites, standardized approaches for biomarker validation, comprehensive and accessible food composition databases, a common ontology for dietary biomarker literature, and methodologic work on statistical procedures for intake biomarker discovery. Multidisciplinary research teams with appropriate expertise are critical to moving forward the field of dietary biomarkers and producing robust, reproducible biomarkers that can be used in public health and clinical research.

Physical fitness and physical activity association with cognitive function and quality of life: baseline cross-sectional analysis of the PREDIMED-Plus trial

Physical activity (PA) has been hypothesized to be effective to maintaining cognitive function and delay cognitive decline in the elderly, but physical fitness (PF) could be a better predictor of cognitive function. We aimed to study the association between PA and PF with cognitive function and quality of life using cross-sectional data from 6874 participants of the PREDIMED-Plus trial (64.9 ± 4.9 years, 48.5% female). PF and PA were measured with a Chair Stand Test, the REGICOR and Rapid Assessment Physical Activity questionnaires. Cognitive function was measured with Mini-mental State Examination, Control Oral Word Association Test, Trail Making Test and Digit Span tests; whereas health-related quality of life was assessed with the SF36-HRQL test. Cognitive and quality of life scores were compared among PF quartiles and PA levels (low, moderate and high) with ANCOVA and with Chair Stand repetitions and energy expenditure from total PA with multivariable linear regression adjusted for confounding factors. PF associated with higher scores in phonemic and semantic verbal fluency tests and with lower TMT A time. However, PA was not associated with the neurocognitive parameters evaluated. Both PF and PA levels were strongly associated with a better quality of life. We concluded that PF, but not PA, is associated with a better cognitive function. This trial was retrospectively registered at the International Standard Randomized Controlled Trial (ISRCTN89898870, https://www.isrctn.com/ISRCTN89898870?q=ISRCTN89898870&filters=&sort=&offset=1&totalResults=1&page=1&pageSize=10&searchType=basic-search) on 07/24/2014.

Influence of the ACTN3 R577X genotype on the injury epidemiology of marathon runners

A common single nucleotide polymorphism in the ACTN3 gene might result in the complete deficiency of α-actinin-3 (i.e., XX genotype). It has been found that ACTN3 XX individuals have several traits related to lessened muscle performance. This study aimed to determine the influence, if any, of ACTN3 genotypes on injury incidence of marathoners during the year preceding to participating in a competitive marathon race. Using a cross-sectional experimental design, the type and conditions of sports injuries were documented for one year in a group of 139 marathoners. Injuries were recorded following a consensus statement on injuries in Athletics. Afterward, ACTN3 genotyping was performed, and injury epidemiology was compared among RR, RX, and XX genotypes. The distribution of the RR/RX/XX genotypes was 28.8/42.8/23.5%, respectively. A total of 67 injuries were recorded. The frequency of marathoners that reported any injury during the previous year was not different across the genotypes (55.0/38.8/40.6%, P = 0.241). Although the overall injury incidence was not different among genotypes (2.78/1.65/1.94 injuries/1000 h of running, P = 0.084), the likelihood of suffering an injury was higher in RR than in RX (OR = 1.93: 95%CI = 0.87–4.30), and higher than in XX (OR = 1.79: 0.70–4.58). There was no difference in the conditions, severity, body location, time of year, or leading cause of injury among genotypes. However, XX presented a higher frequency of sudden-onset injuries (P = 0.024), and the OR for muscle-type injuries was 2.0 (0.51–7.79) times higher compared to RR runners. Although XX marathoners did not have a higher overall incidence of injury, the OR in these runners for muscle-type injuries was superior to RR and RX runners. The likelihood of suffering a muscle injury, especially with a sudden-onset, was twice in XX than in RR endurance runners.

Lipidomic profiling identifies signatures of metabolic risk

BACKGROUND

Metabolic syndrome (MetS), the clustering of metabolic risk factors, is associated with cardiovascular disease risk. We sought to determine if dysregulation of the lipidome may contribute to metabolic risk factors.

METHODS

We measured 154 circulating lipid species in 658 participants from the Framingham Heart Study (FHS) using liquid chromatography-tandem mass spectrometry and tested for associations with obesity, dysglycemia, and dyslipidemia. Independent external validation was sought in three independent cohorts. Follow-up data from the FHS were used to test for lipid metabolites associated with longitudinal changes in metabolic risk factors.

RESULTS

Thirty-nine lipids were associated with obesity and eight with dysglycemia in the FHS. Of 32 lipids that were available for replication for obesity and six for dyslipidemia, 28 (88%) replicated for obesity and five (83%) for dysglycemia. Four lipids were associated with longitudinal changes in body mass index and four were associated with changes in fasting blood glucose in the FHS.

CONCLUSIONS

We identified and replicated several novel lipid biomarkers of key metabolic traits. The lipid moieties identified in this study are involved in biological pathways of metabolic risk and can be explored for prognostic and therapeutic utility.

Potential Interplay between Dietary Saturated Fats and Genetic Variants of the NLRP3 Inflammasome to Modulate Insulin Resistance and Diabetes Risk: Insights from a Meta-Analysis of 19 005 Individuals

SCOPE

Insulin resistance (IR) and inflammation are hallmarks of type 2 diabetes (T2D). The nod-like receptor pyrin domain containing-3 (NLRP3) inflammasome is a metabolic sensor activated by saturated fatty acids (SFA) initiating IL-1β inflammation and IR. Interactions between SFA intake and NLRP3-related genetic variants may alter T2D risk factors.

METHODS

Meta-analyses of six Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (n = 19 005) tested interactions between SFA and NLRP3-related single-nucleotide polymorphisms (SNPs) and modulation of fasting insulin, fasting glucose, and homeostasis model assessment of insulin resistance.

RESULTS

SFA interacted with rs12143966, wherein each 1% increase in SFA intake increased insulin by 0.0063 IU mL-1 (SE ± 0.002, p = 0.001) per each major (G) allele copy. rs4925663, interacted with SFA (β ± SE = -0.0058 ± 0.002, p = 0.004) to increase insulin by 0.0058 IU mL-1 , per additional copy of the major (C) allele. Both associations are close to the significance threshold (p < 0.0001). rs4925663 causes a missense mutation affecting NLRP3 expression.

CONCLUSION

Two NLRP3-related SNPs showed potential interaction with SFA to modulate fasting insulin. Greater dietary SFA intake accentuates T2D risk, which, subject to functional validation, may be further elaborated depending on NLRP3-related genetic variants.

DNA methylation modules associate with incident cardiovascular disease and cumulative risk factor exposure

BACKGROUND

Epigenome-wide association studies using DNA methylation have the potential to uncover novel biomarkers and mechanisms of cardiovascular disease (CVD) risk. However, the direction of causation for these associations is not always clear, and investigations to-date have often failed to replicate at the level of individual loci.

METHODS

Here, we undertook module- and region-based DNA methylation analyses of incident CVD in the Women's Health Initiative (WHI) and Framingham Heart Study Offspring Cohort (FHS) in order to find more robust epigenetic biomarkers for cardiovascular risk. We applied weighted gene correlation network analysis (WGCNA) and the Comb-p algorithm to find methylation modules and regions associated with incident CVD in the WHI dataset.

RESULTS

We discovered two modules whose activation correlated with CVD risk and replicated across cohorts. One of these modules was enriched for development-related processes and overlaps strongly with epigenetic aging sites. For the other, we showed preliminary evidence for monocyte-specific effects and statistical links to cumulative exposure to traditional cardiovascular risk factors. Additionally, we found three regions (associated with the genes SLC9A1, SLC1A5, and TNRC6C) whose methylation associates with CVD risk.

CONCLUSIONS

In sum, we present several epigenetic associations with incident CVD which reveal disease mechanisms related to development and monocyte biology. Furthermore, we show that epigenetic modules may act as a molecular readout of cumulative cardiovascular risk factor exposure, with implications for the improvement of clinical risk prediction.

A Genome-Wide Association Study Identifies Blood Disorder-Related Variants Influencing Hemoglobin A1c With Implications for Glycemic Status in U.S. Hispanics/Latinos

OBJECTIVE

We aimed to identify hemoglobin A_1c (HbA_1c)-associated genetic variants and examine their implications for glycemic status evaluated by HbA_1c in U.S. Hispanics/Latinos with diverse genetic ancestries.

RESEARCH DESIGN AND METHODS

We conducted a genome-wide association study (GWAS) of HbA_1c in 9,636 U.S. Hispanics/Latinos without diabetes from the Hispanic Community Health Study/Study of Latinos, followed by a replication among 4,729 U.S. Hispanics/Latinos from three independent studies.

RESULTS

Our GWAS and replication analyses showed 10 previously known and novel loci associated with HbA_1c at genome-wide significance levels (P < 5.0 × 10^-8). In particular, two African ancestry-specific variants, HBB-rs334 and G6PD-rs1050828, which are causal mutations for sickle cell disease and G6PD deficiency, respectively, had ∼10 times larger effect sizes on HbA_1c levels (β = -0.31% [-3.4 mmol/mol]) and -0.35% [-3.8 mmol/mol] per minor allele, respectively) compared with other HbA_1c-associated variants (0.03-0.04% [0.3-0.4 mmol/mol] per allele). A novel Amerindian ancestry-specific variant, HBM-rs145546625, was associated with HbA_1c and hematologic traits but not with fasting glucose. The prevalence of hyperglycemia (prediabetes and diabetes) defined using fasting glucose or oral glucose tolerance test 2-h glucose was similar between carriers of HBB-rs334 or G6PD-rs1050828 HbA_1c-lowering alleles and noncarriers, whereas the prevalence of hyperglycemia defined using HbA_1c was significantly lower in carriers than in noncarriers (12.2% vs. 28.4%, P < 0.001). After recalibration of the HbA_1c level taking HBB-rs334 and G6PD-rs1050828 into account, the prevalence of hyperglycemia in carriers was similar to noncarriers (31.3% vs. 28.4%, P = 0.28).

CONCLUSIONS

This study in U.S. Hispanics/Latinos found several ancestry-specific alleles associated with HbA_1c through erythrocyte-related rather than glycemic-related pathways. The potential influences of these nonglycemic-related variants need to be considered when the HbA_1c test is performed.

Edible Mushrooms Reduce Atherosclerosis in Ldlr-/- Mice Fed a High-Fat Diet

BACKGROUND

Commonly consumed mushrooms, portobello (PBM) and shiitake (SHM), are abundant in nutrients, soluble dietary fibers, and bioactive compounds that have been implicated as beneficial in reducing inflammation, improving lipid profiles, and ameliorating heart disease and atherosclerosis, an inflammatory disease of the arteries.

OBJECTIVE

The aim of this study was to determine effects of PBM and SHM in preventing atherosclerosis and associated inflammation in an animal model.

METHODS

Four-week-old Ldlr-/- male mice were divided into 5 dietary groups for 16 wk: a low-fat control (LF-C, 11 kcal% fat), high-fat control (HF-C, 18.9 kcal% fat), HF + 10% (wt:wt) PBM (HF-PBM, 19.5 kcal% fat) or SHM (HF-SHM, 19.7 kcal% fat) powder, and HF + mushroom control mix (MIX-C, 19.6 kcal% fat), a diet best matched to the average macronutrient content of both mushrooms. Body composition was measured using MRI. Aortic tricuspid valves and aortas were collected and stained to quantify plaque formation. Adhesion molecule expression was quantified by immunohistochemistry. Plasma lipid and cytokine concentrations were measured.

RESULTS

We found that mice fed a HF-SHM diet had ∼86% smaller aortic lesion area than mice in both HF-C (P < 0.01) and MIX-C (P < 0.01) groups and also expressed 31-48% lower vascular cell adhesion molecule-1 levels (P < 0.05) than all other groups. Similarly, HF-PBM-fed mice displayed a 70% reduction in aortic lesion area in the tricuspid valve only (P < 0.05). Both mushroom-fed groups had lower weight gain and fat mass (P < 0.05) than the control groups.

CONCLUSION

These results suggest that consumption of PBMs and particularly SHMs is effective in preventing development of high-fat diet-induced atherosclerosis in Ldlr-/- mice. Future studies will determine active components in mushrooms responsible for this beneficial effect.

Ultra-processed Food Consumption and Incident Frailty: A Prospective Cohort Study of Older Adults

Background

Ultra-processed food intake has been associated with chronic conditions and mortality. The aim of this study was to assess the relationship between ultra-processed food intake and incident frailty in community-dwelling older adults.

Methods

Prospective cohort study with 1,822 individuals aged at least 60 years who were recruited during 2008–2010 in Spain. At baseline, food consumption was obtained using a validated computerized face-to-face dietary history. Ultra-processed foods were identified according to the nature and extent of their industrial processing (NOVA classification). In 2012, incident frailty was ascertained based on Fried’s criteria. Statistical analyses were performed with logistic regression and adjusted for the main potential confounders.

Results

After a mean follow-up of 3.5 years, 132 cases of frailty were identified. The fully adjusted risks of frailty across increasing quartiles of the percentage of total energy intake from ultra-processed foods were the following: 0.04 (0.02–0.05), 0.05 (0.03–0.07), 0.09 (0.07–0.12), and 0.11 (0.08–0.14). Results were similar when food consumption was expressed as gram per day/body weight. Regarding ultra-processed food groups, the highest versus the lowest tertiles of consumption of yogurts and fermented milks, cakes and pastries, as well as nonalcoholic beverages (instant coffee and cocoa, packaged juices, and other nonalcoholic drinks, excluding soft drinks) were also significantly related to incident frailty.

Conclusions

Consumption of ultra-processed foods is strongly associated with frailty risk in older adults. Substituting unprocessed or minimally processed foods for ultra-processed foods would play an important role in the prevention of age-related frailty.

Trial registration

NCT02804672.

Fermented dairy products, diet quality, and cardio-metabolic profile of a Mediterranean cohort at high cardiovascular risk

BACKGROUND AND AIMS

Fermented dairy products have been associated with a better diet quality and cardio-metabolic profile. However, in Mediterranean populations, these associations have not been well characterized. The aim of this study was to assess the diet quality and the associations between the consumption of total fermented dairy products and their subtypes and the prevalence of Metabolic Syndrome (MetS) components in a Mediterranean population at high cardiovascular risk.

METHODS AND RESULTS

Baseline cross-sectional analyses were conducted on 6,572 men and women (mean age: 65 years) with overweight or obesity and MetS recruited into the PREDIMED-Plus cohort. A 143-item Food Frequency Questionnaire (FFQ) was used, and anthropometrical, biochemical, and blood pressure measurements were recorded. Multivariate-adjusted Cox regressions were fitted to analyze the association between quartiles of consumption of fermented dairy products and their subtypes and MetS components to estimate the relative risk (RR) and 95% confidence intervals (95% CIs). Participants who were high consumers of fermented dairy products reported a higher consumption of fruit, vegetables, fish, nuts, and whole bread and a lower consumption of white bread, alcohol, and cookies. Participants in the higher quartile showed a lower prevalence of the low HDL-cholesterol component of the MetS (RR=0.88; 95% CI: 0.78-0.98) than those in the lowest quartile of cheese consumption. Cheese consumption was inversely associated with the prevalence of hypertriglyceridemia. Total fermented dairy products, yogurt, and its types were not associated with any of the MetS components.

CONCLUSIONS

Compared to nonconsumers, participants consuming fermented dairy products reported a better diet quality and, particularly, cheese consumers presented a lower prevalence of hypertriglyceridemia and low HDL-cholesterol plasma levels, which are MetS components.

Dietary epicatechin improves survival and delays skeletal muscle degeneration in aged mice

We recently reported that epicatechin, a bioactive compound that occurs naturally in various common foods, promoted general health and survival of obese diabetic mice. It remains to be determined whether epicatechin extends health span and delays the process of aging. In the present study, epicatechin or its analogue epigallocatechin gallate (EGCG) (0.25% w/v in drinking water) was administered to 20-mo-old male C57BL mice fed a standard chow. The goal was to determine the antiaging effect. The results showed that supplementation with epicatechin for 37 wk strikingly increased the survival rate from 39 to 69%, whereas EGCG had no significant effect. Consistently, epicatechin improved physical activity, delayed degeneration of skeletal muscle (quadriceps), and shifted the profiles of the serum metabolites and skeletal muscle general mRNA expressions in aging mice toward the profiles observed in young mice. In particular, we found that dietary epicatechin significantly reversed age-altered mRNA and protein expressions of extracellular matrix and peroxisome proliferator–activated receptor pathways in skeletal muscle, and reversed the age-induced declines of the nicotinate and nicotinamide pathway both in serum and skeletal muscle. The present study provides evidence that epicatechin supplementation can exert an antiaging effect, including an increase in survival, an attenuation of the aging-related deterioration of skeletal muscles, and a protection against the aging-related decline in nicotinate and nicotinamide metabolism.—Si, H., Wang, X., Zhang, L., Parnell, L. D., Ahmed, B., LeRoith, T., Ansah, T.-A., Zhang, L., Li, J., Ordovás, J. M., Si, H., Liu, D., Lai, C.-Q. Dietary epicatechin improves survival and delays skeletal muscle degeneration in aged mice.

Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent

SCOPE

Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption.

METHODS AND RESULTS

A genome-wide interaction study to discover genetic variants that account for variation in BMI in the context of low-fat, high-fat and total dairy intake in cross-sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta-analyzed. Twenty-six genetic variants reached the selected significance threshold (p-interaction <10-7) , and six independent variants (LINC01512-rs7751666, PALM2/AKAP2-rs914359, ACTA2-rs1388, PPP1R12A-rs7961195, LINC00333-rs9635058, AC098847.1-rs1791355) were evaluated meta-analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3' of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 × 10-8) such that each serving of low-fat dairy was associated with 0.225 kg m-2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2-rs1388) approached interaction replication significance for low-fat dairy exposure.

CONCLUSION

Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight.

Advances in Understanding the Molecular Basis of the Mediterranean Diet Effect

Increasingly, studies showing the protective effects of the Mediterranean diet (MedDiet) on different diseases (cardiovascular, diabetes, some cancers, and even total mortality and aging indicators) are being published. The scientific evidence level for each outcome is variable, and new studies are needed to better understand the molecular mechanisms whereby the MedDiet may exercise its effects. Here, we present recent advances in understanding the molecular basis of MedDiet effects, mainly focusing on cardiovascular diseases but also discussing other related diseases. There is heterogeneity in defining the MedDiet, and it can, owing to its complexity, be considered as an exposome with thousands of nutrients and phytochemicals. We review MedDiet composition and assessment as well as the latest advances in the genomic, epigenomic (DNA methylation, histone modifications, microRNAs, and other emerging regulators), transcriptomic (selected genes and whole transcriptome), and metabolomic and metagenomic aspects of the MedDiet effects (as a whole and for its most typical food components). We also present a critical review of the limitations of the studies undertaken and propose new analyses and greater bioinformatic integration to better understand the most important molecular mechanisms whereby the MedDiet as a whole, or its main food components, may exercise their protective effects.

Using Genetic Technologies To Reduce, Rather Than Widen, Health Disparities

Evidence shows that both biological and nonbiological factors contribute to health disparities. Genetics, in particular, plays a part in how common diseases manifest themselves. Today, unprecedented advances in genetically based diagnoses and treatments provide opportunities for personalized medicine. However, disadvantaged groups may lack access to these advances, and treatments based on research on non-Hispanic whites might not be generalizable to members of minority groups. Unless genetic technologies become universally accessible, existing disparities could be widened. Addressing this issue will require integrated strategies, including expanding genetic research, improving genetic literacy, and enhancing access to genetic technologies among minority populations in a way that avoids harms such as stigmatization.