Effects of ambient air pollution on obesity and ectopic fat deposition:a protocol for a systematic review and meta-analysis

Introduction - Globally, the prevalence of obesity tripled from 1975 to 2016. There is evidence that air pollution may contribute to the obesity epidemic through an increase in oxidative stress and inflammation of adipose tissue. However, the impact of air pollution on body weight at a population level remains inconclusive. This systematic review and meta-analysis will estimate the association of ambient air pollution with obesity, distribution of ectopic adipose tissue, and the incidence and prevalence of non-alcoholic fatty liver disease among adults. Methods and analysis.The study will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for conduct and reporting. The search will include the following databases: Ovid Medline, Embase, PubMed, Web of Science and Latin America and the Caribbean Literature on Health Sciences, and will be supplemented by a grey literature search. Each article will be independently screened by two reviewers, and relevant data will be extracted independently and in duplicate. Study-specific estimates of associations and their 95% Confidence Intervals will be pooled using a DerSimonian and Laird random-effects model, implemented using the RevMan software. The I2 statistic will be used to assess interstudy heterogeneity. The confidence in the body of evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.Ethics and disseminationAs per institutional policy, ethical approval is not required for secondary data analysis. In addition to being published in a peer-reviewed journal and presented at conferences, the results of the meta-analysis will be shared with key stakeholders, health policymakers and healthcare professionals.Prospero registration numberCRD42023423955

Metabolic Trajectories Following Contrasting Prudent and Western Diets from Food Provisions: Identifying Robust Biomarkers of Short-Term Changes in Habitual Diet

A large body of evidence has linked unhealthy eating with an alarming increase in obesity and chronic disease worldwide. However, existing methods of assessing dietary intake rely on food frequency questionnaires or dietary records that are prone to bias and selective reporting. Herein, metabolic phenotyping was performed on 42 healthy participants from the Diet and Gene Intervention (DIGEST) pilot study, a parallel two-arm randomized clinical trial that provided complete diets to all participants. Matching urine and plasma specimens were collected at baseline and following 2 weeks of provision of either a Prudent or Western diet with a weight-maintaining menu plan designed by a dietician. Targeted and nontargeted metabolite profiling was conducted using three complementary analytical platforms, where 80 serum metabolites and 84 creatinine-normalized urinary metabolites were reliably measured (CV 75%) after implementing a rigorous data workflow for metabolite authentication with stringent quality control. We classified a panel of metabolites with distinctive trajectories following 2 weeks of food provisions when using complementary univariate and multivariate statistical models. Unknown metabolites associated with contrasting dietary patterns were identified with high resolution MS/MS and/or co-elution after spiking with authentic standards. Overall, 3-methylhistidine and proline betaine concentrations increased consistently when participants were assigned a Prudent diet (q ± 0.30, p < 0.05) to changes in average intake of specific nutrients from self-reported diet records reflecting good adherence to food provisions. This study revealed robust biomarkers sensitive to short-term changes in habitual diet that can be used to reliably monitor healthy eating patterns for new advances in nutritional epidemiology, as well as the design of evidence-based public health policies for chronic disease prevention

Serum Metabolic Signatures of Chronic Limb-Threatening Ischemia in Patients with Peripheral Artery Disease

Peripheral artery disease (PAD) is characterized by the atherosclerotic narrowing of lower limb vessels, leading to ischemic muscle pain in older persons. Some patients experience progression to advanced chronic limb-threatening ischemia (CLTI) with poor long-term survivorship. Herein, we performed serum metabolomics to reveal the mechanisms of PAD pathophysiology that may improve its diagnosis and prognosis to CLTI complementary to the ankle&ndash;brachial index (ABI) and clinical presentations. Non-targeted metabolite profiling of serum was performed by multisegment injection&ndash;capillary electrophoresis&ndash;mass spectrometry (MSI&ndash;CE&ndash;MS) from age and sex-matched, non-diabetic, PAD participants who were recruited and clinically stratified based on the Rutherford classification into CLTI (n = 18) and intermittent claudication (IC, n = 20). Compared to the non-PAD controls (n = 20), PAD patients had lower serum concentrations of creatine, histidine, lysine, oxoproline, monomethylarginine, as well as higher circulating phenylacetylglutamine (p &lt; 0.05). Importantly, CLTI cases exhibited higher serum concentrations of carnitine, creatinine, cystine and trimethylamine-N-oxide along with lower circulating fatty acids relative to well matched IC patients. Most serum metabolites associated with PAD progression were also correlated with ABI (r = &plusmn;0.24&minus;0.59, p &lt; 0.05), whereas the ratio of stearic acid to carnitine, and arginine to propionylcarnitine differentiated CLTI from IC with good accuracy (AUC = 0.87, p = 4.0 &times; 10&minus;5). This work provides new biochemical insights into PAD progression for the early detection and surveillance of high-risk patients who may require peripheral vascular intervention to prevent amputation and premature death

Effects of ambient air pollution on obesity and ectopic fat deposition: a protocol for a systematic review and meta-analysis

Introduction Globally, the prevalence of obesity tripled from 1975 to 2016. There is evidence that air pollution may contribute to the obesity epidemic through an increase in oxidative stress and inflammation of adipose tissue. However, the impact of air pollution on body weight at a population level remains inconclusive. This systematic review and meta-analysis will estimate the association of ambient air pollution with obesity, distribution of ectopic adipose tissue, and the incidence and prevalence of non-alcoholic fatty liver disease among adults.Methods and analysis The study will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for conduct and reporting. The search will include the following databases: Ovid Medline, Embase, PubMed, Web of Science and Latin America and the Caribbean Literature on Health Sciences, and will be supplemented by a grey literature search. Each article will be independently screened by two reviewers, and relevant data will be extracted independently and in duplicate. Study-specific estimates of associations and their 95% Confidence Intervals will be pooled using a DerSimonian and Laird random-effects model, implemented using the RevMan software. The I2 statistic will be used to assess interstudy heterogeneity. The confidence in the body of evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.Ethics and dissemination As per institutional policy, ethical approval is not required for secondary data analysis. In addition to being published in a peer-reviewed journal and presented at conferences, the results of the meta-analysis will be shared with key stakeholders, health policymakers and healthcare professionals.PROSPERO registration number CRD42023423955

Sources of Variation in Food-Related Metabolites during Pregnancy

The extent to which variation in food-related metabolites are attributable to non-dietary factors remains unclear, which may explain inconsistent food-metabolite associations observed in population studies. This study examined the association between non-dietary factors and the serum concentrations of food-related biomarkers and quantified the amount of variability in metabolite concentrations explained by non-dietary factors. Pregnant women (n = 600) from two Canadian birth cohorts completed a validated semi-quantitative food frequency questionnaire, and serum metabolites were measured by multisegment injection-capillary electrophoresis-mass spectrometry. Hierarchical linear modelling and principal component partial R-square (PC-PR2) were used for data analysis. For proline betaine and DHA (mainly exogenous), citrus foods and fish/fish oil intake, respectively, explained the highest proportion of variability relative to non-dietary factors. The unique contribution of dietary factors was similar (15:0, 17:0, hippuric acid, TMAO) or lower (14:0, tryptophan betaine, 3-methylhistidine, carnitine) compared to non-dietary factors (i.e., ethnicity, maternal age, gestational age, pre-pregnancy BMI, physical activity, and smoking) for metabolites that can either be produced endogenously, biotransformed by gut microbiota, and/or derived from multiple food sources. The results emphasize the importance of adjusting for non-dietary factors in future analyses to improve the accuracy and precision of the measures of food intake and their associations with health and disease