Gene expression and fatty acid profiling in longissimus thoracis muscle, subcutaneous fat, and liver of light lambs in response to concentrate or alfalfa grazing

A better understanding of gene expression and metabolic pathways in response to a feeding system is critical for identifying key physiological processes and genes associated with polyunsaturated fatty acid (PUFA) content in lamb meat. The main objective of this study was to investigate transcriptional changes in L. thoracis (LT) muscle, liver, and subcutaneous fat (SF) of lambs that grazed alfalfa (ALF) and concentrate-fed (CON) slaughtered at 23 kg and using the Affymetrix Ovine Gene 1.1 ST whole-genome array. The study also evaluated the relationship between meat traits in LT muscle, including color, pigments and lipid oxidation during 7 days of display, a-tocopherol content, intramuscular fat (IMF) content and the fatty acid (FA) profile. Lambs that grazed on alfalfa had a greater a-tocopherol concentration in plasma than CON lambs (P 0.05). Grazing increased the a-tocopherol content (P < 0.001) and decreased lipid oxidation on day 7 of display (P < 0.05) in LT muscle. The ALF group contained a greater amount of conjugated linoleic acid (CLA), C18:3 n-3, C20:5 n-3, C22:5 n-3, and C22:6 n-3 than did the CON group (P < 0.05). We identified 41, 96 and four genes differentially expressed in LT muscle, liver, and subcutaneous fat, respectively. The most enriched biological processes in LT muscle were skeletal muscle tissue development, being the genes related to catabolic and lipid processes downregulated, except for CPT1B, which was upregulated in the ALF lambs. Animals grazing alfalfa had lower expression of desaturase enzymes in the liver (FADS1 and FADS2), which regulate unsaturation of fatty acids and are directly involved in the metabolism of n-3 PUFA series. The results found in the current study showed that ingesting diets richer in n-3 PUFA might have negative effects on the de novo synthesis of n-3 PUFA by downregulating the FADS1 and FADS2 expression. However, feeding diets poorer in n-3 PUFA can promote fatty acid desaturation, which makes these two genes attractive candidates for altering the content of PUFAs in meat

Work shift, lifestyle factors, and subclinical atherosclerosis in spanish male workers: A mediation analysis

(1) Background: Working night shifts has been associated with altered circadian rhythms, lifestyle habits, and cardiometabolic risks. No information on the potential association of working shift and the presence of atherosclerosis is available. The aim of this study was to quantify the association between different work shifts and the presence of subclinical atherosclerosis objectively measured by imaging. (2) Methods: Analyses were conducted on the baseline data of the Aragon Workers Health Study (AWHS) cohort, including information on 2459 middle-aged men. Categories of shift work included central day shift, rotating morning-evening or morning-evening-night shift, and night shift. The presence of atherosclerotic plaques was assessed by 2D ultrasound in the carotid and femoral vascular territories. Multivariable logistic models and mediation analysis were conducted to characterize and quantify the association between study variables. (3) Results: Participants working night or rotating shifts presented an overall worse cardiometabolic risk profile, as well as more detrimental lifestyle habits. Workers in the most intense (morning-evening-night) rotating shift presented higher odds of subclinical atherosclerosis (odds ratio: 1.6; 95% confidence interval: 1.12 to 2.27) compared to workers in the central shift, independently of the presence of lifestyle and metabolic risk factors. A considerable (21%) proportion of this association was found to be mediated by smoking, indicating that altered sleep-wake cycles have a direct relationship with the early presence of atherosclerotic lesions. (4) Conclusions: Work shifts should be factored in during workers health examinations, and when developing effective workplace wellness programs

Nutrigenomics, the microbiome, and gene-environment interactions: New directions in cardiovascular disease research, prevention, and treatment

Cardiometabolic diseases are the leading cause of death worldwide and are strongly linked to both genetic and nutritional factors. The field of nutrigenomics encompasses multiple approaches aimed at understanding the effects of diet on health or disease development, including nutrigenetic studies investigating the relationship between genetic variants and diet in modulating cardiometabolic risk, as well as the effects of dietary components on multiple "omic" measures, including transcriptomics, metabolomics, proteomics, lipidomics, epigenetic modifications, and the microbiome. Here, we describe the current state of the field of nutrigenomics with respect to cardiometabolic disease research and outline a direction for the integration of multiple omics techniques in future nutrigenomic studies aimed at understanding mechanisms and developing new therapeutic options for cardiometabolic disease treatment and prevention

Automatic quantification of cardiomyocyte dimensions and connexin 43 lateralization in fluorescence images

Cardiomyocytes’ geometry and connexin 43 (CX43) amount and distribution are structural features that play a pivotal role in electrical conduction. Their quantitative assessment is of high interest in the study of arrhythmias, but it is usually hampered by the lack of automatic tools. In this work, we propose a software algorithm (Myocyte Automatic Retrieval and Tissue Analyzer, MARTA) to automatically detect myocytes from fluorescent microscopy images of cardiac tissue, measure their morphological features and evaluate the expression of CX43 and its degree of lateralization. The proposed software is based on the generation of cell masks, contouring of individual cells, enclosing of cells in minimum area rectangles and splitting of these rectangles into end-to-end and middle compartments to estimate CX43 lateral-to-total ratio. Application to human ventricular tissue images shows that mean differences between automatic and manual methods in terms of cardiomyocyte length and width are below 4 µm. The percentage of lateral CX43 also agrees between automatic and manual evaluation, with the interquartile range approximately covering from 3% to 30% in both cases. MARTA is not limited by fiber orientation and has an optimized speed by using contour filtering, which makes it run hundreds of times faster than a trained expert. Developed for CX43 studies in the left ventricle, MARTA is a flexible tool applicable to morphometric and lateralization studies of other markers in any heart chamber or even skeletal muscle. This open-access software is available online

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

Lipoprotein metabolism indicators improve cardiovascular risk prediction

Background: Cardiovascular disease risk increases when lipoprotein metabolism is dysfunctional. We have developed a computational model able to derive indicators of lipoprotein production, lipolysis, and uptake processes from a single lipoprotein profile measurement. This is the first study to investigate whether lipoprotein metabolism indicators can improve cardiovascular risk prediction and therapy management. Methods and Results: We calculated lipoprotein metabolism indicators for 1981 subjects (145 cases, 1836 controls) from the Framingham Heart Study offspring cohort in which NMR lipoprotein profiles were measured. We applied a statistical learning algorithm using a support vector machine to select conventional risk factors and lipoprotein metabolism indicators that contributed to predicting risk for general cardiovascular disease. Risk prediction was quantified by the change in the Area-Under-the-ROC-Curve (ΔAUC) and by risk reclassification (Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI)). Two VLDL lipoprotein metabolism indicators (VLDLE and VLDLH) improved cardiovascular risk prediction. We added these indicators to a multivariate model with the best performing conventional risk markers. Our method significantly improved both CVD prediction and risk reclassification. Conclusions: Two calculated VLDL metabolism indicators significantly improved cardiovascular risk prediction. These indicators may help to reduce prescription of unnecessary cholesterol-lowering medication, reducing costs and possible side-effects. For clinical application, further validation is required. © 2014 van Schalkwijk et al

Actigraphic sleep fragmentation, efficiency and duration associate with dietary intake in the Rotterdam Study

Short self-reported sleep duration is associated with dietary intake and this association may partly mediate the link between short sleep and metabolic abnormalities. Subjective sleep measures, however, may be inaccurate and biased. The objective of this study was to evaluate the associations between actigraphic measures of sleep fragmentation, efficiency and duration and energy and macronutrient intakes. We used data from a subgroup of 439 participants of the population-based cohort, Rotterdam Study. Sleep was assessed using 7-day actigraphy and sleep diaries, and dietary data with a validated food frequency questionnaire. We assessed the associations of actigraphic sleep parameters with dietary intake using multivariable linear regression models. Higher sleep fragmentation was associated with 4.19 g lower carbohydrate intake per standard deviation of fragmentation {β [95% confidence interval (CI) = −4.19 (−8.0, −0.3)]; P = 0.03}. Each additional percentage increase in sleep efficiency was associated with 11.1 kcal lower energy intake [β (95% CI) = −11.1 (−20.6, −1.7); P = 0.02]. Furthermore, very short sleep duration (<5.5 h) was associated with 218.1 kcal higher energy intake [β (95% CI = 218.06 (33.3, 402.8), P = 0.02], relative to the reference group (≥6.5 to <7.5 h). We observed associations between higher sleep fragmentation with lower carbohydrate intake, and both lower sleep efficiency and very short sleep duration (<5 h) with higher energy intake. The association between sleep and higher energy intake could mediate, in part, the link between short sleep or sleep fragmentation index and metabolic abnormalities

Actigraphic sleep fragmentation, efficiency and duration associate with dietary intake in the Rotterdam Study

Short self-reported sleep duration is associated with dietary intake and this association may partly mediate the link between short sleep and metabolic abnormalities. Subjective sleep measures, however, may be inaccurate and biased. The objective of this study was to evaluate the associations between actigraphic measures of sleep fragmentation, efficiency and duration and energy and macronutrient intakes. We used data from a subgroup of 439 participants of the population-based cohort, Rotterdam Study. Sleep was assessed using 7-day actigraphy and sleep diaries, and dietary data with a validated food frequency questionnaire. We assessed the associations of actigraphic sleep parameters with dietary intake using multivariable linear regression models. Higher sleep fragmentation was associated with 4.19 g lower carbohydrate intake per standard deviation of fragmentation {β [95% confidence interval (CI) = −4.19 (−8.0, −0.3)]; P = 0.03}. Each additional percentage increase in sleep efficiency was associated with 11.1 kcal lower energy intake [β (95% CI) = −11.1 (−20.6, −1.7); P = 0.02]. Furthermore, very short sleep duration (<5.5 h) was associated with 218.1 kcal higher energy intake [β (95% CI = 218.06 (33.3, 402.8), P = 0.02], relative to the reference group (≥6.5 to <7.5 h). We observed associations between higher sleep fragmentation with lower carbohydrate intake, and both lower sleep efficiency and very short sleep duration (<5 h) with higher energy intake. The association between sleep and higher energy intake could mediate, in part, the link between short sleep or sleep fragmentation index and metabolic abnormalities