Selection of complementary foods based on optimal nutritional values

Human milk is beneficial for growth and development of infants. Several factors result in mothers ceasing breastfeeding which leads to introduction of breast-milk substitutes (BMS). In some communities traditional foods are given as BMS, in others they are given as complementary foods during weaning. Improper food selection at this stage is associated with a high prevalence of malnutrition in children under 5 years. Here we listed the traditional foods from four continents and compared them with human milk based on their dietary contents. Vitamins such as thiamine (similar to[2-10] folds), riboflavin (similar to[4-10] folds) and ascorbic acid (< 2 folds) contents of Asian and African foods were markedly lower. In order to extend the search for foods that includes similar dietary constituents as human milk, we designed a strategy of screening 8654 foods. 12 foods were identified and these foods were evaluated for their ability to meet the daily nutritional requirement of breastfed and nonbreastfed infants during their first year of life. Genome-scale models of infant's hepatocytes, adipocytes and myocytes were then used to simulate in vitro growth of tissues when subjected to these foods. Key findings were that pork ham cured, fish pudding, and egg lean white induced better tissue growth, and quark with fruit, cheese quarg 45% and cheese cream 60% had similar lactose content as human milk

Perspectives on systems modeling of human peripheral blood mononuclear cells

Human peripheral blood mononuclear cells (PBMCs) are the key drivers of the immune responses. These cells undergo activation, proliferation and differentiation into various subsets. During these processes they initiate metabolic reprogramming, which is coordinated by specific gene and protein activities. PBMCs as a model system have been widely used to study metabolic and autoimmune diseases. Herein we review various omics and systems-based approaches such as transcriptomics, epigenomics, proteomics, and metabolomics as applied to PBMCs, particularly T helper subsets, that unveiled disease markers and the underlying mechanisms. We also discuss and emphasize several aspects of T cell metabolic modeling in healthy and disease states using genome-scale metabolic models.</p

Dysregulation of secondary bile acid metabolism precedes islet autoimmunity and type 1 diabetes

The gut microbiota is crucial in the regulation of bile acid (BA) metabolism. However, not much is known about the regulation of BAs during progression to type 1 diabetes (T1D). Here, we analyzed serum and stool BAs in longitudinal samples collected at 3, 6,12,18, 24, and 36 months of age from children who developed a single islet autoantibody (AAb) (P1Ab; n = 23) or multiple islet AAbs (P2Ab; n = 13) and controls (CTRs; n = 38) who remained AAb negative. We also analyzed the stool microbiome in a subgroup of these children. Factor analysis showed that age had the strongest impact on both BA and microbiome profiles. We found that at an early age, systemic BAs and microbial secondary BA pathways were altered in the P2Ab group compared with the P1Ab and CTR groups. Our findings thus suggest that dysregulated BA metabolism in early life may contribute to the risk and pathogenesis of T1D.Peer reviewe

Exposure to environmental contaminants is associated with altered hepatic lipid metabolism in non-alcoholic fatty liver disease

Background & aims: Recent experimental models and epidemiological studies suggest that specific environmental contaminants (ECs) contribute to the initiation and pathology of nonalcoholic fatty liver disease (NAFLD). However, the underlying mechanisms linking EC exposure with NAFLD remain poorly understood and there is no data on their impact on the human liver metabolome. Herein, we hypothesized that exposure to ECs, particularly perfluorinated alkyl substances (PFAS), impacts liver metabolism, specifically bile acid metabolism. Methods: In a well-characterized human NAFLD cohort of 105 individuals, we investigated the effects of EC exposure on liver metabolism. We characterized the liver (via biopsy) and circulating metabolomes using 4 mass spectrometry-based analytical platforms, and measured PFAS and other ECs in serum. We subsequently compared these results with an exposure study in a PPARa-humanized mouse model. Results: PFAS exposure appears associated with perturbation of key hepatic metabolic pathways previously found altered in NAFLD, particularly those related to bile acid and lipid metabolism. We identified stronger associations between the liver metabolome, chemical exposure and NAFLD-associated clinical variables (liver fat content, HOMA-IR), in females than males. Specifically, we observed PFAS-associated upregulation of bile acids, triacylglycerols and ceramides, and association between chemical exposure and dysregulated glucose metabolism in females. The murine exposure study further corroborated our findings, vis-a-vis a sex-specific association between PFAS exposure and NAFLD-associated lipid changes. Conclusions: Females may be more sensitive to the harmful impacts of PFAS. Lipid-related changes subsequent to PFAS exposure may be secondary to the interplay between PFAS and bile acid metabolism. Lay summary: There is increasing evidence that specific environmental contaminants, such as perfluorinated alkyl substances (PFAS), contribute to the progression of non-alcoholic fatty liver disease (NAFLD). However, it is poorly understood how these chemicals impact human liver metabolism. Here we show that human exposure to PFAS impacts metabolic processes associated with NAFLD, and that the effect is different in females and males. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of European Association for the Study of the Liver.Peer reviewe

Metabolic alterations in immune cells associate with progression to type 1 diabetes

Aims/hypothesis Previous metabolomics studies suggest that type 1 diabetes is preceded by specific metabolic disturbances. The aim of this study was to investigate whether distinct metabolic patterns occur in peripheral blood mononuclear cells (PBMCs) of children who later develop pancreatic beta cell autoimmunity or overt type 1 diabetes. Methods In a longitudinal cohort setting, PBMC metabolomic analysis was applied in children who (1) progressed to type 1 diabetes (PT1D, n = 34), (2) seroconverted to >= 1 islet autoantibody without progressing to type 1 diabetes (P1Ab, n = 27) or (3) remained autoantibody negative during follow-up (CTRL, n = 10). Results During the first year of life, levels of most lipids and polar metabolites were lower in the PT1D and P1Ab groups compared with the CTRL group. Pathway over-representation analysis suggested alanine, aspartate, glutamate, glycerophospholipid and sphingolipid metabolism were over-represented in PT1D. Genome-scale metabolic models of PBMCs during type 1 diabetes progression were developed by using publicly available transcriptomics data and constrained with metabolomics data from our study. Metabolic modelling confirmed altered ceramide pathways, known to play an important role in immune regulation, as specifically associated with type 1 diabetes progression. Conclusions/interpretation Our data suggest that systemic dysregulation of lipid metabolism, as observed in plasma, may impact the metabolism and function of immune cells during progression to overt type 1 diabetes. Data availability The GEMs for PBMCs have been submitted to BioModels (), under accession number MODEL1905270001. The metabolomics datasets and the clinical metadata generated in this study were submitted to MetaboLights (), under accession number MTBLS1015.Peer reviewe

Systems biology approaches to study lipidomes in health and disease

Lipids have many important biological roles, such as energy storage sources, structural components of plasma membranes and as intermediates in metabolic and signaling pathways. Lipid metabolism is under tight homeostatic control, exhibiting spatial and dynamic complexity at multiple levels. Consequently, lipid-related disturbances play important roles in the pathogenesis of most of the common diseases. Lipidomics, defined as the study of lipidomes in biological systems, has emerged as a rapidly-growing field. Due to the chemical and functional diversity of lipids, the application of a systems biology approach is essential if one is to address lipid functionality at different physiological levels. In parallel with analytical advances to measure lipids in biological matrices, the field of computational lipidomics has been rapidly advancing, enabling modeling of lipidomes in their pathway, spatial and dynamic contexts. This review focuses on recent progress in systems biology approaches to study lipids in health and disease, with specific emphasis on methodological advances and biomedical applications.</div

Early-life exposure to perfluorinated alkyl substances modulates lipid metabolism in progression to celiac disease

Celiac disease (CD) is a systemic immune-mediated disorder with increased frequency in the developed countries over the last decades implicating the potential causal role of various environmental triggers in addition to gluten. Herein, we apply determination of perfluorinated alkyl substances (PFAS) and combine the results with the determination of bile acids (BAs) and molecular lipids, with the aim to elucidate the impact of prenatal exposure on risk of progression to CD in a prospective series of children prior the first exposure to gluten (at birth and at 3 months of age). Here we analyzed PFAS, BAs and lipidomic profiles in 66 plasma samples at birth and at 3 months of age in the Type 1 Diabetes Prediction and Prevention (DIPP) study (n = 17 progressors to CD, n = 16 healthy controls, HCs). Plasma PFAS levels showed a significant inverse association with the age of CD diagnosis in infants who later progressed to the disease. Associations between BAs and triacylglycerols (TGs) showed different patterns already at birth in CD progressors, indicative of different absorption of lipids in these infants. In conclusion, PFAS exposure may modulate lipid and BA metabolism, and the impact is different in the infants who develop CD later in life, in comparison to HCs. The results indicate more efficient uptake of PFAS in such infants. Higher PFAS exposure during prenatal and early life may accelerate the progression to CD in the genetically predisposed children.</p

Conjugated C-6 hydroxylated bile acids in serum relate to human metabolic health and gut Clostridia species

Knowledge about in vivo effects of human circulating C-6 hydroxylated bile acids (BAs), also called muricholic acids, is sparse. It is unsettled if the gut microbiome might contribute to their biosynthesis. Here, we measured a range of serum BAs and related them to markers of human metabolic health and the gut microbiome. We examined 283 non-obese and obese Danish adults from the MetaHit study. Fasting concentrations of serum BAs were quantified using ultra-performance liquid chromatography-tandem mass-spectrometry. The gut microbiome was characterized with shotgun metagenomic sequencing and genome-scale metabolic modeling. We find that tauro- and glycohyocholic acid correlated inversely with body mass index (P = 4.1e-03, P = 1.9e-05, respectively), waist circumference (P = 0.017, P = 1.1e-04, respectively), body fat percentage (P = 2.5e-03, P = 2.3e-06, respectively), insulin resistance (P = 0.051, P = 4.6e-4, respectively), fasting concentrations of triglycerides (P = 0.06, P = 9.2e-4, respectively) and leptin (P = 0.067, P = 9.2e-4). Tauro- and glycohyocholic acids, and tauro-a-muricholic acid were directly linked with a distinct gut microbial community primarily composed of Clostridia species (P = 0.037, P = 0.013, P = 0.027, respectively). We conclude that serum conjugated C-6-hydroxylated BAs associate with measures of human metabolic health and gut communities of Clostridia species. The findings merit preclinical interventions and human feasibility studies to explore the therapeutic potential of these BAs in obesity and type 2 diabetes.Peer reviewe

Dysregulation of secondary bile acid metabolism precedes islet autoimmunity and type 1 diabetes

The gut microbiota is crucial in the regulation of bile acid (BA) metabolism. However, not much is known about the regulation of BAs during progression to type 1 diabetes (T1D). Here, we analyzed serum and stool BAs in longitudinal samples collected at 3, 6, 12, 18, 24, and 36 months of age from children who developed a single islet autoantibody (AAb) (P1Ab; n = 23) or multiple islet AAbs (P2Ab; n = 13) and controls (CTRs; n = 38) who remained AAb negative. We also analyzed the stool microbiome in a subgroup of these children. Factor analysis showed that age had the strongest impact on both BA and microbiome profiles. We found that at an early age, systemic BAs and microbial secondary BA pathways were altered in the P2Ab group compared with the P1Ab and CTR groups. Our findings thus suggest that dysregulated BA metabolism in early life may contribute to the risk and pathogenesis of T1D.</p

Use of big data from health insurance for assessment of cardiovascular outcomes

Outcome research that supports guideline recommendations for primary and secondary preventions largely depends on the data obtained from clinical trials or selected hospital populations. The exponentially growing amount of real-world medical data could enable fundamental improvements in cardiovascular disease (CVD) prediction, prevention, and care. In this review we summarize how data from health insurance claims (HIC) may improve our understanding of current health provision and identify challenges of patient care by implementing the perspective of patients (providing data and contributing to society), physicians (identifying at-risk patients, optimizing diagnosis and therapy), health insurers (preventive education and economic aspects), and policy makers (data-driven legislation). HIC data has the potential to inform relevant aspects of the healthcare systems. Although HIC data inherit limitations, large sample sizes and long-term follow-up provides enormous predictive power. Herein, we highlight the benefits and limitations of HIC data and provide examples from the cardiovascular field, i.e. how HIC data is supporting healthcare, focusing on the demographical and epidemiological differences, pharmacotherapy, healthcare utilization, cost-effectiveness and outcomes of different treatments. As an outlook we discuss the potential of using HIC-based big data and modern artificial intelligence (AI) algorithms to guide patient education and care, which could lead to the development of a learning healthcare system and support a medically relevant legislation in the future