Dietary plant microRNAs as potential regulators of cellular cholesterol efflux.

AIM: Epidemiological evidence suggests adherence to vegetable-rich diets is associated to atheroprotective effects and bioactive components are most likely to play a relevant role. The notion of inter-kingdom regulation has opened a new research paradigm and perhaps microRNAs (miRNAs) from edible vegetables could influence consumer gene expression and lead to biological effects. We aimed to investigate the potential impact of broccoli-derived miRNAs on cellular cholesterol efflux in vitro. METHODS: Four miRNAs (miR159a, miR159b, miR166a and miR403) from Brassica oleracea var. italica (broccoli), a widely consumed cruciferous vegetable, were selected for further investigation, based on their high abundancy in this vegetable and their presence in other plants. Selected miRNAs were synthesized with a 3'-terminal 2'-O-methylation and their cellular toxicity, in vitro gastrointestinal resistance and cellular uptake were evaluated. Potential target genes within the mammalian transcriptome were assessed in silico following pathway analysis. In vitro cholesterol efflux was assessed in human THP-1-derived macrophages. RESULTS: miRNAs survival to in vitro GI digestion was around 1%, although some variation was seen between the four candidates. Cellular uptake by mammalian cells was confirmed, and an increase in cholesterol efflux was observed. Pathway analysis suggested these miRNAs are involved in biological processes related to phosphorylation, phosphatidylinositol and Wnt signaling, and to the insulin/IGF pathway. CONCLUSIONS: Health-promoting properties attributed to cruciferous vegetables, might be mediated (at least in part) through miRNA-related mechanisms.

A Diet Profiling Algorithm (DPA) to Rank Diet Quality Suitable to Implement in Digital Tools-A Test Study in a Cohort of Lactating Women.

Although nutrient profiling systems can empower consumers towards healthier food choices, there is still a need to assess diet quality to obtain an overall perspective. The purpose of this study was to develop a diet profiling algorithm (DPA) to evaluate nutritional diet quality, which gives a final score from 1 to 3 with an associated color (green-yellow-orange). It ranks the total carbohydrate/total fiber ratio, and energy from saturated fats and sodium as potentially negative inputs, while fiber and protein are assumed as positive items. Then, the total fat/total carbohydrate ratio is calculated to evaluate the macronutrient distribution, as well as a food group analysis. To test the DPA performance, diets of a lactating women cohort were analyzed, and a correlation analysis between DPA and breast milk leptin levels was performed. Diets classified as low quality showed a higher intake of negative inputs, along with higher energy and fat intakes. This was reflected in body mass index (BMI) and food groups, indicating that women with the worst scores tended to choose tastier and less satiating foods. In conclusion, the DPA was developed and tested in a sample population. This tool can be easily implemented in digital nutrition platforms, contributing to real-time dietary follow-up of patients and progress monitoring, leading to further dietary adjustment.

An Interplay between Oxidative Stress (Lactate Dehydrogenase) and Inflammation (Anisocytosis) Mediates COVID-19 Severity Defined by Routine Clinical Markers.

Viral infections activate the innate immune response and the secretion of inflammatory cytokines. They also alter oxidative stress markers, which potentially can have an involvement in the pathogenesis of the disease. The aim of this research was to study the role of the oxidative stress process assessed through lactate dehydrogenase (LDH) on the severity of COVID-19 measured by oxygen saturation (SaO2) and the putative interaction with inflammation. The investigation enrolled 1808 patients (mean age of 68 and 60% male) with COVID-19 from the HM Hospitals database. To explore interactions, a regression model and mediation analyses were performed. The patients with lower SaO2 presented lymphopenia and higher values of neutrophils-to-lymphocytes ratio and on the anisocytosis coefficient. The regression model showed an interaction between LDH and anisocytosis, suggesting that high levels of LDH (>544 U/L) and an anisocytosis coefficient higher than 10% can impact SaO2 in COVID-19 patients. Moreover, analysis revealed that LDH mediated 41% (p value = 0.001) of the effect of anisocytosis on SaO2 in this cohort. This investigation revealed that the oxidative stress marker LDH and the interaction with anisocytosis have an important role in the severity of COVID-19 infection and should be considered for the management and treatment of the oxidative phenomena concerning this within a precision medicine strategy.

Machine learning insights concerning inflammatory and liver-related risk comorbidities in non-communicable and viral diseases.

The liver is a key organ involved in a wide range of functions, whose damage can lead to chronic liver disease (CLD). CLD accounts for more than two million deaths worldwide, becoming a social and economic burden for most countries. Among the different factors that can cause CLD, alcohol abuse, viruses, drug treatments, and unhealthy dietary patterns top the list. These conditions prompt and perpetuate an inflammatory environment and oxidative stress imbalance that favor the development of hepatic fibrogenesis. High stages of fibrosis can eventually lead to cirrhosis or hepatocellular carcinoma (HCC). Despite the advances achieved in this field, new approaches are needed for the prevention, diagnosis, treatment, and prognosis of CLD. In this context, the scientific com-munity is using machine learning (ML) algorithms to integrate and process vast amounts of data with unprecedented performance. ML techniques allow the integration of anthropometric, genetic, clinical, biochemical, dietary, lifestyle and omics data, giving new insights to tackle CLD and bringing personalized medicine a step closer. This review summarizes the investigations where ML techniques have been applied to study new approaches that could be used in inflammatory-related, hepatitis viruses-induced, and coronavirus disease 2019-induced liver damage and enlighten the factors involved in CLD development.

Breast Milk MicroRNAs Related to Leptin and Adiponectin Function Can Be Modulated by Maternal Diet and Influence Offspring Phenotype in Rats.

There is evidence of the role of milk components in the metabolic programming of offspring. Here, we aimed to investigate the effects of a diet during lactation on breast milk leptin, adiponectin, and related miRNAs' expression, and their impact on dams and their offspring. Dams were fed a control diet (controls) or a diet enriched with oleic acid, betaine, and leucine (TX) throughout lactation. A TX diet promoted higher leptin at lactation day (LD) five and lower adiponectin on LD15 (vs. controls) in milk, resulting in increased leptin to adiponectin (L/A) ratio throughout lactation. Moreover, TX diet reduced milk levels of miR-27a, miR-103, miR-200a, and miR-222. Concerning TX offspring, higher body fat was early observed and maintained into adult life, accompanied by higher HOMA-IR than controls at three months of age. Offspring body fat content in adulthood correlated positively with milk L/A ratio at LD15 and negatively with miRNAs modulated by the TX diet. In conclusion, maternal diet during lactation can modulate leptin and adiponectin interplay with miRNAs in milk, setting up the metabolic programming of the offspring. Better knowledge about the influence of diet on this process is necessary to promote a healthy adult life in the progeny.

Mutations in C-natriuretic peptide (NPPC): a novel cause of autosomal dominant short stature.

PurposeC-type natriuretic peptide (CNP) and its principal receptor, natriuretic peptide receptor B (NPR-B), have been shown to be important in skeletal development. CNP and NPR-B are encoded by natriuretic peptide precursor-C (NPPC) and natriuretic peptide receptor 2 (NPR2) genes, respectively. While NPR2 mutations have been described in patients with skeletal dysplasias and idiopathic short stature (ISS), and several Npr2 and Nppc skeletal dysplasia mouse models exist, no mutations in NPPC have been described in patients to date.MethodsNPPC was screened in 668 patients (357 with disproportionate short stature and 311 with autosomal dominant ISS) and 29 additional ISS families in an ongoing whole-exome sequencing study.ResultsTwo heterozygous NPPC mutations, located in the highly conserved CNP ring, were identified. Both showed significant reductions in cyclic guanosine monophosphate synthesis, confirming their pathogenicity. Interestingly, one has been previously linked to skeletal abnormalities in the spontaneous Nppc mouse long-bone abnormality (lbab) mutant.ConclusionsOur results demonstrate, for the first time, that NPPC mutations cause autosomal dominant short stature in humans. The NPPC mutations cosegregated with a short stature and small hands phenotype. A CNP analog, which is currently in clinical trials for the treatment of achondroplasia, seems a promising therapeutic approach, since it directly replaces the defective protein.