A notable shift in understanding the human microbiome’s influence on cardiovascular disease (CVD) is underway, although the causal association remains elusive. A systematic review and meta-analysis were conducted to synthesise current knowledge on microbial taxonomy and metabolite variations between healthy controls (HCs) and those with CVD. An extensive search encompassing three databases identified 67 relevant studies (2012–2023) covering CVD pathologies from 4707 reports. Metagenomic and metabolomic data, both qualitative and quantitative, were obtained. Analysis revealed substantial variability in microbial alpha and beta diversities. Moreover, specific changes in bacterial populations were shown, including increased Streptococcus and Proteobacteria and decreased Faecalibacterium in patients with CVD compared with HC. Additionally, elevated trimethylamine N-oxide levels were reported in CVD cases. Biochemical parameter analysis indicated increased fasting glucose and triglycerides and decreased total cholesterol and low- and high-density lipoprotein cholesterol levels in diseased individuals. This study revealed a significant relationship between certain bacterial species and CVD. Additionally, it has become clear that there are substantial inconsistencies in the methodologies employed and the reporting standards adhered to in various studies. Undoubtedly, standardising research methodologies and developing extensive guidelines for microbiome studies are crucial for advancing the field.

Gestational diabetes, affecting about 10% of pregnancies, is characterized by impaired glucose regulation and can lead to complications for health of pregnant women and their offspring. The microbiota, the resident microbes within the body, have been linked to the development of several metabolic conditions. This systematic review with meta-analysis aims to summarize the evidence on the differences in microbiota composition in pregnant women with gestational diabetes and their offspring compared to healthy pregnancies. A thorough search was conducted in the PubMed, Scopus, and Web of Science databases, and data from 21 studies were analyzed utilizing 41 meta-analyses. In the gut microbiota, Bifidobacterium and Alistipes were found to be more abundant in healthy pregnancies, while Roseburia appears to be more abundant in gestational diabetes. The heterogeneity among study findings regarding the microbiota in the meconium is considerable. The placental microbiota exhibited almost no heterogeneity, with an increased abundance of Firmicutes in the gestational diabetes group and a higher abundance of Proteobacteria in the control. The role of the microbiota in gestational diabetes is reinforced by these findings, which additionally point to the potential of microbiome-targeted therapies. To completely comprehend the interactions between gestational diabetes and the microbiome, standardizing methodologies and further research is necessary.

A major bottleneck in the successful development of central nervous system (CNS) drugs is the discovery and design of molecules that can cross the blood-brain barrier (BBB). Nano-delivery strategies are a promising approach that take advantage of natural portals of entry into the brain such as monoclonal antibodies (mAbs) targeting endogenous BBB receptors. However, the main selected mAbs rely on targeting broadly expressed receptors, such as the transferrin and insulin receptors, and in selection processes that do not fully mimic the native receptor conformation, leading to mistargeting and a low fraction of the administered dose effectively reaching the brain. Thus, there is an urgent need to identify new BBB receptors and explore novel antibody selection approaches that can allow a more selective delivery into the brain. Considering that in vitro models fail to completely mimic brain structure complexity, we explored an in vivo cell immunization approach to construct a rabbit derived single-domain antibody (sdAb) library towards BBB endothelial cell receptors. The sdAb antibody library was used in an in vivo phage display screening as a functional selection of novel BBB targeting antibodies. Following three rounds of selections, next generation sequencing analysis, in vitro brain endothelial barrier (BEB) model screenings and in vivo biodistribution studies, five potential sdAbs were identified, three of which reaching >0.6% ID/g in the brain. To validate the brain drug delivery proof-of-concept, the most promising sdAb, namely RG3, was conjugated at the surface of liposomes encapsulated with a model drug, the pan-histone deacetylase inhibitor panobinostat (PAN). The translocation efficiency and activity of the conjugate liposome was determined in a dual functional in vitro BEB-glioblastoma model. The RG3 conjugated PAN liposomes enabled an efficient BEB translocation and presented a potent antitumoral activity against LN229 glioblastoma cells without influencing BEB integrity. In conclusion, our in vivo screening approach allowed the selection of highly specific nano-antibody scaffolds with promising properties for brain targeting and drug delivery.

The role of epicardial adipose tissue (EAT) in the pathophysiology of coronary artery disease (CAD) remains unclear. The present systematic review aimed at compiling dysregulated proteins/genes from different studies to dissect the potential role of EAT in CAD pathophysiology. Exhaustive literature research was performed using the keywords “epicardial adipose tissue and coronary artery disease”, to highlight a group of proteins that were consistently regulated among all studies. Reactome, a pathway analysis database, was used to clarify the function of the selected proteins and their intertwined association. SignalP/SecretomeP was used to clarify the endocrine function of the selected proteins. Overall, 1886 proteins/genes were identified from 44 eligible studies. The proteins were separated according to the control used in each study (EAT non-CAD or subcutaneous adipose tissue (SAT) CAD) and by their regulation (up- or downregulated). Using a Venn diagram, we selected the proteins that were upregulated and downregulated (identified as 27 and 19, respectively) in EAT CAD for both comparisons. The analysis of these proteins revealed the main pathways altered in the EAT and how they could communicate with the heart, potentially contributing to CAD development. In summary, in this study, the identified dysregulated proteins highlight the importance of inflammatory processes to modulate the local environment and the progression of CAD, by cellular and metabolic adaptations of epicardial fat that facilitate the formation and progression of atherogenesis of coronaries.

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading cause of chronic liver disease globally, with rising prevalence linked to metabolic syndrome (MetS). Excessive liver fat accumulation (steatosis) worsens disease progression and MASLD prognosis. Moreover, gut microbiota dysbiosis might promote steatosis, accelerating the disease progression to severe stages. Identifying gut microbiota signatures specific to steatosis severity might improve its diagnosis and inform personalised interventions in MASLD. This study aimed to characterise associations between gut microbiota composition and hepatic steatosis severity in a cohort of patients with MASLD/MetS. Ultimately, we aimed to assess the potential for microbiota features to enhance the diagnosis of severe steatosis. Methods: A cross-sectional cohort of 61 patients with MetS with extensive clinical history was recruited at different stages of MASLD. Transient elastography was used to evaluate liver fibrosis and steatosis severity. Participants’ faecal microbiota were profiled using 16S rRNA gene sequencing. Statistical analyses first identified correlations between microbiota profiles and patients’ phenotypes, while disentangling important confounders such as medication. Identified features were then used to build predictive models for diagnosing severe steatosis. Results: High steatosis severity was distinctly associated with a higher prevalence of the inflammation-associated Bacteroides 2 (Bact2)-enterotype, accompanied by a lower proportion of beneficial commensals (eg, Akkermansia) and a higher proportion of opportunistic bacteria (eg, Streptococcus). Patients harbouring a Bact2-enterotype reached severe steatosis at lower Fatty Liver Index (FLI) thresholds. Using Bact2-carrier status together with FLI in a predictive model significantly improved the classification of severe steatosis (accuracy 90%, receiver operating characteristics 96%) when compared with FLI alone. Conclusion: Gut microbiota composition and dysbiosis (defined as Bact2-enterotype) are distinctly associated with steatosis severity in MASLD/MetS. Patient stratification by microbiota composition enhances the diagnostic classification of severe steatosis in MASLD, suggesting a potential for personalised interventions in patients with microbiota dysbiosis.