Metabolic syndrome in children.

Despite plenty of currently available information on metabolic syndrome (MetS) in children and adolescents, there are still uncertainties regarding definition, prevention, management and treatment of MetS in children. The first approach to MetS in children consists of lifestyle interventions (nutritional education, physical activity). These recommendations are often difficult to achieve, especially for adolescents, therefore, there is usually a lack of successful outcomes. A pharmacological intervention in obese children may be needed in some cases, with the aim to improve the effects of these primary prevention interventions. Metformin seems to be safe and presents evident positive effects on insulin sensitivity, but long-term and consistent data are still missing to establish its role in the pediatric population and the possible effectiveness of other emergent treatments such as glucagon-like peptide-1 analogues, dipeptidylpeptidase-4 inhibitors, dual inhibitors of SGLT1 and SGLT2 and weight loss drugs. Bariatric surgery might be helpful in selected cases. The aim of this review is to present the most recent available treatments for the main components of metabolic syndrome, with a focus on insulin resistance. A short mention of management of congenital forms of insulin resistance will be included too.

Autoantibody discovery across monogenic, acquired, and COVID-19-associated autoimmunity with scalable PhIP-seq.

Phage immunoprecipitation sequencing (PhIP-seq) allows for unbiased, proteome-wide autoantibody discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation. Despite several successful implementations of PhIP-seq for autoantigen discovery, including our previous work (Vazquez et al., 2020), current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. Here, we develop and validate a high throughput extension of PhIP-seq in various etiologies of autoimmune and inflammatory diseases, including APS1, IPEX, RAG1/2 deficiency, Kawasaki disease (KD), multisystem inflammatory syndrome in children (MIS-C), and finally, mild and severe forms of COVID-19. We demonstrate that these scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel autoantigens, such as prodynorphin (PDYN) in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in two patients with RAG1/2 deficiency, one of whom had very early onset IBD. Scaled PhIP-seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID-19, including the endosomal protein EEA1. Together, scaled PhIP-seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.