Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk-factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data, and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific autoantibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8 + T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.

Obesity rates among children are growing rapidly worldwide, placing massive pressure on healthcare systems. Untargeted metabolomics can expand our understanding of the pathogenesis of obesity and elucidate mechanisms related to its symptoms. However, the metabolic signatures of obesity in children have not been thoroughly investigated. Herein, we explored metabolites associated with obesity development in childhood. Untargeted metabolomic profiling was performed on fasting serum samples from 27 obese Caucasian children and adolescents and 15 sex- and age-matched normal-weight children. Three metabolomic assays were combined and yielded 726 unique identified metabolites: gas chromatography–mass spectrometry (GC–MS), hydrophilic interaction liquid chromatography coupled to mass spectrometry (HILIC LC–MS/MS), and lipidomics. Univariate and multivariate analyses showed clear discrimination between the untargeted metabolomes of obese and normal-weight children, with 162 significantly differentially expressed metabolites between groups. Children with obesity had higher concentrations of branch-chained amino acids and various lipid metabolites, including phosphatidylcholines, cholesteryl esters, triglycerides. Thus, an early manifestation of obesity pathogenesis and its metabolic consequences in the serum metabolome are correlated with altered lipid metabolism. Obesity metabolite patterns in the adult population were very similar to the metabolic signature of childhood obesity. Identified metabolites could be potential biomarkers and used to study obesity pathomechanisms.

Type 2 diabetes (T2D) is a deficiency in how the body regulates glucose. Uncontrolled T2D will result in chronic high blood sugar levels, eventually resulting in T2D complications. These complications, such as kidney, eye, and nerve damage, are even harder to treat. Identifying individuals at high risk of developing T2D and its complications is essential for early prevention and treatment. Numerous studies have been done to identify biomarkers for T2D diagnosis and prognosis. This review focuses on recent T2D biomarker studies based on circulating nucleic acids using different omics technologies: genomics, transcriptomics, and epigenomics. Omics studies have profiled biomarker candidates from blood, urine, and other non-invasive samples. Despite methodological differences, several candidate biomarkers were reported for the risk and diagnosis of T2D, the prognosis of T2D complications, and pharmacodynamics of T2D treatments. Future studies should be done to validate the findings in larger samples and blood-based biomarkers in non-invasive samples to support the realization of precision medicine for T2D.

INTRODUC TI ONSleeve gastrectomy (SG) is the most common bariatric surgery procedure in Poland and other countries, including the United States (1-3). It is a less complicated procedure and it has fewer surgery complications compared with other methods (4-7). Although SG is comparable to other methods for weight loss and weight regain (8-10), SG has a lower success rate for type 2 diabetes (T2D) remission

A novel pathophysiology-based method to subphenotype individuals at elevated risk for type 2 diabetes has recently identified 6 subgroups, 2 of which constitute obese, high-risk subpopulations with different glycemic, renal, cardiovascular and all-cause mortality risk profiles. The aim of our study was to evaluate differences in response to weight-loss surgery between these clusters, termed clusters 5 & 6 by Wagner et al. We performed this clustering on the Bialystok Bariatric Surgery Study Cohort consisting of nondiabetic patients with at least one year of follow-up data who underwent sleeve gastrectomy surgery. We used generalized linear models to test for differences between clusters in baseline parameters and changes after one year. At baseline, 48 (47%) patients were classified as cluster 5 and 54 (53%) as cluster 6. Before the surgery, cluster 5 subjects had significantly (q-value<0.05) higher levels of fasting and 2-hour glucose and insulin, HbA1c, triglycerides and visceral fat mass, and lower levels of HDL-cholesterol and Matsuda Index. There were no significant differences in age, weight, BMI or body composition. Further, we found that cluster 5 presented a greater reduction in fasting and 2-h glucose, but lesser in hip and waist circumferences, compared to cluster 6. However, after adjusting for baseline values of these parameters, only change in hip and waist circumferences remained significant. We did not find any differences in body composition or lipid parameter responses between clusters. Our study confirms that cluster 5 shows more severe glycemic and lipid deterioration compared to cluster 6 despite their shared obese phenotypes. However, bariatric surgery seems to be equally beneficial in both clusters, except for small differences in hip and waist circumference response. Disclosure L. Szczerbinski: None. J. Goscik: None. W. Kwedlo: None. G.E.P. Wojciechowska: None. A. Citko: None. P. Konopka: None. A. Paszko: None. M. Taylor: None. H.R. Hady: None. A.J. Kretowski: None.

No abstract