Correct classification of type 1 (T1D) and type 2 diabetes (T2D) is challenging due to overlapping clinical features and the increasingly early onset of T2D, particularly in South Asians. Polygenic risk scores (PRSs) for T1D and T2D have been shown to work relatively well in South Asians, despite being derived from largely European-ancestry samples. Here we used PRSs to investigate the rate of potential misclassification of diabetes amongst British Bangladeshis and Pakistanis.
View Article and Find Full Text PDFBackground: In children with type 1 diabetes (T1D), diabetic ketoacidosis (DKA) triggers a significant inflammatory response; however, the specific effector proteins and signaling pathways involved remain largely unexplored. This pediatric case-control study utilized plasma proteomics to explore protein alterations associated with severe DKA and to identify signaling pathways that associate with clinical variables.
Methods: We conducted a proteome analysis of plasma samples from 17 matched pairs of pediatric patients with T1D; one cohort with severe DKA and another with insulin-controlled diabetes.
Measuring attention and engagement is essential for understanding a wide range of psychological phenomena. Advances in technology have made it possible to measure real-time attention to naturalistic stimuli, providing ecologically valid insight into temporal dynamics. We developed a research protocol called Trace, which records anonymous facial landmarks, expressions, and patterns of movement associated with engagement in screen-based media.
View Article and Find Full Text PDFSepsis is a major cause of morbidity and mortality worldwide. Among the various types of end-organ damage associated with sepsis, hepatic injury is linked to significantly higher mortality rates compared to dysfunction in other organ systems. This study aimed to investigate potential biomarkers of hepatic injury in sepsis patients through a multi-center, case-control approach.
View Article and Find Full Text PDFA Type 1 Diabetes Genetic Risk Score (T1DGRS) aids diagnosis and prediction of Type 1 Diabetes (T1D). While traditionally derived from imputed array genotypes, Whole Genome Sequencing (WGS) provides a more direct approach and is now increasingly used in clinical and research studies. We investigated the concordance between WGS-based and array-based T1DGRS across genetic ancestries in 149,265 UK Biobank participants using WGS, TOPMed-imputed, and 1000 Genomes-imputed array genotypes.
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