Publications by authors named "P Kho"
Background: We previously reported significant correlations between a direct measure of insulin sensitivity (IS) and blood levels of proteins measured using the Proximity Extension Assay (PEA) in two European cohorts. However, protein correlations with IS within non-European populations, in response to short-term interventions that improve IS, and any causal associations with IS have not yet been established.
Methods: We measured 1,470 proteins using the PEA in the plasma of 1,015 research participants at Stanford University who underwent one or more direct measures of IS.
Plasma proteomics and carotid intima-media thickness in the UK biobank cohort.
Front Cardiovasc Med
October 2024
Article Synopsis
- This study explored how traditional risk factors and plasma proteins can predict carotid intima-media thickness (cIMT), an important measure for cardiovascular risk, nearly a decade later in participants from the UK Biobank.
- It analyzed data from over 6,000 participants, finding that age, blood pressure, and specific body composition measurements were the strongest predictors of cIMT.
- The research concluded that incorporating plasma proteins alongside traditional risk factors improved prediction accuracy, pointing to the significance of blood pressure and certain proteins related to the extracellular matrix in understanding cIMT development.
Background: While risk stratification for atherosclerotic cardiovascular disease (ASCVD) is essential for primary prevention, current clinical risk algorithms demonstrate variability and leave room for further improvement. The plasma proteome holds promise as a future diagnostic and prognostic tool that can accurately reflect complex human traits and disease processes. We assessed the ability of plasma proteins to predict ASCVD.
View Article and Find Full Text PDFArticle Synopsis
- The study evaluates the potential of plasma proteins to predict the risk of type 2 diabetes mellitus (T2DM) and related traits using data from UK Biobank participants.
- Different analysis methods, like LASSO regression, were employed to compare the effectiveness of proteomic data against traditional clinical and genetic data for predicting traits like truncal fat and fitness levels.
- Results showed that integrating proteomic signatures enhanced prediction accuracy for T2DM and other traits beyond existing clinical risk scores, indicating their value in disease prognostics.
Objective: South Asians (SAs) may possess a unique predisposition to insulin resistance (IR). We explored this possibility by investigating the relationship between 'gold standard' measures of adiposity, fitness, selected proteomic biomarkers, and insulin sensitivity among a cohort of SAs and Europeans (EURs).
Methods: A total of 46 SAs and 41 EURs completed 'conventional' (lifestyle questionnaires, standard physical exam) as well as 'gold standard' (dual energy X-ray absorptiometry scan, cardiopulmonary exercise test, and insulin suppression test) assessments of adiposity, fitness, and insulin sensitivity.