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Principal Investigator: Anthony T Vella
Organization: UNIVERSITY OF CONNECTICUT SCH OF MED/DNT
Fiscal Year: 2024
Award: $566,723
Funding agency: National Heart Lung and Blood Institute
Project Summary
Type 2 diabetes mellitus (T2DM) is a primary cause of the marked increase of ASCVD, accounting for over 30%
of symptomatic cases. Accordingly, the ASCVD risk in T2DM patients is 2-4 fold more than in the non-T2DM
population. The concomitant increase of T2DM and ASCVD in the US prompted the urgency for accurate ASCVD
prediction followed by an effective mitigation strategy. However, recent clinical trials and extensive cohort studies
revealed underachievement by controlling conventional lipid/hypertension/glycemic factors, warranting new
directions additional to the existing mitigation paradigm. Furthermore, multiple studies comparing existing
ASCVD risk prediction models, including those derived from general or T2DM populations, achieved only
marginal or underperformance in multiple independent cohorts, endorsing the significance of this significant
unmet biomedical challenge. Our proposed study aims to fill this critical scientific and clinical gap in increased
atherosclerosis cardiovascular disease risk (ASCVD) in T2DM. Supported by our recent discoveries and
development of multiple immune cell annotation tools, we propose to test the overarching hypothesis that the
foaming process in circulating monocytes can be directly altered by T2DM towards pathogenic foaming, thus
directly contributing to the elevated risk of ASCVD. Application of our newly developed cell function annotation
tools uncovered distinct macrophage-derived foam cell development programs, followed by ASCVD causal gene
signature identification and proof-of-concept ASCVD predictive modeling by incorporating a selected gene list
using the original machine learning program. Our new work further revealed that super-networks governed by
three upstream regulators are uniquely altered by T2DM and associated with future ASCVD incidence. Hence,
in two aims: (AIM 1) we will determine the impact of suppressed super-networks governed by identified master
regulators (SNW1, NCOR2, CITED2) on pathogenic foaming program using established foam cell development
system with quantitative methods and single cell transcriptomics; (AIM 2) will assess the efficacy of T2DM-
ASCVD signatures on predictive modeling using existing and innovative feature selection and feature extraction
tools. Completing this project will provide crucial information to significantly advance our understanding of
ASCVD risk in the T2DM population. Our innovative computational programs, derived from novel and in-depth
mechanistic investigation, will offer translatable ASCVD prediction tools and molecular targets for drug
development to achieve personalized intervention for T2DM patients to mitigate ASCVD risks.
Terms: <Accounting><Adoptive Transfer><Adult-Onset Diabetes Mellitus><Affect><Algorithms><Atherosclerosis><Atherosclerotic Cardiovascular Disease><Blood monocyte><Body Tissues><Cell Body><Cell Function><Cell Physiology><Cell Process><Cells><Cellular Function><Cellular Physiology><Cellular Process><Clinical><Clinical Trials><Closure by Ligation><Cohort Studies><Complex><Concurrent Studies><Data><Data Analyses><Data Analysis><Data Set><Development><Equation><Exhibits><Foam Cells><Future><Genes><Health Care Costs><Health Care Systems><Health Costs><Healthcare Costs><Healthcare Systems><Human><Hypertension><Immune><Immunes><Immunology><In Vitro><Incidence><Inflammatory><Investigation><Ketosis-Resistant Diabetes Mellitus><Knowledge><Ligation><Lipids><Machine Learning><Macrophage><Marrow monocyte><Maturity-Onset Diabetes Mellitus><Methods><Mice><Mice Mammals><Modeling><Modern Man><Molecular><Multi-Ethnic Study of Atherosclerosis><Murine><Mus><Mφ><NCOA-62><NCOR2><NCOR2 gene><NIDDM><Non-Insulin Dependent Diabetes><Non-Insulin-Dependent Diabetes Mellitus><Noninsulin Dependent Diabetes><Noninsulin Dependent Diabetes Mellitus><PBMC><Pathogenicity><Patients><Performance><Peripheral Blood Mononuclear Cell><Persons><Population><Predicting Risk><Process><Program Development><Proteins><RNA Splicing><Resolution><Risk><Risk Assessment><Risk Factors><Role><SNW1><SNW1 Gene><Slow-Onset Diabetes Mellitus><Splicing><Stable Diabetes Mellitus><Subcellular Process><System><Systems Development><T-Cells><T-Lymphocyte><T2 DM><T2D><T2DM><TRAC-1><TRAC1><Testing><Tissues><Type 2 Diabetes Mellitus><Type 2 diabetes><Type 2 diabetic><Type II Diabetes Mellitus><Type II diabetes><Type II diabetic><Underachievement><Vascular Hypertensive Disease><Vascular Hypertensive Disorder><Volatilization><Work><adult onset diabetes><annotation system><annotation framework><annotation tool><atheromatosis><atherosclerosis risk><atherosclerotic disease><atherosclerotic risk><atherosclerotic vascular disease><cardiovascular disease risk><cardiovascular disorder risk><causal allele><causal gene><causal mutation><causal variant><causative mutation><causative variant><cell type><clinical risk><cohort><computer based prediction><data interpretation><determine efficacy><developmental><drug development><efficacy analysis><efficacy assessment><efficacy determination><efficacy evaluation><efficacy examination><evaluate efficacy><evidence base><examine efficacy><feature extraction><feature selection><forecasting risk><gene signatures><genetic signature><high blood pressure><high risk><hyperpiesia><hyperpiesis><hypertensive disease><hypertensive disorder><improved><innovate><innovation><innovative><ketosis resistant diabetes><knock-down><knockdown><machine based learning><maturity onset diabetes><molecular drug target><molecular pharmacotherapy target><monocyte><multiomics><multiple omics><novel><overexpress><overexpression><panomics><personalized health intervention><personalized intervention><precision interventions><predict risk><predict risks><predicted risk><predicted risks><predicting risks><predictive modeling><predictive risk><predictive tools><predicts risk><programs><resolutions><risk prediction><risk prediction algorithm><risk prediction model><risk predictions><social role><thymus derived lymphocyte><tool><transcriptomics><type 2 DM><type II DM><type two diabetes>