An observational study in Type 2 Diabetes Mellitus (DM), sponsored by Louisiana State University Health Sciences Center in New Orleans. Not yet recruiting. Open to participants aged 40 Years to 84 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-09-22.
Sponsored by Louisiana State University Health Sciences Center in New Orleans · Observational
Type 2 diabetes is a common condition in which the body has difficulty controlling blood sugar. This study will use existing genetic, protein, and health data from prior research studies to identify blood proteins that may play a role in type 2 diabetes. The study will not recruit participants, provide treatment, or collect new samples. Researchers will use computer-based analyses to identify and prioritize protein targets for future laboratory and clinical research. The goal is to support the development of better approaches for understanding, preventing, and treating type 2 diabetes.
Type 2 diabetes is a major cause of illness and health disparities. Genetic association studies can identify regions of the genome associated with disease risk, but they do not always identify the proteins or biological mechanisms that contribute to disease development. This project will conduct a retrospective secondary analysis of existing, controlled-access genetic, proteomic, and phenotype data, including data accessed through the UK Biobank and other previously collected datasets. No new participants will be recruited, enrolled, contacted, treated, or followed as part of this study.
The study will use proteome-wide association methods to evaluate whether genetically predicted circulating protein levels are associated with type 2 diabetes risk. Analyses will consider evidence across African American and European American datasets when available, with attention to population-specific and shared signals. Statistical genetic evidence will be integrated with relevant biological and clinical information to prioritize protein targets that may have a causal role in type 2 diabetes.
Large language model-based methods will be used as a structured evidence-synthesis tool to organize and summarize publicly available information relevant to prioritized proteins, including biological function, disease relevance, and potential therapeutic tractability. All computational results will be reviewed by the research team. The project will generate reproducible analytic workflows, a ranked list of candidate protein targets, and hypotheses for future experimental validation. Findings are intended for research use and will not be used to make clinical decisions for individual patients.
Existing adult participants from the UK Biobank and Multi-Ethnic Study of Atherosclerosis with available genetic and OLINK proteomic data, including African American and European American/European ancestry participants. Type 2 diabetes GWAS summary statistics from the Million Veteran Program will be integrated for association analyses. No new participants will be recruited or contacted.
No new participants will be recruited for this study. The study will conduct a retrospective secondary analysis of existing, controlled-access datasets. Eligible records are from adult participants aged 40 to 84 years at enrollment in the source studies who have available genetic data and plasma proteomic data for population-specific protein prediction modeling. Participants with and without type 2 diabetes may be included, depending on the source dataset and analytic objective. Type 2 diabetes genome-wide association summary statistics will also be used; no individual-level participant contact or enrollment will occur.
Retrospective analysis of existing genetic and OLINK proteomic data to develop and validate population-specific protein prediction models and evaluate genetically predicted proteins associated with type 2 diabetes risk.
Retrospective analysis of existing genetic and OLINK proteomic data to develop and validate population-specific protein prediction models and evaluate genetically predicted proteins associated with type 2 diabetes risk.
Performance of Population-Specific Protein Prediction Models
Cross-validated and external validation R-squared values for cis-SNP-based prediction models of 2,943 plasma proteins. Models with reproducible performance (R-squared greater than 0.01) will be retained
Time frame: Up to 12 months
Genetically Predicted Protein Associations With Type 2 Diabetes Risk
Number and effect estimates of proteins associated with type 2 diabetes risk after integration of validated population-specific protein prediction models with type 2 diabetes genome-wide association summary statistics. Statistical significance will be assessed using false discovery rate less than 0.05.
Time frame: Up to 12 months
Prioritized Protein Targets With Citation-Grounded Functional Evidence
umber of PWAS-identified proteins assigned a structured, citation-grounded functional evidence profile and prioritization score using retrieval-augmented large language model-assisted annotation and expert review.
Time frame: Up to 12 months
No study locations are listed for this record.
Plan to share: No — Individual participant data will not be shared because this study uses controlled-access data from external sources, including the UK Biobank and the Multi-Ethnic Study of Atherosclerosis, that are subject to source-specific data use agreements and participant privacy protections. The study team does not have authority to redistribute these data. To support transparency and reproducibility, analytic code, study documentation, and aggregate, non-identifiable results will be shared when permitted by applicable agreements.
No publications or documents are linked to this record.
This study is not yet recruiting, as verified in Sep 2026. You cannot join it, but the record below documents what was studied.
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Louisiana State University Health Sciences Center in New Orleans