Type 2 Diabetes Mellitus (DM)LAUNCH-T2DNCT07832656
Proteome-Wide Association and LLM-Based Prioritization of Type 2 Diabetes Protein Targets
An observational study of Type 2 Diabetes Mellitus (DM), run by Louisiana State University Health Sciences Center in New Orleans.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 40 to 84 yearsHealthy volunteers can take part
- Conditions the study is for
- Type 2 Diabetes Mellitus (DM)
- How many people
- 31,994 participants
- Where
- No sites listed yet
- Study dates
- 15 Sep 2026to 2 Aug 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 40 to 84 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: 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.
Who may be able to join
- Participants enrolled in the source studies who were aged 40 to 84 years at enrollment.
- Availability of genetic data and plasma proteomic data for population-specific protein prediction modeling.
- Participants with or without type 2 diabetes, depending on the source dataset and analytic objective.
Who cannot join
- Participants younger than 40 years or older than 84 years at enrollment in the source studies.
- Participants lacking genetic data or plasma proteomic data required for protein prediction modeling.
- This study will conduct a retrospective secondary analysis of existing, controlled-access datasets. No new participants will be recruited or contacted. Type 2 diabetes genome-wide association summary statistics will also be used for association analyses; the participant-level eligibility criteria above apply to individual-level source-study records used for protein prediction modeling.
About this study
Official title: Integrative Proteome-Wide Association Study and Large Language Model-Based Prioritization of Causal Protein Targets of Type 2 Diabetes
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.
Read the detailed description
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 United Kingdom Biobank (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.
- Conditions
- Type 2 Diabetes Mellitus (DM)
- Medical subject headings
- Diabetes Mellitus, Type 2
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| African American Participants | 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. | |
| European American Participants | 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. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Performance of Population-Specific Protein Prediction Models
Cross-validated and external validation coefficients of determination (R-squared values) for prediction models of 2,943 plasma proteins based on single-nucleotide polymorphisms located near the genes encoding the corresponding proteins (cis variants). Models with reproducible performance (R-squared greater than 0.01) will be retained.
Measured: Up to 12 months
Secondary outcomes (2)
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.
Measured: Up to 12 months
Prioritized Protein Targets With Citation-Grounded Functional Evidence
Number of proteins identified through proteome-wide association analyses that are assigned a structured, citation-grounded functional evidence profile and prioritization score using retrieval-augmented large language model-assisted annotation and expert review.
Measured: Up to 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Sep 2026
- Study start15 Sep 2026 (estimated)
- Primary completion2 Jul 2027 (estimated)
- Study completion2 Aug 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Type 2 Diabetes Mellitus (DM)Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Retrospective
- Enrolment
- 31,994 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Louisiana State University Health Sciences Center in New Orleans
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07832656
- Sponsor's protocol ID
- LSUHSC-LAUNCHED-T2D-01
- Other IDs
- U24DK132740
- Acronym
- LAUNCH-T2D
- Status last verified
- Sep 2026
- First submitted
- 15 Sep 2026
- Last updated
- 28 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- 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.
Study at a glance
From the registry record, last updated by the sponsor on 28 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Integrative Proteome-Wide Association Study and Large Language Model-Based Prioritization of Causal Protein Targets of Type 2 Diabetes
- ClinicalTrials.gov ID
- NCT07832656
- Acronym / sponsor ID
- LAUNCH-T2D / LSUHSC-LAUNCHED-T2D-01
- Conditions
- Type 2 Diabetes Mellitus (DM)
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 31,994 participants (estimated)
- Lead sponsor
- Louisiana State University Health Sciences Center in New OrleansUniversity, hospital or other
- Collaborators
- National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
- Study start
- 15 Sep 2026 (estimated)
- Primary completion
- 2 Jul 2027 (estimated)
- Study completion
- 2 Aug 2027 (estimated)
- First posted
- 22 Sep 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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 United Kingdom Biobank (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.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| African American Participants | – | –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. |
| European American Participants | – | –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. |
Who may qualify
- Ages
- 40 to 84 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- 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.
Key inclusion criteria (3 listed)
- Participants enrolled in the source studies who were aged 40 to 84 years at enrollment.
- Availability of genetic data and plasma proteomic data for population-specific protein prediction modeling.
- Participants with or without type 2 diabetes, depending on the source dataset and analytic objective.
Key exclusion criteria (3 listed)
- Participants younger than 40 years or older than 84 years at enrollment in the source studies.
- Participants lacking genetic data or plasma proteomic data required for protein prediction modeling.
- This study will conduct a retrospective secondary analysis of existing, controlled-access datasets. No new participants will be recruited or contacted. Type 2 diabetes genome-wide association summary statistics will also be used for association analyses; the participant-level eligibility criteria above apply to individual-level source-study records used for protein prediction modeling.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Performance of Population-Specific Protein Prediction Models
Time frame: Up to 12 months
Cross-validated and external validation coefficients of determination (R-squared values) for prediction models of 2,943 plasma proteins based on single-nucleotide polymorphisms located near the genes encoding the corresponding proteins (cis variants). Models with reproducible performance (R-squared greater than 0.01) will be retained.
2 secondary outcomes
Genetically Predicted Protein Associations With Type 2 Diabetes Risk
Time frame: Up to 12 months
Prioritized Protein Targets With Citation-Grounded Functional Evidence
Time frame: Up to 12 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 28 Sep 2026.
- Individual participant dataSharing planned: 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
An observational study of Type 2 Diabetes Mellitus (DM), run by Louisiana State University Health Sciences Center in New Orleans.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 28 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Performance of Population-Specific Protein Prediction Models (time frame: Up to 12 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 28 Sep 2026; AzTrials last refreshed its copy on 6 Nov 2026.