Overview
Cross-system analysis of diabetes has generated hypotheses about T1D-autoimmune connections, T2D-CV links, and drug optimization. These build on foundational endocrinology and metabolism research to identify potential therapeutic opportunities.
The Hypotheses
1
T1D-Autoimmune Prevention
Observation: T1D shares genetic risk factors with other autoimmune diseases.
Prediction: Interventions that prevent other autoimmune diseases may also prevent or delay T1D.
Testable: Study T1D incidence in patients on immunomodulators for other autoimmune conditions.
2
GLP-1 Cross-Disease Effects
Observation: GLP-1 agonists show benefits in both diabetes and CV disease.
Prediction: GLP-1 agonists may show unexpected benefits in other diseases.
Testable: Analyze outcomes beyond glucose/CV in GLP-1 trial data (cognition, cancer, etc.).
3
SGLT2 Response Clustering
Observation: Different SGLT2 inhibitors show correlated response patterns.
Prediction: Patients who respond well to canagliflozin will respond to other drugs with similar characteristics.
Testable: Correlate SGLT2i response with response to statins and PCSK9 inhibitors.
4
T2D Gene-Drug Matching
Observation: TCF7L2 is the strongest T2D risk gene.
Prediction: TCF7L2 genotype may predict response to specific diabetes drugs.
Testable: Stratify drug response by TCF7L2 genotype in pharmacogenomics databases.
5
Dual GLP-1/SGLT2 Optimization
Observation: Semaglutide and canagliflozin may share response predictors.
Prediction: Patients responding well to one will respond to the other.
Testable: Compare response to combination therapy vs sequential therapy.
6
Diabetes-CV Integration
Observation: GLP-1s and SGLT2s improve both glycemic and CV outcomes.
Prediction: Baseline CV risk markers can predict glycemic response and vice versa.
Testable: Cross-correlate CV and glycemic outcomes in major trials.
Research Priority Matrix
| Hypothesis | Data Required | Feasibility | Impact |
|---|---|---|---|
| H1: T1D prevention | Autoimmune registries | Moderate | Very High |
| H2: GLP-1 cross-disease | Trial secondary endpoints | High | High |
| H3: SGLT2 clustering | Registry data | High | Moderate |
| H4: Gene-drug matching | Pharmacogenomics | Moderate | High |
| H5: Dual therapy | Combination trials | Moderate | High |
| H6: CV-glycemic integration | Major trial data | High | High |
Potential Impact
537 million people have diabetes. 6.7 million die annually.
If these hypotheses improve outcomes by 5%:
- 335,000 deaths prevented/year
- 27 million with better disease control
- Reduced blindness, dialysis, amputations
Related: Microbiome & Type 1 Diabetes
Elevated zonulin and increased intestinal permeability precede T1D onset. See our Microbiome & Immunity hypotheses for testable predictions on barrier biomarkers and early-life interventions.