Genetic and Clinical Determinants of Variation in Drug Response in Type 2 Diabetes: Insights From the Scottish and UK Biobank Cohorts
- Design
- Retrospective cohort · 802 participants · Intermediate outcome
- Match to healthy normal-weight adults aged 55–75
- Different population[Auto] Participants had type 2 diabetes and obesity/overweight (age/BMI not reported in abstract).
- Could weight loss explain it?
- Possibly[Auto] Participants had obesity and/or type 2 diabetes and the abstract does not separate direct drug effects from weight loss or glycaemic improvement.
- Study tier
- Study tier 3[Auto] Observational design; confounding by indication and healthy-user effects cannot be excluded (auto-provisional).
- Assessment
- Version 1 · automatic, not yet reviewed by a person · Sep 13, 2026
Study facts come from the paper. Population match, weight-loss explanation and study tier are our judgments, made against the reference group of healthy normal-weight adults aged 55–75.
[Auto, unreviewed; quoted from abstract conclusions] Both clinical and genetic factors significantly contribute to inter-individual variability in T2D drug response. Partitioned PRSs provide mechanistic insights into drug-specific pathways and have the potential to inform precision prescribing and optimise therapeutic outcomes in routine diabetes care.
01Findings
What the study reported
- Drugs
- Class unspecified
- Primary outcome
- Not extracted
- Effect
- Not extracted
- 95% confidence interval
- Not extracted
- Follow-up
- 12 months
- Adverse events
- Not extracted
- Limitations
- Auto-classified from abstract only; effect estimates, adverse events and limitations not extracted. Requires manual review.
Who was studied
- Obesity status
- obesity/overweight present (all or most)
- Diabetes status
- type 2 diabetes present (all or most)
- Sample size
- 802
Study quality details
- Study design
- Retrospective cohort
- Sample size
- 802
- Randomization
- no
- Blinding
- not stated
- Comparator
- not stated
- Follow up duration
- 12 months
- Outcome type
- intermediate
- Replication
- not assessed (auto)
- Consistency with other evidence
- not assessed (auto)
- Population applicability
- INDIRECT
- Statistical precision
- not extracted
- Risk of bias
- not assessed (auto)
- Funding conflicts
- partial
- Peer review status
- yes
02Funding
Funding and conflicts
- Funding
- Novo Nordisk; University of Dundee
- Industry funded
- Partial
- Manufacturer
- Novo Nordisk
- Sponsor role
- mixed industry and public/foundation funding
- Author conflicts
- not available in metadata
- Independent replication
- unknown
Funding is shown on every study and never used to score it.
04Source
The source, as retrieved
Abstract
[OBJECTIVE] Treatment response in type 2 diabetes (T2D) varies widely among individuals. This study aimed to quantify the contributions of clinical characteristics and genetic predisposition as measured through partitioned polygenic risk scores (pPRS) to variation in glycemic response to glucose-lowering therapies. [RESEARCH DESIGN AND METHOD] We analysed data from two population-based cohorts: the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) and the UK Biobank (UKBB). GoDARTS included 41 802 patients who initiated one of six major drug classes, of whom 11 615 had available genotype data. UKBB contributed 9371 individuals, including 8293 with genetic data. The primary outcome was glycaemic response, defined as the change in HbA1c 12 months after treatment initiation. Variables included demographic and clinical factors (age, sex, BMI, baseline HbA1c, kidney and liver function markers) and 14 pPRS representing T2D-related biological pathways. Linear regression models were fitted within each cohort and drug class (metformin, sulfonylureas, TZDs, DPP4i, SGLT2i, GLP-1RA), and effect estimates were combined using fixed-effect meta-analysis. [RESULT] Baseline HbA1c was most strongly associated with glycemic response (p < 0.001). Older age was consistently associated with greater HbA1c reduction, while BMI and total cholesterol demonstrated drug-class-specific associations, with higher BMI associated with improved response to TZDs and higher total cholesterol generally associated with poorer glycaemic outcomes. Meta-analysis across GoDARTS and UK Biobank showed that higher overall T2D genetic risk was associated with greater HbA1c reduction with sulfonylureas (β = -0.46 mmol/mol, p = 0.013). Specific genetic profiles were also associated with drug responses, including β-cell function clusters with sulfonylureas (β = -0.57, p = 0.002), obesity-related variants with GLP-1RA (β = -1.49, p = 0.04), liver-lipid variants with SGLT2 inhibitors (β = -0.84, p = 0.05), and bilirubin pPRS with DPP-4 inhibitors (β = -0.69, p = 0.006). [CONCLUSION] Both clinical and genetic factors significantly contribute to inter-individual variability in T2D drug response. Partitioned PRSs provide mechanistic insights into drug-specific pathways and have the potential to inform precision prescribing and optimise therapeutic outcomes in routine diabetes care.
Where this record came from
| Source | Retrieved | Identifier |
|---|---|---|
| pubmed | Sep 13, 2026 | 42681821 first ingestion |