Multi-omic prediction of incident type 2 diabetes
Main finding · C index for incident T2DResult — go to the resultΔ C index 0.05Authors' conclusion
Omic approaches provided marginal improvements in prediction of incident type 2 diabetes. However, while a polygenic risk score does improve prediction in people with an HbA1c in the normoglycaemic range, the group in whom prediction would be most useful, even individuals with a high polygenic burden in that subgroup had a low absolute type 2 diabetes risk. This suggests a limited feasibility of implementing targeted population-based genetic screening for preventative interventions.
Study context
- Population
- Prospective nested T2D case-cohort; 10,792 person-years of follow-up; 5759 candidate features375 incident T2D cases
- Participants
- 1,105 participants
- Exposure
- Clinical model plus omics features vs clinical model
- Outcome
- Predictive performance (C index) for incident T2D
Methodological detailsprediction modelling, least absolute shrinkage and selection operator (LASSO) regression
- Prediction modelling
- LASSO regression
Main finding
C index for incident T2D
Δ C index
0.05
P = 0.045
By group
Top ten omic features + clinical model
0.87
C index · 95% CI 0.82–0.92
As reported in the abstract
Observational data: associations, not effects.
Further findings
| Outcome | Top ten omic features + clinical model | Δ C index | P value |
|---|---|---|---|
| C index, subgroup HbA1c <42 mmol/mol (6.0%): top ten omic features added to clinical model | C index 0.84 (95% CI 0.77–0.90) | 0.07 | P = 0.03 |
| C index, subgroup HbA1c <42 mmol/mol (6.0%): T2D polygenic risk score added to clinical modelPolygenic risk score + clinical model vs Clinical model · C index=0.83 [95% CI 0.75, 0.90] | 0.06 | P = 0.002 |
Single-omics models without clinical risk factors: top ten proteins alone
- C index, top ten proteins alone (highest single-omics performance)
- 0.82 [95% CI 0.75, 0.88]
Absolute 20-year T2D risk, high polygenic risk in HbA1c <42 mmol/mol subgroup vs prediabetes
- Individuals at high polygenic risk had only around half the absolute risk of those with prediabetes
Original publication
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