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July 18, 2023Scientific ReportsOpen Access

Genome-wide polygenic risk score for type 2 diabetes in Indian population

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Key result

Top South Asian polygenic risk score quartile linked to ~6-fold greater type 2 diabetes risk.

  • OR 5.79
  • 95% CI 4.86-6.90
  • P<2e-16
  • n=4,222

Why the study?

Genome-wide polygenic risk scores for lifestyle disorders like type 2 diabetes identify at-risk individuals early to guide healthier lifestyles, prompting the development and testing of a score specifically for the Indian population.

Does a genome-wide polygenic risk score accurately predict Type 2 Diabetes risk in the Indian population?

Population

959 T2D cases and 2,818 controls from UK Biobank, plus 445 Indians for testing

Comparison

Higher PRS groups vs lower PRS groups

Design

Genetic association and risk score development and validation study

Authors

SPSandhya Kiran PemmasaniSAShravya AtmakuriAAAnuradha Acharya

Discussion

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Overview

PRS may aid T2D risk stratification in Indians; hypothesis-generating and requires prospective validation before clinical adoption.

Study Design

Type

Case-Control (n=4,222)

Multicenter

Yes

Structured PICO

Does a genome-wide polygenic risk score accurately predict Type 2 Diabetes risk in the Indian population?

P
Population
4,222 Indian adults aged over 30 years from the UK Biobank and GenomegaDB, including 1,153 with type 2 diabetes and 3,069 controls.
E
Exposure
Genome-wide polygenic risk score (PRS) for Type 2 Diabetes
C
Comparator
Lower PRS quartiles
O
Outcome
Association of PRS with Type 2 Diabetes (measured by AUC and Odds Ratio)surrogate

Main Result

Odds Ratio: 5.79 (95% CI 4.86–6.9)

p-value: p=< 2e-16

A newly developed genome-wide polygenic risk score for Type 2 Diabetes demonstrates high predictive accuracy in the Indian population, offering a potential tool for personalized preventive strategies.

Limitations

  • GenomegaDB controls were younger than UK Biobank controls, with potential to become diabetic cases in the future.
  • Assessment of T2D status in GenomegaDB was purely based on self-report, which might result in misclassifications.
  • Did not include other clinical and lifestyle variables such as BMI, HDL, LDL, physical activity, sleep duration, smoking, and alcohol consumption in the predictive models.
  • Restricting the analysis to Hapmap3+ variants resulted in a smaller set of variants being considered.

Cite This Study

Pemmasani et al. (2023) conducted a case-control in Type 2 Diabetes (n=4,222). High polygenic risk score (top 25%) vs. Lower polygenic risk score (bottom 75%) was evaluated on Type 2 diabetes risk (OR 5.79, 95% CI 4.86-6.90, p=< 2e-16). Individuals in the highest quartile of a South Asian-specific polygenic risk score had a 5.79-fold increased risk of developing type 2 diabetes compared to the remaining 75% of the population.

synapsesocial.com/papers/6aaa6a3a2401dc9708be078dhttps://doi.org/10.1038/s41598-023-38768-5
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Also Consider

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