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June 7, 2026Diabetes

Cluster-based polygenic risk scores better stratify T2D patients into 7 distinct clinical subgroups.

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Why the study?

How pathway-specific polygenic risk score-based stratification strategies inform therapeutic selection and comorbidity risk in type 2 diabetes remains unclear.

Does a cluster-based polygenic risk score approach better stratify clinical traits and comorbidity risks in patients with Type 2 Diabetes compared to an extreme-value approach?

Population

19,734 East Asian patients with T2D

Comparison

Cluster-based K-means strategy vs extreme-value (top 20%) pPRS strategy

Design

Cohort study

Key result

A cluster-based polygenic risk score approach better stratified 19,734 T2D patients into 7 clinical subgroups with distinct traits and medication associations (e.g., OR 1.98 for injectables; P<.0001).

Authors

WSWAYNE H-H. SHEUJRJEROME I. ROTTER

Discussion

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Overview

May refine T2D subtyping in East Asians; hypothesis-generating and should not yet change practice.

Key Points

  • This research aims to evaluate the effectiveness of two polygenic risk score (pPRS) stratification methods for type 2 diabetes.
  • Analyzed a cohort of 19,734 East Asian patients with type 2 diabetes.
  • Compared cluster-based K-means strategy identifying 7 subgroups with an extreme-value approach targeting the top 20% of pPRS.
  • Evaluated genetic architectures and clinical phenotypes for treatment implications.
  • The cluster-based approach identified 7 distinct patient subgroups with diverse genetic profiles (P<.0001).
  • Cluster subgroups were significantly associated with medication use, showing odds ratios of S-obesity (OR 1.60), S-body fat (OR 1.54), and others (P<.0001).
  • Extreme-value approach showed limited clinical differentiation, reflecting a primary pathway without significant subgroup distinctions.

Study Design

Type

Cohort (n=19,734)

Structured PICO

Does a cluster-based polygenic risk score approach better stratify clinical traits and comorbidity risks in patients with Type 2 Diabetes compared to an extreme-value approach?

P
Population
19,734 East Asian patients with type 2 diabetes evaluated to compare cluster-based versus extreme-value polygenic risk score stratification approaches.
E
Exposure
Cluster-based strategy using K-means clustering across several pathway-specific polygenic risk scores (pPRS) to derive 7 patient subgroups
C
Comparator
Extreme-value strategy defining high-risk groups as the top 20% of each pPRS
O
Outcome
Separation in clinical traits (age, BMI, HbA1c, triglyceride, HDL-C, and GPT levels) and associations with medications use/comorbiditiessurrogate

Main Result

p-value: p=<.0001

A cluster-based approach using multiple pathway-specific polygenic risk scores better stratifies Type 2 Diabetes patients by clinical traits and comorbidity risks than a simple extreme-value cutoff.

Cite This Study

SHEU et al. (2026) conducted a cohort in Type 2 diabetes (n=19,734). Cluster-based K-means polygenic risk score stratification vs. Extreme-value strategy (top 20% of each pPRS) was evaluated on Separation in clinical traits and associations with medication use and comorbidities (p=<.0001). A cluster-based polygenic risk score approach better stratified 19,734 T2D patients into 7 clinical subgroups with distinct traits and medication associations (e.g., OR 1.98 for injectables; P<.0001).

synapsesocial.com/papers/6a250b8b7def13d035e1b934https://doi.org/10.2337/db26-2396-p
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