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Background <p>Type 2 Diabetes Mellitus (T2DM) involves patient-specific immune dysfunction not addressed by current diabetes management methods. Traditional methods to assess functional changes to PBMCs are too costly and time-intensive for routine use.</p> Methods <p>We studied 57 individuals across healthy, prediabetic, and diabetic stages, performing chromatin imaging of live peripheral blood mononuclear cells (PBMCs) using a microfluidic imaging assay.</p> Results <p>Here, we present an orthogonal and adjunct chromatin imaging-based assay to monitor alterations to PBMCs during T2DM progression. By applying representation learning on chromatin images, we identified distinct PBMC clusters, with specific subpopulations enriched at different T2DM stages. We found that the levels of certain PBMC subsets are predictive of T2DM. Additionally, we observed significant changes in nuclear and chromatin mechanics in diabetic individuals compared to prediabetic and healthy individuals, along with decreased Lamin A/C expression and increased cellular activation in diabetic PBMCs.</p> Conclusions <p>Collectively, this study demonstrated a cost-effective and scalable solution for the routine monitoring of T2DM using PBMC chromatin biomarkers.</p>

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Detecting chromatin state alterations in PBMCs associated with Type 2 Diabetes Mellitus

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月17日

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  • Maryam Moazeni Afarani,
  • Rajshikhar Gupta,
  • Caroline Uhler,
  • Issa Fetian,
  • GV Shivashankar

摘要

Background

Type 2 Diabetes Mellitus (T2DM) involves patient-specific immune dysfunction not addressed by current diabetes management methods. Traditional methods to assess functional changes to PBMCs are too costly and time-intensive for routine use.

Methods

We studied 57 individuals across healthy, prediabetic, and diabetic stages, performing chromatin imaging of live peripheral blood mononuclear cells (PBMCs) using a microfluidic imaging assay.

Results

Here, we present an orthogonal and adjunct chromatin imaging-based assay to monitor alterations to PBMCs during T2DM progression. By applying representation learning on chromatin images, we identified distinct PBMC clusters, with specific subpopulations enriched at different T2DM stages. We found that the levels of certain PBMC subsets are predictive of T2DM. Additionally, we observed significant changes in nuclear and chromatin mechanics in diabetic individuals compared to prediabetic and healthy individuals, along with decreased Lamin A/C expression and increased cellular activation in diabetic PBMCs.

Conclusions

Collectively, this study demonstrated a cost-effective and scalable solution for the routine monitoring of T2DM using PBMC chromatin biomarkers.