PDI dysregulation, ER stress, and inflammatory signaling in T2DM.
| Year | Study (authors) | Sample/Model | Findings | Quantitative Data | Interpretation |
|---|---|---|---|---|---|
| 2022 | Su et al. [106] | 553 adults (225 T2DM, 159 NGT) | ↑ PDIA4 in T2DM | Correlation: FPG r = 0.62; BMI r = 0.58; CRP r = 0.55; ISI r = –0.67 | PDI upregulation linked to T2DM severity |
| 2022 | Lee et al. [107] | C2C12 cells, palmitate | PDIA4 ↑ inflammation & resistance | TNF-α, IL-6 ↑ 2.5× (P < 0.01); knockdown ↓ IR 40% | PDI mediates lipotoxic resistance |
| 2023 | Tseng et al. [108] | db/db mice, PS1 inhibitor | ↓ ROS, ↑ glucose tolerance, ↓ HbA1c | ROS ↓ 50% (P < 0.01); HbA1c –1.2% (P < 0.05); β-cell survival +30% | Targeting PDIA4 restores insulin action |
| 2022 | Zhou et al. [109] | Biochemical review | S-nitrosylation of cysteine residues | ↓ IRS-1 phosphorylation | Competes w/disulfide formation, impairs signaling |
| 2016 | Lei et al. [110] | 45 men, PBMCs | Obesity ↑ ER stress & inflammatory markers | ↑ GRP78, CHOP, XBP-1, TLR2/4, APP (P < 0.05) | ER stress linked to obesity & diabetes |
| 2024 | Luo et al. [111] | Adipose snRNA-seq | Maladaptive macrophage subpopulation PDIA3hi | siRNA liposomes ↓ inflammation, ↓ obesity (P < 0.05) | PDI-driven inflammation worsens T2DM |
| 2019 | Jang et al. [112] | β-cell-specific PDIA1 KO mice | ↑ Proinsulin/insulin ratio, ↓ insulin granules, ↑ ER vesiculation | P < 0.01 | PDI is critical for proinsulin folding |
ER: endoplasmic reticulum; IL-6: interleukin-6; IR: insulin receptor; IRS-1: IR substrate-1; PBMCs: peripheral blood mononuclear cells; PDI: protein disulfide isomerase; PDIA4: PDI family A, member 4; ROS: reactive oxygen species; T2DM: type 2 diabetes mellitus; TLR4: toll-like receptor 4; TNF-α: tumor necrosis factor-alpha; APP: amyloid precursor protein; CHOP: CCAAT/enhancer-binding protein homologous protein; GRP78: glucose-regulated protein 78; HbA1c: hemoglobin A1c; PS1: presenilin 1; XBP-1: X-box binding protein 1.
During the preparation of this work, the author(s) used ChatGPT (OpenAI) and Midjourney for figure design and language editing. The figures were generated by providing specific biochemical and structural data to these tools, and all outputs were subsequently reviewed, edited, and verified by the authors, who take full responsibility for the content of this publication.
MMA: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing—original draft, Writing—review & editing. AA: Supervision. Both authors read and approved the submitted version.
The authors declare that there are no conflicts of interest.
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