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Background <p>Latent autoimmune diabetes in adults (LADA) shares core genetic and immunological features with type 1 diabetes (T1D) but is frequently misdiagnosed as type 2 diabetes (T2D). With few biomarkers for its timely diagnosis and management, this study integrated proteome-wide Mendelian randomisation (MR) and observational clinical analysis to identify potential LADA biomarkers.</p> Methods <p>We performed proteome-wide MR using <i>cis</i>-protein quantitative trait loci (<i>cis</i>-pQTLs) for 1,389 plasma proteins from the deCODE study (<i>n</i> = 35,559) and genome-wide association study (GWAS) data for LADA (2,634 cases and 5,947 controls, European ancestry). Robustness was enhanced via multiple sensitivity analyses. Pathway enrichment analysis, druggability evaluation, phenome-wide MR, and interaction analyses were performed to investigate the clinical relevance and biological context of candidate proteins. Candidate proteins were further evaluated using enzyme-linked immunosorbent assays in a matched Chinese clinical study (<i>n</i> = 241) to assess their discriminative ability for LADA.</p> Results <p>Proteome-wide MR and colocalisation analyses indicated associations between genetically predicted plasma levels of C-X-C motif chemokine ligand 10 (CXCL10; OR [95% CI] per 1-SD increase in protein levels: 5.49 [1.74,17.32]), serum amyloid A1 (SAA1; 1.28 [1.14,1.45]), and SAA2 (1.22 [1.11,1.34]) with LADA risk. Replication, multi-tissue eQTL, and multivariable MR supported CXCL10’s association. Druggability evaluation suggested CXCL10 as a drug target under investigation, and phenome-wide MR of 1,006 diseases and traits indicated no major safety concerns for CXCL10 as a potential biomarker. In the observational clinical study, CXCL10 differentiated LADA from healthy controls (area under the receiver operating characteristic curve [ROC-AUC]: 0.889; precision-recall area under the curve [PR-AUC]: 0.919) and T2D (ROC-AUC: 0.838; PR-AUC: 0.921), with both models showing adequate calibration.</p> Conclusions <p>This study suggests that CXCL10 is a putative biomarker associated with LADA, demonstrating discriminative ability to distinguish LADA from T2D in an observational clinical cohort. These findings contribute to understanding the autoimmune molecular aetiology of LADA and support its diagnostic potential in resolving the clinical ambiguity between LADA and T2D.</p> Graphical Abstract <p></p>

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Integrative proteogenomic and observational analysis identifies potential biomarkers for latent autoimmune diabetes in adults

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月9日

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  • Yuanqin Yang,
  • Jiawen Lu,
  • Zhenqian Wang,
  • Tianyuan Lu,
  • Jin Ding,
  • Ruofan Wang,
  • Sirui Zhou,
  • Zhiguang Zhou,
  • Jingyi Hu

摘要

Background

Latent autoimmune diabetes in adults (LADA) shares core genetic and immunological features with type 1 diabetes (T1D) but is frequently misdiagnosed as type 2 diabetes (T2D). With few biomarkers for its timely diagnosis and management, this study integrated proteome-wide Mendelian randomisation (MR) and observational clinical analysis to identify potential LADA biomarkers.

Methods

We performed proteome-wide MR using cis-protein quantitative trait loci (cis-pQTLs) for 1,389 plasma proteins from the deCODE study (n = 35,559) and genome-wide association study (GWAS) data for LADA (2,634 cases and 5,947 controls, European ancestry). Robustness was enhanced via multiple sensitivity analyses. Pathway enrichment analysis, druggability evaluation, phenome-wide MR, and interaction analyses were performed to investigate the clinical relevance and biological context of candidate proteins. Candidate proteins were further evaluated using enzyme-linked immunosorbent assays in a matched Chinese clinical study (n = 241) to assess their discriminative ability for LADA.

Results

Proteome-wide MR and colocalisation analyses indicated associations between genetically predicted plasma levels of C-X-C motif chemokine ligand 10 (CXCL10; OR [95% CI] per 1-SD increase in protein levels: 5.49 [1.74,17.32]), serum amyloid A1 (SAA1; 1.28 [1.14,1.45]), and SAA2 (1.22 [1.11,1.34]) with LADA risk. Replication, multi-tissue eQTL, and multivariable MR supported CXCL10’s association. Druggability evaluation suggested CXCL10 as a drug target under investigation, and phenome-wide MR of 1,006 diseases and traits indicated no major safety concerns for CXCL10 as a potential biomarker. In the observational clinical study, CXCL10 differentiated LADA from healthy controls (area under the receiver operating characteristic curve [ROC-AUC]: 0.889; precision-recall area under the curve [PR-AUC]: 0.919) and T2D (ROC-AUC: 0.838; PR-AUC: 0.921), with both models showing adequate calibration.

Conclusions

This study suggests that CXCL10 is a putative biomarker associated with LADA, demonstrating discriminative ability to distinguish LADA from T2D in an observational clinical cohort. These findings contribute to understanding the autoimmune molecular aetiology of LADA and support its diagnostic potential in resolving the clinical ambiguity between LADA and T2D.

Graphical Abstract