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34 Proteomic and micro rna biomarker discovery to identify novel markers of left ventricular diastolic dysfunction in patients with diabetes
  1. J O'Reilly1,
  2. G Shashi2,
  3. C Tonry1,
  4. L Murphy1,
  5. J Gallagher1,
  6. S Pennington1,
  7. T Thum2,
  8. M Ledwidge1,
  9. J Baugh1,
  10. K McDonald1,
  11. C Watson3
  1. 1University College Dublin, Dublin, Ireland
  2. 2Hannover Medical School, Hannover, Germany
  3. 3Queen's University Belfast, Belfast, Northern Ireland


Introduction The need for biomarkers to identify cardiac dysfunction in patients with diabetes (DM) is becoming increasingly pressing due to the global rise in disease prevalence and reducing healthcare resources to detect and manage these complications. With the risk of heart failure being 2–5 fold greater in those with diabetes, early identification of cardiac dysfunction may facilitate more timely management and reduce or delay future heart failure development. The aim of this ongoing study is to identify serum protein and micro RNA (miRNA) biomarker signatures that can be used to diagnose asymptomatic left ventricular diastolic dysfunction (LVDD) in diabetic patients.

Methods The biomarker discovery cohort consisted of a selected subset of 200 patients from within the STOP-HF population. Four pooled age- and gender-matched groups of 50 patients were analysed, with and without DM and with and without asymptomatic LVDD. LVDD was defined on echocardiography as left atrial volume index ≥34 ml/m2 and E’<10 cm/sec. For proteomics biomarker discovery, samples were enriched via immune-depletion and digested using trypsin before being run on a Q-Exactive mass spectrometer (Thermo Scientific). For miRNA analysis, Taqman array cards were used which have 745 microRNA Taqman probes on a 384-well micro-fluidic card (Applied Biosystems).

Results The proteomics and miRNA discovery analysis identified over 70 potential biomarkers that were differentially expressed in patients with both diabetes and LVDD compared with the other three discovery groups. GO-Term enrichment analysis revealed a significant involvement of processes relating to inflammation, including Humoral immune response, Complement activation, and Acute inflammatory responses (q-values: 1.00 E-30, 1.00 E-30, 1.00 E-30 respectively).

Conclusion Verification and validation of the diagnostic potential of these novel protein and miRNA biomarkers candidates may support future strategies for the early identification and monitoring of LVDD in diabetic populations. Furthermore, functional analysis and identification of disease relevance of these biomarkers could highlight new therapeutic targets, including novel anti-inflammatory approaches.

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