Low free triiodothyronineis predicts worsen neurological outcome of patients with acute ischemic stroke: a retrospective study with bioinformatics analysis

Abstract

Abstract Backgroud Patients with acute ischemic stroke (AIS) often experience low serum free triiodothyronine (FT3), but the association of low FT3 with stroke severity, subtype and prognosis has not yet been thoroughly studied, and the molecular events underlying these clinical observation were also unclear. Methods We retrospectively collected 221 cases of AIS and 182 non-AIS cases with detailed clinical data from our department. FT3 concentrations were measured on admission to predict functional outcome within 3 months using multivariable models adjusted for other risk factors. Receiver operating characteristic (ROC) curves were calculated to define the best cutoff value of FT3 of stroke severity, subtypes and neurological outcome. Gene set enrichment, pathway mapping and network analyses of deferentially expressed genes (DEGs) were performed. Results FT3 was significantly decreased in AIS patients with National Institutes of Health Stroke Scale (NIHSS) > 3 and 3-months modified Rankin Scale (mRS) > 2. The cut-off value of FT3 for NIHSS on admission was 4.30 pmol/L. Also, FT3 level was significantly lower in large artery atherosclerosis (LAA) group and cardioembolism (CE) group than that in small vessel occlusion (SVO). FT3 value served as an independent predictor for neurological outcomes for which the cut-off value of FT3 was 4.38 pmol/l. Gene ontology (GO) analysis showed that the biological function of DEGs was mainly enriched in multicellur organism, neuron differentiation and cellular response to hypoxia. The cellular components were involved in extracelluar region, exosome and matrix, and the molecular functions were transcriptional activator activity, DNA binding and nuclear hormone receptor binding. Signal pathways analysis was indicative of neuroactive ligand-receptor interaction, thyroid hormone signaling pathway, and protein digestion and absorption these DEGs were involved in. Six related gene were identified as hubs from the protein-protein interaction (PPI) networks. Three modules were selected from PPI, of which MMP4, ADRA2C and EIF3E were recognized as the seed genes. Conclusions Low FT3 value on admission was associated with stroke severity, subtype and prognosis. In addition, DEGs identified from bioinformatics analysis are likely to be candidates for elucidating clinical outcomes with low FT3, and provide us with therapeutic targets for improving stroke prognosis.

Keywords

• Stroke
• Triiodothyronineis
• Prognosis
• Bioinformatics analysis