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A Cross-Layer Inflammatory Signature Links Residual Inflammatory Risk to Heart Failure Risk in Metabolic Syndrome:
Chunmei Chen1,2, Xinxin Mao1,2, Yuxin Wang1,2
1Department of General Internal Medicine, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, People's Republic of China.
Background:
Residual inflammatory risk (RIR), commonly indexed by high-sensitivity C-reactive protein (hs-CRP), reflects a persistent inflammatory burden that may not be captured by conventional metabolic indices. Whether RIR is associated with a higher heart failure (HF)-risk phenotype in metabolic syndrome (MetS), and whether it aligns with a coherent cross-level inflammatory signature, remains unclear.
Objective:
To determine the association between RIR and a higher HF-risk phenotype in MetS, and to characterize related inflammatory signatures across clinical, bioinformatic, and experimental datasets.
Methods:
This study integrated three complementary components. First, a propensity score-matched cohort of hospitalized patients with MetS was used to evaluate the association between RIR and a higher HF-risk phenotype. Second, curated disease-gene resources and GEO transcriptomic datasets were integrated for enrichment and network analyses to identify shared inflammatory features between MetS and HF. Third, an HFpEF mouse model induced by high-fat diet (HFD) plus transverse aortic constriction (TAC), together with brown adipose tissue (BAT) bulk RNA sequencing, was used to assess tissue-level transcriptomic context.
Results:
In the propensity score-matched MetS cohort, high RIR (hs-CRP ≥2 mg/L) was associated with higher odds of HF-risk phenotype (NT-proBNP >125 pg/mL) within matched pairs (conditional OR 1.70, 95% CI 1.15-2.51; P = 0.0078). The association remained after additional adjustment (OR 1.59, 95% CI 1.06-2.37; P = 0.02) and was also observed using an alternative NT-proBNP threshold (>300 pg/mL; adjusted OR 1.55, 95% CI 1.14-2.10; P = 0.005). Cross-disease analyses converged on inflammatory programs involving cytokine and chemokine activity, IL-17 and TNF signaling, and extracellular matrix (ECM) remodeling, with six shared genes (CCL2, FOSL1, THBS1, ATP2A2, FASN, and CFH) identified at the MetS-HF interface. In vivo, HFD plus TAC produced an HFpEF phenotype with preserved ejection fraction, diastolic dysfunction, and myocardial fibrosis. BAT transcriptomics showed enrichment of immune and inflammatory pathways, including chemotaxis pathways, which overlapped with the discovery-level inflammatory signature.
Conclusion:
In MetS, RIR was associated with higher odds of a HF-risk phenotype and aligned with a coherent inflammatory network characterized by cytokine-chemokine signaling and remodeling-related pathways. BAT transcriptomic changes provide supportive tissue-level context for this inflammatory signature. These findings are associative and hypothesis-generating, and further mechanistic studies are needed to define causal tissue-to-heart pathways.
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