医学
肥胖
体质指数
混淆
队列
炎症
C反应蛋白
队列研究
比例危险模型
全身炎症
内科学
作者
Eckart M. D. D. De Bie,Priscilla Correa‐Jaque,R. Jones,Harm Jan Bogaard,J. Chan,Colin Church,Gerry Coghlan,Akshay Gaur,Stefano Ghio,Hossein Ardeschir Ghofrani,Ze Ming Goh,Luke Howard,Marc Humbert,Gábor Kovács,Allan Lawrie,James Lordan,Wei‐Yu Lin,Dharshan Neelam-Naganathan,Joseph Newman,Christopher J. Rhodes
标识
DOI:10.1164/rccm.202412-2393oc
摘要
Inflammation is associated with all types of Pulmonary Hypertension (PH) both as a known cause and/or a putative confounder. The most common marker of inflammation, C-reactive protein (CRP), has not been widely studied in PH. This study set out to clarify if CRP informed clinical endotyping and outcomes. Methods & Measurements: Time-series clustering of longitudinal CRP levels was employed. Clinical differences between clusters were validated in three independent UK/international cohorts using clinical cut off values (n=10,301; UK-cohort, ASPIRE and FDA cohort). Associations were analysed with functional and mortality outcomes by linear and Cox regression models including all-causes of PH (groups 1-5). To add mechanistic insight, multi-omics were interrogated from associated previously published arrays. Patients segregated into two stable CRP clusters (median CRP 2 versus 6.5 mg/l), with the high cluster exhibiting significantly higher BMI (difference between medians DBM=5.4 kg/m2), higher RAP (DBM=2mmHg) and reduced 6-minute walk distance (6MWD (DBM=55m)). Inflammation was associated with worse survival, comorbidities, higher pulmonary vascular resistance (PVR), and smoking status. CRP and BMI were associated with differing inflammatory profiles in proteomic and transcriptomic analyses. Despite the relationship with CRP, higher BMI associated with improved survival, lower PVR and did not negatively affect 6MWD treatment-related functional responses. We establish a relationship between CRP and BMI across all-cause PH, though CRP and BMI associate with diverging clinical outcomes. Inflammation and obesity are relevant phenotypes for consideration in clinical trial design. Understanding their impacts on outcomes is important for clinical practice.
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