# Identification of Clinically Distinct Clusters in Patients With Severe COPD Using Circulating Blood Cell Population Parameters

## TL;DR

This study used blood cell data to identify four distinct COPD subgroups with unique clinical features, offering new ways to classify and treat severe COPD patients.

## Contribution

The study introduces a novel approach using blood cell activation status to identify clinically distinct COPD subgroups beyond traditional cell counts.

## Key findings

- Four COPD clusters were identified based on inflammatory profiles and clinical characteristics.
- Cell population data provided insights beyond absolute cell counts, improving patient classification.
- One cluster showed high emphysema severity, while another was associated with low exacerbation rates.

## Abstract

Peripheral blood cell counts are useful biomarkers in COPD, but may not fully reflect disease activity. The Sysmex XN‐Series haematology analyser offers advanced measurements of immune cell populations, providing information about the number and activation status of peripheral blood cells. We hypothesized that assessing immune cell activation status, in addition to cell counts, could provide complementary insights into the clinical heterogeneity of severe COPD.

For this study, 499 extensively characterised patients with severe COPD were included from the Groningen Severe COPD cohort. A total of 24 Sysmex‐derived systemic blood parameters were selected for analysis. Clustering of blood cell population data was performed using Self‐Organising Maps.

The cell population parameters showed various associations with clinical characteristics, such as emphysema severity and lung function. Four clusters were identified based on their inflammatory profiles, each showing distinct clinical characteristics: the ‘normal cell counts, resting pattern’ cluster (n = 156) showed high emphysema severity scores and RV/TLC ratios; the ‘normal cell counts, activated pattern’ cluster (n = 241) was associated with few exacerbations; the ‘elevated cell counts, activated pattern’ cluster (n = 97) displayed high inflammatory cell counts and activity along with high exacerbation rates; and the small ‘low‐eosinophilic’ cluster (n = 5) was characterised by inactive circulating eosinophils.

Cell population data can be used to identify distinct inflammatory profiles with clinical relevance in severe COPD. Cell population data provide information beyond absolute cell counts, supporting the added value of including activation markers in COPD phenotyping.

NCT04023409 at clinicaltrials.gov

This study investigated whether blood cell population data, in addition to cell counts, can identify clinically relevant COPD subgroups. Four distinct inflammatory profiles were identified with distinct clinical characteristics. Cell population data have the potential to provide additional insights beyond inflammatory cell counts and improve patient classification and clinical decision‐making.

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