Inflammatory signatures distinguish metabolic health in African American women with obesity

Abstract

Obesity-driven Type 2 diabetes (T2D) is a systemic inflammatory condition associated with cardiovascular disease. However, plasma cytokines and tissue inflammation that discriminate T2D risk in African American women with obese phenotypes are not well understood. We analyzed 64 circulating cytokines and chemokines in plasma of 120 African American women enrolled in the Black Women's Health Study. We used regression analysis to identify cytokines and chemokines associated with obesity, co-morbid T2D and hypertension, and compared results to obese women without these co-morbidities, as well as to lean women without the co-morbidities. We then used hierarchical clustering to generate inflammation signatures by combining the effects of identified cytokines and chemokines and summarized the signatures using an inflammation score. The analyses revealed six distinct signatures of sixteen cytokines/chemokines (P = 0.05) that differed significantly by prevalence of T2D (P = 0.004), obesity (P = 0.0231) and overall inflammation score (P < E-12). Signatures were validated in two independent cohorts of African American women with obesity: thirty nine subjects with no metabolic complications or with T2D and hypertension; and thirteen breast reduction surgical patients. The signatures in the validation cohorts closely resembled the distributions in the discovery cohort. We find that blood-based cytokine profiles usefully associate inflammation with T2D risks in vulnerable subjects, and should be combined with metabolism and obesity counselling for personalized risk assessment.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1. Hierarchical clustering analysis of sixteen signature cytokines/chemokines in BWHS subjects.

A) Transformed median fluorescence intensities of cytokines detected by multiplex assay are displayed by row and subjects by column in the heat map. Red indicates increased expression and green decreased expression, according to fold-change scale at left. Clusters were detected by cutting the dendrogram at a height seen in less than 1% of randomly generated dendrograms. B) Six clusters of subjects according to inflammation score. C) Representation of each cluster according to metabolic Group: I, normal BMI without T2D or hypertension (‘lean, healthy’); II, obese without T2D or hypertension (‘obese, healthy’); III, obese with both T2D and hypertension, not treated with metformin (‘obese, unhealthy, no metformin’).

Fig 2. Signature patterns of BWHS subjects.

Quantification of sixteen cytokines (median fluorescence intensity in logarithmic scale) that resolve the six clusters of the signature are shown with side-by-side boxplots. Individual cytokines are identified at left: CCL27, C-C motif chemokine ligand 27, also known as CTACK; PDGF-AA, platelet-derived growth factor α polypeptide; CCL11, C-C motif chemokine ligand 11; IL-16, interleukin 16; CCL22, C-C motif chemokine ligand 22; IL-1β, interleukin 1β; TGF-α, transforming growth factor α; IL-5, interleukin 5; IL-7, interleukin 7; IL-12 p70, interleukin 12, 70 kDa subunit; TNF-β, tumor necrosis factor β; IL-2, interleukin 2; IL-6, interleukin 6; IL-12 p40, interleukin 12, 40 kDa subunit; IL-9, interleukin 9; IL-1α, interleukin 1α. Vertical guide bars shown for reference to permit comparison among clusters. Subjects reporting that they were taking metformin or NSAIDs were excluded.

Fig 3. Six-cluster signature in BWHS subjects taking metformin or NSAIDs.

Patterns of sixteen cytokines by signatures assigned with the multi-label classification algorithm. The algorithm used the profiles of cytokines discovered in the original BWHS set of sixty two subjects to infer the most likely signature of fifty eight other subjects, who had been excluded from the first analysis because they were taking medications. The six signatures are very similar to those calculated for Fig 2 subjects, who were not taking medications. Only the distribution of CCL22 in Cluster 3 differed significantly (P-value = 0.003) from the distribution of CCL22 in patients assigned to the same Cluster 3 in the discovery set (Fig 2). For all other signatures, the difference in distributions of individual cytokines by cluster was tested using t-test and no other comparison reached statistical significance after Bonferroni correction for multiple testing (P < 0.003).

Fig 4. Cluster signature in Komen subjects for validation of BWHS–derived signature.

The patterns of cytokines in the four clusters matched very closely the patterns discovered in the original BWHS data set, although CCL27 and IL-16 in Cluster 2 and Cluster 3 were significantly lower compared to the discovery set (P < 0.0002).

Fig 5. Cluster signature in breast reduction surgical subjects for validation of BWHS–derived signature.

The four patterns of clustered cytokines found in the surgical subjects with obesity were very similar to the patterns identified in the original BWHS data set (Fig 2) [28], as well as the independent cohort of Komen subjects (Fig 4) [50].