Proinflammatory and lipid biomarkers mediate metabolically healthy obesity: A proteomics study

OBJECTIVE

The metabolically healthy obesity (MHO) phenotype is an important obesity subtype in which obesity is not accompanied by any metabolic comorbidity. However, the underlying molecular mechanisms remain elusive. In this study, a shotgun proteomics approach to identify circulating biomolecules and pathways associated with MHO was used.

METHODS

The subjects were 20 African-American women: 10 MHO cases and 10 metabolically abnormal individuals with obesity (MAO) controls. Serum proteins were detected and quantified using label-free proteomics. Differential expression of proteins between the two groups was analyzed, and the list of differentially expressed proteins was analyzed to determine enriched biological pathways.

RESULTS

Twenty proteins were differentially expressed between MHO and controls. These proteins included: hemoglobin subunits (HBA1, P = 6.00 × 10(-18) ), haptoglobin-related protein (HPR, P = 1.2 × 10(-15) ), apolipoproteins (APOB-100, P = 1.50 × 10(-40) ; APOA4, P = 1.1 × 10(-14) ), retinol-binding protein 4 (RBP4, P = 7.1 × 10(-08) ), and CRP (P = 2.0 × 10(-04) ). MHO was associated with lower levels of proinflammatory and higher levels of anti-inflammatory biomarkers when compared with MAO. Pathway analysis showed enrichment of lipids and inflammatory pathways, including LXR/RXR and FXR/RXR activation, and acute phase response signaling.

CONCLUSIONS

These findings suggested that protection from dysregulated inflammatory and lipid processes were primary molecular hallmarks of MHO. The candidate biomarkers (AHSG, RBP4, and APOA4) identified in this study are potential prognostic markers for MHO.

Beta cell function and response to treatment in Nigerians with Type 2 diabetes mellitus

There are scant data from African populations on the association between beta-cell function and response to treatment with oral hypoglycaemic agents in Type 2 diabetes mellitus (T2DM). Fasting plasma C-peptide (FCP) and glucagon-stimulated C-peptide (GSCP) levels were measured in 116 Nigerians with T2DM at a university teaching hospital. After 9 months of follow-up and treatment, they were categorized into three groups based on response to treatment: (A) good control but not on maximum sulphonylurea (SU) therapy, (B) inadequate control but not on maximum SU therapy and (C) on maximum SU therapy+/-insulin or biguanide. Logistic regression models were used to investigate how well C-peptide levels predicted the subjects belonging to Group C who are likely to require insulin. The mean FCP and mean GSCP levels of Group C were significantly lower than in the other groups (p=0.024; p= <0.001 respectively). A GSCP cut-off value of < or =1.3 ng/mL predicted membership of Group C with 85% sensitivity and 89% specificity while a cut-off of < or =1.8 ng/mL was associated with 91% sensitivity and 66% specificity. In resource-poor settings where inadequate treatment are common, estimation of GSCP may be useful in predicting treatment response and should be weighed against the cost of inadequate therapy with higher morbidity and mortality.