Utilization of N-glycosylation profiles as risk stratification biomarkers for suboptimal health status and metabolic syndrome in a Ghanaian population

Abstract

Aim: The study sought to apply N-glycosylation profiles to understand the interplay between suboptimal health status (SHS) and metabolic syndrome (MetS). Materials & methods: In this study, 262 Ghanaians were recruited from May to July 2016. After completing a health survey, plasma samples were collected for clinical assessments while ultra performance liquid chromatography was used to measure plasma N-glycans. Results: Four glycan peaks were found to predict case status (MetS and SHS) using a step-wise Akaike’s information criterion logistic regression model selection. This model yielded an area under the curve of MetS: 83.1% (95% CI: 78.0–88.1%) and SHS: 67.1% (60.6–73.7%). Conclusion: Our results show that SHS is a significant, albeit modest, risk factor for MetS and N-glycan complexity was associated with MetS.