Eric Adua1, Elham Memarian2, Alyce Russell1, Irena Trbojević-Akmačić2, Ivan Gudelj2, Julija Jurić2, Peter Roberts1, Gordan Lauc2,3, Wei Wang1,4,5. 1. School of Medical & Health Sciences, Edith Cowan University, WA 6027, Australia. 2. Genos Glycoscience Research Laboratory, Zagreb 10000, Croatia. 3. University of Zagreb, Faculty of Pharmacy & Biochemistry, Zagreb 10000, Croatia. 4. School of Public Health, Taishan Medical University, Shandong, Taian 271000, PR China. 5. Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, PR China.
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.
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.
Entities:
Keywords:
N-glycans; Type 2 diabetes mellitus; biomarker; glycan peaks; metabolic syndrome; population genetics; prediction; risk factors; suboptimal health status; ultra performance liquid chromatography
Authors: Elham Memarian; Leen M 't Hart; Mandy van Hoek; Viktoria Dotz; Roderick C Slieker; Roosmarijn F L Lemmers; Amber A van der Heijden; Femke Rutters; Giel Nijpels; Emma Schoep; Aloysius G Lieverse; Eric J G Sijbrands; Manfred Wuhrer Journal: BMJ Open Diabetes Res Care Date: 2021-10