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Standards for Quantitative Metalloproteomic Analysis Using Size Exclusion ICP-MS
Published on: April 13, 2016
Whole-Blood Metal(loid) Profiles Including Macroelements in Relation to Short-Term Glycemic Status: A Metallome-Based
Xiaochen Shang1, Wenyue Hou1, Jie Yu1
1School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China.
Abstract:
Metals and metalloids (collectively referred to as metal(loid)s) have been implicated in glucose dysregulation, yet interpreting such associations remain challenging because multiple metal(loid)s coexist within complex biological elemental profiles. Whole-blood metallome profiling characterizes the integrated elemental composition of blood, including toxic trace elements, essential trace elements as well as physiologically regulated macroelements. However, most mixture studies have focused on trace or toxic metal(loid)s, while macroelements have been less commonly incorporated into metal(loid) mixture of glycemic studies, despite being integral components of the blood metallome. We conducted a community-based cross-sectional biomonitoring study among 281 non-diabetic adults aged ≥ 45 years residing in a copper-smelting region of China. Whole-blood concentrations of 35 metal(loid)s were measured, with glycated albumin (GA) assessed as the primary marker of short-term glycemic status. Single-metal(loid) regression, quantile g-computation (qgcomp), Bayesian kernel machine regression (BKMR), and category-level analyses were used to characterize individual and joint associations with glycemic status. Macroelements, particularly Ca and Na, consistently showed positive associations with GA and had the largest positive qgcomp weights and the highest BKMR posterior inclusion probability rankings in the metallome mixture. Primary qgcomp results yielded inverse estimates for the full mixture, with a stronger inverse estimate after excluding macroelements, and a positive association for the macroelement-only mixture. Category-level analyses also showed that macroelements category positively associated with GA and having the highest BKMR posterior inclusion probability. Similar association patterns for glycated serum protein (GSP), assessed as a secondary outcome, provided additional support for the GA findings. These findings suggest that incorporating macroelements alongside other trace metal(loid)s can provide a more complete characterization of whole-blood metallome associations with short-term glycemic status in non-diabetic middle-aged and older adults, while their distinct physiological regulation should be considered when interpreting mixture associations.

