Paulo H Harada1, Isabela M Benseñor2, Márcio S Bittencourt1, Khurram Nasir3, Michael J Blaha4, Steven R Jones4, Peter P Toth5, Paulo A Lotufo6. 1. Center for Clinical and Epidemiological Research, University Hospital, University of Sao Paulo, Sao Paulo, Brazil. 2. Center for Clinical and Epidemiological Research, University Hospital, University of Sao Paulo, Sao Paulo, Brazil; Department of Medicine, School of Medicine University of Sao Paulo, Sao Paulo, Brazil. 3. Population Health & Health Systems Research, Center for Outcomes Research & Evaluation, Yale University/YNHH, New Haven, CT, USA; Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University, Baltimore, MD, USA. 4. Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University, Baltimore, MD, USA. 5. Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University, Baltimore, MD, USA; University of Illinois College of Medicine Peoria, Illinois CGH Medical Center, Sterling, IL, USA. 6. Center for Clinical and Epidemiological Research, University Hospital, University of Sao Paulo, Sao Paulo, Brazil; Department of Medicine, School of Medicine University of Sao Paulo, Sao Paulo, Brazil. Electronic address: palotufo@usp.br.
Abstract
BACKGROUND: Inflammation has been weakly associated with coronary artery calcium (CAC) in the overall population. However, it is currently unknown whether this varies according to the cardio-metabolic profile. We evaluated the association between GlycA, a unique composite biomarker of pro-inflammatory acute phase glycoproteins, high sensitivity C-reactive protein (hsCRP), uric acid, and their composite values (composite inflammation) in the overall population and strata according to cardiovascular risk. METHODS: This is a cross-sectional study of 3753 Sao Paulo site participants of the ELSA-Brasil cohort that were free of cardiovascular/chronic inflammatory disease and not taking statins or allopurinol. We measured GlycA by nuclear magnetic resonance spectroscopy. For each biomarker quartile (Qs), we ran adjusted logistic and linear regression for CAC>0 and CAC score. RESULTS: In the overall analysis, the 4th vs. 1st GlycA Q odds ratio (OR) for CAC>0 was 1.53 (95% CI: 1.18, 1.98, p trend<0.001) adjusted for demographics and lifestyle, but null after adding metabolic syndrome (MS) components, OR 1.14 (95% CI: 0.86, 1.51, p trend=0.140). Likewise, for continuous CAC values there was no difference across GlycA Qs in the fully adjusted analysis. Similarly, hsCRP, uric acid, and composite inflammation were not associated with CAC>0 or CAC score. In stratified analysis, GlycA was associated with CAC>0 in No-MS individuals, standardized (SD) OR 1.23 (95% CI: 1.08, 1.40); but not in MS individuals, SD OR 1.01 (95% CI: 0.89, 1.15) (p interaction 0.037). We found similar interaction in stratified analysis for continuous CAC on composite inflammation. CONCLUSIONS: GlycA and composite inflammation are associated with CAC among low cardiovascular risk individuals (No-MS), but not otherwise. GlycA and composite biomarkers may better represent sources of inflammation apart from visceral obesity and traditional cardiovascular risk factors, which may have relevant effect on CAC accumulation in low cardiovascular risk individuals.
BACKGROUND:Inflammation has been weakly associated with coronary artery calcium (CAC) in the overall population. However, it is currently unknown whether this varies according to the cardio-metabolic profile. We evaluated the association between GlycA, a unique composite biomarker of pro-inflammatory acute phase glycoproteins, high sensitivity C-reactive protein (hsCRP), uric acid, and their composite values (composite inflammation) in the overall population and strata according to cardiovascular risk. METHODS: This is a cross-sectional study of 3753 Sao Paulo site participants of the ELSA-Brasil cohort that were free of cardiovascular/chronic inflammatory disease and not taking statins or allopurinol. We measured GlycA by nuclear magnetic resonance spectroscopy. For each biomarker quartile (Qs), we ran adjusted logistic and linear regression for CAC>0 and CAC score. RESULTS: In the overall analysis, the 4th vs. 1st GlycA Q odds ratio (OR) for CAC>0 was 1.53 (95% CI: 1.18, 1.98, p trend<0.001) adjusted for demographics and lifestyle, but null after adding metabolic syndrome (MS) components, OR 1.14 (95% CI: 0.86, 1.51, p trend=0.140). Likewise, for continuous CAC values there was no difference across GlycA Qs in the fully adjusted analysis. Similarly, hsCRP, uric acid, and composite inflammation were not associated with CAC>0 or CAC score. In stratified analysis, GlycA was associated with CAC>0 in No-MS individuals, standardized (SD) OR 1.23 (95% CI: 1.08, 1.40); but not in MS individuals, SD OR 1.01 (95% CI: 0.89, 1.15) (p interaction 0.037). We found similar interaction in stratified analysis for continuous CAC on composite inflammation. CONCLUSIONS:GlycA and composite inflammation are associated with CAC among low cardiovascular risk individuals (No-MS), but not otherwise. GlycA and composite biomarkers may better represent sources of inflammation apart from visceral obesity and traditional cardiovascular risk factors, which may have relevant effect on CAC accumulation in low cardiovascular risk individuals.