Home > Publications Database > Association between inflammatory biomarkers, chronic stress, and pericoronary adipose tissue attenuation obtained with coronary CT. > print

001     281514
005     20251102002051.0
024 7 _ |a 10.1093/ehjci/jeaf217
|2 doi
024 7 _ |a pmid:40886153
|2 pmid
024 7 _ |a 2047-2404
|2 ISSN
024 7 _ |a 2047-2412
|2 ISSN
024 7 _ |a altmetric:181174533
|2 altmetric
037 _ _ |a DZNE-2025-01133
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Albertini, Tobia
|b 0
245 _ _ |a Association between inflammatory biomarkers, chronic stress, and pericoronary adipose tissue attenuation obtained with coronary CT.
260 _ _ |a Oxford
|c 2025
|b Oxford University Press
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1761731956_30627
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Pericoronary adipose tissue (PCAT) attenuation is a novel imaging biomarker of coronary inflammation associated with an increased risk of coronary artery disease (CAD). However, no studies have examined the relationship between chronic stress and PCAT. This study aimed to evaluate the intersection between chronic stress, inflammatory biomarkers, coronary plaque features, and PCAT attenuation.A total of 98 participants without known CAD were included. PCAT attenuation, total plaque volume (TPV) quantification, and vulnerable plaque features were assessed by coronary CT angiography and chronic stress was measured by hair cortisol concentration (HCC) and vital exhaustion questionnaire. Regression models were used to analyse associations of PCAT with the inflammatory biomarkers interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α), TPV, vulnerable plaque features, and coronary stenosis. Moderating analyses were performed to test whether chronic stress modulated the association between inflammatory biomarkers and PCAT attenuation. PCAT attenuation was significantly associated with IL-6 (mean difference 1.05, 95% CI 0.21-1.89, P = 0.014), TNF-α (mean difference 0.60, 95% CI 0.06-1.13, P = 0.027), and a greater TPV (mean difference 3.51, 95% CI 0.02-7.00, P = 0.048), but not vulnerable plaque features or coronary stenosis. HCC (interaction term -0.12, 95% CI -0.22 to -0.02, P = 0.019) and vital exhaustion (interaction term 0.13, 95% CI 0.01-0.25, P = 0.024) moderated the relationship between IL-6, but not TNF-α, and PCAT attenuation.This study suggests that circulating inflammatory biomarkers are associated with PCAT attenuation, which was further correlated with TPV. Chronic stress may moderate the relationship between inflammatory cytokines and PCAT attenuation.
536 _ _ |a 353 - Clinical and Health Care Research (POF4-353)
|0 G:(DE-HGF)POF4-353
|c POF4-353
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: pub.dzne.de
650 _ 7 |a chronic stress
|2 Other
650 _ 7 |a coronary artery disease
|2 Other
650 _ 7 |a hair cortisol
|2 Other
650 _ 7 |a interleukin-6
|2 Other
650 _ 7 |a pericoronary adipose tissue attenuation
|2 Other
650 _ 7 |a vital exhaustion
|2 Other
650 _ 7 |a Biomarkers
|2 NLM Chemicals
650 _ 7 |a Interleukin-6
|2 NLM Chemicals
650 _ 7 |a Tumor Necrosis Factor-alpha
|2 NLM Chemicals
650 _ 2 |a Humans
|2 MeSH
650 _ 2 |a Male
|2 MeSH
650 _ 2 |a Female
|2 MeSH
650 _ 2 |a Middle Aged
|2 MeSH
650 _ 2 |a Biomarkers: blood
|2 MeSH
650 _ 2 |a Computed Tomography Angiography: methods
|2 MeSH
650 _ 2 |a Adipose Tissue: diagnostic imaging
|2 MeSH
650 _ 2 |a Coronary Artery Disease: diagnostic imaging
|2 MeSH
650 _ 2 |a Coronary Artery Disease: blood
|2 MeSH
650 _ 2 |a Coronary Angiography: methods
|2 MeSH
650 _ 2 |a Stress, Psychological
|2 MeSH
650 _ 2 |a Inflammation
|2 MeSH
650 _ 2 |a Plaque, Atherosclerotic: diagnostic imaging
|2 MeSH
650 _ 2 |a Aged
|2 MeSH
650 _ 2 |a Interleukin-6: blood
|2 MeSH
650 _ 2 |a Chronic Disease
|2 MeSH
650 _ 2 |a Tumor Necrosis Factor-alpha: blood
|2 MeSH
650 _ 2 |a Epicardial Adipose Tissue
|2 MeSH
700 1 _ |a Dörner, Marc
|0 P:(DE-2719)9002951
|b 1
|u dzne
700 1 _ |a Giannopoulos, Andreas A
|b 2
700 1 _ |a von Känel, Roland
|0 0000-0002-8929-5129
|b 3
700 1 _ |a Benz, Dominik C
|0 0000-0001-8627-726X
|b 4
700 1 _ |a Mikail, Nidaa
|b 5
700 1 _ |a de Wilde, Daniel
|b 6
700 1 _ |a Voegel, Clarissa D
|b 7
700 1 _ |a Binz, Tina M
|b 8
700 1 _ |a Kaufmann, Philipp A
|0 0000-0002-9451-5210
|b 9
700 1 _ |a Gebhard, Catherine
|b 10
700 1 _ |a Buechel, Ronny R
|0 0000-0001-8064-8904
|b 11
700 1 _ |a Pazhenkottil, Aju P
|0 0000-0002-8847-2154
|b 12
773 _ _ |a 10.1093/ehjci/jeaf217
|g Vol. 26, no. 10, p. 1664 - 1672
|0 PERI:(DE-600)2647943-6
|n 10
|p 1664 - 1672
|t European heart journal - cardiovascular imaging
|v 26
|y 2025
|x 2047-2404
856 4 _ |u https://pub.dzne.de/record/281514/files/DZNE-2025-01133%20SUP.docx
856 4 _ |y OpenAccess
|u https://pub.dzne.de/record/281514/files/DZNE-2025-01133.pdf
856 4 _ |u https://pub.dzne.de/record/281514/files/DZNE-2025-01133%20SUP.doc
856 4 _ |u https://pub.dzne.de/record/281514/files/DZNE-2025-01133%20SUP.odt
856 4 _ |u https://pub.dzne.de/record/281514/files/DZNE-2025-01133%20SUP.pdf
856 4 _ |y OpenAccess
|x pdfa
|u https://pub.dzne.de/record/281514/files/DZNE-2025-01133.pdf?subformat=pdfa
909 C O |o oai:pub.dzne.de:281514
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Deutsches Zentrum für Neurodegenerative Erkrankungen
|0 I:(DE-588)1065079516
|k DZNE
|b 1
|6 P:(DE-2719)9002951
913 1 _ |a DE-HGF
|b Gesundheit
|l Neurodegenerative Diseases
|1 G:(DE-HGF)POF4-350
|0 G:(DE-HGF)POF4-353
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Clinical and Health Care Research
|x 0
914 1 _ |y 2025
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2025-01-06
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2025-01-06
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b EUR HEART J-CARD IMG : 2022
|d 2025-01-06
915 _ _ |a Creative Commons Attribution-NonCommercial CC BY-NC 4.0
|0 LIC:(DE-HGF)CCBYNC4
|2 HGFVOC
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2025-01-06
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2025-01-06
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b EUR HEART J-CARD IMG : 2022
|d 2025-01-06
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2025-01-06
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
|d 2025-01-06
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2025-01-06
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2025-01-06
920 1 _ |0 I:(DE-2719)1310010
|k AG Schreiber
|l Mixed Cerebral Pathologies and Cognitive Aging
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-2719)1310010
980 1 _ |a FullTexts

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21