Association of gamma-glutamyl transferase with subclinical coronary atherosclerosis and cardiac outcomes in non-alcoholics

Kim, Yong-Giun; Park, Gyung‐Min; Lee, Seung Bum; Yang, Dong Hyun; Kang, Joon‐Won; Lim, Tae‐Hwan; Kim, Hong‐Kyu; Choe, Jaewon; Lee, Seung-Whan

doi:10.1038/s41598-020-75078-6

Cited by 5 publications

(4 citation statements)

References 46 publications

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“…Age, PDW, MPV, SUA, and GGT were observed as independent risk factors for SCAS, consistent with previous studies ( 29 – 33 ). Inflammation-related markers such as WBC, BASO, and LYC, were also found to be independent risk factors for SCAS.…”

Section: Discussionsupporting

confidence: 92%

Predicting the risk of subclinical atherosclerosis based on interpretable machine models in a Chinese T2DM population

Tusongtuoheti,

Shu,

Huang

et al. 2024

Front. Endocrinol.

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BackgroundCardiovascular disease (CVD) has emerged as a global public health concern. Identifying and preventing subclinical atherosclerosis (SCAS), an early indicator of CVD, is critical for improving cardiovascular outcomes. This study aimed to construct interpretable machine learning models for predicting SCAS risk in type 2 diabetes mellitus (T2DM) patients.MethodsThis study included 3084 T2DM individuals who received health care at Zhenhai Lianhua Hospital, Ningbo, China, from January 2018 to December 2022. The least absolute shrinkage and selection operator combined with random forest-recursive feature elimination were used to screen for characteristic variables. Linear discriminant analysis, logistic regression, Naive Bayes, random forest, support vector machine, and extreme gradient boosting were employed in constructing risk prediction models for SCAS in T2DM patients. The area under the receiver operating characteristic curve (AUC) was employed to assess the predictive capacity of the model through 10-fold cross-validation. Additionally, the SHapley Additive exPlanations were utilized to interpret the best-performing model.ResultsThe percentage of SCAS was 38.46% (n=1186) in the study population. Fourteen variables, including age, white blood cell count, and basophil count, were identified as independent risk factors for SCAS. Nine predictors, including age, albumin, and total protein, were screened for the construction of risk prediction models. After validation, the random forest model exhibited the best clinical predictive value in the training set with an AUC of 0.729 (95% CI: 0.709-0.749), and it also demonstrated good predictive value in the internal validation set [AUC: 0.715 (95% CI: 0.688-0.742)]. The model interpretation revealed that age, albumin, total protein, total cholesterol, and serum creatinine were the top five variables contributing to the prediction model.ConclusionThe construction of SCAS risk models based on the Chinese T2DM population contributes to its early prevention and intervention, which would reduce the incidence of adverse cardiovascular prognostic events.

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Section: Discussionsupporting

confidence: 92%

Predicting the risk of subclinical atherosclerosis based on interpretable machine models in a Chinese T2DM population

Tusongtuoheti,

Shu,

Huang

et al. 2024

Front. Endocrinol.

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“…In the first approach, upregulation of GGT1 was identified as a common marker of LEAD, AAA and CVD subjects after comparison to healthy controls (Figure 1). This finding is in concordance with previous studies, where increased serum level of GGT was found to be associated with peripheral arterial disease (PAD) in non-alcoholic males [47] and with higher risk of subclinical coronary atherosclerosis, coronary artery calcification and cardiac events [48,49]. Elevated serum GGT levels are related to increased concentrations of homocysteine [50], which is well known independent risk factor of cardiovascular diseases, including LEAD [51].…”

Section: Discussionsupporting

confidence: 92%

Identification of Transcriptomic Differences between Lower Extremities Arterial Disease, Abdominal Aortic Aneurysm and Chronic Venous Disease in Peripheral Blood Mononuclear Cells Specimens

Zalewski

Ruszel

Stępniewski

et al. 2021

IJMS

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Several human tissues are investigated in studies of molecular biomarkers associated with diseases development. Special attention is focused on the blood and its components due to combining abundant information about systemic responses to pathological processes as well as high accessibility. In the current study, transcriptome profiles of peripheral blood mononuclear cells (PBMCs) were used to compare differentially expressed genes between patients with lower extremities arterial disease (LEAD), abdominal aortic aneurysm (AAA) and chronic venous disease (CVD). Gene expression patterns were generated using the Ion S5XL next-generation sequencing platform and were analyzed using DESeq2 and UVE-PLS methods implemented in R programming software. In direct pairwise analysis, 21, 58 and 10 differentially expressed genes were selected from the comparison of LEAD vs. AAA, LEAD vs. CVD and AAA vs. CVD patient groups, respectively. Relationships between expression of dysregulated genes and age, body mass index, creatinine levels, hypertension and medication were identified using Spearman rank correlation test and two-sided Mann–Whitney U test. The functional analysis, performed using DAVID website tool, provides potential implications of selected genes in pathological processes underlying diseases studied. Presented research provides new insight into differences of pathogenesis in LEAD, AAA and CVD, and selected genes could be considered as potential candidates for biomarkers useful in diagnosis and differentiation of studied diseases.

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“…Considerable evidence from epidemiolocal studies support the positive correlation of GGT with the degree of coronary atherosclerosis and incident CVD risk 8 , 17 . In addition, high GGT was associated with high-risk features of atherosclerosis detected by coronary computed tomography and with poorer cardiac outcomes defined as a composite of all-cause death, myocardial infarction, unstable angina requiring hospitalization, or coronary revascularization in subjects without significant alcohol consumption 18 . Similarly, GGT was positively associated with the risk of incident heart failure in prospective cohort studies 19 , 20 and was an independent predictor of death or heart transplantation in patients with heart failure 21 .…”

Section: Discussionmentioning

confidence: 99%

Gamma-glutamyl transferase and risk of all-cause and disease-specific mortality: a nationwide cohort study

Cho

Jeong

Chung

et al. 2023

Sci Rep

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Population-based data regarding the prognostic implication of gamma-glutamyl transferase (GGT) have been inconsistent. We examined the association of GGT with all-cause and disease-specific mortality. Using the Korean nationwide database, we included 9,687,066 subjects without viral hepatitis or cirrhosis who underwent a health examination in 2009. Subjects were classified into three groups by sex-specific tertile of serum GGT levels. The underlying causes of death were classified by 10th Revision of the International Classification of Diseases codes. During the median follow-up period of 8.3 years, 460,699 deaths were identified. All-cause mortality increased as serum GGT levels became higher (hazard ratio [HR], 95% confidence interval [CI] 1.05, 1.04–1.05 in the middle tertile, and 1.33, 1.32–1.34 in the high tertile) compared to the low tertile of serum GGT levels. Similar trends were observed for cardiovascular disease (CVD) (HR, 95% CI 1.07, 1.05–1.09 in the middle tertile, 1.29, 1.26–1.31 in the high tertile), cancer (HR, 95% CI 1.08, 1.07–1.10 in the middle tertile, 1.38, 1.36–1.39 in the high tertile), respiratory disease (HR, 95% CI 1.10, 1.08–1.13 in the middle tertile, 1.39, 1.35–1.43 in the high tertile), and liver disease mortality (HR, 95% CI 1.74, 1.66–1.83 in the middle tertile, 6.73, 6.46–7.01 in the high tertile). Regardless of smoking, alcohol consumption and history of previous CVD and cancer, a higher serum GGT levels were associated with a higher risk of mortality. Serum GGT levels may be useful for risk assessment of all-cause and disease-specific mortality in general population.

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Association of gamma-glutamyl transferase with subclinical coronary atherosclerosis and cardiac outcomes in non-alcoholics

Cited by 5 publications

References 46 publications

Predicting the risk of subclinical atherosclerosis based on interpretable machine models in a Chinese T2DM population

Predicting the risk of subclinical atherosclerosis based on interpretable machine models in a Chinese T2DM population

Identification of Transcriptomic Differences between Lower Extremities Arterial Disease, Abdominal Aortic Aneurysm and Chronic Venous Disease in Peripheral Blood Mononuclear Cells Specimens

Gamma-glutamyl transferase and risk of all-cause and disease-specific mortality: a nationwide cohort study

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