Noninvasive, Blood-Based Biomarkers as Screening Tools for Hepatic Fibrosis in People With Type 2 Diabetes.
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ABSTRACT:
SUBMITTER: Meritsi A
PROVIDER: S-EPMC9331611 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
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Noninvasive, Blood-Based Biomarkers as Screening Tools for Hepatic Fibrosis in People With Type 2 Diabetes.
Meritsi Angeliki A Latsou Dimitra D Manesis Emanuel E Gatos Ilias I Theotokas Ioannis I Zoumpoulis Pavlos P Rapti Stamatia S Tsitsopoulos Eustathios E Moshoyianni Hariklia H Manolakopoulos Spilios S Pektasides Dimitrios D Thanopoulou Anastasia A
Clinical diabetes : a publication of the American Diabetes Association 20220101 3
Nonalcoholic fatty liver disease (NAFLD) is dramatically increasing in parallel with the pandemic of type 2 diabetes. Here, the authors aimed to assess the performance of the most commonly used noninvasive, blood-based biomarkers for liver fibrosis (FibroTest, NAFLD fibrosis score, BARD score, and FIB-4 Index) in subjects with type 2 diabetes. Liver stiffness measurement was estimated by two-dimensional shear wave elastography. Finally, the authors assessed the diagnostic role of ActiTest and Na ...[more]
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Project description:Aims/hypothesisWe examined the association of prevalent and incident cardiovascular disease (CVD) with chronic liver disease in a cohort of community-based people with type 2 diabetes, in order to clarify the relationship between these two important conditions.Methods1,066 participants with type 2 diabetes aged 60-75 years underwent assessment of a range of liver injury markers (non-specific injury, steatosis, steatohepatitis, fibrosis, portal hypertension). Individuals were followed up for incident cardiovascular events.ResultsAt baseline there were 370/1,033 patients with prevalent CVD, including 317/1,033 with coronary artery disease (CAD). After a mean follow-up of 4.4 years there were 44/663 incident CVD events, including 27/663 CAD events. There were 30/82 CVD-related deaths. Risk of dying from or developing CVD was no higher in participants with steatosis than in those without (HR 0.90; 95% CI 0.40, 2.00; p > 0.05). The only notable relationship was with γ-glutamyltransferase (GGT) (incident CVD: adjusted HR for doubling GGT 1.24 [95% CI 0.97, 1.59] p = 0.086; incident CAD: adjusted HR 1.33 [95% CI 1.00, 1.78] p = 0.053), suggesting that in our study population, chronic liver disease may have little effect on the development of, or mortality from, CVD.Conclusions/interpretationAn independent association between GGT and CVD warrants further exploration as a potentially useful addition to current cardiovascular risk prediction models in diabetes. However, overall findings failed to suggest that there is a clinical or pathophysiological association between chronic liver disease and CVD in elderly people with type 2 diabetes.
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Project description:Fatty liver syndrome is an emerging health problem in the world, due to the high prevalence of obesity and alcohol use disorder. Given the nature of the disease's advancement to cirrhosis and liver-related complications, it is important to assess the severity of the disease, which is typically done via a liver biopsy. Due to the limitations and risks of liver biopsy, the role of noninvasive tests is essential and evolving to stratify the stage of the liver disease, predict the outcomes, and/or monitor the treatment response. This review is focused on noninvasive tests, including the use of serum-based biomarkers, ultrasound-based shear wave elastography, transient elastography, and magnetic resonance elastography in both clinical and research settings.
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Project description:ObjectiveExamine the health and economic impact of extending screening intervals in people with Type 2 diabetes (T2DM) and Type 1 diabetes (T1DM) without diabetes-related retinopathy (DR).SettingDiabetic Eye Screening Wales (DESW).Study designRetrospective observational study with cost-utility analysis (CUA) and Decremental Cost-Effectiveness Ratios (DCER) study.InterventionBiennial screening versus usual care (annual screening).InputsAnonymised data from DESW were linked to primary care data for people with two prior screening events with no DR. Transition probabilities for progression to DR were estimated based on a subset of 26,812 and 1232 people with T2DM and T1DM, respectively. DCER above £20,000 per QALY was considered cost-effective.ResultsThe base case analysis DCER results of £71,243 and £23,446 per QALY for T2DM and T1DM respectively at a 3.5% discount rate and £56,822 and £14,221 respectively when discounted at 1.5%. Diabetes management represented by the mean HbA1c was 7.5% for those with T2DM and 8.7% for T1DM.Sensitivity analysisExtending screening to biennial based on HbA1c, being the strongest predictor of progression of DR, at three levels of HbA1c 6.5%, 8.0% and 9.5% lost one QALY saving the NHS £106,075; £58,653 and £31,626 respectively for T2DM and £94,696, £37,646 and £11,089 respectively for T1DM. In addition, extending screening to biennial based on the duration of diabetes > 6 years for T2DM per QALY lost, saving the NHS £54,106 and for 6-12 and > 12 years for T1DM saving £83,856, £23,446 and £13,340 respectively.ConclusionsBase case and sensitivity analyses indicate biennial screening to be cost-effective for T2DM irrespective of HbA1c and duration of diabetes. However, the uncertainty around the DCER indicates that annual screening should be maintained for those with T1DM especially when the HbA1c exceeds 80 mmol/mol (9.5%) and duration of diabetes is greater than 12 years.
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Project description:Type 2 diabetes (T2D) is a leading cause of death and disability worldwide. It is a chronic metabolic disorder that develops due to an interplay of genetic, lifestyle, and environmental factors. The biological onset of the disease occurs long before clinical symptoms develop, thus the search for early diagnostic and prognostic biomarkers, which could facilitate intervention strategies to prevent or delay disease progression, has increased considerably in recent years. Epigenetic modifications represent important links between genetic, environmental and lifestyle cues and increasing evidence implicate altered epigenetic marks such as DNA methylation, the most characterized and widely studied epigenetic mechanism, in the pathogenesis of T2D. This review provides an update of the current status of DNA methylation as a biomarker for T2D. Four databases, Scopus, Pubmed, Cochrane Central, and Google Scholar were searched for studies investigating DNA methylation in blood. Thirty-seven studies were identified, and are summarized with respect to population characteristics, biological source, and method of DNA methylation quantification (global, candidate gene or genome-wide). We highlight that differential methylation of the TCF7L2, KCNQ1, ABCG1, TXNIP, PHOSPHO1, SREBF1, SLC30A8, and FTO genes in blood are reproducibly associated with T2D in different population groups. These genes should be prioritized and replicated in longitudinal studies across more populations in future studies. Finally, we discuss the limitations faced by DNA methylation studies, which include including interpatient variability, cellular heterogeneity, and lack of accounting for study confounders. These limitations and challenges must be overcome before the implementation of blood-based DNA methylation biomarkers into a clinical setting. We emphasize the need for longitudinal prospective studies to support the robustness of the current findings of this review.
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Project description:In the last 20 years, noninvasive serum biomarkers to identify liver fibrosis in patients with non-alcoholic fatty liver disease (NAFLD) have been developed, validated against liver biopsy (the gold standard for determining the presence of liver fibrosis) and made available for clinicians to use to identify ≥F3 liver fibrosis. The aim of this review is firstly to focus on the current use of widely available biomarkers and their performance for identifying ≥F3. Secondly, we discuss whether noninvasive biomarkers have a role in identifying F2, a stage of fibrosis that is now known to be a risk factor for cirrhosis and overall mortality. We also consider whether machine learning algorithms offer a better alternative for identifying individuals with ≥F2 fibrosis. Thirdly, we summarise the utility of noninvasive serum biomarkers for predicting liver related outcomes (e.g., ascites and hepatocellular carcinoma) and non-liver related outcomes (e.g., cardiovascular-related mortality and extra hepatic cancers). Finally, we examine whether serial measurement of biomarkers can be used to monitor liver disease, and whether the use of noninvasive biomarkers in drug trials for non-alcoholic steatohepatitis can accurately, compared to liver histology, monitor liver fibrosis progression/regression. We conclude by offering our perspective on the future of serum biomarkers for the detection and monitoring of liver fibrosis in NAFLD.
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Project description:BackgroundThe influencing factors of diabetic kidney disease (DKD) in Chinese patients with type 2 diabetes mellitus (T2DM) were explored to develop and validate a DKD diagnostic tool based on nomogram approach for patients with T2DM.MethodsA total of 2,163 in-hospital patients with diabetes diagnosed from March 2015 to March 2017 were enrolled. Specified logistic regression models were used to screen the factors and establish four different diagnostic tools based on nomogram according to the final included variables. Discrimination and calibration were used to assess the performance of screening tools.ResultsAmong the 2,163 participants with diabetes (1,227 men and 949 women), 313 patients (194 men and 120 women) were diagnosed with DKD. Four different screening equations (full model, laboratory-based model 1 [LBM1], laboratory-based model 2 [LBM2], and simplified model) showed good discriminations and calibrations. The C-indexes were 0.8450 (95% confidence interval [CI], 0.8202 to 0.8690) for full model, 0.8149 (95% CI, 0.7892 to 0.8405) for LBM1, 0.8171 (95% CI, 0.7912 to 0.8430) for LBM2, and 0.8083 (95% CI, 0.7824 to 0.8342) for simplified model. According to Hosmer-Lemeshow goodness-of-fit test, good agreement between the predicted and observed DKD events in patients with diabetes was observed for full model (χ2=3.2756, P=0.9159), LBM1 (χ2=7.749, P=0.4584), LBM2 (χ2=10.023, P=0.2634), and simplified model (χ2=12.294, P=0.1387).ConclusionLBM1, LBM2, and simplified model exhibited excellent predictive performance and availability and could be recommended for screening DKD cases among Chinese patients with diabetes.
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