Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis

BACKGROUND

Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D).

METHODS

We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies.

RESULTS

Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort.

CONCLUSIONS

Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes: A Systematic Review and Meta-analysis

Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Results Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

High Plasma Levels of Fortilin in Patients with Coronary Artery Disease

Excessive apoptosis is known to be a common feature of atherosclerotic lesions. Fortilin is recognized to have potent antiapoptotic properties. An increased fortilin expression was demonstrated in atherosclerotic lesions, and fortilin knockout mice developed less atherosclerosis. However, no study has reported blood fortilin levels in patients with coronary artery disease (CAD). We investigated plasma fortilin levels in 384 patients undergoing coronary angiography. CAD severity was evaluated as the numbers of stenotic vessels and segments. CAD was found in 208 patients (one-vessel (1VD), n = 86; two-vessel (2VD), n = 68; and three-vessel disease (3VD), n = 54). Plasma C-reactive protein (CRP) levels were higher in patients with CAD than without CAD (median 0.60 vs. 0.45 mg/L, p < 0.01). Notably, fortilin levels were higher in patients with CAD than without CAD (75.1 vs. 69.7 pg/mL, p < 0.02). A stepwise increase in fortilin was found according to the number of stenotic vessels: 69.7 in CAD(−), 71.1 in 1VD, 75.7 in 2VD, and 84.7 pg/mL in 3VD (p < 0.01). Fortilin levels also correlated with the number of stenotic segments (r = 0.16) and CRP levels (r = 0.24) (p < 0.01). In a multivariate analysis, fortilin levels were independently associated with 3VD. The odds ratio for 3VD was 1.93 (95%CI = 1.01−3.71) for a high fortilin level (>70.0 pg/mL). Thus, plasma fortilin levels in patients with CAD, especially those with 3VD, were found to be high and to be associated with the severity of CAD.

Nomogram Based on Risk Factors for Type 2 Diabetes Mellitus Patients with Coronary Heart Disease

INTRODUCTION

This study aimed to study risk factors for coronary heart disease (CHD) in type 2 diabetes mellitus (T2DM) patients and establish a clinical prediction model.

RESEARCH DESIGN AND METHODS

A total of 3402 T2DM patients were diagnosed by clinical doctors and recorded in the electronic medical record system (EMRS) of six Community Health Center Hospitals from 2015 to 2017, including the communities of Huamu, Jinyang, Yinhang, Siping, Sanlin and Daqiao. From September 2018 to September 2019, 3361 patients (41 patients were missing) were investigated using a questionnaire, physical examination, and biochemical index test. After excluding the uncompleted data, 3214 participants were included in the study and randomly divided into a training set (n = 2252) and a validation set (n = 962) at a ratio of 3:1. Through lead absolute shrinkage and selection operator (LASSO) regression analysis and logistic regression analysis of the training set, risk factors were determined and included in a nomogram. The C-index, receiver operating characteristic (ROC) curve, calibration plot and decision curve analysis (DCA) were used to validate the distinction, calibration and clinical practicality of the model.

RESULTS

Age, T2DM duration, hypertension (HTN), hyperuricaemia (HUA), body mass index (BMI), glycosylated haemoglobin A1c (HbA1c), high-density lipoprotein (HDL-C) and low-density lipoprotein (LDL-C) were significant factors in this study. The C-index was 0.750 (0.724-0.776) based on the training set and 0.767 (0.726-0.808) based on the validation set. Through ROC analysis, the set area was 0.750 for the training set and 0.755 for the validation set. The calibration test indicated that the S:P of the prediction model was 0.982 in the training set and 0.499 in the validation set. The decision curve analysis showed that the threshold probability of the model was 16-69% in the training set and 16-73% in the validation set.

CONCLUSION

Based on community surveys and data analysis, a prediction model of CHD in T2DM patients was established.

Non-HDL-cholesterol to HDL-cholesterol ratio as an independent risk factor for the development of chronic kidney disease

BACKGROUND AND AIMS

Dyslipidemia contributes to the development and progression of renal disease. The objective of this study was to investigate whether an elevated non-HDL-cholesterol to HDL-cholesterol ratio (NonHDLc/HDLc) predicts new-onset chronic kidney disease (CKD).

METHODS AND RESULTS

We followed 1891 Chinese adults with normal or near-normal kidney function at baseline who participated in an annual health checkup program for the occurrence of new-onset CKD [defined as an estimated glomerular filtration rate (eGFR) of <60 mL/min/1.73 m(2) (low eGFR) and/or proteinuria (defined as urinary protein ≥1 + on dipstick testing)] or low eGFR. Cox proportional hazards models were used to examine the independent relationship between the plasma NonHDLc/HDLc ratio and new-onset CKD. During a median follow-up period of 2.8 years, 3% (n = 57) of participants developed new-onset CKD. Compared with patients in the lowest tertile, patients with NonHDLc/HDLc ratios in the highest tertile had a 1.45-fold higher risk of new-onset CKD (hazard ratio [HR], 2.45; 95% confidence interval [95% CI], 1.07 to 5.61; P = 0.035) after adjustment for potential confounders. There was a marginally significant association with low eGFR (tertile 3 versus tertile 1: HR, 2.94; 95% CI, 0.98 to 8.82; P = 0.054).

CONCLUSIONS

NonHDLc/HDLc ratio is an independent risk factor for the development of CKD. Assessment of NonHDLc/HDLc ratio may help identify high risk groups with chronic kidney disease.

Non-high-density lipoprotein cholesterol and other risk factors of mild cognitive impairment among Chinese type 2 diabetic patients

OBJECTIVE

To identify some risk factors of MCI among patients with type 2 diabetes(T2DM) and to find if there is any correlation between these factors and the degree of cognitive decline.

METHODS

A total of 155 patients with T2DM referred to the Department of Endocrinology at First Hospital of Qinhuangdao were enrolled. To assess MCI the Montreal Cognitive Assessment (MoCA) scoring system was used. There were 66 patients with MCI and 89 patients without MCI (control). HbAlc, blood lipid, liver and renal functions were measured in all subjects.

RESULTS

Compared with the control group, type 2 diabetic patients with MCI had a longer duration of diabetes; higher non-high-density lipoprotein cholesterol (non-HDL-C), triglycerides, total cholesterol, HbA1c, and BMI; and lower high-density lipoprotein cholesterol (HDL-C) (P<0.05). The rates of patients with a history of habitual light-to-moderate alcohol consumption, a high proportion of Mediterranean-type diet, and regular physical activity were lower; and the rate of current smoking was higher in type 2 diabetic patients with MCI than the control group (P<0.05). Among patients with MCI, the results indicated that MoCA score was negatively correlated with non-HDL-C (r=-0.761 P<0.001).

CONCLUSIONS

Our results suggest that non-HDL-C can act as a readily available method for estimating risk of MCI in Chinese type 2 diabetic patient in routine clinical practice. Good lifestyle likely reduces MCI risk in diabetic patients.