The Finnish Diabetes Risk Score (FINDRISC), incident diabetes and low-grade inflammation

Additive Interaction Between Insulin Resistance, Chronic Low-Grade Inflammation and Vitamin D Deficiency on the Risk of Type 2 Diabetes Mellitus: A Cohort Study

OBJECTIVES

The aim of this study was to explore, on an additive scale, the combined effect of the association between insulin resistance (IR), chronic low-grade inflammation (CLGI) and vitamin D deficiency (VDD) on the risk of type 2 Diabetes Mellitus (T2DM).

METHODS

This is a cohort study, including 1484 non-diabetic subjects, followed for a period of four years. 25 hydroxy-vitamin D (25OHD), hypersensitive C-reactive protein (HsCRP) and triglyceride-glucose index were assessed. Based on VDD and CLGI, the population was subdivided into 4 exposure groups. Analysis was performed both in the case of IR and without IR. Cox proportional regression and additive interaction were applied to explore cumulative effects of exposure.

RESULTS

At follow-up, 162 newly diagnosed cases of T2DM were identified. TYG index (RR = 4.0[2.8-5.6]), HsCRP (RR = 1.6 [1.4-1.7]) and 25OHD (RR = 0.96 [0.39-0.98]) were all significantly associated with the risk of T2DM (p < 0.01). The highest excess risk was recorded in patients cumulating simultaneously IR, CLGI and VDD (RR= 8.4[3.6-19.8], p < 0.0001). The additive interaction was significant, the excess risk linked to the interaction RERI = 10.5[1.43-19.7], the proportion attributable to the combined effect: AP = 0.61[0.37-0.85], and the interaction was synergistic: synergy index: 2.8[1.42-5.69].

CONCLUSION

Baseline levels of TYG index, 25OHD and HsCRP are strongly predictive of future T2DM, and their joint effects are additive and synergistic. Interventional studies are therefore warranted in order to evaluate whether vitamin D supplementation, combined with appropriate anti-inflammatory therapies, is effective as a preventive strategy to reduce the risk of T2DM.

Correlations between Resting Electrocardiogram Findings and Disease Profiles: Insights from the Qatar Biobank Cohort

BACKGROUND

Resting electrocardiogram (ECG) is a valuable non-invasive diagnostic tool used in clinical medicine to assess the electrical activity of the heart while the patient is resting. Abnormalities in ECG may be associated with clinical biomarkers and can predict early stages of diseases. In this study, we evaluated the association between ECG traits, clinical biomarkers, and diseases and developed risk scores to predict the risk of developing coronary artery disease (CAD) in the Qatar Biobank.

METHODS

This study used 12-lead ECG data from 13,827 participants. The ECG traits used for association analysis were RR, PR, QRS, QTc, PW, and JT. Association analysis using regression models was conducted between ECG variables and serum electrolytes, sugars, lipids, blood pressure (BP), blood and inflammatory biomarkers, and diseases (e.g., type 2 diabetes, CAD, and stroke). ECG-based and clinical risk scores were developed, and their performance was assessed to predict CAD. Classical regression and machine-learning models were used for risk score development.

RESULTS

Significant associations were observed with ECG traits. RR showed the largest number of associations: e.g., positive associations with bicarbonate, chloride, HDL-C, and monocytes, and negative associations with glucose, insulin, neutrophil, calcium, and risk of T2D. QRS was positively associated with phosphorus, bicarbonate, and risk of CAD. Elevated QTc was observed in CAD patients, whereas decreased QTc was correlated with decreased levels of calcium and potassium. Risk scores developed using regression models were outperformed by machine-learning models. The area under the receiver operating curve reached 0.84 using a machine-learning model that contains ECG traits, sugars, lipids, serum electrolytes, and cardiovascular disease risk factors. The odds ratio for the top decile of CAD risk score compared to the remaining deciles was 13.99.

CONCLUSIONS

ECG abnormalities were associated with serum electrolytes, sugars, lipids, and blood and inflammatory biomarkers. These abnormalities were also observed in T2D and CAD patients. Risk scores showed great predictive performance in predicting CAD.

Finnish diabetes risk score outperformed triglyceride-glucose index in diabetes risk prediction

Purpose

Triglyceride-Glucose (TyG) index is a surrogate marker of insulin resistance. This study compared the performance of TyG index and the Finnish diabetes risk score (FINDRISC) in diabetes risk prediction.

Methods

This cross-sectional study involved 122 young adults (aged 15-35 years) in Asaba, Delta State, Nigeria. Anthropometric measurements and biochemical analysis were done following standard protocols. Diabetes risk scoring was done using the FINDRISC questionnaire. TyG index was calculated logarithmically. Discrimination between TyG index and FINDRISC was done by plotting receiver operating characteristic (ROC) curves.

Results

High risk participants had significantly (p < 0.001) higher mean values of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) relative to the lower risk categories. Participants in TyG index Quartile 4 had significantly higher mean values of triglyceride (p < 0.001) and fasting plasma glucose (p < 0.05). BMI and triglyceride had the most significant (p < 0.001) positive correlation with FINDRISC and TyG index, respectively. A moderately elevated to high risk (FINDRISC ≥ 12) of developing diabetes was found in 14.8% of the participants; with a female preponderance (20.6%) relative to males (7.4%). More than half of the participants (52.5%) had slightly elevated risk and differences in diabetes risk susceptibility were significant (p < 0.001) across gender. FINDRISC had an AUC value of 0.826 while TyG index had an AUC value of 0.628 for diabetes risk prediction.

Conclusion

FINDRISC had a better performance than TyG index in the prediction of diabetes risk in this population. The use of other TyG-related parameters rather than TyG index is recommended in future studies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01252-y.

Association between the Finnish Diabetes Risk Score and cancer in middle-aged and older adults: Involvement of inflammation

BACKGROUND

Diabetes is associated with increased risk of common cancers. However, evidence of cancer risk in individuals with different diabetes risk is still scarce, and the underlying mechanism remains unknown. Therefore, we aimed to evaluate the relationship between the Finnish Diabetes Risk Score (FINDRISC) and risks of cancer incidence and mortality in a prospective study, and to explore whether low-grade inflammation partially mediated the association.

METHODS

A total of 330,384 participants aged 37 to 73 at baseline from the UK Biobank database was included in this study. The Cox proportional hazards model was used to examine the relationship of the FINDRISC and low-grade inflammation with risks of cancer incidence and mortality. Then, we estimated the contribution of higher FINDRISC to risks of overall and site-specific cancers. In addition, the role of low-grade inflammation in the association between FINDRISC and cancer risks was investigated through mediation analysis.

RESULTS

The increased FINDRISC was dose-dependently associated with higher incidence and mortality risks of overall cancer and an overwhelming majority of site-specific cancers. The higher FINDRISC was a strong contributor to incidence of eighteen site-specific cancers and mortality of fourteen site-specific cancers, with a population-attributable risk of 8.1 %-39.1 %, 14.2 %-39.7 %, respectively. Additionally, low-grade inflammation mainly mediated the association between the FINDRISC and risks of incidence and mortality of overall cancer, colorectal cancer, etc. CONCLUSIONS: Our findings highlighted the higher FINDRISC as critical risk factors of cancer incidence and mortality, partially mediated by low-grade inflammation. Individuals with increased risk of diabetes are also needed to be concerned about cancer prevention.

Predicting the Risk of Type 2 Diabetes Mellitus with the New Chinese Diabetes Risk Score in a Cohort Study

Objectives: The New Chinese Diabetes Risk Score (NCDRS) is a noninvasive tool to assess the risk of type 2 diabetes mellitus (T2DM) in the Chinese population. Our study aimed to evaluate the performance of the NCDRS in predicting T2DM risk with a large cohort. Methods: The NCDRS was calculated, and participants were categorized into groups by optimal cutoff or quartiles. Hazard ratios (HRs) and 95% confidential intervals (CIs) in Cox proportional hazards models were used to estimate the association between the baseline NCDRS and the risk of T2DM. The performance of the NCDRS was assessed by the area under the curve (AUC). Results: The T2DM risk was significantly increased in participants with NCDRS ≥25 (HR = 2.12, 95% CI 1.88-2.39) compared with NCDRS <25 after adjusting for potential confounders. T2DM risk also showed a significant increasing trend from the lowest to the highest quartile of NCDRS. The AUC was 0.777 (95% CI 0.640-0.786) with a cutoff of 25.50. Conclusion: The NCDRS had a significant positive association with T2DM risk, and the NCDRS is valid for T2DM screening in China.

Phenolic compounds can induce systemic and central immunomodulation, which result in a neuroprotective effect

Inflammation may negatively impact health, particularly that of the central nervous system. Phenolic compounds are bioactive molecules present in fruits and vegetables with potential anti-inflammatory effects. The purpose of the present work is to review the immunomodulatory bioactivities of phenolic compounds in the periphery and in the central nervous system. Results show that various types of phenolics are able to counter diet- or pathogen-induced systemic inflammation (among others) in various models. In vitro data show significant effects of flavonoids and phenolic acids in particular; similar bioactivities were reported in vivo, when administering them as pure compounds or from fruit and vegetable extracts that contain them. In the central nervous system, phenolics counter chronic inflammation and aggressive acute inflammatory processes, such as ischemic events, when administered preemptively and even therapeutically. We therefore conclude that the immunomodulatory potential of phenolic compounds can maintain an adequate immune response; their regular consumption should therefore be prioritized in order to maintain health. PRACTICAL APPLICATIONS: The immune response must be carefully regulated in order to avoid its deleterious effects. The present work highlights how phenolic compounds, dietary components ubiquitous in everyday diet, are able to maintain it within an adequate range. As humans are exposed to more proinflammatory stimuli (inadequate dietary pattern, mental stress, environmental pollution, chronic diseases, etc.), it becomes necessary to counter them, and consuming adequate amounts of foods that contain compounds with this ability is a rather simple strategy. Thus, the present work highlights how fruits and vegetables can help to maintain an adequate immune response that can preserve systemic health and that of the central nervous system. Furthermore, specific compounds contained in them can also be ideal candidates for additional in-depth studies, which can potentially lead to the development of potent, targeted, and safe anti-inflammatory molecules.

The FINDRISC scale as a risk assessment tool for liver fibrosis in patients with nonalcoholic fatty liver disease

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in the world, which includes changes from hepatic steatosis and nonalcoholic steatohepatitis to fibrosis and cirrhosis. Attempts to find noninvasive markers of liver fibrosis have led to a variety of scales, diagnostic algorithms, and imaging techniques. Individual studies have analyzed the relationship between the FINDRISC scale and hepatic steatosis and concluded that this questionnaire can be used as part of population screening to identify individuals at risk for hepatic steatosis. However, our review of the literature did not reveal any clinical studies on the use and effectiveness of the FINDRISC in liver fibrosis screening.

AIM: To evaluate diagnostic value of FINDRISC for liver fibrosis detection.

MATERIALS AND METHODS: The study enrolled patients aged 40–60 years from unorganized outpatient population. The sample of patients was formed randomly according to the inclusion and noninclusion criteria. All patients were assessed with standard anthropometric parameters. The FINDRISC questionnaire was used. All patients underwent transabdominal ultrasound examination of the liver and transient liver elastometry. The degree of steatosis was evaluated using Hamaguchi ultrasound scale.

 RESULTS: The study included 100 patients. An increased risk of type 2 DM (≥7 points) was detected in 68% of patients using the FINDRISC scale. Liver steatosis was diagnosed in 41% of patients. Median values of hepatic elastic modulus by transient elastometry were 4.50 (4.00; 5.25) kPa. At the same time, liver elasticity modulus values ≥5.9 kPa were registered in 11 (11.0%) patients. When analyzing the array of sensitivity and specificity values using the ROC-curve, it was found that for the FINDRISC scale the maximum LR+ and the minimum LRvalues were observed when the number of points on the indicated scale exceeded 10. At this cutoff, the FINDRISC scale had a sensitivity of 81.8% and specificity of 61.8% for detecting liver fibrosis (liver modulus of elasticity ≥5.9 kPa). The scale was of good diagnostic value (AUC 0.699; 95% CI 0.530–0.815).

CONCLUSION: In an unorganized sample of patients aged 40–60 years the FINDRISC can serve as a diagnostic tool for liver fibrosis and steatosis. Sum of FINDRISC scores >10 allowed to diagnose liver fibrosis (liver elastic modulus ≥5.9kPa) with sensitivity 81.8% and specificity 61.8%. The probability of absence of hepatic fibrosis with FINDRISC scale values <10 was 96.5%.