Investigation of Causal Effect of Type 2 Diabetes Mellitus on Lung Cancer: A Mendelian Randomization Study

The association between metabolic syndrome and lung cancer risk: a Mendelian randomization study

Metabolic syndrome (MetS) is closely linked to cancer development, with emerging evidence suggesting its association with pulmonary carcinoma. However, causal relationships remain unclear due to observational study limitations. Employing Mendelian randomization, we investigated the causal link between MetS and lung cancer (LC) susceptibility. The data utilized in this study were obtained from the publicly available genetic variation summary database. The causal relationship was assessed using the inverse variance weighting method (IVW), weighted median method, and MR-Egger regression. A sensitivity analysis was carried out to confirm the robustness of the findings. Furthermore, risk factor analyses were conducted to explore potential mediators. Utilizing various analyses, MetS demonstrated a significant positive association with LC (OR, 1.22; 95% CI, 1.09-1.37, p = 7.57 × 10- 4), lung squamous cell carcinoma (LUSC) (OR, 1.47; 95%, 1.23-1.75, p = 2.22 × 10- 5), and small cell lung cancer (SCLC) (OR, 1.76; 95% CI, 1.37-2.26, p = 8.20 × 10- 6) but not lung adenocarcinoma (LUAD) (OR, 1.08; 95% CI, 0.94-1.24, p = 0.28). Risk factor analyses indicated that smoking, alcohol, body mass index, education, and type 2 diabetes might mediate the association. This study genetically validates and reinforces the evidence of MetS increasing the incidence of LC, including both LUSC) and SCLC, especially among individuals with abdominal obesity. It provides valuable insights for the development of lung cancer prevention strategies and directions for future research.

Glycemic status, insulin resistance, and mortality from lung cancer among individuals with and without diabetes

BACKGROUND

The effects of glycemic status and insulin resistance on lung cancer remain unclear. We investigated the associations between both glycemic status and insulin resistance, and lung cancer mortality, in a young and middle-aged population with and without diabetes.

METHODS

This cohort study involved individuals who participated in routine health examinations. Lung cancer mortality was identified using national death records. Cox proportional hazards models were used to calculate hazard ratios (HRs) with 95% CIs for lung cancer mortality risk.

RESULTS

Among 666,888 individuals (mean age 39.9 ± 10.9 years) followed for 8.3 years (interquartile range, 4.6-12.7), 602 lung cancer deaths occurred. Among individuals without diabetes, the multivariable-adjusted HRs (95% CI) for lung cancer mortality comparing hemoglobin A1c categories (5.7-5.9, 6.0-6.4, and ≥ 6.5% or 39-41, 42-46, and ≥ 48 mmol/mol, respectively) with the reference (< 5.7% or < 39 mmol/mol) were 1.39 (1.13-1.71), 1.72 (1.33-2.20), and 2.22 (1.56-3.17), respectively. Lung cancer mortality was associated with fasting blood glucose categories in a dose-response manner (P for trend = 0.001) and with previously diagnosed diabetes. Insulin resistance (HOMA-IR ≥ 2.5) in individuals without diabetes was also associated with lung cancer mortality (multivariable-adjusted HR, 1.41; 95% CI, 1.13-1.75). These associations remained after adjusting for changing status in glucose, hemoglobin A1c, insulin resistance, smoking status, and other confounders during follow-up as time-varying covariates.

CONCLUSIONS

Glycemic status within both diabetes and prediabetes ranges and insulin resistance were independently associated with an increased risk of lung cancer mortality.

Clinical significance of tumor abnormal protein in patients with type 2 diabetes complicated with lung adenocarcinoma in situ

BACKGROUND

To investigate the application value of tumor abnormal protein in patients with type 2 diabetes mellitus complicated with lung adenocarcinoma in situ.

MATERIALS AND METHODS

A total of 140 patients having type 2 diabetes mellitus complicated with lung adenocarcinoma in situ (Group A), 160 patients with type 2 diabetes mellitus (Group B), and 120 healthy controls (Group C) were enrolled in the Department of Thoracic Surgery of the First Affiliated Hospital of Soochow University from November 2021 to December 2022.

RESULTS

The total cholesterol level was higher in Group A than in Group B (p < 0.05) and Group C (p < 0.01), and it was higher in Group B than in Group C (p < 0.01). The comparison results of cholesterol level were similar to those of tumor abnormal protein, low-density lipoprotein cholesterol, and glycosylated hemoglobin among the three groups. The triglyceride level was higher in Group A than in Group B and Group C (both p < 0.01). Group A had a higher level of high-density lipoprotein cholesterol than Group C (p < 0.01). The fasting plasma glucose level was higher in Group A than in Group B and Group C (both, p < 0.01). These findings indicated that tumor abnormal protein, glycosylated hemoglobin, high-density lipoprotein cholesterol, and fasting plasma glucose were independent factors for patients having type 2 diabetes mellitus complicated with lung adenocarcinoma in situ.

CONCLUSION

Therefore, detecting tumor abnormal protein levels may help diagnose lung adenocarcinoma in situ in patients with type 2 diabetes mellitus.

Association Between Baseline C-Reactive Protein and the Risk of Lung Cancer: A Prospective Population-Based Cohort Study

C-reactive protein (CRP), a systemic marker of diagnosing chronic inflammation, has been associated with the incidence of multiple types of cancer. However, little is known about the impact of CRP on lung cancer incidence in Chinese population. A total of 97,950 participants without cancer at baseline (2006-2007) of the Kailuan Cohort Study were followed up. The concentration of plasma high-sensitivity CRP (hsCRP) was tested for all participants at baseline interview. Multivariable Cox proportional hazards regression models were used to assess the association between levels of hsCRP and incident lung cancer. During 8.7-year follow-up, 890 incident lung cancer cases occurred and were divided into three groups according to the level of hsCRP. The risk of incident lung cancer was significantly increased with elevated levels of hsCRP [HRMedium/Low, 1.21; 95% confidence interval (CI), 1.03-1.42; HRHigh/Low, 1.42, 95% CI, 1.20-1.68; Ptrend < 0.001], compared with the low group after adjusting confounders. Moreover, after stratifying by BMI, the significantly positive associations between the hsCRP level and the risk of lung cancer were found among those with BMI < 24 (HRHigh/Low, 1.51; 95% CI, 1.18-1.94; Ptrend = 0.001) and BMI = 24-28 (HRHigh/Low, 1.47; 95% CI, 1.13-1.92; Ptrend = 0.003), but not among those with BMI ≥ 28 (HRHigh/Low, 1.01; 95% CI, 0.64-1.57; Ptrend = 0.991). There was an antagonistic interaction between hsCRP levels and BMI that contributed to development of lung cancer (Pinteraction = 0.049). In conclusion, these findings indicate a dose-dependent relationship between hsCRP and lung cancer risk among Chinese population, especially in nonobese participants, suggesting that CRP could serve as a potential biomarker for prediction of lung cancer risk and identification of high-risk population.

PREVENTION RELEVANCE

In this prospective population-based cohort study, we found an association between higher plasma hsCRP and an increased risk of developing lung cancer, with stronger associations observed among nonobese participants.

High-Resolution Computer Tomography Image Features of Lungs for Patients with Type 2 Diabetes under the Faster-Region Recurrent Convolutional Neural Network Algorithm

The objective of this study was to adopt the high-resolution computed tomography (HRCT) technology based on the faster-region recurrent convolutional neural network (Faster-RCNN) algorithm to evaluate the lung infection in patients with type 2 diabetes, so as to analyze the application value of imaging features in the assessment of pulmonary disease in type 2 diabetes. In this study, 176 patients with type 2 diabetes were selected as the research objects, and they were divided into different groups based on gender, course of disease, age, glycosylated hemoglobin level (HbA1c), 2 h C peptide (2 h C-P) after meal, fasting C peptide (FC-P), and complications. The research objects were performed with HRCT scan, and the Faster-RCNN algorithm model was built to obtain the imaging features. The relationships between HRCT imaging features and 2 h C-P, FC-P, HbA1c, gender, course of disease, age, and complications were analyzed comprehensively. The results showed that there were no significant differences in HRCT scores between male and female patients, patients of various ages, and patients with different HbA1c contents (P > 0.05). As the course of disease and complications increased, HRCT scores of patients increased obviously (P < 0.05). The HRCT score decreased dramatically with the increase in the contents of 2 h C-P and FC-P after the meal (P < 0.05). In addition, the results of the Spearman rank correlation analysis showed that the course of disease and complications were positively correlated with the HRCT scores, while the 2 h C-P and FC-P levels after meal were negatively correlated with the HRCT scores. The receiver operating curve (ROC) showed that the accuracy, specificity, and sensitivity of HRCT imaging based on Faster-RCNN algorithm were 90.12%, 90.43%, and 83.64%, respectively, in diagnosing lung infection of patients with type 2 diabetes. In summary, the HRCT imaging features based on the Faster-RCNN algorithm can provide effective reference information for the diagnosis and condition assessment of lung infection in patients with type 2 diabetes.