In this retrospective cohort study, we found that low HDL-C was independently related to DM risk after adjusting for gender, age, ethanol consumption, smoking status, regular exerciser, SBP, DBP, BMI, WC, TC, TG, HbA1c, FPG. Further analysis showed a non-linear relationship between HDL-C level and DM risk (Log-likelihood ratio test P = 0.005). This result suggested that the HDL-C level was negatively associated with DM risk when the HDL-C level was ≤ 1.72mmol/L(HR: 0.36, 95%CI: 0.21 to 0.59, P < 0.0001). However, their relationship tended to be saturated when HDL-C was >1.72mmol/L. (HR: 2.90, 95%CI: 0.96 to 8.75, P = 0.0594). It could be better understood the trend of HDL-C and diabetes incidence in different populations by analysis of sub-groups. A stronger association between HDL-C and DM risk was discovered in the participants with ex-smoker, current-smoker and hypertension(SBP≥140mmHg or DBP≥90mmHg). In contrast, there was a weaker association in the people with never-smoker, SBP <140mmHg, and DBP<90mmHg.
Cardiovascular disease is a significant cause of morbidity and mortality in type 2 diabetes mellitus patients[8], and HDL-C plays an essential role in cardiovascular disease and diabetes. It was reported that low mean and high variability of HDL-C were independent predictors of diabetes with an additive effect[21]. Our study found that low HDL-C is an independent risk of DM, which was consistent with previous studies[22]. HDL-C affected the incident of diabetes through different mechanisms. Studies found that HDL also has anti-inflammatory and antioxidant activities[23]. HDL-C can inhibit apoptosis of isletβcell induced by oxidative stress [11]. Besides, HDL-C improves cell sensitivity to insulin and glucose uptake in skeletal muscle cells by activating Adenosine 5 '-monophosphate (AMP)-activated protein kinase (AMPK) pathway[24]. Moreover, HDL-C can promote insulin secretion by increasing the outflow of cholesterol from pancreatic B cells[25]. These mechanisms can provide a reasonable explanation for reducing HDL-C and increasing the DM risk.
In the past, it was generally believed that higher HDL-C was more beneficial. However, lin et al. [12] found that high serum HDL-C levels increase the risk of DM after adjusting for the demographic and clinical covariates in a retrospective study of 9764 Chinese. Also, Chen et al.[13] found high serum HDL-C levels increase the risk of DM after adjusting for potential confounders in a large retrospective cohort study. A population-based study in 2016 showed that plasma HDL-C levels were significantly increased by carriers of scavenger receptor BI P376L mutations have HDL-C levels, but the risk of coronary heart disease was increased[26]. Animal studies showed that SR-BI knockout mice increased HDL-C levels considerably, but the probability of atherosclerosis also increased[27]. A population-based study in 2016 showed that carriers of scavenger receptor BI P376L mutations have significantly increased plasma HDL-C levels, but the risk of coronary heart disease is increased[27]. Animal studies have also shown that SR-BI knockout mice have increased HDL-C levels considerably, but the probability of atherosclerosis has increased[28]. To clarify the association between HDL-C and the risk of diabetes, we did a smooth curve fitting. The results showed that when HDL-C≤1.72mmol/L, the risk of diabetes is inversely proportional to HDL-C. When HDL-C>1.72mmol/L, the risk of diabetes is directly proportional to HDL-C, but it is not statistically significant (HR: 2.90, 95%CI: 0.96 to 8.75, P = 0.0594). It suggests that HDL-C is not as high as possible in the occurrence of diabetes.
The current study has several following strengths. (1) We processed and further explored the non-linear relationship between HDL-C and diabetes in the present study; (2) Strict statistical adjustments were used to minimize residual confounding factors; (3) In order to decrease the contingency of data analysis and increase the reliability of the results, we divided HDL-C into continuous and categorical variables; (4) We used a GAM model and a smooth curve fitting (penalty curve method) to explore the non-linear relationship; therefore, our analysis has greater clinical value, which has not been explored in previous studies.
The current study has several following limitations. Firstly, the retrospective cohort study was based on the personal medical records of Murakami Memorial Hospital in Japan, and Takuro Okamura et al. screened the data. We could not conclude that our conclusion could be generalized to other races, areas, and some unique population because the participants were all from Japan. Similarly, we could not adjust some variables not included in the data because our study was based on the original data's reanalysis. Secondly, the incidence of diabetes may be underestimated because the original research lacked a 2 hours oral glucose tolerance test to diagnose DM. However, it was not feasible to perform 2 hours oral glucose tolerance tests for all participants due to a lack of financial and logistical support. Thirdly, only baseline HDL-C was measured in the original study, and the original study did not involve changes in HDL-C over time. Finally, our research could not exclude some residual or unmeasured confounding factors, such as dietary factors, which may bias the results. Further investigations are needed for longer-term follow-up and more population studies.