Evaluation of the value of conventional and unconventional lipid parameters for predicting the risk of diabetes in a non-diabetic population

The high prevalence of diabetes and its extensive complications have created a huge disease burden for mankind, which is one of the leading causes of death and disability worldwide [1‐3]. Diabetes is known to be associated with a series of interrelated abnormalities of plasma lipids and lipoproteins. Diabetic individuals generally exhibit a pattern of atherogenic risk factors compared with individuals without diabetes [4]. Among them, metabolic disturbances of triglyceride-rich lipoproteins are thought to be key to the pathophysiology of this lipids-induced atherosclerosis, including increased hepatic secretion of VLDL and impaired clearance of VLDL and gut-synthesized chylomicrons [4‐7]. Clinically, the main manifestations in conventional lipids are decreased HDL-C levels and increased TG levels [4, 8], while that in unconventional lipids are elevated levels of RC, TC/HDL ratio, non-HDL-C, TG/HDL-C ratio, non-HDL/HDL-C ratio, and LDL/HDL-C ratio [9‐12]. These dyslipidemia characteristics are associated with an increased risk of cardiovascular disease [13‐15], which is the leading cause of death in patients with type 2 diabetes [16]. Therefore, early identification of the above-mentioned diabetic dyslipidemia manifestations can effectively prevent and intervene the risk of diabetes, which is all-important for reducing the incidence of diabetes and diabetes-related mortality. In recent years, a series of studies have been carried out on the relationship between conventional and unconventional lipid parameters and the risk of diabetes [8‐12, 17, 18]; on the whole, unconventional lipid parameters appear to have good application value, and they reveal excellent performance in the assessment and prediction of diabetes risk. However, comparative studies on lipid parameters for predicting future diabetes risk are still relatively limited [10, 18, 19], and the value of conventional and unconventional lipid parameters in predicting future diabetes has not been evaluated. To address this question, in the current study, we investigated the independent association and predictive value of conventional and unconventional lipid parameters (addition the RC/HDL-C ratio on the basis of previous studies) with the future risk of diabetes based on NAGALA large longitudinal cohort study data.

There were four main findings in this longitudinal cohort study: (1) In the baseline non-diabetic population, only TG and HDL-C among the conventional lipid parameters were associated with future diabetes risk, while all the unconventional lipid parameters except non-HDL-C were significantly associated with the future risk of diabetes. (2) Compared with other conventional and unconventional lipid parameters, the RC/HDL-C ratio can better reflect the future diabetes risk. (3) Compared with conventional lipid parameters, unconventional lipid parameters were of higher value for predicting the diabetes risk in the future. (4) RC/HDL-C ratio had the best predictive value for the short-term diabetes risk, non-HDL/HDL-C ratio and LDL/HDL-C ratio for the short-to medium-term diabetes risk, while RC, non-HDL/HDL-C ratio, and TC/HDL-C ratio for the mid-to long-term and long-term diabetes risk.

Diabetes mellitus, one of the most rapidly growing chronic non-communicable diseases in this century, is a complex metabolic disease that presents with different subphenotypes according to various etiologies [35, 36]. The most common one is the metabolic syndrome-related phenotype, which is mainly characterized by dyslipidemia and obesity. Effective management of these complex lipid metabolic disorders and obesity is an important part of comprehensive diabetes prevention, treatment, and care, and can reduce the risk of cardiovascular morbidity and mortality [37]. The relationship between conventional lipid parameters HDL-C, TC, LDL-C, and TG and diabetes has been widely studied in the past, in which high concentrations of TG and low concentrations of HDL-C significantly increased diabetes risk has become the consensus of almost every scholar in the field of metabolism [37‐39], but there is still some debate about the direct relationship between LDL-C, TC, and diabetes [10, 40, 41]. However, it should be mentioned that in terms of treatment, reducing LDL-C levels is still the primary task of lipid management in patients with diabetes [37], and multifaceted treatment strategies for hyperlipidemia, hyperglycemia, and hypertension can further improve the health status of diabetic patients [42]. In the current study, we also observed, from the comparison of baseline information, that compared with those who did not develop diabetes during the follow-up period, people with new-onset diabetes showed significant differences in all conventional and unconventional lipid parameters except non-HDL-C, LDL-C, and TC at baseline. Moreover, in regression analysis, when only adjusting for lifestyle and demographic data, all conventional lipid parameters were associated with future diabetes risk. In further covariation-adjusted models, the associations of LDL-C and TC with diabetes risk disappeared. A similar situation was also described in the work of Khaloo et al. [10]. This phenomenon suggested that LDL-C and TC may play a certain role in the risk of diabetes in the future, but this role may be weak and unstable compared with other lipid parameters.

Unconventional lipid parameters such as lipid ratio, RC, and non-HDL-C are hot topics in recent years. These lipid parameters are calculated by conventional lipid parameters according to certain formulas or direct division [10‐12, 23‐25]. At present, a series of epidemiological studies have been carried out using unconventional lipid parameters as novel markers in the endocrine system, cardio-cerebrovascular system, digestive system, respiratory system, and urinary system diseases [8‐12, 43‐48]. In general, unconventional lipid parameters improved the ability of conventional lipid parameters to assess and identify the risk of most diseases.

The relationship between conventional and unconventional lipid parameters and diabetes has been reported in many studies [8‐12, 17, 18], but comparative studies on lipid parameters for predicting future diabetes are extremely limited. There were still some differences in the results of several longitudinal studies that have been published. Hadaegh et al. conducted the first comparative study in Iran in 2010 to evaluate the utility of conventional and unconventional lipid parameters to predict future diabetes risk [19]. They measured/calculated TG/HDL-C ratios, non-HDL-C, HDL-C, TC, and TG in 5,201 baseline diabetes-free subjects. After a median follow-up of 5.6 years, they found that the TG/HDL-C ratio was a better indicator of future diabetes risk in women, while the TC/HDL-C ratio was a better indicator of future diabetes risk in men. Subsequently, in 2011, South Korea’s Seo et al. conducted another longitudinal study of 5577 subjects without diabetes [18]. During the 4-year follow-up, they found that TC/HDL-C ratio had the best performance in reflecting future diabetes risk. It should be noted that in the study of Professor Hadaegh and Professor Seo [18, 19], despite their follow-up, the time factor was not taken into account in the final data analysis. The results of their final analysis were based on multivariate Logistic regression analysis, which may be biased. Recently, a longitudinal study by Khaloo et al. involving 5474 non-diabetic subjects showed that Ln-TG/HDL-C ratio was a better lipid parameter to predict future diabetes risk [10]. Summing up the results of several similar studies above, among multiple lipid parameters, the TC/HDL-C ratio and TG/HDL-C ratio may be good parameters for predicting future diabetes. In our current study, we included more unconventional lipid parameters in a cohort of 15,464 participants with baseline normoglycemia. During a follow-up of up to 13 years, we further confirmed their findings: both TC/HDL-C ratio and TG/HDL-C ratio were good lipid parameters for predicting future diabetes risk. On this basis, our results added more evidence, and we found that among all lipid parameters, the RC/HDL-C ratio was the best parameter to reflect the risk of developing diabetes in the future. This finding has not been reported in previous similar studies, and so far as we know, this is the first study to evaluate the relationship between diabetes and RC/HDL-C ratio.

Several studies have been reported on the thresholds of conventional versus unconventional lipid parameters for the diagnosis/prediction of diabetes [9, 18, 49, 50]. In summary, the main differences between the results of the threshold analysis of lipid parameters in the published studies and the analysis in our current study are in the TG and the consideration of time variables. Compared with other threshold analysis studies, our current study fully considered time-dependent variables and assessed baseline lipid parameters as predictors of future diabetes risk, while the existing similar studies focused more on the present [9, 18, 49, 50]. Furthermore, in the current study, we also evaluated the predictive value of conventional and unconventional lipid parameters for predicting short -, medium-and long-term diabetes risk. Overall, the RC/HDL-C ratio had the best predictive value for predicting the short-term diabetes risk, non-HDL/HDL-C ratio and LDL/HDL-C ratio for the short-to medium-term diabetes risk, while RC, non-HDL/HDL-C ratio, and TC/HDL-C ratio for the mid-to long-term and long-term diabetes risk.

Conventional methods for measuring lipids and lipoproteins include chemical methods and enzymatic methods. Generally speaking, chemical methods are relatively time-consuming, so they are usually only used for calibration in the clinic, while the enzyme method has been used as the most commonly used analysis method in automatic biochemical analytical instruments due to its relative simplicity and accuracy [51, 52]. Although the conventional lipid measurement methods have excellent diagnostic performance, they still require expensive instruments, trained operators, and dedicated laboratories. Therefore, conventional lipid measurement methods may not be optimal for primary health care institutions and people with limited mobility [53]. Recently, biosensors for measuring lipids and lipoproteins have been developed for preventive and therapeutic monitoring of chronic diseases at the proof-of-concept stage, allowing simultaneous measurement of multiple lipid parameters in a home setting by a user with minimal training [54‐56]. Compared with conventional methods, biosensors for lipids and lipoproteins are more convenient, rapid, and easy to operate. In addition, recent studies have shown that new biomaterials (such as nanomaterials) have better biocompatibility, stability, and unique physical, electronic and chemical properties [52, 57, 58]. These new materials and techniques may have great potential for early screening of people at high risk of diabetes by testing lipid parameters [59].

There are many mechanisms by which lipid parameters are associated with diabetes. From a clinical point of view, the atherogenic effect of lipid parameters and IR caused by lipid parameters may be the main factors associated with diabetes [4, 60‐62]. Among them, the vasoactive hormone pathway including the renin–angiotensin–aldosterone system (RAAS) seems to play an important role in this process [63]. The RAAS is known to be an important system in the body for maintaining plasma sodium concentration, arterial blood pressure, and extracellular volume [64]. The imbalance between renin and angiotensin II can lead to a large number of chronic and acute diseases [64, 65], and plaque formation induced by angiotensin II in the early stage is one of the most important effects of RAAS on atherosclerosis [66], while under pathological conditions, RAAS also contributes directly or indirectly to the development of atherosclerosis and its various complications through its effects on other systems [67]. In addition to this, when renin and angiotensin II are imbalanced, the RAAS detrimental axis will also increase the release of inflammatory cytokines, and generate and increase oxidative stress; these pathological changes will further promote the formation of atherosclerosis, exacerbated IR, and decreased insulin secretion [66, 68]. On the other hand, it should also be noted that serum hepcidin and hepcidin/ferritin ratio also play an important role in the development of IR and diabetes [69, 70]. In the current research, we calculated the IR substitute index METS-IR, and the correlation analysis showed that all lipid parameters were closely related to METS-IR, among which TG/HDL-C ratio had the strongest correlation (Pearson r = 0.7447 for TG/HDL-C ratio). Additionally, it is worth noting that unconventional lipid parameters were also more powerful in identifying atherosclerosis and IR than conventional lipid parameters [61, 71]. Combining current research findings, we have several simple suggestions for a series of possible future work: (1) it is suggested that medical staff should strengthen their understanding of unconventional lipid parameters. (2) It is suggested that based on conventional lipid measurement, the inspection center of medical institutions can add unconventional lipid parameters as detection items to the display list by adding an algorithm to the computer. (3) It is suggested that more comparative studies on conventional and unconventional lipid parameters should be carried out to find out the value of lipid parameters in the risk assessment of other diseases. (4) It is suggested to add more unconventional lipid parameters on the basis of non-HDL-C as the main target of lipid management [72]. (5) It is suggested that unconventional lipid parameters should be considered as a potential target for developing high-sensitivity biosensors for diabetes.