Transitioning from having no metabolic abnormality nor obesity to metabolic impairment in a cohort of apparently healthy adults

The metabolic syndrome (MetS) is a-well studied condition which is associated with an increased risk for diabetes and cardiovascular disease (CVD) [1]. While having multiple definitions from different societies and in different populations, the syndrome usually comprises a combination of the following metabolic derangements: high fasting glucose levels, hypertension, low HDL-C (high-density lipoprotein cholesterol) levels, high triglycerides levels and an increased waist circumference [2].

Although the prevalence of MetS and its components have been extensively documented in large populations [3, 4], and the changes in MetS status and its subsequent risks were previously described [5, 6], the rates and characteristics of metabolically healthy individuals (i.e. free of any metabolic abnormalities), especially when stable over time, are rarely mentioned. We note that there is an abundance of studies regarding metabolically healthy obesity (MHO), i.e. obesity as a single metabolic abnormality. However, a recent prospective study has stated that MHO individuals were at higher risk of all-cause mortality, diabetes, CVD, heart failure and respiratory disease compared to metabolically healthy people without obesity [7]. Nonetheless, our group has recently shown that overweight and obese individuals in an apparently healthy population are associated with significant blood tests abnormalities [8]. It is also noteworthy to mention that metabolic health was found to be a more important determinant for the development of diabetes than obesity [9].

A recent prospective study by Guembe et al. [10] has found that individuals with MetS or one of its single components present major cardiovascular events, cardiovascular mortality and all-cause mortality earlier than individuals without MetS. Sinning et al. has recently provided evidence that glycohemoglobin (HemA1C) is independently linked to cardiovascular mortality, overall mortality, and CVD in the general European population [11]. Wang et al. referred to the relevance of triglycerides and fasting glucose by stating that elevated cumulative average triglyceride-glucose index independently predicts ischemic stroke in the general population [12]. Moreover, recovery from MetS was previously suggested to be associated with decreased risk for major cardiovascular events [13]. These findings emphasize the importance of early detection and prevention of metabolic morbidity by differing it from metabolic health and allows us to identify the unique biomarkers that predict new onset of metabolic disorders. Not long ago, Kouvari et al. had published that the baseline presence of non-alcoholic fatty liver disease (NAFLD) acted as a predictor for the development of metabolically unhealthy status and an elevated cardiometabolic risk overtime [14]. We thus sought to assess the prevalence of metabolic health (i.e., the absence of any of the defining characteristics of the metabolic syndrome and diagnosed diseases) in a large cohort of adult individuals, describe its natural trajectory (i.e. development over time) and identify parameters (e.g. liver enzymes, blood count, electrolytes and lipids) that may predict development of future metabolic derangements or even identify current hidden ones.

The study population consisted of 20,507 apparently healthy participants of which 13,019 were men and 7488 women with a mean age of 44.9 (± 11) years. Participants ranged in age from 18 to 86 years, and 7759 (37.8%) returned for a follow-up visit within 4.8 (± 0.6) years. We compared the entire cohort with the returnees on their first visit (Additional file 1: Table S1). While some variables showed significance, the differences are likely influenced by large sample sizes or other factors. Overall, the cohorts appear similar, representing the same population.

First, we sought to determine the prevalence of individuals without any metabolic abnormality or existing co-morbidities at baseline. Only 5379 participants (26.2% of the cohort) met our exclusion criteria and were defined as “metabolically healthy” on their first visit (Fig. 1). A general comparison of “metabolically healthy” and metabolically impaired participants on the baseline visit is presented in Additional file 2: Table S2. Clinical characteristics by groups of metabolic health status on both visits are presented in Table 1. A comparison of the metabolically healthy and metabolically impaired groups revealed several significant differences: Metabolically healthy individuals were younger, included more women, were less likely to smoke and had lower levels of hs-CRP, fibrinogen, BUN, WBC, RBC, creatinine, hemoglobin, uric acid, liver enzymes, LDH and LDL-C.

We report here the relatively low prevalence of apparently healthy individuals without any metabolic abnormality (roughly 26% of our cohort). The most prevalent metabolic syndrome criterion in our cohort was hypertension. Furthermore, we found several small significant changes in non-direct-metabolic biomarkers in participants that changed their status of metabolic health over time.

The groups of our study, especially the group that developed metabolic abnormalities over time, provide an opportunity to evaluate the metabolic health transition point, along with continuous metabolic health or impairment statuses. Our findings imply the possible existence of antecedent biomarkers for metabolic impairment. Equally important, our results may also point out the importance of aggressive early screening for hypertension as an indicator of early metabolic impairment and associated co-morbidities [23, 24], especially if accompanied with current active inflammation.

The significant prevalence of hypertension in comparison to all other metabolic components could be explained by the influence of the cohort's mean age and males as the prevalent gender. These results are in line with previous studies that found hypertension to be the most prevalent component among younger men and older men and women [25]. However, it is important to mention that some studies in different populations found the low HDL-C component as the most prevalent component, followed by hypertension [26, 27]. Nevertheless, since blood pressure (especially systolic blood pressure) tends to increase with age [28], and previous studies have shown that its prevalence is significantly high and somewhat stable over time [29], our findings further support the need to aggressively screen for elevated blood pressure in patients with any metabolic abnormality.

Previous studies suggest a strong association between MetS and subclinical inflammation demonstrated in elevated levels of CRP [16]. Thus, it is not surprising that our results present increased prevalence of active inflammation among metabolically impaired individuals. The relatively large intersection of hypertension and elevated hs-CRP on the group that became metabolically impaired overtime, could suggest that the emergence of hypertension at the metabolic transition process is widely accompanied by active inflammation. Previous studies like the Women’s Health Study and the Framingham Offspring Study strengthen this concept by showing that CRP could independently predict the development of new-onset hypertension [30, 31].

Metabolic health has a time-varying nature. For this reason, the small changes we found in non-direct-metabolic biomarkers may imply subjects at risk of developing metabolic syndrome or diseases. Amongst these findings, a relative elevation of WBC in participants that became metabolically impaired could be explained by its positive association to hyperglycemia, low HDL-C and hypertriglyceridemia [32]. Another interesting finding is the relatively lower decrease and even elevation of RBC count in the metabolically impaired group. We previously found that enhanced erythropoiesis is associated with the multiplicity of MetS components [33], while other studies indicate that insulin resistance mechanisms support erythropoiesis [34, 35], these findings collectively point to a potential explanation for our observation. The RBC change’s clinical relevance is attributed to the fact that an alteration of erythrocytes count, shape or elasticity could contribute to vascular damage and reduced blood flow, as the cells’ aggregative and adhesive qualities change [36]. Sub-sequentially this may lead to a decrease of circulating oxygen, insulin and glucose which could catalyze the progression of metabolic abnormalities like diabetes [37]. Thus, it is not surprising that elevated RBC count could contribute to transition in metabolic health and may potentially serve as an early indicator for metabolic deterioration.

Other findings like the elevated LDH could derive from an extensive tissue damage that causes its release to the bloodstream due to hypertension or diabetes emergence [38]. Bilirubin was previously found to be negatively correlated with MetS 39], while liver enzymes such as ALT seem to be higher in metabolic abnormalities [40].

Surprisingly, there was no significant difference of the change in concentrations of LDL-C in the group that became metabolically impaired. Even though LDL-C was found in numerous studies to be an independent risk factor of CVD [41], it is not part of the official MetS criteria. The exact association between LDL-C and the MetS seems to be controversial. Some studies report LDL-C has no significant correlation with MetS prevalence [42, 43], while others claim that LDL-C levels are not only associated with the MetS, but can also serve as a predictor for the syndrome's development [44]. In addition, it is not clear what are the levels of LDL-C concentration responsible for an increase of MetS prevalence in the overall population [45]. A possible cause for our finding could be that a change in LDL-C concentrations depends on the change in LDL-C subclasses. While small density LDL-C particles seem to increase in the MetS, there is a significant reduction of large LDL-C particles. This elevation and decrease could affect the LDL particle number but not result in a change of the total LDL-C concentration [46, 47]. Another possible speculation is that LDL-C concentration simply does not change rapidly on the verge of change of metabolic status. Furthermore, it is worth noting that 56 participants (5.7%) in the group that developed metabolic impairment initiated a new lipid-lowering treatment between visits, which may have influenced the results.

Unfortunately, this study reflects the unfavorable reality of metabolic health and illness. Even though this study's population consisted of apparently healthy, work-aged participants, our analyses show significant high rates of various illnesses among them, mainly metabolic abnormalities. To the best of our knowledge, numerous studies have discussed the definitions of metabolic abnormalities, but few have mentioned an agreeable definition of health, other than the MHO definition. Nevertheless, even when considering MHO as an accepted health definition it is important to remember that metabolic health is a transient status in nature [48], along with the very fact that it is yet to be clear what are the best antecedent biomarkers for MHO individuals who may progress to impaired cardiometabolic health.

Therefore, we believe there is a crucial value of evaluating and accurately defining metabolic health, in order to investigate borderline conditions, preventable medical cases that could be invertible using aggressive screening of metabolic or other indicators.

The main limitation of this study is that our cohort is comprised of participants in a health screening program, thus it is not a population-based sample. Additionally, our cohort experiences loss of follow-up, which could potentially cause some selection bias regarding the results. However, our cohort primarily included working participants whose periodic attendance is facilitated by workplace benefits, contributing to a high rate of participation (91.6% of those asked). Also, comparing both cohorts revealed non-fundamental differences. It is important to mention that although participants are invited to our center several months in advance, it is possible that some may have chosen to attend due to a recent illness, which could have served as a motivating factor. To address this, we took specific measures for participants who exhibited increased CRP values (hs-CRP > 10 mg/dL). We reinvited them for a second CRP examination, and only the values from the second blood test were included in our analysis. In addition, while the observed differences in biomarkers are statistically significant, they exhibit relatively modest magnitudes. Consequently, their clinical significance is limited, possibly due to the dichotomization around cut-off values. The group that developed metabolic impairment was already close to impairment levels initially, suggesting this outcome could be an artifact of the chosen cut-offs. Further research is essential to determine precise cut-off points and personalize them for more reliable and relevant studies.

This study provides further evidence that metabolic abnormality is very common and should be taken into consideration in terms of early screening and treatment. Hypertension, especially when combined with active inflammation, is a prime candidate for agxgressive screening of patients in increased risk to develop MetS over time. Further investigation is needed to examine the potentially predicting role of additional biomarkers like blood count, liver enzymes, LDH and uric acid. We recommend further research focused on the transition between metabolic health and abnormality to improve detection abilities and reduce future morbidity.