Hyperlipidemia was a condition that was characterized by abnormally elevated blood lipids broadly including increase in low-density lipoprotein cholesterol (LDL-C) and triglycerides (TG) as well as reduce in high-density lipoprotein cholesterol (HDL-C) (1), which could be attributed to a variety of genetic predispositions or acquired health conditions (2). Hereditary hyperlipidemia referred to congenital disorders such as familial hypercholesterolemia, whereas primary hyperlipidemia generally referred to elevations of all lipoproteins (3) (except HDL-C). In adults, hyperlipidemia was recognized to contribute to the development of cardiovascular disease (CVD) (2). The available evidence suggested an association between hyperlipidemia which was characterized by the increase of TG and LDL-C in plasma, and the prevalence of coronary artery disease (4). Not only did it promote atherosclerosis of blood vessels, hyperlipidemia could also act directly on the heart leading to ischemia-reperfusion injury (5). Moreover, the CVD accounted for the highest percentage of all causes of death among adults in the United States, and the risk of developing CVD in people with hyperlipidemia was about twice than those without dyslipidemia (1).

The link between atherosclerosis and hyperlipidemia, as well as the role of persistent low-grade inflammation and lipid abnormalities, has prompted research into the potential association between elevated lipid levels and inflammatory states (6). The cholesterol has been proved to directly induce inflammation by the activation of the NLRP3 inflammasomes, possibly contributing to the initiation and exacerbation of local and systemic immune inflammatory responses (7).

The pan-immune-inflammation value (PIV) represented a novel biomarker for predicting inflammatory status, including four cell types in peripheral blood (8). The definition of it relied on the counts of neutrophils, monocytes, lymphocytes, and platelets (9). In 2020, it was initially used in metastatic colorectal cancer patients, showing a good ability to assess the prognosis of them and it even exceeded that of previously established markers related to inflammation (10). PIV was a potent and independent predictor of coronary slow flow, superior to other inflammatory markers (11). In a cross-sectional study, elevated PIV was associated with an increased risk of all-cause mortality (1.37 (1.20-1.55); P < 0.001) and cardiovascular mortality (1.62 (1.22-2.15); P < 0.001) in hypertensive patients (12). The systemic immune-inflammation index (SII: platelet count × neutrophil count/lymphocyte count) was applied to the assessment of the risk of dyslipidemia previously, but the correlation between them was relatively small (Model 2: OR (95%CI): 1.03 (1.01-1.05); Model 3: OR (95%CI): 1.02 (1.00-1.04)) (13).

The association between novel composite biomarker PIV and dyslipidemia has not been reported. Therefore, the study is aimed to explore the association between PIV and dyslipidemia and answer whether PIV can be used to assess the risk of dyslipidemia more effectively.

In the present study, the authors selected 6,821 adults in United States from the NHANES datasets. The important discovers of this cross-sectional study were as follows: (1) PIV index had an significantly positive association with the risk of dyslipidemia. And this effect maintained stable in both continuous and quartile independent variables even after adjustment for all confounders. The prevalence of dyslipidemia was relatively high in older, non-Hispanic white, not above high school, BMI ≥ 25 kg/m², larger waist circumference, higher creatinine and uric acid, hypertensive, diabetic, drinkers, nonsmokers, had the history of coronary heart disease, arthritis, stroke, cancer, congestive heart failure, as well as higher PIV. (2) In the stratified analyses, except for age and BMI, the interaction tests for the rest were not statistically significant (P > 0.05). Elevated PIV significantly increased the prevalence of dyslipidemia especially in young (20-39 years old) and overweight (25–30 kg/m²) individuals.

To our knowledge, the association between PIV and dyslipidemia was first reported in this study based on a national population of the United States. The PIV was derived from the four important immune cells in plasma, neutrophils, monocytes, lymphocytes, and platelets (15).

The long-term existence of inflammation could cause abnormal lipid metabolism (16). In chronic inflammation, the direction of lipid synthesis altered, manifesting in a reduction of HDL and an elevation in TG levels (17). In individuals with primary Sjogren’s syndrome (an chronic inflammatory autoimmune disease), interleukin-2 was positively correlated with LDL-C (r = 0.7, P = 0.02) (18). In addition, interleukin-6 (r = 0.39, P = 0.01) and tumor necrosis factor-alpha (TNF-α) had an significant association with TG (r = 0.4, P = 0.007) and HDL-C (r = -0.4, P < 0.001) (18). Among patients with heterozygous familial hypercholesterolemia, nuclear factor-kappa B (NF-kB) activity of monocytes in blood was independently associated with apolipoprotein B (r = 0.287, P = 0.03) and oxidized LDL (r = 0.300, P = 0.02) (19). In newly diagnosed patients with metabolic syndrome, TNF-α was significantly associated with fasting blood glucose (r = 0.179, P = 0.021), LDL-C (r = 0.199, P = 0.01), atherogenic index (r = 0.219, P = 0.004), TG (r = 0.351, P < 0.001), and HDL-C (r = -0.244, P = 0.001) (20). Among individuals without severe cardiovascular risks, there was a positive relationship between serum TG and high-sensitivity C-reactive protein (CRP) (r = 0.298, P < 0.001) (21). The relationship between inflammation and cholesterol was complementary in CVD. Excessive migration of LDL to the artery wall triggered an inflammatory cascade, which then accelerated the accumulation of cholesterol, further exacerbating the inflammatory response. This vicious cycle could ultimately lead to the atherosclerosis (22). Modified LDLs had the ability to activate the toll-like receptors, thereby priming the Nod-like receptor protein 3 inflammasomes and ultimately leading to the activation of interleukin-1β and secondary inflammatory responses (23). It was also reported that the lipoprotein-mediated enhancement of inflammation was mainly mediated by TG-rich lipoproteins, not LDL (24). Hypertriglyceridemia enriched with apolipoproteins C-III, could activate toll-like receptor 2 and NF-kB inflammatory signaling pathways, leading to development of atherosclerosis (25). In addition, remnant cholesterol calculated from the equation TC-HDL-LDL was rich in TG (25). In our study, PIV had an inverted J-shaped relationship with TG and remnant cholesterol, but a negative correlation with HDL-C ( Supplementary Figure 2 ). There was no significant association between PIV and LDL-C or TC (P > 0.05). In vivo, higher TG concentrations were associated with higher levels of plasma glycoproteins which were reliable biomarkers reflecting chronic inflammation (26). Meanwhile, a stronger association of TG or remnant cholesterol with inflammation than LDL-C was similar to our study (27, 28). The inverted J-shaped curve might be explained by the phenomenon (26) that the proportion of TG in lipoprotein began to decrease when it reached a certain degree of inflammatory state, and the increase of other components such as cholesterol and phospholipids was more conducive to the maintenance and further development of inflammation.

In this study, the association between PIV and dyslipidemia was modified by age and BMI. Interestingly, this effect was more significant in younger adults (20-39 years). In a cohort study from China (29), the risk of cardiovascular diseases and all-cause mortality was greatest in people younger than 45 years old with hypertriglyceridemia. Unhealthy lifestyle habits such as smoking, alcohol consumption, high-calorie diets and lack of exercise might be the cause of dyslipidemia in such patients (30). These adverse factors were also associated with intestinal dysbiosis and non-specific inflammation, eventually leading to a chronic low-grade inflammatory state of the body (31). A large cohort study in Dutch (32) revealed that the prevalence of non-LDL dyslipidemia (high triglycerides, high remnant cholesterol and low HDL-C) was highest in men aged 35 to 55. Obesity, smoking and diabetes were important risk factors for this kind of dyslipidemia (32). In addition, chronic inflammation and dyslipidemia were common in patients with higher BMI (33, 34). Elevated levels of interleukin-6 and TNF-α in obese individuals could increase insulin resistance and cardiovascular risk (35). A cohort study from Japan showed that women with BMI ≥ 25 kg/m² had a 1.54-fold higher risk of dyslipidemia than BMI < 25 kg/m² (36). BMI and waist circumference both had a significant positive relationship with dyslipidemia in adults over thirty-five years old in two thousand Chinese (37). The levels of inflammatory markers also increased in obese patients and were positively correlated with BMI (38). In obese, more pro-inflammatory M1 macrophages than anti-inflammatory M2 macrophages existed in adipose tissue (39). The obese mice with hepatocyte -specific PPARα knockout exhibited higher triglycerides in plasma and promoted a shift from M2 to M1 macrophages, thereby activating inflammatory responses such as elevated levels of TNF-α (40). It was also reported that HDL-C could be oxidized by myeloperoxidase in neutrophils and macrophages, hindering cholesterol transport and inducing inflammation (41). Given the increasing prevalence of overweight and obesity in adolescents and young adults (42), future treatment strategies should focus on optimizing lifestyle and weight management to reduce the risks of chronic inflammation and dyslipidemia in this group.

There were several strengths and limitations in the study. The authors performed statistical analyses using a large, nationally representative sample with adjustment for demographic, examination, questionnaire, and laboratory covariates to ensure that the findings are generalizable to practice. In addition, the study used a novel inflammatory biomarker PIV, which might be reliable and effective in the assessment of inflammation. Lastly, the definitions of independent and dependent variables in the study were based on standardized laboratory tests, which largely ensured the objectivity and accuracy of the data and avoided recall bias. Some limitations were also considered. First, it was a cross-sectional study which had statistical significance between both variables, but could not verify their causal connection. Second, the study only considered the population in United States, so it was unclear whether the findings could be generalized to other races in the world. Third, although this study adjusted the relevant confounders, there might be other unknown confounders.

The study discovered a significantly positive association between PIV and dyslipidemia in United States adults, especially in young and overweight individuals. Our findings suggested that weight control in early adulthood might be beneficial to maintain lipid homeostasis and prevent the disruption of chronic inflammation. More studies are needed to explore the relationship between inflammation and lipid status in the future.