Association Between Cardiac Natriuretic Peptides and Lipid Profile: a Systematic Review and Meta-Analysis

Cardiac natriuretic peptides (NPs) play a fundamental role in maintaining cardiovascular (CV) and renal homeostasis. Moreover, they also affect glucose and lipid metabolism. We performed a systematic review and meta-analysis of studies investigating the association of NPs with serum lipid profile. A PubMed and Scopus search (2005–2018) revealed 48 studies reporting the association between NPs and components of lipid profile [total cholesterol (TC), low-density lipoprotein cholesterol (LDLc), high-density lipoprotein cholesterol (HDLc) and triglycerides (TG)]. Despite high inconsistency across studies, NPs levels were inversely associated with TC [k = 32; pooled r = −0.09; I2 = 90.26%], LDLc [k = 31; pooled r = −0.09; I2 = 82.38%] and TG [k = 46; pooled r = −0.11; I2 = 94.14%], while they were directly associated with HDLc [k = 41; pooled r = 0.06; I2 = 87.94%]. The relationship with LDLc, HDLc and TG lost significance if only studies on special populations (works including subjects with relevant acute or chronic conditions that could have significantly affected the circulating levels of NPs or lipid profile) or low-quality studies were taken into account. The present study highlights an association between higher NP levels and a favorable lipid profile. This confirms and extends our understanding of the metabolic properties of cardiac NPs and their potential in CV prevention.

Study selection and data extraction. Two independent investigators (F.S., F.G.) screened all identified records (title and abstract) and assessed the selected full-text articles for eligibility. Disagreements were resolved through discussion. Descriptive, methodological and outcome data were extracted from all the eligible studies by the two reviewers who worked independently using a predefined data extraction form. The following data were collected: study design, number of enrolled subjects, mean age, sex, body mass index (BMI), renal function [estimated glomerular filtration rate (eGFR)], prevalence of diabetes and hypertension, prevalence of lipid-lowering treatment, NPs levels, circulating lipid levels (TC, LDLc, HDLc, TG), NPs assay. In studies reporting median values, the mean and variance were estimated from the median, range, and the sample size, according to Wan X et al. 14 .
In the manuscript, we included both "NT-proBNP" and "BNP" with the term "B-type NPs", and, similarly, we included "NT-proANP", "MR-proANP" and "ANP" with the term "A-type NPs". Assessment of risk of bias and study quality. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomized studies in meta-analyses 15 was adapted for use in the current review, as previously reported 16 . The studies was assessed in 3 domains: (1) the selection (representativeness of the sample population, appropriate sample size, and ascertainment of the exposure; (2) the comparability (appropriate control of confounding factors); and (3) the outcome (appropriate assessment of the outcome and appropriate description of the statistical test). From the original quality assessment tool, the item "respondents comparability and response rate" was excluded because not applicable to the current review. Instead, the item "appropriate sample size" was added in the section "selection" (a sample size of 100 or more was justified as satisfactory). The maximum attainable quality score was 6. A score of 5 was chosen as cutoff to indicate studies of high quality (Supplemental Table 1).

Statistical analysis.
Four distinct meta-analyses were performed for each individual component of the lipid profile (TC, LDLc, HDLc, TG). Correlation coefficient (r) has been chosen as the effect estimate for the data synthesis. As the majority of studies reported univariate analyses for the outcome of interest, Pearson or Spearman correlations were extracted. Adjusted beta was extracted if available in the absence of the univariate analyses. If the authors reported different effect estimates (i.e. one-way analysis of variance), data were extracted and used for the reconstruction of effect size (ES) and data synthesis. In studies reporting the outcome of interest in subgroups of the study population, we analyzed each subgroup separately in order to consider the ES of each one. Data were synthesized using meta-analytic methods 17 , and statistically pooled by the standard meta-analysis approach, i.e. studies were weighted by the inverse of the sampling variance. The DerSimonian and Laird random effects model was used as a conservative approach to account for different sources of variation among studies. Forest plots were constructed to graphically represent the results. Q statistics were used to assess heterogeneity among studies. A significant Q value indicates a lack of homogeneity of findings among studies 17 . I 2 statistics were then used to quantify the proportion of observed inconsistency across study results not explained by chance 18 . I 2 values of <25%, 50% and >75% represent low, moderate and high inconsistency, respectively 18 . Several variables were identified and their effects on outcome examined. Sensitivity analyses were performed by excluding studies with possible confounders in order to assess the influence of confounders on the pooled ES. Categorical variables were treated as moderators and the ES was assessed and compared across subgroups formed by these moderators (study design, age classes, BMI classes, cardiac NP type, special populations, NT-proBNP assays, BNP assays, study quality). According to each study sample, we defined "studies on special populations" those works including subjects with relevant acute or chronic conditions that could have significantly affected the circulating levels of NPs or lipid profile, and therefore their association: patients with human immunodeficiency virus, kidney transplant patients, women with polycystic ovary syndrome, patients in peritoneal dialysis, subjects with active systemic lupus erythematosus, patients with acute myocardial infarction, patients with acute ischemic stroke, patients hospitalized for worsening heart failure. NP assay was considered as moderator for B-type NPs, while the low number of included studies (k = 5) and the different assays used did not allow us to perform this sensitivity analysis for A-type NPs. Continuous variables were examined as covariates using random effects meta-regression (age, BMI, NT-proBNP levels, prevalence of males, eGFR, prevalence of diabetics, prevalence of hypertensives, prevalence of lipid-lowering therapy). Sub-group analyses were performed to assess the effect of study quality (NOS score, risk of bias) on the calculated estimates. Given the possible important bias linked to the lipid-lowering treatment, we also evaluated the overall ES after considering only the included studies explicitly conducted on untreated subjects (subjects without lipid-lowering therapy). The presence of publication bias was investigated through funnel plots both visually and formally by trim and fill analysis and Eggers's linear regression method 19 . A p value less than 0.05 was used to indicate statistical significance. All analyses were conducted using a computer software package (ProMeta Version 2, Italy).

Results
Included studies. The study selection process is described in Fig. 1. Among the initial 7119 records, 48 studies published between 2005 and 2018 met our inclusion criteria and 46 were included in the meta-analysis  . The characteristics of the 46 included studies are described in Supplemental Table 2. Of the 46 resulting studies, the majority was cross-sectional (n° 28), 16 were cohort and 2 were case-control studies. Ten studies reported the outcome of interest in subgroups of study population, therefore the ES was considered accordingly. The majority of studies (n° 27) were focused on N-terminal pro B-type natriuretic peptide (NT-proBNP), 14 on BNP and only 5 on A-type NPs. The mean of cardiac NPs levels varied substantially across the available studies. In the sensitivity analyses, 13 studies included special populations 21,31,35,36,38,39,41,43,46,49,56,60,63 . Regarding lipid-lowering treatment, 23 studies reported the prevalence of treated subjects, and only 11 studies were conducted on untreated subjects 20,21,32,36,42,43,52,54,55,64,66 . Thirty-seven studies reported the assays for B-type NPs. All the assays had a good coefficient of variations (<10%), except for one study, although it reported a coefficient of variation <15% 32 . Regarding NT-proBNP, 22 studies used electrochemiluminescence immunoassay (ECLIA) 20,[22][23][24][25][27][28][29]33,37,38,40,41,45,48,[51][52][53][54][55]57,61 , 2 studies used enzyme immunoassay (EIA) 60,64 , 1 study used immunofluorescence assay (IFA) 39 and 1 study used chemiluminescence immunoassay (CLIA) 46 . Regarding BNP, 7 studies used assays for NH 2 -terminal fragment 26,32,43,49,50,63,66 , 3 studies used assays for COOH-terminal fragment 42,44,62 and 1 study used radioimmunoassay (RIA) 21 . In the systematic review, we found two studies that have not been included in the meta-analysis due to the lack of usable data. One article investigated the link between NT-proBNP and lipids based on metabolomics profile determined by 1 H-NMR spectroscopy in 872 subjects 67 . In this study, higher NT-proBNP levels were linearly associated with a beneficial lipoprotein profile, including lower very low-density lipoprotein (VLDL), intermediate-density lipoprotein (IDL), and LDL-particles along with higher large HDL particle measures, lower small Sensitivity analyses. In order to search for possible sources of heterogeneity related to different characteristics of studies and populations, the moderator analysis was performed (Supplemental Tables 3-6). Regarding TC, studies on subjects with a mean age ≥65 years or a mean BMI <25 kg/m 2 showed a stronger association. Moreover, the association was confirmed only in those studies that used ECLIA for NT-proBNP and was stronger in those studies that used assay for NH 2 -terminal fragment of BNP.
The associations with LDLc, HDLc and TG lost significance in studies on special populations and with low quality for LDLc and HDLc. Moreover, the association with LDLc was not confirmed for the studies that used RIA for NT-proBNP. Regarding HDLc, the positive association with NPs was stronger with A-type NPs compared to B-type NPs, while no difference between the two cardiac NP types emerged for the other lipids. Regarding TG, the negative association was confirmed only for those studies that used ECLIA and EIA for NT-proBNP, while the studies that used assay for NH 2

Discussion
The present systematic review and meta-analysis of 46 studies shows a continuous linear association between cardiac NPs and serum lipid parameters. Higher NPs levels are associated with a more favorable lipid profile, in particular with lower LDLc and TG, higher HDLc, as summarized in Fig. 6. These findings confirm a positive role of this hormonal system on circulating lipid levels and therefore on CV risk.  www.nature.com/scientificreports www.nature.com/scientificreports/ Dyslipidemia is one of the most common CV risk factors, and a major determinant of CV disease and mortality 69,70 . In addition to the well-established role of LDLc in determining atherosclerosis, all the other components of the lipid profile are also implicated in vascular damage 71 . Our meta-analysis highlights the association between cardiac NPs levels and all the components of the lipid profile.
The first clinical study on this topic was performed by Olsen and colleagues 20 in 2005. They found that patients with dyslipidemia had lower NT-proBNP levels that were inversely associated with higher levels of both TC and TG. Afterwards, many other studies investigated the relationship between cardiac NPs and lipid profile, particularly in the context of the MetS 20,22,24,25,30,45,47,60,62,64 . Indeed, a close association between NPs system and MetS is well recognized 72 . Previous clinical studies found an association between higher NPs levels and less development of diabetes mellitus and MetS 11 . At the same time, hyperinsulinemia, a classical marker of MetS, induces an overexpression of the NPs clearance receptor (NPRC) in human adipocytes, contributing to lower NPs circulating levels in these subjects 7 . A genetic variant of the NPs precursor A gene (NPPA) is associated with higher circulating levels of both A-type and B-type NPs, and with higher HDLc levels and lower prevalence of obesity and MetS 12,73,74 . In our meta-analysis, no differences emerged between A-type and B-type NPs in the associations with lipid parameters (see moderator analysis in the Supplemental Material). However, HDLc was more strongly associated with A-type NPs than B-type NPs, although far fewer clinical studies on A-type NPs were available in literature (5 studies for A-type NPs vs 41 studies for B-type NPs). Interestingly, this is in line with the previous evidence that A-type NPs could exert more a cardiometabolic function compared to B-type NPs, which may be more related to cardiac remodeling 8 .
Several mechanisms that could explain the clinical relationship between circulating NPs and serum lipid levels are emerging. Cardiac NPs have the ability to positively affect distant target organs. In fact, NP receptors are  www.nature.com/scientificreports www.nature.com/scientificreports/ expressed in several organs and tissues, such as vessels, kidney, skeletal muscle and adipose tissue 5 . In human adrenocortical cells, BNP was found to inhibit cholesterol biosynthesis stimulated by angiotensin II 75 . Adipose tissue and the kidney are the organs where NP receptors are mainly expressed 76 . Indeed, cardiac NPs exert several actions on adipocytes and lipid metabolism. They promote the "browning" of white adipocytes 77 increasing the uptake of triglycerides derived from plasma triglyceride-rich lipoproteins. Brown adipose tissue is also actively involved in the metabolic flux of HDLc to the liver 78 . Furthermore, NPs promote the degradation of TG and the oxidation of the circulating non-esterified fatty acids, inducing mitochondrial biogenesis and thermogenesis 77,79 , hence the inverse association between NP and TG found in our work. Recently, based on a metabolomics approach, NT-proBNP had an inverse association with aromatic and branched-chain aminoacids and related degradation intermediates, likely due to the induction of mitochondrial biogenesis by NP 67 . Most of these metabolic actions are mediated by the binding of cardiac NPs to the NP receptor A (NPRA) that induces the generation of the second messenger cyclic guanosine monophosphate (cGMP) 80 . Overexpressing BNP or genetic/pharmacological cGMP augmentation in several animal models induced adipose tissue browning and lipid oxidation, promoted mitochondrial biogenesis and fat oxidation in skeletal muscle, preventing obesity and glucose intolerance 77,79,81 . Finally, cardiac NPs were recently found to exert a direct role on the main determinants of LDLc levels, such as LDLc receptor (LDLR) and PCSK9 10 . PCSK9 is expressed in human adipose tissue and regulated by insulin and ANP, which act in opposite ways. In fact, ANP is able to reduce the insulin-mediated induction of PCSK9, thereby reducing the degradation of LDLR 10 . All these mechanisms, together with the well-established protective role against MetS and diabetes mellitus, can lead to a more favorable circulating lipid profile.
Our systematic review and meta-analysis focused on cardiac NPs (A-type NPs and B-type NPs) given the extensive literature regarding their relationship with CV risk factors, including MetS and lipid metabolism, based on their well-known endocrine effects. Although not taken into account in our work, recent evidence is emerging on the CV and metabolic role of C-type NP. Very recently, C-type NP has been identified as a good early marker of renal damage in diabetic patients, probably reflecting renal inflammation and fibrosis 82 . Moreover, an important role on blood pressure, through its anti-fibrotic and vasodilatory effect 83 and on lipid metabolism has been found in transgenic mice, in which the overexpression of C-type-NP led to increase in fatty acid β-oxidation and lipolysis and decrease in insulin-resistance and fat weight 84,85 .
Several moderators were taken into account in our meta-analysis. Sex did not affect our outcome, likely due to the average age of most populations studied with most menopausal women, as well as renal function, prevalence of hypertension and diabetes mellitus. On the other hand, age, BMI and NT-proBNP levels were likely to play a role in the associations between cardiac NPs and lipid profile, at least for TC. The association was found to be stronger in older subjects compared to younger ones. This finding could be explained, at least in part, by the fact that older patients are more likely to have both higher NPs levels, caused by cardiac and non-cardiac comorbidities 86 , and lower TC levels, due to lipid-lowering therapy or clinical conditions such as malnutrition and frailty 87,88 . On the other hand, the association between cardiac NPs and TC was weaker in overweight/obese subjects. A possible explanation could be the lower ratio between NPRA and NPRC in the obese subjects that may attenuate the beneficial actions of NPs 89 . It is well known that obese subjects have lower circulating NPs levels 90 . However, the relationship between NPs and obesity is still not fully understood [91][92][93] , as well as the precise role of obesity in the development of dyslipidemia 94 . Regarding the role of NPs levels, we took into account only NT-proBNP in the sensitivity analysis. Sanchez et al. 51 found that the initial linear association with blood lipids was followed by a tendency towards a plateau at higher NT-proBNP concentrations, given the continuous resetting between active NPs levels and NPRA activity. On the contrary, our extensive meta-analysis confirmed this association even for higher NT-proBNP values.
Our meta-analysis showed a high proportion of observed inconsistency across studies. This could be explained both by the considerable heterogeneity in study population (Supplemental Table 2) and by the quality of the included studies. We identified those studies performed on populations that were likely to interfere with our outcome and grouped them (studies on special populations) in the moderator analysis. The relationship with LDLc, HDLc and TG lost significance if only studies on special populations were taken into account. Same results were found for low-quality studies. Moreover, the inconsistency of the relationship with LDLc and TG decreased from high to moderate after taking into account only those studies on subjects without lipid-lowering therapy, although the association with HDLc lost its significance. Part of the heterogeneity could also be explained by the use of different NP assays in the included studies. We tried to classify them in the sensitivity analyses and the strength of the association differed through the several assays considered. In fact, the assays developed for both BNP and NT-proBNP lack standardization and the results obtained using different assays are not transferable 95 . A significant cross-reactivity among BNP, NT-proBNP, and proBNP peptides, variable for each assay, is present in all the conventional BNP and NT-proBNP immunoassays 96 . A study with mass spectrometry showed that proBNP 1-108 is the most common circulating form detected by the iteration of BNP assays in patients with chronic heart failure 97 . After comparing several NP immunoassays commercially available, the B-type NPs levels differed from one assay to another with a lack of inter-assay transferability. Moreover, also the methods using the same calibrator with or without the same antibodies targeting the same epitopes, did not guarantee an agreement, likely due to a difference in reagent formulation and signal detection, hardware, assay parameters 95 . Although almost all the included studies had a good coefficient of variation, the use of different NP assays is likely one main driver of the heterogeneity of our study results.
Clinical implications. Our results should stimulate the basic research to better investigate the pathophysiological mechanisms implicated in the regulation of lipid metabolism by NPs and their impact on the circulating lipid levels.
Designer NPs and modulators of cGMP signaling are being developed and investigated for the treatment of the cardiometabolic diseases 98,99 .
Recently, an innovative drug (Sacubitril/Valsartan) that simultaneously inhibits both RAAS and the degradation of NPs (angiotensin II receptor-neprilysin inhibitor, ARNI) has been approved for the treatment of heart failure with reduced ejection fraction 100 . The potential benefits of this drug could go beyond the treatment of heart Scientific RepoRtS | (2019) 9:19178 | https://doi.org/10.1038/s41598-019-55680-z www.nature.com/scientificreports www.nature.com/scientificreports/ failure 101 , given the actions of NPs on lipid and glucose metabolism. Recent evidences suggest that all these beneficial effects appear to be driven by a potentiation of ANP rather than BNP 102,103 . Sacubitril/Valsartan improved glycemic control by increasing the insulin-sensitivity and the levels of glucagon-like peptide 1 102,104,105 . On the other side, its effects on lipid metabolism are controversial without apparent benefits on exercise-induced lipolysis and substrate oxidation in obese patients with hypertension 105 . A post-hoc analysis of the PARADIGM-HF trial showed, in addition to a reduction of glycated hemoglobin, an increase in HDLc levels in diabetics receiving Sacubitril/Valsartan compared with those receiving Enalapril 106 . Many factors could play a role in the discrepancy of evidence on this drugs: the other neprilysin substrates that potentially modulate lipid metabolism in the opposite way, the potential anti-lipolytic effects of insulin in adipose tissue, the role played by NPRC (scavenger receptor) in adipocytes, that could be more important than neprilysin activity 105,107 . Further ad hoc trials are needed to clarify the possible beneficial effects of this drug class on dyslipidemia and lipid metabolism. Study limitations. Our analysis has some limitations. Firstly, all the included studies were observational investigations and therefore we cannot support any causality between the cardiac NPs levels and the different components of serum lipid profile. Although we performed an extensive review of the main electronic databases, we cannot be sure to have included all relevant studies on this topic. The symmetry of the funnel plots indicates the absence of publication bias that may have influenced our results. However, we found high inconsistency between study findings and high heterogeneity among studies. Therefore, the quality of evidence is moderate at most, and the results of this meta-analysis should be taken with caution. We performed several sensitivity analyses in order to evaluate possible sources of heterogeneity, but we cannot exclude the influence of unmeasured confounding factors. However, taken together, our results show an inverse relationship between NP levels and TC, LDLc and triglyceride, but a positive association with higher HDLc, indicating that a biological positive effect of NPs on lipid profile is very likely and, on the contrary, it's very unlikely that these results were generated by spurious association due to meta-analysis limitations or by chance. Our meta-analysis focused on TC, LDLc, HDLc and TG. The presence in literature of only one article regarding NPs and ApoB 21 did not allow us to include this lipid parameter.

Conclusions
The present systematic review and meta-analysis of 46 studies highlights an association between higher cardiac NPs levels and a more favorable lipid profile. This both confirms and extends our understanding of the metabolic properties of cardiac NPs and their potential in CV prevention.