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Smoking and apolipoprotein levels: A meta-analysis of published data

Background Apolipoproteins are major components of lipoproteins such as high-density lipoprotein (HDL) and very-low-density lipoprotein and are considered nontraditional markers in the risk assessment for cardiovascular disease. The goal of this review was to quantify the effects of smoking and smoking cessation on serum levels of apolipoproteins AI, AII, and B and the ratio of apolipoproteins B and AI. Methods PubMed and Scopus were searched up to June 2021 to identify publications that reported the levels of apolipoproteins AI, AII, and B and the apolipoprotein B/AI ratio in smokers and nonsmokers as well as articles reporting the effect of smoking cessation on the same endpoints. Meta-analyses were performed when a sufficient number (n ≥ 3) of articles evaluating the same outcome were available. Results Forty-nine studies had assessed apolipoprotein levels in smokers and nonsmokers. The meta-analyses comparing the levels of apolipoproteins AI and AII showed decreased levels in smokers relative to nonsmokers. On the other hand, the apolipoprotein B levels and apolipoprotein B/AI ratio were increased in smokers relative to nonsmokers. Insufficient publications were available on which to perform meta-analyses on the effects of smoking cessation on apolipoprotein levels. Conclusions Smoking is associated with reduced levels of apolipoproteins AI and AII (in line with reduced levels of HLD-cholesterol) and increased apolipoprotein B levels and apolipoprotein B/AI ratio, thereby confirming the negative impact of smoking on lipid metabolism, which contributes to increased cardiovascular risk. More data are needed to elucidate the effects of smoking cessation on these cardiovascular risk endpoints.


Introduction
Cigarette smoking has been implicated as a major risk factor in chronic pulmonary disease, carcinogenesis and atherosclerotic arterial disease leading to cardiovascular disease (CVD) [1][2][3]. The mechanisms through which smoking increases the risk of atherosclerosis and CVD include oxidative damage and the alteration of lipid levels [4,5]. For instance, it has been shown that cigarette smoking decreases high-density lipoprotein-cholesterol (HDL-C) [6].
Even though low-density lipoprotein-cholesterol (LDL-C) is recognized as the primary lipid risk factor for CVD [7], other lipid measurements have been associated with an increased or decreased risk of CVD, such as apolipoproteins, which are the protein components of lipoproteins [8]. Two major types of apolipoproteins have been described: apolipoprotein A (I and II) and apolipoprotein B. Apolipoprotein AI, the major constituent of HDL, comprises roughly 70% of the HDL protein mass [9]. It mediates the efflux of cholesterol from the peripheral cell membranes and activates lecithin cholesterol acetyltransferase, which is an important enzyme in the reverse transport of cholesterol from peripheral tissues to the liver [10]. Apolipoprotein AII is the second most abundant protein in HDL, accounting for about 20% of total HDL [11]. Apolipoprotein B is an essential component of LDL and very-low-density lipoprotein (VLDL-C). It facilitates cholesterol delivery to peripheral tissues and promotes LDL-C accumulation by acting as a ligand for LDL-C receptors [1]. Apolipoprotein B is the major protein not only of LDL but also of all atherogenic particles, e.g. VLDL and intermediate-density lipoprotein (IDL). Because only one apolipoprotein B protein is present per particle [12], the total apolipoprotein B value reflects the total number of potentially atherogenic particles [13]. Due to the close association between apolipoproteins and serum lipids, their measurement has been proposed as an important factor in predicting the risk of cardiovascular diseases [8,10]. Additionally, population-based studies have suggested that the apolipoprotein B:AI ratio could be used as an indicator of the balance between atherogenic and atheroprotective cholesterol transport, as an increase in this ratio predicts cardiovascular risk more accurately and strongly than the use of either apolipoprotein B or apolipoprotein AI individually, or any of the other cholesterol indexes [14][15][16].
Studies assessing the association of smoking status and smoking cessation with lipid parameters are abundant in the literature. A review of the association of HDL-C levels and smoking status was performed by Maeda et al. [17], demonstrating increased levels of HDL-C after smoking cessation. To date, no meta-analyses have been published comparing the effects of smoking status or smoking cessation on the levels of apolipoproteins, which is the objective of the present review.

Methods
Searches were performed through PubMed and Scopus databases to identify publications that evaluated the relationship between smoking or smoking cessation and plasma levels of apolipoproteins, including AI, AII, and B, and the ratio of apolipoprotein B to apolipoprotein AI in humans. The last search was performed on June 25, 2021. The following query was used in PubMed: ("apolipoproteins"[MeSH Terms] OR "apolipoproteins"[All Fields] OR "apolipoprotein"[All Fields]) AND (("smoking"[MeSH Terms] OR "smoking"[All Fields]) OR ("tobacco"[MeSH Terms] OR "tobacco"[All Fields] OR "tobacco products"[MeSH Terms] OR ("tobacco"[All Fields] AND "products"[All Fields]) OR "tobacco products"[All Fields]) OR cessation [All Fields] OR quitting [All Fields]). In Scopus, the following query was used: apolipoprotein AND (smoking OR tobacco OR cessation OR quitting). The reference lists of the publications obtained through the original search were checked for additional articles.

Study selection
Case-control, cohort, or interventional studies in healthy adult subjects reporting any measurements of apolipoproteins AI, AII, and B levels and/or apolipoprotein B/AI ratio by smoking exposure (smokers vs. nonsmokers and baseline vs. time after smoking cessation) were included if they provided the following: mean or median values by group, standard deviation (SD) or standard error (SE), sample size per group, or had enough information to allow for the calculation of mean and SD. Review articles, case reports, editorials, and duplicates of publications of data that were part of a more recent publication were not included.

Data extraction
The following information was extracted from each study independently by three researchers: first author's name, year of publication, country where study was performed, study design and population characteristics, number of participants per exposure group, mean, SD or SE, and smoking status definition. Apolipoprotein levels were converted from mg/dL to g/L as needed.
To quantify the effects of smoking and smoking cessation on apolipoprotein levels, pooled mean differences between smokers and nonsmokers (when assessing effects of smoking on apolipoproteins) or differences between baseline and follow-up measures after smoking cessation (when assessing the effects of quitting smoking on apolipoprotein levels) and 95% confidence intervals (95% CI) were calculated using the fixed-effects model in the 'metamean' function [18]. The 'metamean' function uses the inverse variance method for pooling, giving studies with small variance relatively higher weight and studies with larger variance relatively smaller weight [18]. Meta-analyses were carried out using the 'metacont' function when at least three measures of a single estimate were available. The degree of heterogeneity between the study results was assessed by the I 2 statistic. Funnel plot symmetry and Egger's regression test were used to evaluate publication bias [21].
To explore possible sources of heterogeneity, the meta-analyses were performed using the random-effects model and sensitivity analyses were conducted using the 'InfluenceAnalysis' function, to eliminate studies that contributed the most to heterogeneity. This function conducts an influence analysis using the "Leave-One-Out" paradigm and produces data for four influence diagnostics (Baujat plot, Viechtbauer-Cheung influence characteristics plot, and forest plots for the leave-one-out analysis, sorted by effect size and I 2 ). The Baujat plot and forest plot sorted by I 2 were used to identify the studies with high heterogeneity contribution and low influence on the overall results. These studies represent outliers and were removed to reduce the amount of betweenstudy heterogeneity. Additionally, subgroup analyses were performed based on smoking status, geographical region, study design, period of publication, and sex.
The reason for using different models in the meta-analyses is that, while the fixed-effects model assumes that the estimated effects from the component studies in a meta-analysis come from a single homogeneous population, the random-effects model seeks to account for the fact that the study effect estimates are often more variable than assumed in the fixed-effects model [22].
For the analysis of smoking cessation impact on apolipoprotein levels, eight studies were retrieved. In total, five studies had complete information, with follow-up times of six weeks [88], eight weeks [89], 12 weeks [90,91], and 90 days [92]. Of the other studies, one included patients that had followed up from two to six weeks after smoking cessation [93], one reported results from smoking reduction [94] and one was a duplicate of another publication [95]. Due to the lack of a sufficient number of studies, no meta-analysis was performed to evaluate the effects of smoking cessation on apolipoprotein levels. The characteristics of the retrieved studies can be found in Tables 3 and 4.

Effects of smoking status on apolipoprotein AI levels
The pooled mean levels of apolipoprotein AI were 1.48 ± 0.009 g/L A.R. Kauss et al. in smokers and 1.54 ± 0.007 g/L in nonsmokers. The meta-analysis for apolipoprotein AI levels between smokers and nonsmokers was performed using data from 39 studies including 59 estimates . The fixed-effects model mean difference was − 0.038 (95% CI: − 0.041, − 0.035 g/L, I 2 =90%). Because of the large heterogeneity, sensitivity analyses were conducted, removing the studies that were driving the most heterogeneity. Data from 36 studies, including 55 estimates, were included in the sensitivity analysis. The fixed-effects model mean difference was − 0.036 (95% CI: − 0.039, − 0.033 g/L, I 2 =71%). To address the large heterogeneity further, exploratory subgroup analyses were performed. The results of these analyses can be found in Table 5. Stratification by region explained up to 28% points of the I 2 value when considering only studies run in the Americas (mean difference= − 0.062, 95% CI: − 0.073, − 0.051 g/L, I 2 = 43%), while most of the heterogeneity originated from Asian and African studies (I 2 =73%). Stratification by study design explained up to one percentage point (mean difference = − 0.034, 95% CI: − 0.039, − 0.029 g/L, I 2 = 70% in the cohort subgroup). The stratification by period of publication explained up to 59% points (mean difference= − 0.010, 95% CI: − 0.013, 0.033 g/L, I 2 = 12% in the 2000 s subgroup) and the stratification by smoking definition explained up to 20% points (mean difference= − 0.074, 95% CI: − 0.134, − 0.014 g/L, I 2 = 51% in the 15 + CPD subgroup). The stratification by sex explained up to 30% points (mean difference = − 0.040, 95% CI: − 0.044, − 0.036 g/L, I 2 = 41% in the women-only subgroup).
Applying the random-effects model to acknowledge the high interstudy heterogeneity resulted in a mean difference of − 0.073 (95% CI: − 0.088, − 0.058 g/L) for all studies and − 0.042 (95% CI: − 0.053, − 0.032 g/L) for studies included in the sensitivity analysis. Visual inspection of the funnel plots ( Fig. 2) revealed some asymmetries, with several large studies showing a significant negative effect. Funnel plot asymmetry was confirmed using Egger's regression test (intercept = − 0.62, 95% CI: − 1.17, − 0.07, t = − 2.21, p = 0.03) and may be an indication of publication bias.

Effects of smoking status on apolipoprotein AII levels
The pooled mean levels of apolipoprotein AII were 0.32 ± 0.007 g/L in smokers and 0.30 ± 0.004 g/L in nonsmokers. The meta-analysis of the effects of smoking on apolipoprotein AII levels included ten studies and 16 estimates [23,24,26,32,34,36,43,47,53,55] and found no differences in levels of apolipoprotein AII between smokers and nonsmokers (mean difference = − 0.003; 95% CI: − 0.007, 0.002 g/L, I 2 =66%). Considerable heterogeneity was found among studies; however, the studies identified through the sensitivity analysis did not report estimates for apolipoprotein AII levels. Therefore, subgroup analyses were performed using data from all studies. The detailed results of these analyses can be found in Table 6. The stratification by study design explained up to 25% points of the I 2 value (mean difference= 0.002, 95% CI: − 0.003, 0.007 g/L, I 2 = 41% in the cross-sectional studies subgroup). The stratified analysis by period of publication explained 14% points (mean difference = − 0.014, 95% CI: − 0.023, − 0.005 g/L, I 2 = 52% in the 1990 s subgroup). The major source of heterogeneity seemed to come from studies in the US (mean difference= − 0.008, 95% CI: − 0.027, 0.011 g/L I 2 = 73%) and studies involving only women (mean difference= 0.00, 95% CI: − 0.007, 0.008 g/L, I 2 = 74%). Applying the random-effects model estimated a mean difference of − 0.004 (95% CI: − 0.014, 0.005 g/L). The evaluation of the funnel plot ( Fig. 3) did not show evidence of publication bias and the results of Egger's regression test were not significant (intercept = 0.20, 95% CI: − 1.32, 1.73, t = 0.26, p = 0.80).

Effects of smoking status on apolipoprotein B levels
The pooled mean levels of apolipoprotein B were 1.06 ± 0.009 g/L in smokers and 0.98 ± 0.007 g/L in nonsmokers. The meta-analysis of apolipoprotein B levels in smokers versus nonsmokers included 40 studies and 63 estimates [23,24,27-30,32,34,35,37-42,44-46,48-58, 62,70]. Increased levels of apolipoprotein B were found in smokers using the fixed-effects model (mean difference= 0.056, 95% CI: 0.053, 0.059 g/L, I 2 =95%). The heterogeneity was high; therefore, sensitivity and subgroup analyses were performed. The sensitivity analysis included data from 36 studies and 59 estimates. The fixed-effects mean difference was 0.053 g/L (95% CI: 0.050, 0.055 g/L, I 2 =81%). The results of the subgroup analysis can be found in Table 7. The stratified analyses found that four percentage points of the I 2 value could be explained by including only cohort studies (mean difference= 0.057, 95% CI: 0.053, 0.61 g/L, I 2 = 77%), 14% points could be explained by limiting the studies to those performed in Europe (mean difference=              Visual evaluation of the funnel plot (Fig. 4) showed some evidence pointing toward publication bias; however, the results of Egger's regression test were not significant (intercept = − 0.62, 95% CI: − 1.30, 0.06, t = − 1.78, p = 0.08).

Effects of smoking status on the ratio of apolipoprotein B to AI
The pooled mean ratios of apolipoprotein B to AI were 0.62 ± 0.002 in smokers and 0.65 ± 0.001 in nonsmokers. The meta-analysis assessing the effects of smoking on the apolipoprotein B: AI ratio included 31 studies with 46 estimates [23,24,27-30,32,34,35,37-42,44-46,48-58, 62,70]. The fixed-effects model showed an increased ratio in smokers (mean difference= 0.047, 95% CI: 0.047, 0.048 g/L, I 2 =99%). The heterogeneity was high; thus, sensitivity and subgroup analyses were Table 2 Meta-analyses of smoking and apolipoprotein levels (g/L). All estimates. The estimates used can be found in Table 1. The estimates used can be found in Table 1.

Table 4
Characteristics of studies assessing levels of apolipoprotein levels after smoking cessation. Subjects did not receive any therapy and were not allowed to use nicotine replacement therapy.
After eight weeks of abstinence there were statistically significant increases in apolipoprotein AI (from 1.23 ± 0.05 g/L to 1.39 ± 0.03 g/L). Haziza et al.
2020 [92] USA Interventional 160 healthy male and female smokers aged 37.7 ± 11.45 Subjects were randomized to mTHS, mCC, or smoking abstinence for 5 days in confinement and 86 subsequent ambulatory days. Subjects in the smoking abstinence group were not allowed to use nicotine replacement therapy. performed. The sensitivity analysis included data from 28 studies and 42 estimates; however, the results did not show much reduction in heterogeneity (mean difference= 0.050, 95% CI: 0.049, 0.050 g/L, I 2 =97%). Heterogeneity did not vary much across subgroups. Considering only studies from the 2000 s resulted in the lowest heterogeneity; however, this revealed an opposite effect (mean difference= − 0.048,

Discussion
The meta-analyses performed comparing levels of apolipoprotein levels in smokers versus nonsmokers found that apolipoprotein AI and AII levels were higher in nonsmokers than in smokers. On the other hand, apolipoprotein B levels and apolipoprotein B:AI ratios were higher in smokers compared to nonsmokers. These findings describe an overall worse lipid profile in smokers compared to nonsmokers. A limited number of publications was found where the influence of smoking cessation on apolipoprotein levels or the ratio of apolipoprotein B to AI was assessed. For this reason, no meta-analysis was performed on the effects of smoking cessation and these endpoints. Nevertheless, the retrieved publications individually suggested that it is likely apolipoprotein AI and AII levels improve after quitting smoking.
Cigarette smoking can result in disease and disability and is the leading cause of preventable death [96]. Quitting greatly reduces the risk of developing smoking-related disease [97], but it has been proven difficult to achieve [98]. The FDA has published draft guidelines on modified risk tobacco products (MRTPs) [99]. These have led to the evaluation of risk reduction through the use of clinical risk markers [97], which should, in principle, be associated with smoking and be influenced by smoking cessation. A class of clinical risk endpoints usually assessed is lipids, but mostly with conventional measurements such as HDL-C and LDL-C [100]. Cigarette smoking is positively associated with increased levels of triglycerides and lower levels of (HDL-C) [6,101]. However, other than for HDL-C, no meta-analysis has been published on the effects of smoking and cessation on apolipoprotein levels.
Standard lipid analyses for cardiovascular risk assessment include measuring serum or plasma total cholesterol, triglycerides, and HDL-C after an overnight fast [102]. Data from the Framingham Offspring study indicate that LDL-C, small dense LDL-C, lipoprotein(a) or Lp(a), and HDL particle measurements add significant information about CVD risk to the standard lipid profile (summarized in [102]). Furthermore, it has been shown that cardiovascular risk assessment cannot rely solely on the determination of these measurements and that other lipid parameters can be more useful and more predictive of CVD [103,104]. For instance, the measurement of apolipoprotein AI in HDL particles by gel electrophoresis is important in assessing CVD risk and HDL functionality [102]. Evidence from epidemiologic data suggests that instead of measuring the cholesterol in LDL-C or HDL-C, measuring their respective apolipoproteins, apolipoprotein B and apolipoprotein AI, may improve coronary heart disease risk assessment, and in some observational and interventional studies, ratios of lipids and/or apolipoproteins have been better predictors of coronary heart disease risk than levels of any one lipid fraction [104][105][106]. According to our findings, smoking deteriorates lipid profiles by affecting the levels of all the apolipoprotein measurements.  Meta-analyses involve a two-step analysis approach, whereby in the first step, analyses of the data from the individual studies result in effect estimates and standard errors [107]. In the second step, these data are then combined. For this step, individual subject data are not generally available and effects are typically extracted from publications and then pooled [107]. Meta-analysis is a statistical method recommended by the Cochrane Collaboration [108] to combine individual results to make the best use of all available data and therefore increase the power of the analysis. Nonetheless, although meta-analyses are a robust method, they have limitations. These limitations are mostly related to the identification of studies, interstudy heterogeneity, and the availability of information [109]. For instance, in both the PubMed and Scopus searches and in the review of the reference lists, 66 publications were identified as assessing the influence of smoking status on apolipoprotein measurements, but only 49 had complete information that could be used in the analyses. Additionally, for the effects of smoking cessation, only five studies out of the eight retrieved contained useful information. Furthermore, substantial interstudy heterogeneity appeared in all analyses (I 2 values ranging from 66% in the apolipoprotein AII analysis to 99% in the apolipoprotein B:AI ratio analysis). The latter value is probably because ratios are usually not normally distributed, which could have added to the interstudy heterogeneity. It should be noted that the heterogeneity for apolipoprotein AI and B levels is mainly due to the size of the estimates, whereas for apolipoprotein AII levels, there is also heterogeneity in regard to the direction of the effect. The fact that the studies originated from diverse populations may have also contributed to the high interstudy heterogeneity, as many biological and environmental factors are known to influence apolipoprotein levels. For example, differences in lipoprotein metabolism [110], age [110,111], diet [110], BMI [112], and alcohol intake [110,112] have been shown to contribute to variation in serum apolipoprotein concentrations. For this reason, sensitivity analyses were conducted in which the studies that contributed most to the heterogeneity were removed. These studies included Casasnovas et al. [27], Pasupathi et al. [60], Sirisali et al. [59], and Sharma et al. [67]. The characteristics of the study populations in these studies may have differed from those in the other publications, resulting in increased heterogeneity. Participants in the study by Casasnovas et al. [27], for instance, had an average age of 19.9 ± 0.9 years, which is much lower than other studies. The results of the sensitivity analyses were consistent with the fixed analyses, and the interstudy heterogeneity was reduced by 19% and 14% for apolipoproteins AI and B, respectively, and by 2% for the apolipoprotein B/AI ratio. No sensitivity analysis was conducted for apolipoprotein AII as the excluded studies did not report data for this measure. Subgroup analyses and a random-effects model were implemented to account for the interstudy heterogeneity, both of which showed consistent results to the fixed analyses.

Conclusions
The meta-analyses show increased levels of apolipoproteins AI and AII in nonsmokers relative to smokers, while apolipoprotein B levels and apolipoprotein B/AI ratio were increased in smokers relative to nonsmokers. Based on the findings of the meta-analyses, smoking appears to negatively alter the lipid profile of current smokers relative to nonsmokers. These data need to be interpreted with caution, however, due to the high heterogeneity encountered in the analyses. Concerning smoking cessation and apolipoprotein levels, more data is needed to evaluate whether smoking cessation improves the levels of these