Abstract
We conducted a cross-sectional study to investigate the effects of the adenosine triphosphate-binding cassette transporter 1 (ABCA1) I883M and lipoprotein lipase (LPL) HindIII polymorphisms on lipid levels in patients with hyperlipidemia. A total of 533 patients were enrolled. Serum lipid parameters were determined by an automatic biochemistry analyzer. Genotyping of the ABCA1 I883M and LPL HindIII was carried out using the polymerase chain reaction-restriction fragment length polymorphism technique. Multiple linear regression analysis was used to estimate the associations between serum lipid levels and the genetic polymorphisms. The frequency distribution of the ABCA1 I883M and LPL HindIII polymorphisms did not deviate from Hardy-Weinberg equilibrium. The major finding of our regression analysis showed that neither the ABCA1 I883M nor the LPL HindIII polymorphism was associated with baseline serum lipid levels in the total population. However, among patients with elevated alanine aminotransferase (ALT) levels (ALT ≥ 40 U/L), carriers of the M allele of the ABCA1 gene had lower levels of high-density lipoprotein cholesterol (HDL-C) and higher levels of low-density lipoprotein cholesterol (LDL-C) after adjusting for age, sex, smoking status, alcohol consumption, education level, occupation, and work intensity (P < .05 for both). A test on interaction terms between the ABCA1 I833M polymorphism and ALT on HDL-C and LDL-C levels also remained significant (P = .001 and P = .014, respectively). Our data suggest that there are significant interactive effects between ABCA1 I883M and ALT levels on HDL-C and LDL-C levels. However, the LPL HindIII polymorphism did not influence lipid levels.
Keywords: ABCA1 I883M, LPL HindIII, polymorphism, hyperlipidemia, ALT
Introduction
Hyperlipidemia is a critical clinical and public health problem in developed and developing countries. It is a risk factor in the development and progression of atherosclerosis and increases the risk of cardiovascular diseases.1,2 It is well known that a high prevalence of hyperlipidemia may be caused by both environmental (eg, smoking status, medication use, weight, and physical activity levels) and genetic factors, as well as their interactions.1–3
Lipoprotein lipase (LPL) is a key enzyme in triglyceride hydrolysis.4 This enzyme plays a central role in lipid metabolism by hydrolyzing triglycerides in chylomicrons and very low-density lipoproteins (VLDLs).5–7 The human LPL gene is situated on chromosome 8p22, spans approximately 35 kb, and comprises of 10 exons and 9 introns encoding a 448-aminoacid mature protein.8–11 The LPL gene contains numerous variations, 80% of which occur in the coding regions.12 Most of these mutations have been associated with lipid traits, including hypertriglyceridemia and reduced high-density lipoprotein (HDL) levels, which can lead to more serious lipid disorders.13,14 Some evidence has demonstrated that the LPL polymorphism is correlated with serum lipid levels,15–18 though other research has provided contradictory results.19,20
Adenosine triphosphate (ATP)–binding cassette transporter 1 (ABCA1) is the prototypic member of the ATP-binding cassette (ABC) membrane transporter family. It mediates the efflux of cholesterol and phospholipids to lipid-poor apolipoproteins (Apo A1 and Apo E), which then form nascent HDL.21 Therefore, ABCA1 plays an important role in reverse cholesterol transport (RCT), a major pathway for removing excess cholesterol from peripheral tissues back to the liver22 and promoting HDL-C formation.23 The human ABCA1 gene, located on chromosome 9q31 and spanning approximately 149 kb in length, encompasses 50 exons and 49 introns.24,25 Mutations in this gene have been associated with Tangier disease and atherosclerotic cardiovascular disease.26,27 For instance, Hodoğlugil et al reported that the R219K and I883M polymorphisms were related to higher HDL-C levels.28 Jensen et al have shown that the I883M locus of the ABCA1 gene is associated with plasma HDL-C levels in female patients with coronary heart disease (CHD).29 Contrary to these conclusions, several other studies have suggested that the I883M polymorphism of the ABCA1 gene is not related to lipid levels.30,31
Thus, correlations between the 2 polymorphisms and serum lipid levels are still debated. The inconsistencies across studies may be partly due to different environmental factors and their interactions with genes masking the associations. It is well known that alanine aminotransferase (ALT) and aspartate aminotransferase (AST) are the most prevalent liver enzymes,32 and that ALT activity is related to lipid and carbohydrate metabolism.33 Therefore, it would be beneficial to explore the interaction between ALT levels and genetic variants on serum lipid levels.
In the present study, we primarily investigate the effects of the ABCA1 I883M and LPL HindIII polymorphisms on lipid levels and further verify whether interactions between the 2 polymorphisms and ALT affect lipid levels in a Chinese hyperlipidemic population.
Materials and Methods
Study Population
Seven hundred thirty-four patients with hyperlipidemia from Beijing and Anhui, China, were recruited and consented to participate. Of these, 533 patients were available for this study, as 201 were excluded due to missing information on genotypes and other parameters. Participants who met the following criteria of fasting serum lipid levels were considered to have hyperlipidemia: total cholesterol (TC) 5.72 to 8.32 mmol/L or LDL 3.64 to 6.50 mmol/L, as well as triglyceride (TG) greater than or equal to 1.70 mmol/L.34,35 Patients with any of these characteristics were excluded: (1) impaired hepatic function (aminotransferase levels >2 × normal and history of chronic liver disease, such as cirrhosis or alcohol abuse), (2) impaired renal function (serum creatinine levels >1.8 mg/dL, and/or a history of chronic renal disease, such as glomerulonephritis, chronic pyelonephritis, obstructive renal disease, or proteinuria), (3) diabetes mellitus (fasting blood glucose >126 mg/dL [7.0 mmol/L]), (4) raised thyroid-stimulating hormone levels (>5.0 μU/L), and (5) any medical conditions that might preclude successful completion. No participant had either symptomatic ischemic heart disease or any other vascular disease. Patients were required to discontinue lipid-lowering medication use at least 4 weeks prior to the start of the study. All participants gave their written informed consent, and the study protocol was approved by the ethics committee of the Institute of Biomedicine at Anhui Medical University.
Laboratory Determinations
After fasting overnight, patients had blood samples taken and stored in ethylenediaminetetraacetic acid (EDTA) tubes. In our analytical center, serum lipid parameters and liver function (ALT and AST) were measured by reflective photometry using an automatic biochemistry analyzer, but LDL-C was calculated by Friedewald equation. The automatic biochemistry analyzer based on spectrophotometric principle is one of the necessary instruments for clinical diagnostics in hospital. The TC and TG were determined enzymatically with the cholesterol oxidase/p-aminophenazone (PAP) method and the glycerophosphate oxidase/PAP method, respectively. The HDL-C determination is by phosphotungstic acid and magnesium chloride precipitation. Both ALT and AST are detected using the continuously monitoring method. Blood samples were drawn and collected in EDTA tubes and then centrifuged at 3000 rpm for 10 minutes to obtain the serum. In order to ensure optimum operation, the automatic biochemistry analyzer was warmed up 10 minutes after turning on. Serum samples were placed in a rack of test tubes, which was rotated through a stepper motor for positioning of blood samples through the measurement chamber of the analyzer. For example, serum cholesterol was estimated by mixing 0.03 mL serum sample with 3 mL of matching working reagent, and the absorbance of the assay mixture was measured by a spectrophotometer at 546 nm, against distilled water as a blank. Similarly, different working reagents for all biochemical indexes were used for their estimation. The intra- and interassay coefficients of variation were less than 5%.
Genotyping of the ABCA1 I883M and LPL HindIII
DNA was extracted from the EDTA-treated whole blood and stored at −20°C. Genotyping of the ABCA1 I883M and LPL HindIII was carried out using polymerase chain reaction-restriction fragment length polymorphism assays.
For the ABCA1 I883M polymorphism, the oligonucleotide primers were as follows: 5′-GAGAAGAGCCACCCTGGTTCCAACCAGAAGAGGAT-3′ forward and 5′-AGAAAGGCAGGAGACATCGCTT-3′ reverse. Polymerase chain reaction (PCR) amplification was carried out using 25 μL of PCR mixture in a PCR amplifier (Long Gene) as follows: an initial denaturation at 95°C for 5 minutes, followed by 30 cycles of denaturation at 95°C for 30 seconds, annealing at 65°C for 30 seconds, and extension at 72°C for 30 seconds, with a final extension at 72°C for 7 minutes producing a fragment of 132 bp. This fragment was subsequently cleaved by EcorV, creating fragments for the M allele of 132 bp and for the I allele of 97 and 35 base pair (bp). These allele fragments were subjected to electrophoresis on 3% agarose gel and visualized with ethidium bromide.
For the LPL HindIII polymorphism, the oligonucleotide primers were as follows: 5′-GATGTCACCTGGATAATCAAAG-3′ forward and 5′-CTTCAGCTAGACATTGCTAG-3′ reverse. The PCR amplification was carried out using 25 μL of PCR mixture in a PCR Amplifier (Long Gene) as follows: an initial denaturation at 94°C for 5 minutes, followed by 35 cycles of denaturation at 94°C for 1 minute, annealing at 56°C for 1 minute, and extension at 72°C for 1 minute, with a final extension at 72°C for 10 minutes producing a fragment of 355 bp. This fragment was subsequently cleaved by HindIII, creating fragments for the H− allele of 355 bp and for the H+ allele of 214 and 141 bp. These allele fragments were subjected to electrophoresis on 3% agarose gel and visualized with ethidium bromide. We selected 10% of all samples for replication, and concordance of 100% was repeated for all samples’ quality control.
Statistical Analysis
Epidata 3.1 software was used to establish a database of the patients, and the double entry method was used for data input and logic error detection. For continuous variables, data were presented as mean (standard deviation); for categorical variables, data were presented as percentages. The frequency of the ABCA1 and LPL alleles was determined by gene counting, and the standard goodness-of-fit test was used to test the Hardy-Weinberg equilibrium. Elevated ALT was defined as ALT of at least 40 U/L, while normal ALT was defined as ALT less than 40U/L.36,37 t Tests were used to compare the mean differences for continuous variables, and Pearson χ2 tests were used to evaluate the independence of categorical variables. Multiple linear regression analysis was used to estimate the effects of the ABCA1 and LPL polymorphisms on lipid levels at baseline with adjustments for sex, age, education level, occupation, work intensity, smoking status, and alcohol consumption. By convention, a P value less than .05 was considered to be significant. All statistical analyses were performed using the SPSS statistical package (version 19.0 for windows; IBM Inc, Armonk, New York).
Results
Clinical Data and Biochemical Characteristics of Study Participants
The study consisted of 533 unrelated adults with hyperlipidemia who resided in Beijing and Anhui, China. The study population had an average age of 52 ± 7.9 years. There were 180 (33.8%) men and 353 (66.2%) women. Baseline clinical and epidemiologic characteristics of the entire sample grouped by ABCA1 and LPL genotypes were summarized in Tables 1 and 2, respectively. Significant associations were detected between AST and the ABCA1 I883M genotypes (P = .048), as well as between glucose and the LPL HindIII genotypes (P = .047). Differences in other general characteristics and serum lipid levels across the genotype categories were not statistically significant (all P > .05). Additionally, as shown in Table 3, the genotypic distributions of the ABCA1 I883M and LPL HindIII polymorphisms did not deviate from the Hardy-Weinberg equilibrium (both P > .05).
Table 1.
Baseline Clinical and Epidemiologic Characteristics of Sample Grouped by ABCA1 Genotype.
| Variables | Total (N = 533) | Genotype | P Value | ||
|---|---|---|---|---|---|
| II (n = 34) | IM (n = 204) | MM (n = 295) | |||
| Age (years) | 52.27 ± 7.97 | 51.15 ± 8.14 | 52.62 ± 7.9 | 52.15 ± 8.01 | .57 |
| SBP (mm Hg) | 127.17 ± 20.6 | 126.85 ± 22.70 | 126.03 ± 20.12 | 128 ± 20.71 | .574 |
| DBP (mm Hg) | 77.8 ± 11.01 | 77.35 ± 12.40 | 77.02 ± 10.94 | 78.39 ± 10.89 | .382 |
| ALT (U/L) | 28.92 ± 19.84 | 31.88 ± 16.44 | 29.3 ± 25.50 | 28.32 ± 15.22 | .576 |
| AST (U/L) | 31.13 ± 11.02 | 35.47 ± 12.52 | 31.23 ± 11.09 | 30.56 ± 10.70 | .048 |
| GLU (mmol/L) | 5.65 ± 0.57 | 5.58 ± 0.56 | 5.66 ± 0.59 | 5.65 ± 0.55 | .742 |
| TG (mmol/L) | 1.86 ± 0.89 | 1.79 ± 0.83 | 1.83 ± 0.86 | 1.90 ± 0.91 | .604 |
| TC (mmol/L) | 6.46 ± 0.6 | 6.38 ± 0.50 | 6.44 ± 0.57 | 6.49 ± 0.62 | .478 |
| HDL-C (mmol/L) | 1.77 ± 0.5 | 1.87 ± 0.56 | 1.75 ± 0.49 | 1.77 ± 0.50 | .42 |
| LDL-C (mmol/L) | 3.79 ± 0.71 | 3.68 ± 0.69 | 3.82 ± 0.70 | 3.78 ± 0.72 | .496 |
| Sex, n(%) | |||||
| Male | 180 (33.8) | 15 (44.1) | 65 (31.9) | 100 (33.9) | .376 |
| Female | 353 (66.2) | 19 (55.9) | 139 (68.1) | 195 (66.1) | |
| Education, n(%) | |||||
| High school or lower | 170 (31.9) | 7 (20.6) | 72 (35.3) | 91 (30.8) | .199 |
| College or higher | 363 (68.1) | 27 (79.4) | 132 (64.7) | 204 (69.2) | |
| Occupation | N (%) | ||||
| Farmer | 251 (47.1) | 14 (41.2) | 99 (48.5) | 138 (46.8) | .721 |
| Nonfarmer | 282 (52.9) | 20 (58.8) | 105 (51.5) | 157 (53.2) | |
| Manual work intensity, n(%) | |||||
| Light | 250 (46.9) | 18 (52.9) | 90 (44.1) | 142 (48.1) | .828 |
| Moderate | 197 (37) | 11 (32.4) | 86 (42.2) | 100 (33.9) | |
| Heavy | 86 (16.1) | 5 (14.7) | 28 (13.7) | 53 (18) | |
| Cigarette smoking, n(%) | |||||
| No | 353 (66.2) | 19 (55.9) | 138 (67.6) | 196 (66.4) | .405 |
| Yes | 180 (33.8) | 15 (44.1) | 66 (32.4) | 99 (33.6 | |
| Alcohol drinking, n(%) | |||||
| No | 287 (53.8) | 14 (41.2) | 112 (54.9) | 161 (54.6) | .310 |
| Yes | 246 (46.2) | 2058.8) | 92 (45.1) | 134 (45.4) | |
Abbreviations: ABCA1, adenosine triphosphate-binding cassette transporter 1; ALT, alanine aminotransferase; AST, aspartate aminotransferase; DBP, diastolic blood pressure; GLU, glucose; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TG, triglycerides; TC, total cholesterol; SBP, systolic blood pressure.
Table 2.
Baseline Clinical and Epidemiologic Characteristics of Sample Grouped by LPL Genotype.
| Variables | Total (N = 533) | Genotype | P Value | ||
|---|---|---|---|---|---|
| H+H+ (n = 336) | H+H− (n = 182) | H−H− (n = 15) | |||
| Age (years) | 52.27 ± 7.97 | 52.33 ± 7.85 | 51.97 ± 8.25 | 54.53 ± 7.23 | .476 |
| SBP (mm Hg) | 127.17 ± 20.6 | 127.55 ± 20.84 | 125.74 ± 19.83 | 136 ± 23.20 | .153 |
| DBP (mm Hg) | 77.8 ± 11.01 | 77.49 ± 10.98 | 78.14 ± 11.11 | 80.67 ± 10.43 | .485 |
| ALT (U/L) | 28.92 ± 19.84 | 27.81 ± 14.84 | 30.6 ± 26.75 | 33.53 ± 18.66 | .205 |
| AST (U/L) | 31.13 ± 11.02 | 30.69 ± 10.90 | 31.54 ± 11.06 | 35.93 ± 12.46 | .163 |
| GLU (mmol/L) | 5.65 ± 0.57 | 5.69 ± 0.59 | 5.57 ± 0.52 | 5.76 ± 0.55 | .047 |
| TG (mmol/L) | 1.86 ± 0.89 | 1.87 ± 0.88 | 1.85 ± 0.91 | 1.89 ± 0.79 | .941 |
| TC (mmol/L) | 6.46 ± 0.6 | 6.46 ± 0.60 | 6.47 ± 0.60 | 6.44 ± 0.55 | .96 |
| HDL-C (mmol/L) | 1.77 ± 0.5 | 1.76 ± 0.50 | 1.78 ± 0.51 | 1.83 ± 0.57 | .859 |
| LDL-C (mmol/L) | 3.79 ± 0.71 | 3.77 ± 0.71 | 3.84 ± 0.69 | 3.68 ± 0.73 | .461 |
| Sex, n(%) | |||||
| Male | 180 (33.8) | 110 (32.7) | 63 (34.6) | 7 (46.7) | .515 |
| Female | 353 (66.2) | 226 (67.3) | 119 (65.4) | 8 (53.3) | |
| Education, n(%) | |||||
| High school or lower | 170 (31.9) | 113 (33.6) | 53 (29.1) | 4 (26.7) | .524 |
| College or higher | 363 (68.1) | 223 (66.4) | 129 (70.9) | 11 (73.3) | |
| Occupation, n(%) | |||||
| Farmer | 251 (47.1) | 168 (50) | 76 (41.8) | 7 (46.7) | .201 |
| Nonfarmer | 282 (52.9) | 168 (50) | 106 (58.2) | 8 (53.3) | |
| Manual work intensity, n(%) | |||||
| Light | 250 (46.9) | 158 (47) | 86 (47.3) | 6 (40) | .535 |
| Moderate | 197 (37) | 130 (38.7) | 62 (34.1) | 5 (33.3) | |
| Heavy | 86 (16.1) | 48 (14.3) | 34 (18.7) | 4 (26.7) | |
| Cigarette smoking, n(%) | |||||
| No | 353 (66.2) | 225 (67) | 120 (65.9) | 8 (53.3) | .549 |
| Yes | 180 (33.8) | 111 (33) | 62 (34.1) | 7 (46.7) | |
| Alcohol drinking, n(%) | |||||
| No | 287 (53.8) | 173 (51.5) | 105 (57.7) | 9 (60) | .358 |
| Yes | 246 (46.2) | 163 (48.5) | 77 (42.3) | 6 (40) | |
Abbreviations: ALT, alanine aminotransferase; AST, aspartate aminotransferase; DBP, diastolic blood pressure; GLU, glucose; HDL-C, high-density lipoprotein cholesterol; LPL, lipoprotein lipase; LDL-C, low-density lipoprotein cholesterol; TG, triglycerides; TC, total cholesterol; SBP, systolic blood pressure;.
Table 3.
Hardy-Weinberg Equilibrium Tests for ABCA1 I883M and LPL HindIII Polymorphisms.
| Gene | n | Observed Frequency | Expected Frequency | Cell χ2 | P Value |
|---|---|---|---|---|---|
| ABCA1 I883M | |||||
| II | 34 | 34 | 34.7 | 0.026 | .8720 |
| IM | 204 | 204 | 202.6 | ||
| MM | 295 | 295 | 295.7 | ||
| LPL HindIII | |||||
| H+H+ | 336 | 336 | 342.08 | 2.733 | .0980 |
| H+H− | 182 | 182 | 169.84 | ||
| H−H− | 15 | 15 | 21.08 | ||
Abbreviations: ABCA1, adenosine triphosphate-binding cassette transporter 1; LPL, lipoprotein lipase.
Associations of ABCA1 and LPL Genotypes With ALT, AST, and Serum Lipid Levels at Baseline by Linear Regression Model
The results of the multiple linear regression analysis were shown in Table 4. This demonstrated that neither the ABCA1 I883M nor the LPL HindIII polymorphism was associated with baseline serum lipid levels (all P > .05). However, AST concentration was significantly different across genotypes of the ABCA1 gene. Compared with II genotype individuals, IM and MM genotype individuals had lower AST levels (P = .044 and P = .013, respectively). These observed differences remained significant after adjustment for confounding factors, including age, sex, smoking status, alcohol consumption, education level, occupation, and work intensity(P = .025 and P = .004, respectively).
Table 4.
Association Between ABCA1 I883M Polymorphism and Baseline ALT, AST, and Serum Lipid Levels by Linear Regression Models.a
| Variable | ABCA1 I883M | N | Mean (SD) | Unadjusted | Adjusted | ||||
|---|---|---|---|---|---|---|---|---|---|
| β | SE | P | β | SE | P | ||||
| ALT | II | 34 | 31.88 (16.44) | Ref | Ref | ||||
| IM | 204 | 29.3 (25.50) | −2.578 | 4.527 | .57 | −1.701 | 4.512 | .707 | |
| MM | 295 | 28.32 (15.22) | −1.784 | 1.39 | .2 | −1.669 | 1.313 | .204 | |
| II | 34 | 31.88 (16.44) | Ref | Ref | |||||
| IM+MM | 499 | 28.72 (20.05) | −3.163 | 3.518 | .369 | −2.753 | 3.398 | .418 | |
| AST | II | 34 | 35.47 (12.52) | Ref | Ref | ||||
| IM | 204 | 31.23 (11.09) | −4.24 | 2.095 | .044 | −4.267 | 1.893 | .025 | |
| MM | 295 | 30.56 (10.70) | −2.454 | 0.987 | .013 | −2.537 | 0.87 | .004 | |
| II | 34 | 35.47 (12.52) | Ref | Ref | |||||
| IM+MM | 499 | 30.84 (10.86) | −4.635 | 1.945 | .018 | −4.764 | 1.707 | 0.005 | |
| TG | II | 34 | 1.79 (0.83) | Ref | Ref | ||||
| IM | 204 | 1.83 (0.86) | 0.034 | 0.159 | .833 | 0.042 | 0.161 | .793 | |
| MM | 295 | 1.90 (0.91) | 0.055 | 0.082 | .508 | 0.057 | 0.082 | .488 | |
| II | 34 | 1.79 (0.83) | Ref | Ref | |||||
| IM+MM | 499 | 1.87 (0.89) | 0.081 | 0.158 | .611 | 0.086 | 0.158 | .586 | |
| TC | II | 34 | 6.38 (0.50) | Ref | Ref | ||||
| IM | 204 | 6.44 (0.57) | 0.058 | 0.105 | .58 | 0.043 | 0.106 | .682 | |
| MM | 295 | 6.49 (0.62) | 0.054 | 0.056 | .336 | 0.055 | 0.056 | .327 | |
| II | 34 | 6.38 (0.50) | Ref | Ref | |||||
| IM+MM | 499 | 6.47 (0.60) | 0.087 | 0.107 | .413 | 0.09 | 0.107 | .4 | |
| HDL-C | II | 34 | 1.87 (0.56) | Ref | Ref | ||||
| IM | 204 | 1.75 (0.49) | −0.124 | 0.094 | .19 | −0.138 | 0.084 | .101 | |
| MM | 295 | 1.77 (0.50) | −0.05 | 0.047 | .282 | −0.055 | 0.038 | .148 | |
| II | 34 | 1.87 (0.56) | Ref | Ref | |||||
| IM+MM | 499 | 1.76 (0.50) | −0.11 | 0.09 | .222 | −0.041 | 0.053 | .445 | |
| LDL-C | II | 34 | 3.68 (0.69) | Ref | Ref | ||||
| IM | 204 | 3.82 (0.70) | 0.147 | 0.13 | .261 | 0.149 | 0.123 | .225 | |
| MM | 295 | 3.78 (0.72) | 0.05 | 0.065 | .443 | 0.059 | 0.06 | .328 | |
| II | 34 | 3.68 (0.69) | Ref | Ref | |||||
| IM+MM | 499 | 3.80 (0.71) | 0.119 | 0.126 | .346 | 0.13 | 0.117 | .265 | |
Abbreviations: ABCA1, adenosine triphosphate-binding cassette transporter 1; ALT, alanine aminotransferase; AST, aspartate aminotransferase; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TG, triglycerides; TC, total cholesterol; SE, standard error.
aAdjusted for age, sex, smoking, alcohol, education, occupation, and working intensity.
Interactive Effects of ABCA1 I833M Polymorphism and ALT on Lipid Levels
The associations between genotypes and serum lipid levels stratified by ALT level were displayed in Table 5. In the elevated ALT group, our findings showed that, after adjustment for confounding factors, IM and MM genotype individuals had significantly lower levels of serum HDL-C (both P = .002)and significantly higher levels of serum LDL-C (P = .001 and P = .003, respectively) when compared to II genotype carriers. Nevertheless, in the normal ALT group, we did not observe an association of the ABCA1 I883M genotypes with either HDL-C or LDL-C levels (P > .05 for both). A further test on interaction terms between the ABCA1 I833M polymorphism and ALT on HDL-C and LDL-C levels still remained significant (P = .001 and P = .014, respectively).
Table 5.
Interactive Effects of ABCA1 Polymorphism and ALT on Lipid Levels.a
| ABCA1 I883M | ALT < 40 | ALT ≥ 40 | P for Interaction | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Mean (SD) | Adjusted | Mean (SD) | Adjusted | ||||||
| β | SE | P | β | SE | P | ||||
| HDL-C | |||||||||
| II | 1.70 (0.43) | Ref | 2.28 (0.66) | Ref | |||||
| IM | 1.76 (0.51) | .034 | 0.095 | .72 | 1.67 (0.40) | −.635 | 0.193 | .002 | .002 |
| MM | 1.77 (0.51) | .021 | 0.044 | .635 | 1.75 (0.46) | −.273 | 0.086 | .002 | .002 |
| II | 1.70 (0.43) | Ref | 2.28 (0.66) | Ref | |||||
| IM+MM | 1.77 (0.51) | .028 | 0.089 | .749 | 1.72 (0.44) | −.557 | 0.157 | .001 | .001 |
| LDL-C | |||||||||
| II | 3.87 (0.61) | Ref | 3.21 (0.68) | Ref | |||||
| IM | 3.80 (0.71) | −.035 | 0.144 | .808 | 3.97 (0.61) | .866 | 0.226 | .001 | .005 |
| MM | 3.79 (0.71) | −.02 | 0.069 | .773 | 3.72 (0.75) | .362 | 0.114 | .003 | .037 |
| II | 3.87 (0.61) | Ref | 3.21 (0.68) | Ref | |||||
| IM+MM | 3.79 (0.71) | −.042 | 0.137 | .757 | 3.82 (0.70) | .748 | 0.222 | .001 | .014 |
| TG | |||||||||
| II | 1.84 (0.83) | Ref | 1.66 (0.87) | Ref | |||||
| IM | 1.77 (0.83) | −.1 | 0.182 | .582 | 2.13 (0.97) | .542 | 0.387 | .171 | .146 |
| MM | 1.82 (0.88) | −.008 | 0.093 | .931 | 2.30 (1.01) | .299 | 0.184 | .111 | .07 |
| II | 1.84 (0.83) | Ref | 1.66 (0.87) | Ref | |||||
| IM+MM | 1.80 (0.86) | −.038 | 0.18 | .834 | 2.23 (0.99) | .607 | 0.355 | .091 | .08 |
| TC | |||||||||
| II | 6.41 (0.49) | Ref | 6.30 (0.52) | Ref | |||||
| IM | 6.41 (0.56) | .007 | 0.123 | .957 | 6.59 (0.61) | .34 | 0.23 | .149 | .265 |
| MM | 6.47 (0.60) | .037 | 0.064 | .567 | 6.58 (0.72) | .199 | 0.121 | .108 | .421 |
| II | 6.41 (0.49) | Ref | 6.30 (0.52) | Ref | |||||
| IM+MM | 6.45 (0.59) | .032 | 0.123 | .794 | 6.59 (0.68) | .405 | 0.22 | .069 | .329 |
Abbreviations: ALT, alanine aminotransferase; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TG, triglyceride; TC, .total cholesterol.
aAdjusted for age, sex, smoking, alcohol, education, occupation, and working intensity.
Discussion
In the current study, associations between the ABCA1 I883M and LPL HindIII polymorphisms and serum lipid profiles were tested in Chinese patients with hyperlipidemia. Although our initial findings indicated that these polymorphisms did not influence lipid levels, associations between the ABCA1 I883M genotypes and serum lipid profiles were dependent on ALT levels.
The LPL is found predominantly in muscle cells, adipocytes, and macrophages as the key rate-limiting enzyme in the TG metabolic pathway, affecting all classes of lipoprotein particles.5,6 The LPL hydrolyses core TG from circulating chylomicrons and VLDL, which are the neither degraded by the liver or converted to LDL particles by hepatic lipase.38,39 The LPL gene mutation can impact the catalytic activity and expression of LPL. The HindIII polymorphism of LPL, located on intron 8 and created by a thymine (T) to guanine (G) substitution, affects LPL activity through an unknown mechanism. Previous studies have reported that the HindIII polymorphism may affect the transcription or translation of the LPL gene by interacting with regulatory elements in the 3′ region.40 Senti et al have reported that, for sedentary people, H+H+ genotype smokers had higher TG levels and lower HDL-C levels when compared to smokers carrying the H− allele, though there was no such relationship among nonsmokers.15 Peacock et al also found a significant increase in plasma TG levels in smokers bearing the H+H+ genotype, with this effect even more pronounced in women.16 These studies showed that the association between the HindIII H+H+ genotype and lipid levels may be modified by environmental factors. Jemaa et al hold that the HindIII and PuvII polymorphisms are closely related to lipid metabolism. The TC and TG levels were significantly higher in patients carrying the H+ allele, while HDL-C levels were lower in H+H− genotype patients.17 Anjana et al suggested that the HindIII polymorphism was significantly associated with elevated levels of plasma TG and reduced plasma HDL levels.18 However, contradictory to these results, our data showed that baseline serum lipid profiles were not significantly different across the 3 HindIII genotypes before or after adjustment for confounding factors.
ABCA1, a 2261-aminoacid integral membrane protein, is located at the plasma membrane and in trans-Golgi–derived vesicles. It is thought to promote HDL formation and cholesterol efflux.41,42 The genetic polymorphisms of ABCA1 could alter the transcription and expression of the protein, thereby affecting RCT and causing lipid metabolism disorders.43,44 Chawla et al provided evidence that peroxisome proliferator-activated receptor (PPAR)γ induces ABCA1 expression and cholesterol removal from macrophages through a transcriptional cascade mediated by the nuclear receptor LXRα. They proposed that PPARγ coordinates a complex physiologic response to oxLDL that involves particle uptake, processing, and cholesterol removal through ABCA1.45 The rs4149313 of the ABCA1 polymorphism is a transversion mutation with a G to A substitution at position 883 in exon 18, which leads to changes in the encoded protein of 883 amino acids from isoleucine to methionine and was studied widely for its association with lipid levels.25,46 Hodoğlugil et al reported that the R219K and I883M polymorphisms were related to higher HDL-C levels,28 whereas Jensen et al have shown that the I883M locus of the ABCA1 gene is associated with plasma HDL-C levels in female patients with CHD.29 However, our investigation, as well as multiple others,30,31 did not replicate such associations. This discrepancy might be caused by differences in the genetic and environment background of the study patients.
Interestingly, in our study, the effects of the ABCA1 I883M variants on HDL-C and LDL-C were only seen in patients with elevated ALT, demonstrating the complexity of multiple genetic and environmental effects acting simultaneously on lipid traits. Many studies have reported that certain lipid-related genetic variants interact with environmental factors, including body mass index, alcohol consumption, and cigarette smoking, to modify blood lipid profiles.1,3 However, literature about interactions between the ABCA1 polymorphism and ALT levels on blood lipid profiles was limited. This is the first study reporting on interactions between the ABCA1 I883M polymorphism and ALT status on lipid traits. For patients with high ALT, carriers of the M allele of the ABCA1 gene had lower levels of HDL-C and higher levels of LDL-C. This ALT activity level correlates with obesity,47 which reflects hepatocellular injury and is the most frequent test for screening and monitoring patients with nonalcoholic fatty liver disease (NAFLD).48 Research has shown that hyperlipidemia is a primary risk factor for NAFLD.49 A study by Iqbal et al has confirmed that increased cholesterol and TG levels result in increased ALT and AST levels, because high cholesterol and LDL-C are contributing factors for the development of hepaticlipidosis and disturb normal function of the liver.50 ABCA1 mediates the initial step of RCT and the onset of HDL generation, by which excess cholesterol in peripheral tissues is transported to the liver51 and potentially damage the liver function (elevated ALT and AST). Thus, ABCA1M allele may affect the transcription and expression of their protein, thereby interacting with elevated ALT on serum lipid levels.
A limitation of our present study was that all of our participants had hyperlipidemia, mostly involving primary hyperlipidemia, but possibly a few idiopathic patients. Thus, we could not determine whether our findings were limited to those with hyperlipidemia or whether they could be generalized to individuals with normal lipid levels, as well.
In conclusion, our results suggest that the ABCA1 I883M and LPL HindIII polymorphisms alone have no effect on lipid levels. Nevertheless, the ABCA1 polymorphism was significantly associated with HDL-C and LDL-C levels among patients with elevated ALT levels.
Acknowledgment
We gratefully acknowledge the assistance and cooperation of the faculty and staff of Anhui Medical University and thank all of the participants in our study.
Authors’ Note: This study was conducted in accordance with the current regulations of the People’s Republic of China.
Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the National Key Research and Development Program (grant nos 2016YFC0903100 and 2016YFC0903102), the National Natural Science Foundation of China (nos 81373484, 81141116, and 30700454), the Academic Top Talents Funding of University (no gxbjZD2016008), and the Academic Leader and Reserve Candidate of Anhui Province (no 05010543).
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