Published online before print March 24, 2003, doi: 10.1161/01.HYP.0000064944.60569.87
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(Hypertension. 2003;41:1041.)
© 2003 American Heart Association, Inc.
Scientific Contributions |
An Acyl-CoA Synthetase Gene Family in Chromosome 16p12 May Contribute to Multiple Risk Factors
From the National Cardiovascular Center, Suita, Osaka, Japan.
Correspondence to Naoharu Iwai, MD, Research Institute, National Cardiovascular Center, 5-7-1 Fujishirodai, Suita, Osaka 565-8565, Japan. E-mail niwai{at}res.ncvc.go.jp
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Abstract |
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We recently reported that genetic polymorphisms of SAH, an acyl-CoA synthetase for fatty acids, might contribute to multiple risk factors, especially hypertriglyceridemia. There are at least 4 members in this SAH gene family, SAH, MACS1, MACS2, and MACS3, and these 4 members are clustered in human Ch16p12. It is possible either that the previously observed associations were due to linkage disequilibrium with truly important polymorphisms in other members of the SAH gene family or that other polymorphisms in this gene family may also influence multiple risk factors. Thus, we performed association studies between genetic polymorphisms in this SAH region and multiple risk factors, using a large cohort representing the general population in Japan. The L513S polymorphism in MACS2 was shown to significantly influence the triglyceride level and the waist-to-hip ratio. The previously observed associations between an SAH polymorphism and the waist-to-hip ratio appear to be due to linkage disequilibrium with the L513S polymorphism. Haplotype analysis indicated that a haplotype defined by the I/D polymorphism of SAH and the L513S polymorphism in MACS2 was highly significantly associated with the triglyceride level. This study confirmed the importance of this chromosomal region in the pathogenesis of hypertriglyceridemia and visceral obesity.
Key Words: epidemiology • fatty acids • genetics • hyperlipidemia • obesity
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Introduction |
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Differential screening was used to isolate SAH (Spontaneously hypertensive rat–Clone A–Hypertension-associated) from a genetically hypertensive rat strain, spontaneously hypertensive rat (SHR).1 The expression of SAH in the kidneys of SHR is markedly higher than that in the kidneys of a normotensive control stain, Wistar-Kyoto rat. The rat SAH is localized on chromosome 1 near the most prominent QTL for blood pressure and had been expected to contribute to hypertension in SHR.2,3 However, subsequent congenic analysis excluded rat SAH from the genes that contribute to hypertension in SHR.4,5
Recently, SAH protein has been reported to be significantly homologous to bovine xenobiotic-metabolizing medium-chain fatty acids: CoA ligase.6 We revealed that human SAH had acyl-CoA synthetase activity toward medium chain fatty acids and that a genetic polymorphism of SAH might contribute to multiple risk factors, including hypertriglyceridemia, obesity, and hypertension.7 It is likely that a genetic polymorphism of SAH might influence triglyceride metabolism, energy expenditure, and fat metabolism by influencing fatty acid metabolism.
A homology search of SAH in the human genome indicates that there are at least 4 members in this SAH gene family, SAH, MACS1, MACS2, and MACS3 (Figure). Moreover, these 4 appear to be clustered in chromosome 16p12 (see Results). It is possible that the associations seen between the SAH polymorphism and multiple risk factors in the preceding study7 might be due to linkage disequilibrium with genetic polymorphisms in other members of this gene family and that genetic polymorphisms in other members of this gene family might also contribute to multiple risk factors. Thus, to extend our previous work, we searched for genetic variations in this chromosomal region and performed association studies between polymorphisms in this region and multiple risk factors using a large cohort representing the general population in Japan.
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Methods |
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DNA Studies
Genomic DNA from 36 subjects was used for sequence screening for polymorphisms. The promoter region and all of the exons of the MACS18 (Medium Chain Acyl-CoA Synthetase 1; MACS1) gene were sequenced according to the human draft sequence. The genome structures of MACS2 (GenBank accession; AX451437) and MACS3 (GenBank accession; AK000588) had not been determined at the beginning of the present study. We determined exon-intron boundaries on the basis of homology to SAH and MACS1 and amplified intronic sequences by primers residing on the neighboring exons to determine the flanking sequences of exons. Based on the flanking sequences, all of the coding exons of MACS2 and MACS3 were amplified and sequenced. Primer sequences can be provided on request. The polymorphisms were determined by use of the TaqMan system (PE Applied Biosystems). The sequences of the primers and probes used in the TaqMan method can be provided on request.
The expression levels of MACS1, MACS2, MACS3, and SAH mRNA were assessed by PCR, with the use of a human cDNA panel (Clontech) with 2 independent sets of primers.
Subjects
The selection criteria and design of the Suita Study have been described previously.7 The genotypes were determined in 1976 consecutive subjects (written informed consent was obtained), who constituted the latter half of the study population in the preceding study. The study protocol was approved by the institutional ethics committee.
The characteristics of the subjects analyzed in the present study are summarized in Table 1, according to L513S polymorphism of MACS2. Hypertension was defined as systolic blood pressure >140 mm Hg, diastolic blood pressure >90 mm Hg, or the current use of antihypertensive medication. Total cholesterol and triglyceride levels were determined by enzymatic methods and kits (L-TC WAKO, Wako Pure Chemical, and Clinimate TG-2, Daiichi Chemicals). Homeostasis model assessment of insulin resistance (HOMA) was calculated as follows9: HOMA=[fasting insulin (µU/mL)x fasting glucose (mmol/L)]/22.5. Total immunoreactive insulin was measured by a kit (TOSOH), with the use of a 2-site immunoenzymometric assay.
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Statistical Analysis
Values are expressed as mean±SEM. All statistical analyses were performed with the JMP statistical package (SAS Institute Inc). Multiple linear regression and multiple logistic analyses were performed with other covariates. Residuals of the waist-to-hip ratio and triglycerides were calculated by adjusting for age, gender, alcohol consumption (ethanol mL/d), and smoking (cigarettes/d). In some settings, the probability value was corrected (Pc) by the Bonferroni method. Principal component analysis was performed on the basis of correlations.
Linkage disequilibrium10 and haplotype analyses were performed using the SNPAlyze statistical package (Dynacom Inc, http://www. dynacom.co.jp/; accessed March 5, 2003). Haplotype estimation was performed by the expectation-maximization algorithm.11 To measure linkage disequilibrium between SNPs, Lewontin’s D' was calculated.12
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Results |
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Confirmation of the SAH Gene Family
A BLAST search revealed the existence of 3 transcripts homologous to SAH, namely MACS1 to MACS3. The complete genome structure of MACS1 has been described previously.8 The genome structure of MACS3 and part of the genome structure of MACS2 have not been reported, and we determined flanking sequences of coding exons of MACS2 and MACS3 for sequence screening of polymorphisms.
The polymorphisms found in the present study are summarized in Table 2. Polymorphisms in introns were not studied in detail and are not included in Table 2.
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The expression of MACS1 was not detected, as described below, which may downplay the importance of this gene. The AC repeat polymorphism in the promoter may not be suitable for high-throughput genotyping and was neglected in the present study. The polymorphisms in exons 8, 11, 12, and 13 were in complete linkage disequilibrium in the 36 subjects sequenced, and we selected the exon 12 polymorphism for the association study.
We found 3 polymorphisms in the coding region of MACS2, which were selected for the association study. The L513S polymorphism may have some functional meaning, since hydrophobic leucine is replaced by hydrophilic serine.
We found 4 polymorphisms in the coding region of MACS3. The Q159H (exon 3) and P353R (exon 7 to 1) polymorphisms were in complete linkage disequilibrium with the T534M (exon 12) and H361R (exon 7 to 2) polymorphisms, respectively. Thus, we selected the H361R (exon 7 to 2) and T534M (exon 12) polymorphisms for the association study. We also determined 2 polymorphisms of SAH, I/D polymorphism in the promoter and A/G polymorphism in intron 12, which were concluded to be associated with multiple risk factors in the preceding study in 4039 subjects.7
Linkage disequilibrium among these polymorphisms is shown in Table 3. Although the locus for MACS3 has not been clarified, strong linkage disequilibrium between the MACS3 and MACS2 polymorphisms indicates that MACS3 may reside in this human chromosome 16p12 region near the MACS2 locus.
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Expression of the MACS Gene Family
RT-PCR analysis of expression levels of MACS1, MACS2, and MACS3 and SAH revealed that MACS2 and MACS3 and SAH were expressed mainly in the kidney and liver. However, we could not detect PCR product from MACS1 in any of the tissues examined including the spleen, thymus, prostate, testis, ovary, small intestine, colon, lymph node, heart, brain, placenta, lung, liver, skeletal muscle, kidney, and pancreas.
Association Study
Association studies between the polymorphisms in Table 2 and various phenotypes in the 1976 subjects revealed that the L513S polymorphism in MACS2 strongly influenced triglycerides (TG), HDL cholesterol, waist-to-hip ratio (W/H), and body mass index (BMI) (Table 1). More intriguingly, an index for insulin resistance (HOMA) was influenced by the L513S polymorphism. Since members of the SAH gene family appear to have acyl-CoA synthetase activity toward fatty acids, it is likely that principal phenotypes influenced by this gene family may be the triglyceride level and/or visceral obesity (waist-to-hip ratio).
The effects of other polymorphisms on the triglyceride level and W/H ratio are indicated in Table 4. Residuals of the triglyceride level (R-TG) and W/H ratio (R-W/H) were calculated by adjusting for age, sex, alcohol consumption, and smoking. Residuals of the triglyceride level were also calculated after excluding subjects with hypolipidemic drugs to correctly assess the influence of polymorphisms on the triglyceride level (R-TG'). The influence of a SAH polymorphism on triglycerides and W/H ratio, which was evident in 4039 subjects in the preceding study, was weak in the present group of 1976 subjects, who comprised a subset (latter part) of the preceding 4039 subjects.
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To avoid the problems of multiple testing, a principal component analysis was also performed. After performing a correlation analysis among TG, HDL, W/H, and BMI, the principal components were identified. The first principal component explained 50.5% of the total variance, and the influence of genotype on this component was analyzed by 1-way ANOVA (Table 4). The first principal component was defined as [0.422 (TG)+0.499 (HDL)+0.531 (W/H)+0.539 (BMI)]. Although the pathophysiological meaning of this component is difficult to discern at a glance, it was significantly affected by the L513S polymorphism (Table 4).
To clarify the possible contribution of polymorphisms other than the L513S polymorphism to triglycerides and W/H ratio, diplotypes defined by L513S and another polymorphism were determined in the study population. The effects of various haplotypes on triglycerides and W/H ratio were also evaluated.
There are 4 haplotypes defined by the L513S and I/D (SAH) polymorphisms: L513-D (haplotype1, allele frequency 0.559, 95% CI, 0.533 to 0.585), L513-I (haplotype2, allele frequency 0.200, 95% CI, 0.180 to 0.216), S513-D (haplotype3, allele frequency 0.136, 95% CI, 0.119 to 0.155), and S513-I (haplotype4, allele frequency 0.105, 95% CI, 0.086 to 0.120). The effects of the diplotypes defined by these 4 haplotypes on the triglyceride level are shown in Table 5. One-way ANOVA indicated that the diplotype had significant effects on R-TG (P=0.0012) and R-TG' (P=0.0002). As shown in Table 5, the diplotype 33 had significantly higher R-TG and R-TG' levels. Thus, we recategorized the 10 diplotypes into 2 groups, that is, diplotype 33 and others. The influence of this diplotype 33 on the triglyceride level was highly significant even after correction by the Bonferroni method (P<0.0001 and Pc<0.0032, Table 4).
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Discussion |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
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We recently reported that genetic polymorphisms in SAH influenced multiple risk factors, including TG, HDL cholesterol, BMI, W/H ratio, and blood pressure status.7 Since then, 3 other genes with high homology to SAH have been identified to cluster in the SAH region, chromosome16p12. Thus, it is possible either that the previously observed associations were due to linkage disequilibrium with truly important polymorphisms in other members of the SA gene family or that other polymorphisms in this gene family may also influence multiple risk factors.
In the present study, to evaluate the above-mentioned hypotheses, we performed extensive association studies between genetic polymorphisms in this region and multiple risk factors using a large cohort representing the general population in Japan. The L513S polymorphism in MACS2 was shown to significantly influence TG, HDL, W/H, BMI, and HOMA index.
Because the L513S genotype appeared to influence various phenotypes including TG, HDL, W/H, and BMI, a principal component analysis was performed to avoid the problems of multiple testing. The L513S polymorphism had a highly significant influence on the first principal component. However, the pathophysiological meaning of this component is difficult to discern.
The members of the SAH gene family seem to have acyl-CoA synthetase activity toward medium chain fatty acids.6–8 Thus, it is logically highly likely from the biological viewpoint that principal phenotypes influenced by this gene family may be the TG level and/or visceral obesity. Therefore, we studied the influence of polymorphisms on the TG level and W/H ratio (an excellent index of visceral obesity) (Table 4). Diplotype 33 had a highly significant influence on the TG level and the L513S polymorphism of MACS2 had a weak but significant influence on the W/H ratio. Therefore, most of the previously observed associations between a SAH polymorphism and multiple risk factors appear to be due to linkage disequilibrium with the L513S polymorphism and haplotype 3.
In conclusion, the present study confirmed the importance of this chromosomal region, especially MACS2 and SAH, in the pathogenesis of hypertriglyceridemia and visceral obesity. Intriguingly, this locus has been reported to be one of the suggestive loci for body mass index in the Framingham Heart Study.13
Perspectives
Human MACS1, human SAH, and bovine counterparts have been reported to act as acyl-CoA synthetases for various fatty acids, especially medium-chain fatty acids (MCFA).6–8,14 MCFA are abundant in milk, coconut oil, and various synthetic oils. The activation of MCFA takes place mostly in the mitochondrial matrix by acyl-CoA synthetase for MCFA. Most of the MCFA incorporated into hepatocytes is subject to ß-oxidation. Some of the acyl-CoA produced during MCFA oxidation is directed toward ketone body production, and the rest is directed to de novo synthesis of long-chain fatty acids, which are then incorporated into triglycerides or other complex lipids.15,16 Recently, it has been proposed that medium-chain triglycerides may help to prevent obesity.17 Therefore, it is highly likely that members of the SAH gene family (possible acyl-CoA synthetases for MCFA) may play some important roles in triglyceride metabolism, energy expenditure, fat metabolism, and, therefore, insulin resistance. However, the precise in vivo functions of the members of this gene family and the functional properties of the L513S polymorphism remain to be clarified and await further investigation.
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Acknowledgments |
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This study was supported by the Program for Promotion of Fundamental Studies in Health Science of the Organization for Pharmaceutical Safety and Research of Japan. We express our gratitude to Prof Soichiro Kitamura for his support of this study. We also thank Ms Akemi Fukumoto for technical assistance.
Received December 10, 2002; first decision January 10, 2003; accepted February 21, 2003.
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