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Originally published In Press as doi:10.1194/jlr.M500521-JLR200 on February 7, 2006

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Journal of Lipid Research, Vol. 47, 944-952, May 2006
Copyright © 2006 by American Society for Biochemistry and Molecular Biology

Zinc Finger Protein 202, genetic variation, and HDL cholesterol in the general population

Maria C. Stene*, Ruth Frikke-Schmidt*, Børge G. Nordestgaard{dagger},§ and Anne Tybjærg-Hansen1,*,§

* Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
{dagger} Department of Clinical Biochemistry, Herlev University Hospital, Copenhagen, Denmark
§ Copenhagen City Heart Study, Bispebjerg University Hospital, Copenhagen, Denmark

Published, JLR Papers in Press, February 7, 2006.

1 To whom correspondence should be addressed. e-mail: at-h{at}rh.dk


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Zinc Finger Protein 202 (ZNF202) is a transcriptional repressor that binds elements found predominantly in genes involved in HDL metabolism. We tested the following hypotheses: 1) frequencies of single-nucleotide polymorphisms (SNPs) and haplotypes in ZNF202 differ between individuals with low and high HDL cholesterol; and 2) SNPs in ZNF202 affect HDL cholesterol levels in the general population. We screened the promoter and protein-coding exons of ZNF202 in individuals with the highest 1% (n = 95) and lowest 1% (n = 95) HDL cholesterol among 9,259 Danish adults. None of the 10 SNPs identified differed in frequency as single sites or as haplotypes between low and high HDL cholesterol groups. In accordance with this, seven mutations were equally frequent (4–5%) in individuals with low or high HDL cholesterol. Finally, for all five SNPs identified in the coding region, we determined the association of genotype with HDL cholesterol in 9,259 individuals from the general population. Four SNPs were not associated with variation in HDL cholesterol, although c.*2T>G homozygosity was associated with a discrete effect on HDL cholesterol in men. We show that genetic variation in ZNF202 is common in the general population. However, SNPs in the protein-coding region of ZNF202 do not make a major contribution to HDL cholesterol levels.

Supplementary key words apolipoproteins • genetic epidemiology • large-scale genotyping • lipids • lipoproteins • molecular biology • molecular medicine • reverse cholesterol transport • transcription factors • high density lipoprotein cholesterol

Abbreviations: apoA-I, apolipoprotein A-I; BMI, body mass index; KRAB, Krüppel-associated box; LD, linkage disequilibrium; SCAN, SRE-ZBP, CT-finS1, AW-1, Number 18; SNP, single-nucleotide polymorphism; UTR, untranslated region; ZNF202, Zinc Finger Protein 202


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Levels of HDL cholesterol are inversely related to risk of ischemic heart disease in the general population (1, 2). The HDL particle is responsible for the delivery of cellular cholesterol from peripheral tissues to the liver and is thus a key component in reverse cholesterol transport (3).

Twin and family studies suggest that approximately half of the variation in HDL cholesterol is genetically determined (4–7). A new susceptibility locus for familial hypoalphalipoproteinemia (Online Mendelian Inheritance in Man 604091) on chromosome 11q23 was identified in Utah pedigrees (8); this region contains the Zinc Finger Protein 202 (ZNF202) gene. ZNF202 is functionally characterized by a SRE-ZBP, CT-finS1, AW-1, Number 18 (SCAN) oligomerization domain, a Krüppel-associated box (KRAB) repression domain, and eight zinc finger (Cys2His2) DNA binding motifs, a typical domain architecture for transcription factors (9). ZNF202 target genes are mainly involved in lipid and, particularly, HDL cholesterol metabolism (10–12), suggesting that this transcriptional repressor might be important in the determination of HDL cholesterol levels in the general population. However, it is largely unknown to what extent ZNF202 varies genetically in the general population and whether such genetic variation influences HDL cholesterol levels.

We tested the following hypotheses: 1) frequencies of single-nucleotide polymorphisms (SNPs) and haplotypes in ZNF202 differ between individuals with low and high HDL cholesterol levels; and 2) SNPs in the protein-coding region of ZNF202 affect HDL cholesterol levels in the general population. To increase the likelihood of identifying genetic variation with significant effects on HDL cholesterol levels, we screened the promoter and protein coding regions of ZNF202 (~2 kb) in 95 individuals with the 1% lowest and in 95 individuals with the 1% highest HDL cholesterol levels for age and gender from a general population sample, the Copenhagen City Heart Study (n = 9,259). All SNPs identified in and around the protein-coding region were genotyped in the entire general population sample, and the effect on HDL cholesterol and apolipoprotein A-I (apoA-I) levels was determined.


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Subjects
The Copenhagen City Heart Study is a prospective cardiovascular population study of individuals selected based on the Central Population Register Code to reflect the adult Danish general population aged 20 to 80+ years. In 1991–1994, 9,259 participants (55% women) gave blood for DNA analyses (13, 14). More than 99% were white and of Danish descent. This study was approved by the local ethical committee: Nos. 100.2039/91 and 01-421/94, Copenhagen and Frederiksberg committee. All participants gave written informed consent.

For the genetic screening of ZNF202 (GenBank accession number NM_003455), we selected individuals from the Copenhagen City Heart Study with the 1% lowest (n = 95) and 1% highest (n = 95) HDL cholesterol levels for age and gender (in 10 year age groups). Consequently, the cutoff levels for HDL cholesterol depend upon the seven age groups for each gender (15). We previously showed that by screening these groups with extreme phenotypes, we increased the likelihood of identifying mutations and SNPs (rare allele frequency of <1% and >=1%, respectively) with impact on HDL cholesterol levels in the general population (15). With the exception of a synonymous SNP [c.731A>G (p.V244V)], all five SNPs identified in or around the protein-coding region by screening ZNF202 were genotyped in the entire general population sample (n = 9,259), and the effect of each SNP on variation in HDL cholesterol and apoA-I levels was determined as overall effects (regardless of variation at the other four sites) and as isolated single-site effects (five SNP genotypes differing only at the relevant SNP) using data from the third examination of the Copenhagen City Heart Study (1991–1994). In tables and figures, data for the general population sample are presented only for individuals in whom the five SNP genotypes for all SNPs were available (n = 9,103 of 9,259).

Gene screening
Genomic DNA was isolated from frozen whole blood (QiaAmp® DNA Blood Mini Kit; Qiagen, Hilden, Germany). The ZNF202 gene contains ten exons; however, only six exons (exons 5–10) encode the ZNF202 protein (648 amino acids) (10). Sixteen PCR fragments were amplified covering 700 bp of the ZNF202 promoter upstream of exon 1 (12), all six protein-encoding exons (exons 5–10) (accession number NM_003455) (10), and exon-intron boundaries. Mutational analysis of the amplicons was performed by denaturing HPLC. PCR fragments showing heteroduplex formation were subsequently sequenced on an ABI PRISM 310 Genetic Analyzer (Applied Biosystems, Inc., Foster City, CA).

SNP genotyping in the general population
The ABI PRISM 7900HT Sequence Detection System (Applied Biosystems, Inc.) was used to genotype the general population sample for all five SNPs identified in and around the coding region. TaqMan-based assays were used. Combined genotypes for all five SNPs were available for 9,103 individuals of the total cohort of 9,259 individuals.

Biochemical assays
Colorimetric and turbidimetric assays (Hitachi autoanalyzer) were used to measure plasma levels of total cholesterol, HDL cholesterol, triglycerides, apoB, and apoA-I (all from Boehringer Mannheim, Mannheim, Germany).

Statistical analyses
Differences in allele frequencies between individuals with low and high HDL cholesterol were evaluated using Fisher's exact test. Pairwise disequilibrium statistics were calculated from D = h – pq, where h is the frequency of the rare estimated haplotype for a pair of sites and p and q are the frequencies, assuming no linkage, of the alleles in that haplotype (16). Linkage disequilibrium (LD) was expressed as D' (17). Significance levels for pairwise LD were estimated by the likelihood-ratio test. Estimated haplotype frequencies were calculated using the expectation maximization algorithm (18). The association of ZNF202 genotype with variation in HDL cholesterol and apoA-I levels was determined by ANOVA with Student's t-test as a posthoc test. P < 0.05 on a two-sided test was considered significant. P values were not corrected for multiple comparisons.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Characteristics of individuals with the lowest 1% and highest 1% HDL cholesterol levels and of the total general population sample are shown in Table 1 . Individuals in the low HDL cholesterol group had lower apoA-I levels, higher triglyceride levels, and were more obese than individuals in the high HDL cholesterol group or in the general population.


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  		TABLE1. Characteristics of individuals from the general population with the lowest 1% and highest 1% HDL cholesterol levels and of the total general population sample

 
Genetic variation in ZNF202
Six SNPs [c.IVS4-240A>T, c.IVS4-223T>C, c.461C>T (p.A154V), c.731A>G (p.V244V), c.775A>G (p.K259E), and c.*2T>G] and two mutations [c.820G>C (p.V274L) and c.1813A>T (p.R605W)] were identified in or flanking the protein-coding regions of the gene and in the 3' untranslated region (3'UTR), four of which introduced amino acid substitutions (Table 2 , Fig. 1 ): c.461C>T (p.A154V) and c.820G>C (p.V274L) substitute similar amino acids, c.775A>G (p.K259E) introduces a shift between positively charged and negatively charged side chains, and c.1813A>T (p.R605W) introduces a shift between positively charged nonpolar and uncharged polar side chains. c.461C>T (p.A154V) is located in the SCAN domain, known to be important for protein-protein interaction, whereas both c.775A>G (p.K259E) and c.820G>C (p.V274L) are in the KRAB A domain, important for transcriptional repression. The amino acid residues affected by these two variants are situated in highly conserved areas of ZNF202 and are themselves completely conserved between species (human, mouse, rat) (Fig. 2 ). c.1813A>T (p.R605W) is located in the seventh zinc finger motif, in a highly conserved area, and p.R605 is also conserved between species (human, mouse, rat). c.*2T>G is located 2 bp downstream of the translation stop site (Table 2, Fig. 1). Of the four nonsynonymous variants identified, c.820G>C (p.V274L), c.1813A>T (p.R605W), and c.775A>G (p.K259E) have not been reported previously.


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  		TABLE 2. Genetic variation in protein-coding and regulatory sequences of ZNF202 in individuals from the general population with extreme HDL cholesterol levels

 

Figure 1
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  		Fig. 1. Schematic model of Zinc Finger Protein 202 (ZNF202) according to Wagner et al. (10) and corresponding protein domains. Single-nucleotide polymorphisms (SNPs; green) and mutations (red) identified here are superimposed. ZNF202 protein is characterized by a SRE-ZBP, CT-finS1, AW-1, Number 18 (SCAN) oligomerization domain, a Krüppel-associated box (KRAB) repression domain, and eight zinc finger (Cys2His2) DNA binding motifs. Two asterisks indicate new variants identified in this study.

 

Figure 2
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  		Fig. 2. Partial alignment of human ZNF202 and orthologous murine and rat protein sequences. For alignment, the ClustalW program was used. Parts of the SCAN domain (top, in italics), the KRAB domain (middle), and zinc finger motifs (bottom) are presented and underlined. The four nonsynonymous variants identified in this study are highlighted. SNPs are shown in green, and mutations are shown in red. Asterisks indicate that amino acid residues are identical in all sequences aligned.

 
Four SNPs (g.–685G>A, g.–660A>G, g.–118G>T, and g.+34G>A) and three mutations (g.–447T>C, g.–232C>T, and g.–122C>T) were identified in the promoter region and 5'UTR of exon 1 (Table 2, Fig. 1): g.–685G>A and g.–660A>G are situated in a silencer sequence, g.–447T>C in a putative Yin Yang 1 binding site, g.–122C>T in a putative myeloid zinc finger 1 binding site (12), and g.+34G>A in a putative downstream promoter element. Four of these seven variants have not been reported previously.

Four variants were identified in introns: two SNPs and two new mutations. Judging from their positions in relation to the exon-intron junctions and the nucleotide substitutions introduced, none of these would be predicted to affect splicing.

Individuals in the low and high HDL cholesterol groups
A total of 17 genetic variants were identified in the promoter and in and around the protein-coding region of ZNF202 (Table 2). Allele frequencies ranged from 1:380 (0.3%) to 147:380 (39%) in the low and high HDL cholesterol groups. Ten SNPs (allele frequencies > 1%) were identified in both HDL cholesterol groups, two of which were new [g.–118 G>T and c.775A>G (p.K259E)]. None of these 10 SNPs differed in frequency between individuals with the lowest 1% and the highest 1% HDL cholesterol levels. Of the seven mutations (allele frequencies <= 1%), four were identified exclusively in four individuals in the low HDL group, two in three individuals in the high HDL group, and one was present in both HDL groups (Table 2). Together, the frequencies of mutations in ZNF202 in the low and high HDL groups were similar (4–5%).

Haplotype analysis of the five SNPs located in and around the coding region estimated that six haplotypes accounted for >98% of all haplotypes in the low HDL cholesterol group and for almost 100% in the high HDL cholesterol group (Table 3 ). However, none of these haplotypes differed in frequency between the low and high HDL groups, suggesting that they did not affect HDL cholesterol levels.


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  		TABLE 3. Estimated haplotype frequencies of SNPs in and around the protein-coding region of ZNF202 in individuals from the general population with the lowest 1% and highest 1% HDL cholesterol levels

 
Individuals in the general population
With the exception of a synonymous SNP [c.731A>G (p.V244V)], we genotyped the total general population sample (n = 9,259) for all SNPs located in and around the protein-coding region [c.IVS4-240A>T, c.IVS4-223T>C, c.461C>T (p.A154V), c.775A>G (p.K259E), and c.*2T>G] (Table 2). Allele frequencies of these five SNPs ranged from 1% to 39% in the total general population sample. Genotype frequencies did not differ from those predicted by Hardy-Weinberg equilibrium.

Overall associations (regardless of variation at the other four sites) for each of the five SNPs with HDL cholesterol and apoA-I levels are presented separately by gender in Fig. 3 . In men (n = 4,064), homozygosity for c.*2G in the 3'UTR was associated with an apparent decrease in HDL cholesterol of ~0.05 mmol/l (ANOVA: P = 0.05; posthoc test: TT versus GG, P = 0.04, TG versus GG, P = 0.02) and a corresponding decrease in apoA-I (ANOVA: P = 0.006; posthoc test: TT versus GG, P = 0.01, TG versus GG, P = 0.002). If P values were corrected for multiple comparisons using the Bonferroni method, only the genotype association with apoA-I levels remained significant (corrected P value with five comparisons: P = 0.05/5 = 0.01). None of the remaining SNPs [c.461C>T (p.A154V), c.775A>G (p.K259E), c.IVS4-223T>C, and c.IVS4-240A>T] were associated with variation in HDL cholesterol or apoA-I levels.


Figure 3
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  		Fig. 3. Mean plasma HDL cholesterol and apolipoprotein A-I (apoA-I) levels as a function of five SNPs [c.IVS4-240A>T, c.IVS4-223T>C, c.461C>T(p.A154V), c.775A>G(p.K259E), and c.*2T>G] in ZNF202 regardless of variation at the other four sites (overall association) in women (n = 5,039) and men (n = 4,064) in the general population. Values shown are means ± SEM. P values are by ANOVA or Student's t-test. After Bonferroni correction for multiple comparisons, only P ≤ 0.01 remained significant (corrected value with five comparisons: P = 0.05/5 = 0.01). * P < 0.05, ** P ≤ 0.01 by posthoc test.

 
To further explore these results, we tested the isolated single-site effect of the c.*2T>G SNP on HDL cholesterol and apoA-I levels in men by comparing five SNP genotypes differing only at this site (Fig. 4 ). Using this approach, we found an association between c.*2T>G genotype and HDL cholesterol in one of five tests and an association between c.*2T>G genotype and apoA-I levels in three of five tests. After Bonferroni correction, only one association between genotype and apoA-I levels remained significant (P = 0.01).


Figure 4
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  		Fig. 4. Plasma HDL cholesterol and apoA-I levels in men in the Copenhagen City Heart Study as a function of five SNP genotypes differing only at c.*2T>G (isolated single-site association). Values shown are means ± SEM. P values are by one-way ANOVA and Student's t-test. After Bonferroni correction for multiple comparisons, only P ≤ 0.01 remained significant (corrected value with five comparisons: P = 0.05/5 = 0.01). * P < 0.05, ** P ≤ 0.01 by posthoc test.

 
Pairwise LD was tested for the five SNPs located in and around the coding region and genotyped in 9,103 individuals from the general population (Table 4 ). Strong pairwise LD was present for all SNP pairs. However, because allele frequencies varied widely between SNPs (from 1% to 39%), these LDs should be interpreted with caution.


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  		TABLE 4. Pairwise linkage disequilibrium between ZNF202 SNPs in and around the protein-coding region of ZNF202 in the general population (n = 9,103)

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
With the aim to identify genetic variation in ZNF202 affecting HDL cholesterol levels in the general population, we used a systematic approach in which we screened 700 bp of the promoter and all protein-coding exons of the ZNF202 gene in 190 individuals with extreme HDL cholesterol levels selected from a large sample of the general population (n = 9,259). We subsequently genotyped the entire general population sample for the five SNPs located in and around the protein coding region and determined the association with HDL cholesterol and apoA-I levels.

Novel observations in this study include the following: 1) we identified nine new genetic variants (two SNPs and seven mutations), of which two were located in predicted transcription factor binding sites in the proximal promoter, and three were nonsynonymous variants; 2) common SNPs in and around the coding region and haplotypes harboring these SNPs did not segregate differently in individuals with low and high HDL cholesterol levels; 3) these SNPs also did not have a major effect on HDL cholesterol and apoA-I levels in the total general population, as single sites or as combined genotypes differing only at the relevant SNP; and 4) mutations in ZNF202 were equally frequent (5%) in individuals with low or high HDL cholesterol levels.

This is the first systematic study to determine the genetic variation in the promoter and in and around the protein-coding region of ZNF202 in a substantial number of individuals with low or high HDL cholesterol levels and to investigate the role of ZNF202 in HDL metabolism in the general population. Because ZNF202 has been identified in a low hypoalphalipoproteinemia locus (8, 19), and because in vitro studies suggest that ZNF202 is a transcriptional repressor of several key genes in HDL cholesterol homeostasis (10), genetic variation in ZNF202 might affect HDL cholesterol levels in plasma and perhaps play a role in the development of atherosclerosis in the general population. However, the data summarized above suggest that genetic variation in and around the protein-coding region of ZNF202 is not a major determinant of HDL cholesterol or apoA-I levels in the general population.

We detected all previously reported SNPs in the promoter and coding region of the gene as well as two new SNPs, one in the proximal promoter (g.–118G>T) and a nonsynonymous SNP in exon 8 [c.775A>G (p.K259E)]. The c.775A>G (p.K259E) SNP was the least frequent of the six SNPs identified in and around the coding region, suggesting that we did not overlook any important SNPs. Three SNPs were identified in the protein-coding region, one synonymous [c.731A>G (p.V244V)] and two nonsynonymous [c.461C>T (p.A154V) and c.775A>G (p.K259E)], and one in the 3'UTR (c.*2T>G). The c.461C>T (p.A154V) SNP is located in the SCAN domain of ZNF202. The SCAN domain is important for protein-protein interaction and thus regulates ZNF202 activity (11, 20, 21). However, A154 was not conserved between species (human, mouse, rat), and alanine and valine are very similar amino acids. c.461C>T (p.A154V) was equally distributed between the two HDL cholesterol groups, suggesting that this SNP did not affect HDL cholesterol levels. This was confirmed when genotyping c.461C>T (p.A154V) in 9,103 individuals from the general population; no association between c.461C>T (p.A154V) genotype and HDL cholesterol levels was found. c.731A>G (p.V244V) and c.775A>G (p.K259E) are both located in the KRAB A domain, an important repressor domain. The KRAB A domain is highly conserved, and selected conserved amino acids have been shown to be essential for repression (22). K259 is highly conserved between species (human, mouse, rat), and the positive charge of the K259 residue is also conserved between paralogous human proteins with the same protein architecture, SCAN-KRAB-Cys2His2, as ZNF202. K259 is located close to residues proven to be essential for the repressor activity of the KRAB A domain (22); therefore, it is possible that a SNP in this position could affect interaction with other protein residues, leading to decreased repressor activity. However, c.775A>G (p.K259E) was identified in both high and low HDL cholesterol groups with equal frequencies and showed no association with HDL cholesterol levels in the general population. c.*2T>G is a very common SNP located in the 3'UTR, 2 bp downstream of the translation stop site. In men in the general population, c.*2G homozygosity appeared to be associated with marginally lower levels of HDL cholesterol and apoA-I compared with c.*2T heterozygotes and homozygotes. However, this association was not robust and may be attributable to a type I error: only the association with apoA-I levels remained significant after correction for multiple comparisons. Thus, iteration in a large, independent population to confirm or reject the association between c.*2G homozygosity and low HDL cholesterol and apoA-I levels would be desirable.

The HapMap data for Caucasians uses nine SNPs [in introns and protein-coding exons, including dbSNP 1144507 and c.461C>T (p.A154V); Table 2] in 60 individuals (120 alleles) spanning both non-protein-coding and protein-coding exons of ZNF202 to define four haplotypes with frequencies of >1% and three with frequencies of >5% (www.hapmap.org). In our sample of individuals with low and high HDL cholesterol, we used five SNPs in 190 individuals (380 alleles) spanning the protein-coding exons only to define five haplotypes with frequencies of >1% and four with frequencies of >5%. Adding one (g.+34 G>A in exon 1; Table 2) of only two SNPs reported in non-protein-coding exons from the National Center for Biotechnology Information SNP database (http://www.ncbi.nlm.nih.gov/entrez/) to our haplotype data did not add additional haplotypes in our sample. Finally, had we used HapMap SNPs spanning only the protein-coding exons to determine haplotypes in our data (assuming that the same haplotypes are found in the two groups of Caucasians), we would have detected only two common haplotypes.

Four new mutations were identified in and around the protein-coding region, two of which were nonsynonymous. The affected amino acid residues were located in functionally important areas of ZNF202 in the KRAB A domain [c.820G>C (p.V274L)] and in the zinc finger domain [c.1813A>T (p.R605W)]. V274 is conserved between species but does not introduce a change in amino acid charge. R605 is conserved between species but not between paralogous proteins. However, a change from a positively charged nonpolar amino acid (arginine) to an uncharged polar amino acid (tryptophan) might alter the conformation of the zinc finger motif and perhaps change the DNA binding specificity.

The systematic approach by which we screened individuals with extreme HDL cholesterol levels has previously proven sensitive in the detection of both mutations with strong phenotypic effects and SNPs with more modest effects on HDL cholesterol levels, illustrated by differential segregation of the functional SNPs in groups with extreme phenotypes (15, 23). Whether one can detect such a frequency difference between extreme phenotype groups depends on the size of the study, the frequency of the SNP, the order of magnitude of the phenotype effect of the SNP (in this case, on HDL cholesterol or apoA-I), and whether this effect is equally strong in both genders. In this study, we used this approach to determine whether genetic variation in ZNF202 affected HDL cholesterol, because the majority of ZNF202 target genes play a role in HDL metabolism. However, because ZNF202 is a transcriptional repressor of the actual functional gene, genetic variation in ZNF202 may have a less distinct effect on the intermediate phenotype than genetic variation in the structural gene itself.

Limitations
HDL cholesterol levels are affected by many factors, both environmental and genetic, among them body mass index (BMI), triglycerides, and genetic variation in other genes (cholesteryl ester transfer protein, hepatic lipase, lipoprotein lipase, endothelial lipase, APOAI, APOE, and others). This is illustrated in our study by the significant increase in mean BMI in the low HDL group compared with the high HDL group (27 kg/m2 in women and 25 kg/m2 in men compared with 23 and 24 kg/m2, respectively) and by triglyceride concentrations in the low HDL group that were 2.4- to 3.8-fold higher than those in high HDL individuals. Nevertheless, we knew from experience in previous studies (15) that by selecting individuals in the low HDL group with normal BMI and triglycerides only we would have failed to detect any of the nine carriers with mutations associated with low HDL cholesterol, so we chose only to correct for age and gender in the extreme HDL groups. Had we only included individuals with BMI < 25 kg/m2 and/or triglycerides < 2.2 mmol/l in the low HDL group, we would have failed to detect five of six mutations identified in the low HDL group.

The high HDL cohort had extremely elevated HDL cholesterol concentrations (2.9–3.3 mmol/l), so we cannot rule out that a subset of these subjects may harbor functional variants in other genes, such as cholesteryl ester transfer protein, hepatic lipase, lipoprotein lipase, and endothelial lipase, that are also associated with increased HDL cholesterol levels.

Finally, we screened a relatively small portion of the promoter (700 bp), all protein-coding exons (exons 5–10), and the corresponding exon/intron boundaries of ZNF202, raising the possibility that functional variants affecting gene expression, or variants in introns or non-protein-coding exons affecting gene regulation, may have been missed. In support of intronic variants being important for gene regulation, a functional variant in an intron was recently identified in the USF1 gene (24).

In conclusion, we show that genetic variation in ZNF202 is common in the general population. However, SNPs in and around the protein-coding region of ZNF202 do not make a major contribution to HDL cholesterol levels in the general population.


   ACKNOWLEDGMENTS
 
The authors thank Mette Refstrup for expert technical assistance. The authors also thank the subjects who participated in the study. This work was supported by the Danish Heart Foundation, the Danish Medical Research Council, Ingeborg and Leo Dannin's Grant, and the Research Fund at Rigshospitalet, Copenhagen University Hospital.

Manuscript received November 30, 2005 and in revised form January 27, 2006.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
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M. C.A. Stene, R. Frikke-Schmidt, B. G. Nordestgaard, P. Grande, P. Schnohr, and A. Tybjaerg-Hansen
Functional Promoter Variant in Zinc Finger Protein 202 Predicts Severe Atherosclerosis and Ischemic Heart Disease
J. Am. Coll. Cardiol., July 29, 2008; 52(5): 369 - 377.
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