Quantitative Trait Loci and Candidate Genes Regulating HDL Cholesterol
A Murine Chromosome Map
Objective— Summarizing the many discovered mouse and human quantitative trait loci (QTL) for high density lipoprotein (HDL) cholesterol (HDL-C) levels is important for guiding future research on the genetic regulation of HDL concentrations and for finding gene targets for upregulating HDL levels in mice and humans.
Methods and Results— We summarized the 27 QTL and candidate genes associated with HDL-C concentrations in mice and plotted them on a mouse chromosome map. We also summarized the 22 human QTL for HDL-C levels and compared them with those of the mouse by comparative genomics. At least part of the mouse homologies for 18 of the 22 human HDL-C QTL were within the murine HDL-C QTL.
Conclusions— Murine QTL for HDL-C levels may predict their homologous location in humans, and their underlying genes may be appropriate genes to test in humans.
The risk of developing atherosclerosis, the leading cause of death in industrialized countries, is considerably reduced in people with relatively high concentrations of plasma HDL. Although it is unclear how HDL protects against atherosclerosis, it may (1) stimulate reverse cholesterol transport and thereby decrease the deposition of cholesterol in peripheral tissues (including arteries), (2) prevent foam cell formation by inhibiting physical and chemical modifications of LDL, (3) inhibit chronic inflammation in atherogenesis by suppressing the formation of adhesion molecules and macrophage chemotactic proteins (see recent reviews1,2⇓), (4) reduce lipoprotein retention, and (5) attenuate endothelial dysfunction. Plasma HDL levels are regulated by genes and the environment, and it is believed that up to 70% of the variation in HDL cholesterol (HDL-C) levels among humans is genetically determined (see recent reviews2–4⇓⇓).
Genes controlling HDL metabolism and function can be found either through biochemical studies of occasional natural mutations in humans and other animals or by genetic mapping. However, whereas conventional genetic mapping approaches were designed for single-gene traits, the genes regulating complex quantitative traits such as HDL-C levels are best mapped by using a quantitative trait loci (QTL) approach.5 Once QTL regions are found and narrowed, candidate genes can be identified and tested. This process has been considerably simplified ever since the human and mouse genomes have been sequenced. When genes are identified in mouse models, their human orthologues can be predicted. Thus, to help researchers identify genes that regulate HDL-C concentrations, we compiled a composite genetic map of the currently mapped QTL and associated candidate genes in mouse models. We also explored the correlation of QTL for HDL-C concentrations in humans with those in mice.
Many genes are already known to regulate either HDL function or metabolism or both (see recent reviews2–4,6,7⇓⇓⇓⇓). Table 1 categorizes these genes into 5 groups that encode (1) HDL-associated apolipoproteins, (2) HDL-associated enzymes and transfer proteins, (3) plasma and cell enzymes that affect HDL, (4) cellular receptors and transporters that interact with HDL, and (5) transcription factors that affect HDL. Table 1 also lists the positions of these genes on mouse and human chromosomes.
QTL for HDL-C Concentrations
Methods of Identifying and Narrowing HDL-C QTL
Conventionally, QTL associated with HDL-C concentrations in mice are identified in 4 steps: (1) generation of either backcross or intercross progeny of 2 inbred mouse strains with different HDL-C concentrations, (2) determination of HDL-C concentrations, usually normally distributed, in the second generation (F2 for intercross, N2 for backcross) progeny, (3) use of microsatellite markers that are polymorphic between the 2 strains to genotype the 1600-cM genome of each progeny animal at 15- to 20-cM intervals, and (4) determination of the marker-associated chromosomal regions (the QTL) that most likely contain genes responsible for differences in HDL-C concentrations between the 2 strains by using a variety of statistical programs.
Besides commonly used inbred stains, some mutant mouse stains were also used as parental strains in an intercross to map QTL for HDL-C levels.8,9⇓ In one report, the mutant Fas gene (now renamed Tnfrsf6) may contribute to autoimmunity and abnormal lipid profiles,9 and in the other report,8 KK.Cg-Ay mice develop diabetes and obesity. Thus, the relationship and interactions of the genes involved in regulating HDL-C levels and those in the respective diseases might be revealed in these crosses.
Although most of the QTL associated with HDL-C concentrations in the present review were resolved by using either intercross or backcross designs, some were detected in recombinant inbred (RI) strains (see Figure 1 for generation of RI strains). In each RI strain set, alleles of unlinked genes that vary between the parental strains are randomized by the accumulation of recombination events that become fixed in successive generations.10 Alleles at closely linked genes tend to remain linked in the final RI sets. The genetic loci among the strains constituting an RI set have an inheritance pattern known as a strain distribution pattern (SDP). If 2 genes are closely linked, their SDP among the strains of an RI set should be very similar. Because the data are cumulative, a new gene can be mapped by comparing its SDP with the SDPs of polymorphic markers in the RI set. Because RI strains have 4 times the recombination opportunity of standard backcrosses and 2 times the recombination opportunity of standard intercrosses, QTL may be identified in a relatively small number of RI strain sets. In addition, several RI sets have C57BL/6 as 1 of the parental strains: AXB, BXA, BXD, BXH, or CXB (A indicates A/J; B, C57BL/6; D, DBA/2J; H, C3H/HeJ; and C, BALB/cByJ). Therefore, it is possible to collapse all non-B alleles into a single class and combine linkage-likelihood ratios of the component RI sets,11 making more RI sets available for mapping each QTL.
More recently, the strategy of advanced intercross lines (AILs) was proposed for fine mapping of QTL (see Figure 1 for generation of AILs).12 We have used this novel approach in narrowing several HDL-C QTL (see below). Although AILs take relatively longer to produce than do backcrosses and intercrosses, only the progeny in the final generation need to be phenotyped and genotyped. Given the same population size and QTL effect, the 95% CI of a QTL map location obtainable from an AIL can be t/2 times smaller than that obtainable from either the same size intercross or backcross scheme (t is the number of the advanced generations). Such fine resolution can even dissect linked QTL.12
Some have pointed out that the promise of QTL mapping, which was to identify the genes underlying complex common diseases, has not been realized13 because so few genes underlying the QTL have been identified. The identification of genes has been slow. However, QTL mapping did not really begin until 1989, with the appearance of the Lander and Botstein article5; in 1989 and during the early 1990s, many critical resources were still being developed, such as polymorphic markers, statistical analysis tools, yeast artificial chromosome and bacterial artificial chromosome libraries for constructing a physical map, and expressed sequence tags. The recent availability of the mouse and human genomic sequences and the powerful technology of microarrays for expression studies have just begun to make their impact on QTL mapping. From 1991 through 1998, only 1 or 2 genes were identified per year as the basis of a QTL, but 4 genes were identified in 1999, 6 were identified in 2000, and 13 were identified in 2001.14 For genes underlying HDL-C QTL, only hepatic lipase has been identified so far.15,16⇓ However, a review of the genome locations of QTL and candidate genes, an examination of whether the QTL has been confirmed in multiple studies, and a consideration of whether a QTL is found in a homologous region of the human genome may lead to testable hypotheses and further experiments to define the genes that regulate HDL-C levels.
Studies of rare human genetic defects, which often result in the total absence of encoded proteins, indicate that APOA1, APOA4, LCAT, CETP, ABCA1, and CUBN (where LCAT is lecithin-cholesterol acyltransferase, CETP is cholesteryl ester transfer protein, ABC is ATP-binding cassette transporter, and CUBN is the gene for cubilin) can regulate HDL-C concentrations,4 but such rare defects do not account for the variation in HDL-C concentrations in humans. However, more common alleles at these same loci could be responsible. It is especially important to find the genes that are responsible for the common causes of population variance of HDL-C because these are more likely to be effective therapeutic targets. Identifying HDL-C QTL is much easier in mice than in humans for many reasons. Mice can be bred quickly, inexpensively, in strictly controlled environments, and with a variety of inbreeding, intercross, and backcross strategies. Furthermore, inbred mouse strains have unique genetically defined backgrounds, many of which can be taken advantage of in designing crosses to identify HDL-C QTL. A survey of >40 inbred mouse strains revealed that some, such as NZB/B1NJ, PERA/CamEi, SPRET/Ei, and BALB/cJ, have relatively high HDL-C concentrations, whereas others, such as SM/J, DBA/2J, SWR/J, and CAST/Ei, have relatively low HDL-C concentrations.17–19⇓⇓ Some strains, such as C57BL/6J and C57L,18,20,21⇓⇓ respond to a high-fat diet by decreasing their HDL-C concentrations; others, such as NZB and SM, respond to the same diet by increasing their HDL-C concentrations.22
We and other research groups have taken advantage of such strain differences in HDL-C concentrations to design crosses identifying QTL associated with HDL-C concentrations (Table 223–28⇓⇓⇓⇓⇓). Altogether, 10 different mouse crosses have been used to detect QTL for HDL-C concentrations: (1) C57BL/6×C3H, (2) C57BL/6×NZB, (3) C57BL/6×129, (4) C57BL/6×CAST/Ei, (5) C57BL/6×KK.Cg-Ay, (6) A/J×C57BL/6, (7) NZB×SM, (8) PERA/Ei×I/Ln, (9) DBA/2×CAST/Ei, and (10) MRL/MPJ-Tnfrsflpr×BALB/c. Among them, 8 were used in intercrosses, 3 were used in RI strain sets, and 1 was used in AIL. A total of 27 QTL for HDL-C levels were found: 6 of the QTL were detected only in mice fed a chow diet, 10 were detected only in mice fed a high-cholesterol diet, and 11 were detected in mice fed both diets. Thirteen of the 27 QTL were detected with only 1 cross, 8 were detected with 2 different crosses, and 6 were detected with ≥3 different crosses. QTL for HDL-C levels were found on all the mouse chromosomes except for chromosomes 10, 11, 13, and X (Table 2). We have proposed 40 candidate genes, among which 26 are within the QTL regions for HDL-C concentrations. Because 36% of the mouse genome is covered by the QTL, only 14.4 of the 40 candidate genes would be within the 27 QTL simply by chance, which differs significantly from the 26 candidate genes that were observed (P<0.01, χ2 test).
Murine Chromosome Map for HDL
Figure 2 depicts the chromosomal locations of all the HDL-C QTL and associated candidate genes currently identified in the mouse genome. Each QTL derived from a separate cross (not sharing the same parental strains), as shown in Table 2, is depicted as a separate bar on the figure even though these may represent the same QTL. For example, the QTL on chromosomes 1, 5, and distal 18 have been replicated independently several times. Some QTL intervals contain genes known to regulate either HDL metabolism or function or both; others do not have obvious candidate genes.
Seventy percent of HDL protein consists of apoA-I, whose plasma concentrations are directly correlated with those of HDL-C. Humans with apoA-I deficiency have very little HDL-C and are susceptible to atherosclerosis.29 Apoa1-targeted mutant mice have abnormally low HDL-C concentrations, and mice transgenic for human APOA1 have abnormally high HDL-C concentrations (see review30). As do Apoa1-targeted mutants, mice with targeted mutations of Apoa4 have lower HDL-C concentrations than do wild-type mice.31 Also, mice transgenic for either human APOA432 or mouse Apoa433 have higher HDL-C concentrations than do wild-type mice. Clinical studies of human APOA4 are scant. APOA1 and APOA4 are clustered with APOC3, another gene that encodes HDL-associated apolipoproteins, on human chromosome 11q23. The orthologous mouse genes, Apoa1, Apoa4, and Apoc3, cluster on mouse chromosome 9 (cM 27.0, Figure 2). Allelic variation in the human gene cluster accounted for 22% of total interindividual variation in plasma HDL-C levels in a study of 73 white nuclear families.15 An HDL-C QTL identified in a C57BL/6J×KK-Ay intercross colocalizes with the mouse gene cluster (Table 2 and Figure 2). This result, combined with the critical role of apoA-I in HDL structure and metabolism, suggests that APOA1 may be an important target for gene-based atherosclerosis therapy.
ApoA-II is the second most abundant structural protein in HDL, constituting 20% of its protein. Whereas transgenic mice carrying the mouse Apoa2 gene have higher HDL-C concentrations than do control mice,34 transgenic mice carrying the human APOA2 gene have lower HDL-C concentrations than do control mice.35 This is because human apoA-II, being more hydrophobic than the mouse protein, displaces human apoA-I from HDL, thus decreasing HDL concentrations. Apoa2 maps to mouse chromosome 1 (cM 92.6) and colocalizes with an HDL-C QTL identified in 4 different mouse crosses (C57BL/6×C3H, NZB×SM, C57BL/6×NZB, and C57BL/6×129) with 4 different approaches (intercross, backcross, RI sets, and AIL; Table 2).
Genes Encoding Enzymes and Transfer Proteins That Affect HDL-C Concentrations
Products of several genes dynamically and constantly modify the composition, structure, size, and function of HDL. These include some enzymes directly associated with HDL and plasma or intracellular enzymes that use HDL as substrate (Table 1). Plasma phospholipid transfer protein (PLTP) is bound to HDL and mediates the net transfer and exchange of phospholipids among different lipoproteins and participates in the transformation of larger HDL3 into smaller HDL2 (see recent review36). In mice, PLTP deficiency reduces plasma HDL-C concentrations,37 whereas moderate overexpression of human38,39⇓ or mouse40–42⇓⇓ PLTP either increases38–40⇓⇓ or decreases41,42⇓ plasma HDL-C levels in different reports. An HDL-C QTL on chromosome 2 found in the C57BL/6×CAST intercross colocalizes with the Pltp gene26 (Figure 2), making Pltp a plausible candidate for this QTL. Hepatic lipase has been identified as an important gene for HDL-C QTL in humans14,15⇓ and lies within a mouse QTL as well. Another possible candidate gene is Lipg, which encodes endothelial lipase. Endothelial lipase is synthesized in endothelial cells, macrophages, and hepatocytes and is found in the placenta, thyroid, testes, liver, lungs, kidneys, and spleen. Its sequence is 45% homologous with that of lipoprotein lipase and 40% homologous with that of hepatic lipase. Of the 3, endothelial lipase has the most phospholipase activity and the least triglyceride lipase activity. C57BL/6J mice, APOA1 transgenic mice, and LDL receptor–deficient mice that are transgenic for Lipg all have lower plasma HDL-C concentrations than do control mice.43 Although the function of endothelial lipase is unknown, it might play an important role in HDL metabolism, possibly by hydrolyzing HDL phospholipids and facilitating selective HDL uptake by scavenger receptor class B type I (SR-BI).43 After performing a BLASTN search of the Celera database for the physical position of Lipg, we estimated its centimorgan position from the position of its flanking genes in the MGD database44 (see footnotes in Table 1 for the detailed method). Interestingly, the same chromosome 18 HDL-C QTL identified in 3 different crosses (NZB×SM intercross, C57BL/6J×C3H intercross, and C57BL/6J×CAST intercross) colocalizes with the newly found endothelial lipase gene, Lipg43,45⇓ (Table 2 and Figure 2).
Cellular Transporters and Receptors
ABC transporters constitute a group of evolutionarily highly conserved cellular transmembrane proteins that act either as active pumps, ion channels, or ATP sensors.46 The human genome sequence indicates that 51 ABC transporters exist.47 ABCA1 controls the active transport of cellular cholesterol and phospholipids to lipid-poor apolipoproteins. In humans, ABCA1 mutations affect HDL-C levels48 and cause Tangier disease, a severe HDL deficiency syndrome characterized by a rapid turnover of plasma apoA-I, accumulation of sterol in tissue macrophages, and atherosclerosis49–51⇓⇓ (see recent reviews7,52⇓). Abca1-deficient mice have extremely low HDL-C levels,53 and overexpression of ABCA1 in transgenic mice results in elevated apoA-I and HDL-C levels.54,55⇓ Abca1 colocalizes with a QTL for HDL-C concentrations to mouse chromosome 4 at cM 23.1 (Figure 2), making it an excellent candidate for this QTL.
ABCB4, encoded by ABCB4 (MDR3) in humans and Abcb4 (Mdr2) in mice, is a multidrug-resistant gene product. It has a highly restricted transport function, acting as a “flippase” in translocating phosphatidylcholine from the inner to the outer leaflet of the bile canalicular membrane.56 In Mdr2-targeted mutant mice, besides a complete absence of biliary phospholipid secretion, plasma levels of all classes of lipoproteins were reduced, particularly HDL.57 The reason is not clear. Therefore, it is interesting to find that Abcb4 colocalizes with an HDL-C QTL on chromosome 5 identified in the (PERA/Ei×I/Ln)F2 intercross.
Another ABC family member with an undefined role in HDL homeostasis is ABCB11 (bile salt export pump). Abcb11 (chromosome 2, cM 38.4) was shown to be upregulated in macrophages by cholesterol loading and downregulated by cholesterol unloading with HDL3 in 1 report,58 although no experimental data were shown in that study. Because of colocalization with an HDL-C QTL (lod score of 5.6) identified in a (C57BL/6J×CAST)F2 intercross (Table 2 and Figure 2), its role in HDL metabolism and atherosclerosis warrants future investigation. In addition to its potential role in HDL metabolism, Abcb11 is also a candidate for the gallstone QTL Lith159 (ABCB11 pumps bile salts from hepatocytes to bile canaliculi).
Recently, a polymorphism of ABCC660 was found to be associated with variations of HDL-C concentrations in humans. With the same method for mapping Lipg as mentioned above, we mapped mouse Abcc6 to chromosome 7 (cM 24.0), which is within the HDL-C QTL on chromosome 7.
The first HDL receptor was cloned in 1994 (see review61), although several cellular HDL binding sites had been described before. When first cloned, it was named SR-BI because it bound modified LDL (hence, the designation SR) and was the second (hence, the designation B) class of scavenger receptors found. However, it was later found to be primarily an HDL receptor mediating the selective uptake of HDL lipids. Among other functions, SR-BI selectively takes up cholesteryl esters and, under certain conditions, mediates cholesterol efflux from cells.62 Although Srb1-targeted mutant mice have twice as much HDL-C as do control mice, their susceptibility to atherosclerosis is higher than that of control mice.63,64⇓ Conversely, overexpression of Srb1 enhances selective cholesteryl ester uptake and HDL catabolism and severely decreases HDL-C concentrations.65 Mice overexpressing Srb1 are resistant to atherosclerosis66,67⇓; however, the protective effect was found in mice with moderately overexpressed Srb1 but was lost in mice with very high level of Srb1 transgene, probably because of the dramatic decrease of HDL cholesterol levels in these mice.68 An HDL-C QTL identified in 3 crosses (C57BL/6×CAST, NZB×SM, and C57BL/6×NZB) colocalizes with Srb1 (chromosome 5, cM 68.0; Table 2). However, the coding region of Srb1 had no polymorphic differences between NZB and SM.27 Furthermore, levels of liver SR-BI mRNA and protein did not differ between NZB and SM strains fed a chow diet.27 Because the QTL that mapped close to Srb1 was observed in the chow-fed mice from (NZB×SM)F2, these results do not support Srb1 as a candidate gene. The only study of the human orthologue of Srb1, CD36L1 (CD36 and LIMPII analogue 1, which encodes CLA-1), reveals no association between its polymorphisms and plasma HDL-C concentrations.69 However, the importance of mouse Srb1 in HDL metabolism and in its colocalization with mouse HDL-C QTL in several different crosses justifies more studies on this docking receptor for HDL cholesteryl esters.
CD36, another member of the class B scavenger receptor family, preferentially binds to and takes up moderately oxidized LDL. It also binds to HDL.70 However, neither overexpression of Cd36 in C57BL/6 mice71 nor Cd36 deficiency in Apoe-targeted mutant mice72 affects plasma HDL concentrations. Thus, even though Cd36 is in the region of the HDL QTL identified in (PERA/Ei×I/Ln)F2, no solid evidence supports it as a promising candidate gene for the QTL.
Recent studies have focused on the regulation of Abca1 and Abcg1 because therapies that upregulate them may increase HDL concentrations, promote reverse cholesterol transport, and thereby either prevent or even reverse atherosclerosis. As with Abcg1, Abca1 in macrophages is upregulated by cholesterol loading and downregulated by cholesterol unloading via HDL3.73 Abca1 is activated by the ligands for either or both retinoid X receptors (RXRs [retinoids]) and liver X receptors (LXRs [oxysterols]),74–76⇓⇓ which heterodimerize as either LXRα/RXR or LXRβ/RXR and bind to a DR4 element in the Abca1 promoter. Specifically, LXRβ binds to DR1 or DR4 elements consisting of direct AGGTCA repeats interrupted by either 1- or 4-nt spacers, respectively, and LXRα binds only to DR4 elements whose direct AGGTCA repeats are interrupted by 4-nt spacers. LXR/RXR heterodimers also upregulate Abcg1.77 The 2 genes encoding these transcription factors, Nr1h3 (Lxra) and Nr1h2 (Lxrb), colocalize with HDL-C QTL on chromosomes 2 and 7, respectively (Figure 2), making them excellent candidates for these QTL. Nr1h2 (Lxrb) may be a more attractive candidate than is Nr1h3 (Lxra) because LXRβ is more highly expressed in macrophages than is LXRα and is clearly more effective than LXRα in mediating the sterol response of ABCA1.74 Because these QTL studies suggest the candidacy of Nr1h3 (Lxra) and Nr1h2 (Lxrb) in HDL metabolism in mice, it will be interesting to discover how the polymorphisms for these genes in humans affect HDL-C concentrations.
The peroxisome proliferator–activated receptors (PPARs) are encoded by members of the nuclear receptor gene family that regulates lipid metabolism, glucose metabolism, and cellular differentiation. Like LXR, they can heterodimerize with RXR.78 Three Ppar genes have been found and mapped: Ppara (chromosome 15, cM 48.8, encoding PPARα), Pparg (chromosome 6, cM 52.7, encoding PPARγ), and Ppard (chromosome 17, cM 13.5, encoding PPARδ, also termed PPARβ). Although macrophages express all 3, the liver mainly expresses PPARα, adipose tissue mainly expresses PPARγ, and many tissues express PPARδ. PPARα and PPARγ activators have been shown to enhance the expression of ABCA1 via the stimulation of Nrlh3 (Lxra).79,80⇓ In addition, the agonists for these 2 PPARs enhance the expression of SR-BI/CLA-1, a docking receptor for HDL.81 In mice transgenic for human APOA1 and in humans, the PPARα agonist fibrate increases plasma HDL-C levels by inducing APOA1 and APOA2 genes in humans and the APOA1 gene in mice. However, in nontransgenic mice, fibrate decreases plasma HDL-C levels by repressing Apoa1 transcription.82 This opposite regulation of apoA-I expression in humans versus rodents is linked to differences in cis elements in their respective promoters.82 The PPARγ agonist troglitazone also increases serum HDL-C concentrations.83,84⇓ Consistent with the roles that PPARα and PPARγ play in HDL metabolism, QTL on chromosome 15 for plasma HDL-C levels occur near the Ppara gene in a (NZB×SM)F2 cross and are colocalized with the Pparg gene on chromosome 6 in (NZB-LXR×SM)F2 and (DBA/2×CAST/Ei)F2 crosses (Table 2 and Figure 2). Recently, GW501516, an agonist specific for PPARδ, was also found to upregulate Abca1. Additionally, it was found that agonists for PPARδ activate Abca1 better than do agonists for PPARγ and that agonists for PPARγ activate Abca1 better than do agonists for PPARα.85 However, GW501516 did not consistently upregulate LXR, suggesting that alternate mechanisms may contribute to the regulation of ABCA1 expression by PPARδ agonists. PPARδ agonists have also been found to increase plasma HDL-C concentrations in insulin-resistant C57BLKS-Leprdb/Leprdb mice86 and in rhesus monkeys.85 A QTL for HDL-C concentrations in an NZB×SM intercross colocalizes with Ppard on chromosome 17,25 which is consistent with the role of PPARδ in upregulating ABCA1 and HDL-C levels.
Our knowledge regarding the pathogenesis of atherosclerosis and the role HDL plays in the process is incomplete. Therefore, some QTL mentioned in the present review do not colocalize with obvious candidate genes. However, the human and mouse genome sequences will greatly facilitate finding those genes that affect HDL-C concentrations and atherosclerosis.
QTL for HDL-C Levels in Humans
So far, 10 published reports exist on genome-wide scans for identification of human QTL that determine HDL-C levels.87–96⇓⇓⇓⇓⇓⇓⇓⇓⇓ The results are summarized in Table 3. To gain further insight into the relevance of the mouse QTL to human studies, we list the mouse chromosome regions homologous to human HDL-C QTL. Interestingly, for 18 of the 22 human HDL-C QTL, at least part of their mouse homologous segments are within QTL for HDL-C levels detected in mouse crosses. Because the mouse HDL-C QTL represent ≈36% percent of the genome, it might be possible that the concordance between the QTL for HDL-C levels in the homologous regions of the human and mouse genome is by chance. However, statistically, this is not the case (χ2 test, P<0.01). The result of this comparison implies that many of the QTL for HDL-C levels found in humans have homologous counterparts in mice, implying that the QTL may result from common candidate genes. Because more mouse QTL for HDL-C concentrations have been found, possibly as a result of more extensive studies in mice than in humans, additional human chromosome segments that affect HDL-C concentrations can be predicted by the comparative genomic strategy. In this regard, QTL analysis for HDL-C levels in inbred strains of mice provides an immediate as well as long-term guideline and reference for studying genes regulating HDL metabolism and may be used to bridge mouse models and clinical investigations.
Identifying and Proving Candidate Genes
QTL mapping has identified a number of regions that contain genes affecting HDL-C concentrations in mice and humans. The next step is to identify those genes. Several approaches are possible. One is to narrow the QTL region genetically by carrying out crosses in mice until only 1 logical candidate remains or by searching for shared haplotypes in regions of linkage disequilibrium in humans. A second method is to test candidate genes directly. In humans, this can be done by searching for all the common polymorphisms in a gene and its regulatory region and then determining the frequency of each polymorphism in persons that differ in HDL-C concentrations. In mice, this is done by searching for sequence differences between the strains in which the QTL was found. Once a sequence difference in a gene has been found, the investigator has the task of proving that the sequence difference causes a functional difference, so the third method is to test for expression differences in mRNA or protein concentrations. Once an expression difference has been found, the investigator has the task of proving that the quantitative difference in mRNA or protein causes a quantitative difference in the HDL-C concentrations. In mice, this can be done by overexpressing the gene with the use of transgenic technology or by deleting the gene with the use of homologous recombination. Deletion of the gene produces many types of compensatory mechanisms; a better strategy would be to examine the phenotype in a heterozygote of the deleted gene, which would have only a single copy of a functional gene and, thus, theoretically 50% expression. In all these strategies, attention must be paid to the strain background, with strong preference to using the strains that gave the original QTL.
Finally, much of the search so far has focused on differences in HDL-C concentrations. Such a search tests only 1 aspect of the functions of HDL, and important and significant changes in HDL function that result from a change in composition, size, or metabolism might be missed by focusing only on concentrations of HDL-C. These other changes may be critical in determining the risk of developing atherosclerosis. Thus, the final task is to demonstrate that the gene change causing the difference in HDL-C concentrations also alters the development of atherosclerosis.
Notes on Nomenclature
Gene symbols used in the present review follow standard nomenclature for human and mouse genes as defined and updated by the Human Genome Organization (HUGO) Nomenclature Committee97 and the International Committee on Standardized Genetic Nomenclature in Mice,98 respectively. As a rule, mouse genes begin with a capital letter and are italicized. Human genes are entirely capitalized and are also italicized. Proteins are entirely capitalized but not italicized.
This work was funded by the National Institutes of Health (grant HL-62652) and by the Program for Genomic Applications of the Heart, Lung, and Blood Institute, National Institutes of Health (HL-66611). Map positions of 8 genes were determined by using the Celera database on the mouse sequence. The authors thank Ray Lambert for assistance in manuscript preparation and Jürgen K. Naggert and Beverly Richards-Smith for helpful review of the manuscript.
Received March 19, 2002; revision accepted June 28, 2002.
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