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Am J Hum Genet. 2005 July; 77(1): 1–16. Published online 2005 May 19. | PMCID: PMC1226181 |
Copyright © 2005 by The American Society of Human Genetics. All rights reserved. Identifying Novel Genes for Atherosclerosis through Mouse-Human Comparative Genetics Xiaosong Wang,1 Naoki Ishimori,2 Ron Korstanje,3 Jarod Rollins,1 and Beverly Paigen1 1The Jackson Laboratory, Bar Harbor, ME; 2Department of Cardiovascular Medicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan; and 3Department of Pathology and Laboratory Medicine, Medical Biology Section, University of Groningen and University Medical Centre Groningen, Groningen, The Netherlands Received April 14, 2005; Accepted May 4, 2005. Susceptibility to atherosclerosis is determined by both environmental and genetic factors. Its genetic determinants have been studied by use of quantitative-trait–locus (QTL) analysis. So far, 21 atherosclerosis QTLs have been identified in the mouse: 7 in a high-fat–diet model only, 9 in a sensitized model (apolipoprotein E– or LDL [low-density lipoprotein] receptor–deficient mice) only, and 5 in both models, suggesting that different gene sets operate in each model and that a subset operates in both. Among the 27 human atherosclerosis QTLs reported, 17 (63%) are located in regions homologous (concordant) to mouse QTLs, suggesting that these mouse and human atherosclerosis QTLs have the same underlying genes. Therefore, genes regulating human atherosclerosis will be found most efficiently by first finding their orthologs in concordant mouse QTLs. Novel mouse QTL genes will be found most efficiently by using a combination of the following strategies: identifying QTLs in new crosses performed with previously unused parental strains; inducing mutations in large-scale, high-throughput mutagenesis screens; and using new genomic and bioinformatics tools. Once QTL genes are identified in mice, they can be tested in human association studies for their relevance in human atherosclerotic disease. Atherosclerosis is the pathological basis of ischemic coronary artery disease (CAD), the leading cause of death in industrialized nations. It is characterized by accumulation of plasma lipids, fibrous tissues, and cell components (mostly macrophages, smooth-muscle cells, and lymphocytes) in large arteries. Atherosclerosis is a complex disease caused by both genetic (with ~50% heritability) and environmental (mostly diet) factors. The underlying genes have been studied through genotype- and phenotype-driven approaches. In the genotype-driven approach, a gene suspected of contributing to atherosclerosis is tested for a pathological role either in atherogenesis, by use of transgenic/knockout animal models, or in rare Mendelian forms of human atherosclerosis. Studies with mouse models have identified >80 atherosclerosis-regulating genes, and some of their human orthologs have confirmed polymorphisms associated with human atherosclerotic diseases, including genes encoding the angiotensin-converting enzyme ( ACE [MIM 106180]); adrenergic receptor, beta 2 ( ADRB2 [MIM 109690]); 5-lipoxygenase–activating protein ( ALOX5AP [MIM 603700]); apolipoprotein E ( APOE [MIM 107741]); coagulation factor VII ( F7 [MIM 227500]); fibrinogen, B beta polypeptide ( FGB [MIM 134830]); glycoprotein 1b, alpha polypeptide ( GP1BA [MIM 606672]); matrix metalloproteinase 3 ( MMP3 [MIM 185250]); matrix metalloproteinase 9 ( MMP9 [MIM 120361]); 5,10-methylenetetrahydrofolate reductase ( MTHFR [MIM 607093]); nitric oxide synthase 3, endothelial cell ( NOS3 [MIM 163729]); serum paraoxonase ( PON1 [MIM 168820]); transforming growth factor, beta 1 ( TGFB1 [MIM 190180]); thrombospondin 2 ( THBS2 [MIM 188061]); thrombospondin 4 ( THBS4 [MIM 600715]); toll-like receptor 4 ( TLR4 [MIM 603030]) (Agah and Topol 2002; Humphries and Morgan 2004; Lusis et al. 2004; Manolio et al. 2004; McCarthy et al. 2004); and tumor necrosis factor (ligand) superfamily, member 4 ( TNFSF4 [MIM 603594]) (Wang et al. 2005b). In the phenotype-driven approach, no assumption is made as to which genes cause a disease phenotype, and atherosclerosis is linked to chromosome locations, QTLs, in a genomewide scan. This approach has the advantage of finding novel atherosclerosis-susceptibility genes. Two reviews summarize some of these QTLs (Allayee et al. 2003; Smith 2003). Here, we present an updated review of atherosclerosis QTLs found in mice and humans, compare atherosclerosis QTLs found in the two most commonly used mouse models (diet-induced and sensitized), and comment on their concordance with human atherosclerosis QTLs. Finally, we propose future strategies for finding novel genes regulating human atherosclerosis. QTLs for Atherosclerotic Diseases in Humans So far, nine genomewide scans have been reported for human atherosclerotic diseases, including myocardial infarction (MI), CAD, acute coronary syndrome (ACS; acute MI and unstable angina), and carotid artery intimal-medial thickness (CIMT) ( table 1). Thirty-one individual QTLs (those found in different populations, regardless of whether they are at the same chromosomal locations) have been identified. They are distributed on 27 chromosome locations, and four of them—on chromosomes 2, 3, 12, and 13—are found in two populations, so there are 27 unique QTLs (). Six genes that have confirmed association with the risk of atherosclerotic diseases in at least two independent populations lie in 6 of the 27 QTLs. Analyses consistently indicate that ALOX5AP underlies the MI and stroke QTL on proximal chromosome 13 (Ben-Asher and Lancet 2004; Helgadottir et al. 2004; Lohmussaar et al. 2005). The R353Q polymorphism in F7 is significantly associated with MI (McCarthy et al. 2004), so it is a candidate for the MI QTL on distal chromosome 13q. The C-1252T polymorphism in the promoter region of MMP9 is associated with the size of complicated lesions and the stenosis of coronary arteries (Zhang et al. 1999; Pollanen et al. 2001), suggesting that it is the gene underlying the ACS QTL on chromosome 20q. The C677T SNP in MTHFR is significantly associated with CIMT in a Chinese population and a Japanese population (Humphries and Morgan 2004), making it a candidate for the top chromosome 1p QTL. More than two dozen studies indicate that the Q192R polymorphism of PON1 underlies the CAD QTL on chromosome 7q (Durrington et al. 2001; Agah and Topol 2002), although a recent meta-analysis revealed only a weak relative risk of 1.12 (95% CI 1.07–1.16) (Wheeler et al. 2004). Association studies in two groups of patients with MI revealed that a polymorphism in the first intron of TNFSF4 is associated with the risk of MI and CAD, suggesting that it underlies the CAD QTL on chromosome 1q (Wang et al. 2005b). In addition, it is highly likely that MEF2A (encoding myocyte enhancer factor 2A [MIM 600660]) is the gene underlying the chromosome 15q MI QTL, because there is a 7-aa deletion in MEF2A in all 13 of the patients with MI but not from the 8 normal individuals from a family (Wang et al. 2003a), and three novel mutations in exon 7 of MEF2A are present in 4 of the 207 study patients with CAD/MI but not in 191 control subjects (Bhagavatula et al. 2004). | Table 1QTLs for Atherosclerotic Diseases in Humans |
Of the >80 genes shown to influence atherosclerosis in either gene-knockout or transgenic mouse models—and at least 17 genes having confirmed polymorphisms associated with human atherosclerotic diseases—only about a quarter of them fall within human atherosclerosis QTLs, as indicated in . Half of the human atherosclerosis QTLs have no obvious candidate genes, which suggests that their genetic determinants are unknown. QTLs for Atherosclerosis in Mice Atherosclerosis QTLs in mice have been identified in two models: (1) a high-fat–diet model, in which a diet containing 15% fat, 1.25% cholesterol, and 0.5% cholic acid is used to induce atherosclerosis, and (2) the sensitized model, in which mice deficient in Apoe—or low-density lipoprotein receptor ( Ldlr)—are used (Jawien et al. 2004; Meir and Leitersdorf 2004). Apoe-deficient mice develop atherosclerosis spontaneously when fed a chow diet; their lesions develop faster when they are fed a Western diet (containing 21% fat and 0.15% cholesterol) and more so when they are fed the high-fat diet described above. Ldlr-deficient mice also develop atherosclerotic lesions when fed the chow diet, but the lesions are very small and take considerable time to develop; feeding these mice a Western diet or the high-fat diet described above accelerates their lesion formation. A total of 15 studies using mouse models of atherosclerosis detected 35 individual QTLs. Among them, there are 21 unique QTLs (QTLs identified in different crosses but at the same chromosomal location are counted as one unique QTL because they may have the same underlying gene [ table 2 and ]). Of the 21 QTLs, 7 are revealed only in the high-fat–diet model, 9 only in the sensitized model, and 5 in both models (). Of the 21 QTLs, 12 are replicated in more than one cross, which enables the use of haplotype analysis to narrow these QTLs (Wang and Paigen 2005b). The causal genes underlying 2 of the 21 mouse atherosclerosis QTLs have been identified: Tnfsf4 ( Ox40l) for Ath1 (atherosclerosis susceptibility 1) on chromosome 1 (Wang et al. 2005b) and Alox5 for Artles on chromosome 6 (Mehrabian et al. 2002). Additionally, Angptl3 is probably one gene underlying a complex locus, Ath8, on chromosome 4, which may contain more than one QTL (Korstanje et al. 2004). | Table 2QTL for Atherosclerosis in Inbred Mouse Crosses |
Concordance of Human and Mouse Atherosclerosis QTLs The term “concordance” refers to the fact that QTLs for the same trait but from different species map to homologous genomic regions. It was first used to describe hypertension QTLs that map to homologous regions in rats, mice, and humans (Stoll et al. 2000; Sugiyama et al. 2001). It has since been observed for kidney disease (Korstanje and DiPetrillo 2004) and plasma levels of high-density lipoprotein (HDL) (Wang and Paigen 2005a), low-density lipoprotein, and triglycerides (Wang and Paigen 2005b). For atherosclerosis, 13 (62%) of the 21 mouse QTLs are concordant with human QTLs, and 17 (63%) of the 27 human QTLs are concordant with mouse QTLs (figs. and ), suggesting that more than half of the mouse and human atherosclerosis QTLs have the same underlying genes. Thus, identifying them in one species should greatly facilitate identifying them in the other. Concordant QTLs are found for five (71%) of the seven mouse atherosclerosis QTLs in the high-fat model, six (67%) of the nine in a sensitized model, and two (40%) of the five in both models (). Altogether, more than half of the QTLs found in each model have concordant human QTLs, so it cannot be said that one model is more relevant to human atherosclerotic disease than the other. Three reasons may explain why some of the human QTLs do not have concordant mouse QTLs. First, not enough mouse crosses have been made. Second, and perhaps more important, C57BL/6 (B6) mice were used as the susceptible parental strain in 11 of the 13 crosses made so far to detect mouse atherosclerosis QTLs. Use of different susceptible strains may detect different QTLs that are concordant with human QTLs. Third, the size of atherosclerotic lesions in mice (used as the phenotype in all the QTL studies in mice so far) only partially corresponds to the incidence of human atherosclerotic diseases. In fact, the incidence of human ACS is determined not only by lesion size but also, more importantly, by plaque stability. Thus, future mouse QTL studies that include plaque stability as a phenotype may identify additional QTLs that are concordant with human atherosclerosis QTLs. Strategies for Finding Novel Genes Regulating Human Atherosclerosis Using the Mouse-to-Human Strategy Finding QTL genes in mice is much more cost-effective, less time consuming, and less fraught with ethical issues than is finding them first in humans, especially now that many new genetic, genomic, and bioinformatics tools for the mouse are available (discussed in the “ Integrating Traditional Genetic Approaches with New Genetic, Genomic, and Bioinformatic Resources and Tools” section). After a QTL gene is identified in the mouse, it can be tested in human association studies for its role in human diseases. The completion of the human HapMap project will greatly simplify such studies by facilitating the selection of representative SNPs of a haplotype block. In addition, dense SNPs throughout the human genome have made possible whole-genome association studies, whereby the candidacy of all the genes in human diseases are systematically studied (Ozaki et al. 2002; Carlson et al. 2004). This mouse-to-human strategy has been successfully used to identify POMC (encoding pro-opiomelanocortin-alpha [MIM 176830]) as a gene influencing obesity (Krude et al. 1998; Hixson et al. 1999); CTLA4 (encoding cytotoxic T-lymphocyte-associated protein 4 [MIM 123890]) as a gene contributing to autoimmune disorders, including Graves disease, autoimmune hypothyroidism, and type 1 diabetes (Ueda et al. 2003); and EN2 (encoding engrailed 2 [MIM 131310]) as a gene for autism-spectrum disorder (Gharani et al. 2004). This strategy has also been used to identify an atherosclerosis-susceptibility gene in humans. Ath1 is a QTL on chromosome 1 that makes B6 mice more susceptible to atherosclerosis than C3H mice (Paigen et al. 1987a, 1987b). By using congenic strains, we narrowed Ath1 to a 0.66-cM region containing 11 genes (Phelan et al. 2002). Three of the 11 genes could be involved in atherosclerosis: Prdx6 (peroxiredoxin 6 [also called “antioxidant protein 2”]) encodes an antioxidant (Steinberg and Witztum 2002), Tnfsf4 encodes a membrane protein on lymphocytes and endothelial cells (Hansson et al. 2002), and Fasl (Fas ligand) is important for apoptosis (Geng 2001). After analyzing atherosclerosis susceptibility in mouse mutants for each of these genes, we found that only Tnfsf4-targeted mutants were significantly less susceptible to diet-induced atherosclerosis than were wild-type controls and that mice overexpressing Tnfsf4 were more susceptible to atherosclerosis than were wild-type controls. We then tested SNPs in TNFSF4 as well as in the nearby genes in human association studies, and we found that only a polymorphism of TNFSF4 was significantly associated with the risk of MI and CAD in humans (Wang et al. 2005b). We therefore identified a human atherosclerosis gene from a mouse QTL. Making More Mouse Crosses Although 21 mouse atherosclerosis QTLs have been revealed, additional mouse crosses will expedite finding genes that regulate atherosclerosis, for the following reasons. First, among the 25 individual mouse atherosclerosis QTLs published since 2003, 14 are new, and only 11 are replicates of QTLs found before, suggesting that the mouse QTL map has not been saturated and that new QTLs will be identified in new crosses. Second, additional mouse crosses may confirm previously found QTLs (nearly half of the mouse QTLs are found in only one cross) and may provide more strains for haplotype analysis (Wang et al. 2004b; Wang and Paigen 2005b). Third, 11 of the 13 crosses use B6 as the susceptible parent. Using different susceptible strains—such as SM/J, SWR/J, and NON/LtJ—may reveal different QTLs. Fourth, there are 27 human and only 21 mouse QTLs, and 10 of the 27 human ones have no concordant mouse QTL. Additional mouse crosses may reveal QTLs concordant with these human QTLs and may expedite finding their underlying genes with the mouse-to-human strategy. Including Plaque Stability and Coronary Atherosclerosis as Phenotypes Effective treatment of human atherosclerosis should include stabilizing plaque as well as reducing the accumulation of plasma lipids, and consequently the formation of fibrolipid cores in the arterial wall. So far, the only atherosclerosis phenotype used in mouse genomewide-scan studies is the size of the lipid-staining lesions. Thus, some of the genes identified may regulate intimal lipid deposition but not plaque stability. The latter may be more relevant to clinical events of human atherosclerosis, because ACS is usually caused by plaque rupture and the subsequently formed thrombi that obstruct coronary arteries rather than increased plaque size. Thus, future genomewide scans should include phenotypes that reflect stability of atherosclerotic plaques, such as thickness and rupture of fibrous cap and formation of intraplaque hemorrhage, thrombus, and buried fibrous cap. Plaque rupture has been observed in B6 mice with deficiency of Apoe when mice are fed either chow (Rosenfeld et al. 2000) or a diet with high-cholesterol content (Johnson and Jackson 2001; Williams et al. 2002; Johnson et al. 2005). The most frequently observed site of rupture is the innominate (brachiocephalic) artery, as shown in the studies just cited, and genes controlling atherosclerosis in the innominate artery and aortic root may be different (Reardon et al. 2003; Teupser et al. 2004). The vessels most relevant to human atherosclerotic diseases are, of course, the coronary arteries. Advanced atherosclerotic lesions do occur in mouse coronary arteries when mice are deficient in either Apoe, Ldlr, both Apoe and Ldlr, or Scarb1 (encoding scavenger receptor class B, member 1) and when they are fed either chow (Braun et al. 2002) or a diet with high-cholesterol content (Caligiuri et al. 1999; Calara et al. 2001). Thus, future genomewide scans in mice perhaps should include coronary atherosclerosis as a phenotype. Finding Genes Regulating Human Atherosclerosis by Studying QTLs for Both Atherosclerosis and HDL So far, 37 mouse and 30 human HDL-regulating QTLs have been identified (Wang and Paigen 2005a). Some of the genes underlying these QTLs may also regulate atherogenesis, given the compelling evidence that HDL protects against atherosclerosis (Brewer 2004; Gotto and Brinton 2004). Thus, human atherosclerosis-regulating genes can be identified by either (1) finding the gene underlying a mouse atherosclerosis QTL and then testing it for a role in human atherosclerosis or (2) finding the gene underlying a mouse HDL QTL and then testing whether it regulates HDL levels and atherosclerosis in humans. Integrating Traditional Genetic Approaches with New Genetic, Genomic, and Bioinformatic Resources and Tools A QTL interval is usually large and typically contains hundreds of genes. The first step toward finding a causal gene is to narrow the QTL. QTL-narrowing strategies that take advantage of recombinations in mouse crosses include one or more of the following: (1) interval-specific congenic strains, (2) advanced intercross lines, (3) heterogeneous stocks, (4) recombinant inbred (RI) segregation test, (5) recombinant progeny testing, (6) selective phenotyping, (7) yin-yang cross, and (8) collaborative cross. Interval-specific congenic strains Mice that are recombinant in the QTL region are crossed for several generations with the background parental strain to eliminate alleles from the donor parental strain at all QTLs affecting the trait (other than the QTL being mapped). Animals are then intercrossed, and homozygotes for the recombinant haplotype are selected to establish one congenic strain. Several congenic strains with overlapping regions can differentiate which region contains the QTL gene (Darvasi 1998). Recently, two sets of mice with overlapping congenic regions, covering the whole genome, were generated; one set is B6.DBA/2, the other is B6.CAST. These sets will facilitate narrowing QTLs from B6 × DBA/2 and B6 × CAST crosses (Iakoubova et al. 2001). Advanced intercross lines Mice from two inbred progenitor strains are crossed to yield F1 offspring, which are intercrossed to produce F2 offspring. Fifty F2 × F2 matings are made (avoiding brother-sister matings) to produce F3 offspring, and fifty F3 × F3 matings are made (avoiding brother-sister and cousin matings) to produce F4 offspring, and so on, until the desired advanced intercross (F5, F6, and so on) is attained. Thus, the many recombinations required to narrow a QTL accumulate in a relatively small final population (Darvasi 1998). Heterogeneous stocks Heterogeneous stocks are derived from multiple inbred strains (eight strains in current stocks) through continued intercrossing. They are essentially advanced intercross lines made from multiple strains instead of two (Mott et al. 2000). RI segregation test This strategy requires an existing set of RI strains and takes advantage of the high mapping resolution of RI strains and applies it to QTL mapping. An RI strain with a recombinant haplotype in the region of interest is crossed with both parental strains to produce two separate F1 populations. Intercrossing these F1 individuals then produces F2 mice. By analysis of the F2 populations, a QTL can be located relative to the recombination point, because the QTL previously mapped to this region will segregate in only one of the two F2 populations (Darvasi 1998). Recombinant progeny testing Mice carrying a recombinant chromosome in the QTL region are crossed with one of the parental strains, and their progeny are phenotyped to determine the location of the QTL relative to the recombination point (Darvasi 1998). Selective phenotyping In a large intercross or backcross population, only individuals recombinant at an interval previously found to contain a QTL are phenotyped, because only those individuals contribute to further mapping accuracy (Darvasi 1998). Yin-yang cross.—Yin-yang cross is a generalization of the RI segregation test that uses inbred strains as if they are RI lines (Shifman and Darvasi 2005). This method is based on the observation that the many inbred laboratory mice are derived from a limited number of founder populations, so the large number of recombination events accumulated in inbred strains since their origin can be used to fine map a QTL to a very small region. The statistical analysis of a yin-yang cross depends on the knowledge of the SNPs of the strains used and is actually similar to haplotype analysis of multiple crosses (Hitzemann et al. 2002; Park et al. 2003; Manenti et al. 2004; Wang et al. 2004b). Collaborative cross The collaborative cross is not an existing resource, but it has been recently proposed (Churchill et al. 2004). It is a panel of 1,000 RI strains derived from eight inbred strains. With an estimated 135,000 unique recombination events and known genotypes in the whole panel, QTLs can be mapped to a very small interval without making any crosses. However, all these approaches require many recombinant animals, which makes the analyses slow, labor intensive, and sometimes difficult to generate because of the existence of recombination hotspots (Kelmenson et al. 2005). In addition to the above strategies, new genetic and genomic resources, especially mouse and human genome sequences, have led to new strategies in narrowing a QTL and even in identifying its underlying gene by analysis of combined cross data, comparison of mouse and human homologous QTLs, analysis of SNPs and haplotypes in multiple strains, and detection of in silico QTLs, as discussed by Wang and Paigen ( 2005b). It should be cautioned that successfully identifying a QTL gene from haplotype analysis and in silico QTL mapping depends in large part on detailed genome sequence/SNP information in many strains, which is only partly available now. A complete sequence of more mouse strains is likely to fully empower haplotype analysis and in silico QTL mapping, as reviewed by Flint et al. ( 2005). Once a QTL is narrowed with the above approaches, candidate genes can be tested for sequence and expression difference between parental strains (Wang and Paigen 2005b). To study the genetics of gene expression, Jansen and Nap proposed a genomewide scan using gene-expression data as phenotypes that can be obtained from microarray analysis (Jansen and Nap 2001); chromosome segments thus obtained are called “expression QTLs” (eQTLs). Because the vast majority of eQTL genes are cis-regulated (Bystrykh et al. 2005; Chesler et al. 2005; Hubner et al. 2005), candidate genes of a physiological QTL (pQTL) (with use of clinical traits as phenotype) can be identified by overlapping such a pQTL with eQTLs: differentially expressed genes in a pQTL region could be good candidates (Schadt et al. 2003; Chesler et al. 2005; Hubner et al. 2005). Using Mutagenesis as a Complementary Approach Although the QTL approach takes advantage of spontaneous mutations that had accumulated in the past and had been fixed in the various inbred strains of laboratory mice (Lander and Botstein 1989), a mutagenesis approach is capable of generating, in a short time, large numbers of mutations across the genome (Balling 2001). Very efficient at low toxicity, ENU is an alkylating mutagen that induces ~ 1×10-3 random point mutations per locus. It affects germ cells, particularly spermatogonial stem cells. Once adult mice are mutagenized, they are bred, and offspring abnormalities are detected in high-throughput phenotyping screens. Deviants are tested for heritability (Balling 2001). The large-scale and high-throughput features of mutagenesis can potentially generate mutations in every gene. Some of these mutations will help us understand a gene’s functions. The HLB Mutagenesis Program at The Jackson Laboratory is using ENU mutagenesis to identify genes regulating a wide range of cardiovascular phenotypes (Svenson et al. 2003). Atherosclerosis in mutagenized mice cannot be screened with either cross-sectional (Paigen et al. 1987c) or en face analysis (Palinski et al. 1994), because deviant mice need to be kept for breeding. Instead, noninvasive methods should be used. Magnetic resonance imaging (MRI) provides high-resolution images on not only lesion size (Fayad et al. 1998; Choudhury et al. 2002; Hockings et al. 2002) but also its components (lipid core and cap) (McAteer et al. 2004; Schneider et al. 2004). MRI could be used for an atherosclerosis screen in mutagenized mice if the throughput could be increased. The most efficient way to find atherosclerosis-regulating genes in humans is to first find orthologs underlying concordant QTLs, preferably replicate ones, in the mouse. Such QTLs will increase in numbers as new mouse crosses are performed, and they can be rapidly narrowed by analysis of combined cross data, in silico QTL analyses, and haplotype analyses. Because replicated QTLs are likely caused by conserved ancestral alleles, causal genes within the narrowed region should exhibit sequence and/or expression differences consistent with their allele effects in all parental strains. These candidate genes, if associated with atherosclerotic diseases in humans, can then be tested, positively identified, and their functions studied in transgenic and/or knockout mice. This work was supported by National Institutes of Health grants HL66611 and HL77796 (to B.P.) and HL70486 (to X.W.) and from American Heart Association grant AHA430381N (to X.W.). We thank Michael Marion and Ray Lambert, for helping to prepare the manuscript; Jennifer L. Torrance, for helping to prepare the graphics; and Dr. Keith DiPetrillo, for critically reviewing the manuscript. 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