Articles in PresS. Physiol Genomics (March 5, 2013). doi:10.1152/physiolgenomics.00099.2012
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New quantitative trait loci for carotid atherosclerosis identified in an intercross
derived from apolipoprotein E-deficient mouse strains
Short title: QTLs for carotid Atherosclerosis
*Jessica S. Rowlan, *Zhimin Zhang, Qian Wang, Yan Fang, Weibin Shi
Departments of Radiology & Medical Imaging and of Biochemistry & Molecular Genetics,
University of Virginia, Charlottesville, VA 22908
Correspondence to:
Weibin Shi, MD, PhD
University of Virginia
Fontaine Research Park
P.O. Box 801339
480 Ray C Hunt Drive
Charlottesville, VA 22908
Fax: (434) 982 5680
Phone: (434) 243 9420
E-mail: [email protected]
* Authors contributed equally.
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Copyright © 2013 by the American Physiological Society.
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Abstract
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Carotid atherosclerosis is the primary cause of ischemic stroke. To identify genetic factors
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contributing to carotid atherosclerosis, we performed quantitative trait locus (QTL) analysis
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using female mice derived from an intercross between C57BL/6J (B6) and BALB/cJ (BALB)
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apolipoprotein E (Apoe−/−) mice. 266 F2 mice were started on a Western diet at 6 weeks of age
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and fed the diet for 12 weeks. Atherosclerotic lesions in the left carotid bifurcation and plasma
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lipid levels were measured.
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genotyped. Three significant QTLs, Cath1 on chromosome (Chr) 12, Cath2 on Chr5, and Cath3
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on Chr13, and four suggestive QTLs on Chr6, Chr9, Chr17, and Chr18 were identified for
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carotid lesions. The Chr6 locus replicated a suggestive QTL and was named Cath4. Six QTLs
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for HDL, three QTLs for non-HDL cholesterol, and three QTLs for triglyceride were found. Of
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these, a significant QTL for non-HDL on Chr1 at 60.3 cM, named Nhdl13, and a suggestive QTL
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for HDL on ChrX were new. A significant locus for HDL (Hdlq5) was overlapping with a
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suggestive locus for carotid lesions on Chr9. A significant correlation between carotid lesion
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sizes and HDL cholesterol levels was observed in the F2 population (R=-0.153, P=0.0133).
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Thus, we have identified several new QTLs for carotid atherosclerosis and the locus on Chr9
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may exert effect through interactions with HDL.
130 microsatellite markers across the entire genome were
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Introduction
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Stroke is the leading cause of disability in adults and the fourth most common cause of death in
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the United States (33). Ischemic stroke, resulting from the obstruction of blood flow to the brain,
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accounts for over 80% of all stroke cases (4). Most of the ischemic strokes are caused by
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atherosclerosis in the carotid arteries. Carotid plaques directly or indirectly, through formation
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of thrombi, result in stenosis of the vessels and block the blood flow to the brain (24). Due to the
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ready accessibility and the close association with the brain, the carotid arteries are the most
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extensively studied vessels in vivo with ultrasonography.
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stenosis have severely impaired cerebral blood flow and markedly increased risk for ipsilateral
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stroke (24),(26). For those with no obvious carotid stenosis, perspective studies also show a
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close association between the intima-media thickening and the risk of stroke (21)(25)(48).
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Intima-media thickening of the carotid arteries is an established parameter of subclinical
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atherosclerosis(9)(40).
Patients with noticeable carotid
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Genetic studies of twin pairs and families have demonstrated the heritability of carotid
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atherosclerosis or common and internal carotid artery intima media thickness (34)(44)(60).
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However, identification of susceptibility genes involved has not been achieved. To date, robust
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and replicatible associations in non-isolated populations are only limited to variants in the APOE
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gene (29). A recent meta-analysis of genome-wide association studies (GWAS) from the CHARGE
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consortium has identified a few common variants associated with carotid intima media thickness and
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plaque, including LRIG1, EDNRA, SLC17A4, PIK3CG, PINX1, ZHX2, APOC1, and LDLR (2).
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However, it is challenging to establish causality between the variants and the disease in humans
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due to small gene effect, complex genetic structure, and environmental influences.
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A complementary approach to the identification of human disease genes is to use model
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organisms.
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deficient (Apoe-/-) mouse, which develops all phases of atherosclerotic lesions throughout the
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aorta and its branches (27). We have demonstrated a dramatic influence of genetic backgrounds
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on the development of carotid atherosclerosis in Apoe-/- mouse strains(19). In an intercross
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derived from C57BL/6 (B6) and C3H/HeJ (C3H) Apoe-/- mice, we performed quantitative trait
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locus (QTL) analysis and identified the first significant locus for carotid atherosclerosis (19).
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Like C3H.Apoe-/- mice, BALB/cJ (BALB) Apoe-/- mice are highly resistant to atherosclerosis
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(46). In this study, we generated a F2 population from B6.Apoe-/- and BALB.Apoe-/- mice to
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search for new loci contributing to carotid atherosclerosis and associated lipid traits.
One commonly used mouse model of atherosclerosis is the apolipoprotein E-
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Methods
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Mice: B6.Apoe-/- mice were purchased from the Jackson Laboratories, and BALB.Apoe-/- mice at
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the N10 generation were generated in our laboratory. The creation of a female F2 population
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from the two Apoe-/- mouse strains was as reported (59). Mice were started on a Western diet
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containing 21% fat, 34.1% sucrose, 0.15% cholesterol, and 19.5% casein (Harlan Laboratories,
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TD 88137) at 6 weeks of age and maintained on the diet for 12 weeks. Mice were bled once
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before initiation of the Western diet and once at the end of the feeding period. Blood samples
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were collected from overnight fasted mice through a retro-orbital vein puncture with the animals
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under isoflurane anesthesia. All procedures were performed in accordance with current National
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Institutes of Health guidelines and approved by the University Animal Care and Use
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Committees.
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Plasma lipid analysis: The measurements of total cholesterol, HDL cholesterol, and triglyceride
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were performed as reported previously (46).
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difference between total and HDL cholesterol.
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Quantitation of carotid atherosclerosis: The distal portion of the left common carotid artery
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and its adjacent branches were harvested en bloc, embedded in OCT compound (Tissue-Tek),
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and processed, as we previously reported (19). Sections were stained with oil red O and
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hematoxylin and counterstained with fast green. Lesion areas were quantified using an ocular
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with a square-micrometer grid on a light microscope. The lesion areas of five sections with the
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largest readings were averaged for each mouse and this average was used for statistical analysis.
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Genotyping: A total of 130 microsatellite markers covering all 19 autosomes and the X
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chromosome at an average interval of ~12 cM were typed. Parental and F1 DNA served as
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controls for each marker.
Non-HDL cholesterol was calculated as the
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Statistical analysis. QTL analysis was performed using J/qtl software, as we previously reported
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(41)(42)(57). One thousand permutations of trait values were run to define the genome-wide
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LOD (logarithm of odds) score thresholds for significant and suggestive linkage to each trait.
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Loci that exceeded the 95th percentile of the permutation distribution were defined as significant
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(P<0.05) and those exceeding the 37th percentile were suggestive (P<0.63). Pair-wise genome
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scans were performed to find interacting loci affecting carotid lesions.
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Prioritization of candidate Genes. The Sanger SNP database (http://www.sanger.ac.uk/cgi-
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bin/modelorgs/mousegenomes/snps.pl) was searched to prioritize candidate genes for carotid
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lesion QTL that had been mapped in intercrosses derived from different parental strains.
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Probable candidate genes should possess one or more SNPs in coding or upstream promoter
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regions that are shared by the parental strains carrying the “high” allele but are different from the
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parental strains carrying the “low” allele.
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Results
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Trait value frequency distributions. Values of atherosclerotic lesion sizes in the left carotid
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bifurcation of 266 F2 mice were distributed in the Pareto manner: the proportion of F2 mice with
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a lesion size ≤ 5,000 μm2/section is the highest, and then decreases as lesion sizes increase (Fig.
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1). After being square root-transformed, these values approach a normal distribution. Values of
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LN (natural logarithm)-transformed HDL cholesterol, non-HDL cholesterol, and triglyceride
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concentrations are approximately normally distributed. These data were then analyzed using
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J/qtl software to detect significant and suggestive QTLs affecting the traits.
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Carotid atherosclerotic lesions. Genome-wide QTL analysis of either non-transformed carotid
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lesion sizes with the non-parametric mode or square root-transformed carotid lesion sizes with
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the parametric mode revealed 3 significant QTLs, located on chromosomes (Chr) 5, 12, and 13,
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and 2 suggestive QTLs, on Chr17 and Chr18, for carotid lesion sizes (Fig. 2). The QTL analysis
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of square root-transformed carotid lesions with the parametric mode also revealed 2 additional
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suggestive QTLs, located on Chr6 and Chr9. Details of the QTLs detected, including locus
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name, LOD score, 95% confidence interval (CI), peak location, genome-wide significance P
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value, high allele, and mode of inheritance are presented in Table 1. The significant QTL on
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Chr12 and the suggestive QTL on Chr6 replicated 2 previously reported QTLs (19). The other
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QTLs were novel. The Chr5 locus peaked at 56.7 cM and had a significant LOD score of 6.6
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and a genome-wide significant P value of 0.0001. We named it Cath2 to represent a locus for
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mouse carotid atherosclerosis. Interval mapping plots for Chr5 using either non-transformed
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carotid lesion data or square root-transformed lesion data showed 2 distinct peaks with each
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surpassing the significant LOD score threshold (Fig. 3), indicating the presence of 2 loci for the
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trait on the chromosome. The bootstrap test, a statistical method for defining the confidence
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interval of a QTL using simulation (49), also indicated the existence of 2 QTLs in the region for
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the trait. However, because the 2 loci overlapped in the confidence interval and both exhibited a
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dominant effect from the B6 allele, we designated them as a single QTL. The Chr13 locus had a
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significant LOD score of 5.1 and a genome-wide significance P value of 0.001. Its peak
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appeared at 49 cM. We named it Cath3. The Chr6 locus had a suggestive LOD score of 2.6 and
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peaked at 35.5 cM. It replicated a suggestive QTL for carotid lesions mapped in the B6.Apoe-/- x
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C3H.Apoe-/- intercross (19). We named it Cath4. For all 3 significant QTLs and 1 suggestive
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QTL on Chr17, the B6 allele was responsible for increased lesion sizes and the BALB allele
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accounted for reduced lesion sizes. In contrast, for the Chr18 locus the BALB allele was
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associated with increased lesion sizes and the B6 allele was associated with decreased lesion
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sizes (Table 2). The 2 suggestive QTLs on Chr6 and Chr9 exhibited an under-dominance
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manner of inheritance in that F2s with the heterozygous genotype had a significantly smaller or
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larger lesion size than those homozygous for the B6 or BALB allele.
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Pairwise genome scans were performed to search for interacting loci affecting carotid
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lesion sizes (Fig. 4). Significant interactions were detected between the Chr1 locus at 64 cM
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and the Chr16 locus at 21.7 cM, between the Chr2 locus at 50.2 cM and the Chr6 locus at 33.5
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cM, and between the Chr8 locus at 45.7 cM and the Chr16 locus at 43.7 cM. There were no
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main effect QTLs for carotid atherosclerosis at any of these loci alone. However, in those F2
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mice that were homozygous for the B6 allele at 21.7 cM on Chr16, the Chr1 locus exhibited an
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additive effect from the B6 allele in increasing lesion sizes. In F2 mice homozygous for the B6
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allele at 33.5 cM on Chr6, the BALB allele of Chr2 locus at 50.2 cM increased lesion sizes in an
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additive manner. The BALB allele of Chr8 locus at 45.7 cM also increased lesion sizes when the
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Chr16 locus was homozygous for the BALBc allele at 43.7 cM.
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Plasma lipid levels. Genome-wide QTL analysis showed that plasma HDL cholesterol, non-
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HDL cholesterol, and triglyceride levels were each controlled by multiple loci (Fig. 5, Table 1).
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For HDL, 2 significant QTLs, located on Chr1 and Chr9, and 4 suggestive QTLs on Chr13,
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Chr17, Chr19, and the X chromosome were identified. The 2 significant QTLs on Chr1 and
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Chr9 replicated Hdlq5 and Hdlq17, respectively, which had been mapped in several crosses (53).
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The Chr9 locus was partially overlapping with the suggestive locus for carotid atherosclerosis
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(Table 1). The suggestive locus on Chr13 partially overlapped with Lipq2, a locus identified in
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B6.C-H25C x BALB/cJ) F2 mice (55).
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overlapping in the confidence interval with Hdlq29 and Hdlq32, respectively, identified in a
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NZB x SM F2 cross (16).
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cholesterol, 2 significant QTLs on Chr1 and 1 suggestive QTL on Chr6 were identified. LOD
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score plot for Chr1 showed two distinct peaks, located approximately 14 cM apart (Fig. 6). The
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distal QTL peaked at 74.3 CM, overlapping with Cq1, a locus originally identified in a B6 × KK-
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Ay intercross for plasma cholesterol concentrations (43). The proximal peak occurred at 60.3
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cM with a significant LOD score of 5.93. We named Nhdlq13 to represent a significant QTL for
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non-HDL cholesterol in the mouse. The suggestive QTL on Chr6 replicated Pnhdlc1 mapped in
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a B6 x CASA/Rk intercross (37). Plasma triglyceride levels were controlled by 1 significant
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QTL on Chr1 and 2 suggestive QTLs on Chr7 and Chr8. The Chr1 and Chr7 QTLs replicated
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Tglq1 and Tgq4, respectively, loci originally mapped in a NZB × SM F2 cross (30). The Chr8
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QTL overlapped with Tql1 mapped in a KK/Ta × (BALB/cxKK/Ta) backcross (39).
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Relationships of plasma lipids with carotid atherosclerosis. Associations of carotid lesion
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sizes with plasma lipid levels were analyzed using the F2 population. A small but statistically
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significant inverse correlation was found between plasma HDL cholesterol levels and carotid
The suggestive QTLs on Chr17 and Chr19 were
The locus on the X chromosome was novel.
For non-HDL
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lesion sizes in the F2 mice (R=-0.153, P=0.0133; Fig. 7). Mice with higher HDL cholesterol
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levels tended to develop smaller carotid lesions. No statistically significant correlation was
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observed between non-HDL cholesterol levels and carotid lesion sizes, although there was a
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trend toward statistical significance (R=0.100; P=0.106). There was also a trend toward a
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significant inverse correlation between plasma triglyceride levels and carotid lesion sizes (R=-
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0.094; P=0.130).
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Probable candidate genes for Cath1. As Cath1 has also been mapped in an intercross between
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B6.Apoe-/- and C3H.Apoe-/- mice (19), we conducted a haplotype analysis using Sanger SNP
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database to prioritize candidate genes for the QTL (Table 3). A few candidate genes underneath
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the linkage peak of Cath1 were found, including Egln3 (55.3Mb), Eapp (55.7Mb), Mipol1
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(58.3Mb), Foxa1 (58.6Mb), Clec14a (59.3Mb), and Mis18bp1 (66.2Mb). These candidates
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contain one or more non-synonymous polymorphisms that are shared by the low allele strains
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(C3H and BALB) but are different from the high allele strain (B6) at the locus. Egln3, encoding
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EGL nine homolog 3, possesses the prolyl hydroxylase activity, which is required to suppress the
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activation of NF-kappaB (8). Mipol1, Foxa1, and Mis18bp1 are three genes associated with cell
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growth and tumor development. Recent GWAS studies have identified several new loci for
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coronary heart disease that are also associated with cancer (11)(36).
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endothelial cell-specific protein that plays a role in cell-cell adhesion. Knockdown of Clec14a
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with siRNA suppressed cell migratory activity in vitro (32).
Clec14a encodes an
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Discussion
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In this study, we used a F2 population derived from an intercross between two phenotypically
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divergent Apoe−/− mouse strains to localize chromosomal regions contributing to carotid
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atherosclerosis and associated lipid traits. We have identified three significant QTLs and four
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suggestive QTLs for carotid atherosclerosis and ten QTLs for plasma lipid levels from the cross.
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Moreover, we have observed significant associations of carotid lesion sizes with plasma HDL
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cholesterol levels in the F2 population.
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Cath1 was the first QTL for carotid atherosclerosis identified in an intercross between
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B6.Apoe−/− and C3H.Apoe−/− mice (19). It was located on mouse chromosome 12 at 25cM with
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the B6 allele contributing to an increased lesion size in female mice.
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replicated this QTL and also a suggestive locus on chromosome 6, now named Cath4, mapped in
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the previous cross. The confidence interval of Cath1 corresponds to human chromosome 14q12-
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14q24, a region that has shown linkage to carotid intimal medial thickness and premature
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coronary artery disease (6)(51). As Cath1. Pik3cg (32.8 Mb) is a gene in the region that has
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been found to be associated with carotid intima media thickness and plaque in humans on
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GWAS (2).
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upstream of the Pik3cg gene. We also conducted a haplotype analysis using parental strains in
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intercrosses that led to detection of Cath1, and found several probable candidate genes
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underneath the linkage peak of Cath1, including Egln3 (55.3Mb), Mipol1 (58.3Mb), Foxa1
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(58.6Mb), Clec14a (59.3Mb), and Mis18bp1 (66.2Mb).
The present study
There are multiple polymorphisms between B6 and BALB mice within and
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A new major QTL for carotid atherosclerosis mapped in this cross was Cath2, which had
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a highly significant LOD score. This locus was coincident with a fasting plasma glucose QTL,
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Bglu13, mapped in this cross (59). A significant correlation between fasting plasma glucose and
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carotid lesion sizes was also observed in the cross (data not shown), suggesting a possibility that
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both phenotypes were regulated by the same underlying QTL gene(s).
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encoding hepatocyte nuclear factor 1α, is the most promising candidate in this regard. It is
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located underneath the linkage peaks of Cath2 and Bglu13. One A/G SNP in exon 9 between B6
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and BALB leads to amino acid substitution (P580R) in the Hnf1a protein. In humans, Hnf1a
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mutations are the most common cause of maturity-onset diabetes of the young (MODY) (38).
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Polymorphisms in the Hnf1a gene are associated with risk for type 2 diabetes and coronary heart
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disease (31)(50).
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chromosomal regions of 4q22 and 12q24 in humans. The 12q24 region is associated with
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coronary heart disease (5)(36), carotid intima media thickening (6), metabolic syndrome (12)(58),
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type 1 and type 2 diabetes (47)(50)(56). Other probable candidate genes for the QTL include
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Adamts3 (90.1Mb), Ankrd17 (90.6Mb), and Cxcl5 (91.1Mb). The Adamt proteases are secreted
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enzymes that regulate extracellular matrix turnover by degrading specific matrix components.
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Recent studies have suggested a role for the proteases in inflammation and atherosclerosis (35).
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Ankrd17 encodes an ankyrin repeat protein that mediates protein-protein interactions. Ankyrin
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repeat proteins are involved in a variety of physiological processes, such as cell cycle control and
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inflammatory response(17)(54).
Hnf1a (114.9Mb),
The mouse chromosome 5 region from 48 to 67 cM corresponds to
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A new significant locus for carotid atherosclerosis, named Cath3, was found on
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chromosome 13 at 49 cM. This QTL was colocalized with a HDL locus, Lipq2, originally
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mapped in a B6.C-H25c x BALB/cJ cross (55) and replicated in the current cross. Moreover, a
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significant correlation was found between carotid lesion sizes and HDL cholesterol levels in the
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F2 population. Bhmt2 (94.4Mb), which is located underneath the linkage peak of Cath3, is a
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promising candidate gene. It encodes the betaine-homocysteine methyltransferase, an enzyme
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involved in regulating the susceptibility to acetaminophen-induced liver toxicity (20). This
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enzyme may also affect the susceptibility to high fat diet-induced liver damage. High fat diet
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results in a spectrum of liver damages, ranging from simple steatosis, to active inflammation, to
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advanced fibrosis and cirrhosis (3). B6.Apoe−/− mice develop severe hyperglycemia,
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dyslipidemia and systemic inflammation in response to high fat diet whereas BALB.Apoe−/−
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mice are resistant to these conditions (18)(46). In humans, steatostic liver disease is associated
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with increased prevalence of cardiovascular disease (29). F2rl1 (96.2Mb) and F2rl2 (96.4Mb)
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are also promising candidate genes in the region. They are involved in many processes relevant
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to atherosclerosis, such as inflammatory response, endothelium dysfunction, diet-induced obesity
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and insulin resistance (1)(15)(45).
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We found that QTLs in distal chromosome 1 was responsible for the major variations in
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plasma HDL, non-HDL cholesterol, and triglyceride levels of the cross.
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consistent with our observation made in two separate crosses between B6.Apoe−/− and
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C3H.Apoe−/− mice (19)(42). Apoa2 has been identified as a QTL gene on distal chromosome 1
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contributing to variations in plasma lipid levels of mice (52). We recently have demonstrated
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that Soat1 is also a QTL gene contributing to naturally occurring variations in plasma lipid levels
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of mice (22). In the current cross, we have observed two distinct peaks of the linkage curve for
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non-HDL cholesterol on chromosome 1 with the distal peak appearing at 74.3cM and the
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proximal peak at 60.3cM. The bootstrap test, a statistical method for defining the confidence
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interval of QTLs using simulation (49), also indicated the existence of two QTLs for the trait on
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chromosome 1. We named the proximal QTL Nhdlq13 to represent a new locus for non-HDL
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cholesterol in the mouse. Lct (130.2Mb), encoding lactase, is the only candidate gene in the
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QTL interval that could explain variation in plasma lipid levels.
This finding is
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A significant QTL for HDL was mapped to chromosome 9 at 24 cM in the current cross.
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This QTL was overlapping with Hdlq17 mapped in a B6 x 129S1/SvImJ intercross (13), Chol10
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mapped in a 129S1/SvImJ x RIIIS/J intercross (23), and Phdlc1 mapped in B6 x CASA/RkJ
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intercross (37). There are several promising candidate genes in the region, including St3gal4
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(34.8Mb), Sorl1 (41.7Mb), Sc5d (42Mb), Phldb1 (44.5Mb), Sik3 (46Mb), Apoa1 (46Mb),
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Fam55b (48.1Mb), and Fam55d (48.1Mb).
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Although dyslipidemia is a well-recognized risk factor for ischemic stroke, the present
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study of F2 mice has only revealed a weak correlation between carotid atherosclerotic lesion
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sizes and plasma HDL cholesterol levels. Unexpectedly, no correlations were observed between
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carotid lesions and non-HDL cholesterol or between carotid lesions and triglyceride levels. A
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previous study of F2 mice derived from B6.Apoe−/− and C3H.Apoe−/− mice also demonstrated no
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significant associations between carotid lesion sizes and plasma lipoprotein levels (19).
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In summary, we have identified multiple QTLs contributing carotid atherosclerosis and
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plasma lipid levels in hyperlipidemic Apoe−/− mice. Most of the QTLs identified for carotid
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atherosclerosis in this study are novel. The coincidence of QTLs for carotid atherosclerosis and
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HDL as well as the correlation between the traits suggests that they may be controlled by the
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same gene in the QTL interval.
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Sources of funding:
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This work was supported by NIH grant HL82881.
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562
28
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Legends
564
Figure 1. Frequency distributions of carotid atherosclerotic lesion sizes and plasma lipid levels
565
in 266 female F2 mice fed a Western diet for 12 weeks. The F2 mice were generated from an
566
intercross between B6.Apoe−/− and BALB.Apoe−/− mice. A, carotid atherosclerotic lesion sizes;
567
B, squire root-transformed carotid atherosclerotic lesion sizes; C, LN (natural log)-transformed
568
plasma HDL cholesterol levels; D, plasma non-HDL cholesterol levels; and E, plasma
569
triglyceride levels.
570
Figure 2. Genome-wide QTL analysis to search for loci influencing carotid lesion sizes in the F2
571
population derived from B6.Apoe−/− and BALB.Apoe−/− mouse strains. Chromosomes 1 through
572
20 are represented numerically on the X-axis. The relative width of the space allotted for a
573
chromosome reflects the number of microsatellite markers typed for that chromosome. The Y-
574
axis represents the LOD score. Two horizontal dashed lines denote genome-wide thresholds for
575
suggestive (P=0.63) and significant (P=0.05) linkage. The upper panel shows the QTL analysis
576
of original carotid lesion data with the non-parametric mode (A), and the lower panel shows the
577
QTL analysis of squire root-transformed carotid lesions using the parametric mode (B).
578
Figure 3. LOD score plots for carotid atherosclerotic lesions in the F2 population on
579
chromosome 5. The plots were created with the interval mapping function of Map Manager
580
QTX including a bootstrap test shown as a histogram estimating the confidence interval of a
581
QTL. Two straight vertical lines on the plot represent the genome-wide significance thresholds
582
for suggestive and significant linkage. The black line denotes the likelihood-ratio statistic
583
calculated at 1-cM intervals. The blue line represents the effect of the B6 allele, and the red line
584
represents the effect of the BALB allele. The left panel is the interval mapping graph for the
585
original carotid lesion data (A), and the right panel is the interval mapping graph for the squire
29
586
root-transformed carotid lesion data (B). The histogram in both plots suggests the existence of
587
two significant QTLs.
588
Figure 4. Interacting QTLs detected by pairwise genome scans. BB, homozygous for B6 alleles;
589
CC, homozygous for BALB alleles; BC heterozygous. The Y axe denotes carotid lesion sizes.
590
Error bars represent the standard deviation (SD).
591
Figure 5. Genome-wide QTL analysis to search for loci affecting plasma levels of HDL
592
cholesterol, non-HDL cholesterol, and triglyceride in the F2 population. Chromosomes 1 through
593
X are represented numerically on the X-axis and the Y-axis represents the LOD score.
594
Figure 6. LOD score plot for non-HDL cholesterol levels on chromosome 1. The plot was
595
created with the interval mapping function of Map Manager QTX, including a bootstrap test
596
shown as a histogram estimating the confidence interval for the QTL. The plot indicates the
597
existence of two significant QTLs for the trait on chromosome 1.
598
Figure 7. Scatterplots showing the relationship of carotid lesion sizes with lipid levels in the F2
599
population. Each point represents an individual value of a F2 mouse. The correlation coefficient
600
(R) and significance (P) are shown. Plasma levels of HDL cholesterol were significantly
601
correlated with the sizes of carotid lesions but plasma levels of non-HDL cholesterol and
602
triglyceride were not.
603
30
40
30
20
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Absolute frequency
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0 10 20 3
30 40 50 60 70 8
80 90 100
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y
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20 25 30 35 40 45 50
C tid llesion
Carotid
i size
i ((μm2 x 1000)
55
0
70 140 210 280 350 420 490 560 630 700 770
Squire root of carotid lesion size (μm2 x 1000)
2.4 2.8 3.2 3.6
4.0 4.4
4.8 5.2 5.6
Ln of HDL (mg/dl)
E
D
C
60
390 520 650 780 910 1040 1170 1300 1430 1560
Non-HDL (mg/dl)
63
84 105 126 147 168 189 210 231 252
Triglyceride (mg/dl)
Figure 1
4
3
Threshold: 0.05
Threshold: 0.63
0
1
2
LO
OD score
5
6
7
A
1
2
3
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5
6
7
8
9
10
11
12
13
14 15 16 17 18 19
20
11
12
13
14 15 16 17 18 19
20
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0
LOD s
score
5
B
6
Chromosome
1
2
3
4
5
6
7
8
9
Chromosome
10
Figure 2
A
B
Figure 3
Ca
arotid lesion
n
2
(µm x1000)
250
Chr16 @ 21.7cM
Chr6 @ 33.5cM
Chr16 @ 43.7cM
350
300
200
250
150
200
100
150
100
50
50
0
BB
BC
0
CC
Chr1 @ 64.3cM
Chr2 @ 50.2cM
BB
BC
CC
Chr8 @ 45.7cM
Figure 4
6
5
3
Threshold: 0.63
0
1
2
HDL
4
Threshold: 0.05
2
3
4
5
6
7
8
9
10
11
12
13
14 15 16 17 18 19
20
4
3
2
Threshold: 0.63
0
1
non-HDL
Threshold: 0.05
2
3
4
5
6
7
8
9
10
11
12
13
14 15 16 17 18 19
20
6
1
Triglyceride
0 1 2 3 4 5
LOD score
e
5
6
1
Threshold: 0.05
Threshold: 0.63
1
2
3
4
5
6
7
8
9
10
Chromosome
11
12
13
14 15 16 17 18 19
20
Figure 5
Figure 6
C
Carotid lesions
s (μm2x1000)
Ca
arotid lesions (μm2x1000)
R=-0.153;
R=-0 153; P=0.0133
P=0 0133
600
500
400
300
200
100
0
0
100
200
300
400
HDL (mg/dl)
R=0.100;
R=0 100; P=0.106
P=0 106
600
500
400
300
200
100
0
0
500
1000
1500
Non-HDL (mg/dl)
2000
Ca
arotid lesions (μm2x1000)
R 0 094 P=0.130
P 0 130
R=-0.094;
600
500
400
300
200
100
0
0
50
100
150
200
250
300
Triglyceride (mg/dl)
Figure 7
Table 1. Significant and suggestive QTLs for carotid atherosclerosis and plasma lipid levels in F2 mice derived from B6.Apoe-/- and
BALB.Apoe-/- mice.
Locus
namea
Cath2
Cath1
Cath3
Cath2
Cath4
Cath1
Cath3
Hdlq5
Hdlq17
Lipq2
Hdlq29
Hdlq32
Nhdlq13
Cq1
Pnhdlc1
Tglq1
Tgq4
Tgl1
Chr
5
12
13
17
18
5
6
9
12
13
17
18
1
9
13
17
19
20
1
1
6
1
7
8
Trait
Carotid lesion (nonparametric)
Carotid lesion (nonparametric)
Carotid lesion (nonparametric)
Carotid lesion (nonparametric)
Carotid lesion (nonparametric)
Carotid lesion (parametric)
Carotid lesion (parametric)
Carotid lesion (parametric)
Carotid lesion (parametric)
Carotid lesion (parametric)
Carotid lesion (parametric)
Carotid lesion (parametric)
HDL
HDL
HDL
HDL
HDL
HDL
Non-HDL
Non-HDL
Non-HDL
Triglyceride
Triglyceride
Triglyceride
b
LOD
6.615
5.095
4.292
2.641
2.274
5.64
2.595
2.064
4.734
3.95
2.861
2.234
4.291
5.917
2.428
2.924
2.509
2.763
5.93
5.85
2.617
6.069
2.28
2.481
Peak
(cM)
56.68
32.59
48.99
22.14
30
48.68
35.5
69.87
32.59
50.99
22.14
30
82.31
23.8
59.69
29.73
40.3
51.49
60.31
74.3
53.5
74.31
41.37
69.7
c
95% CI
48.46-66.68
16.59-44.59
18.99-59.69
8.14-28.14
16-40
48.46-70.68
25.5-57.5
17.8-69.87
14.59-44.59
14.99-60.99
8.14-28.14
18-42
74.31-92.31
19.8-27.8
44.99-67.21
23.97-40.14
18.3-46.3
35.49-76.75
54.31-82.31
69.3-82.3
33.5-67.5
68.31-89.0
33.37-65.37
31.7-72.18
d
P value
0.0001
0.001
0.009
0.248
0.455
0.001
0.295
0.652
0.001
0.019
0.175
0.508
0.008
0.0001
0.415
0.166
0.351
0.217
0.0001
0.0001
0.281
0.0001
0.458
0.347
High
allele
B6
B6
B6
B6
BALB
B6
B6
B6
B6
BALB
BALB
BALB
BALB
BALB
BALB
BALB
BALB
B6
BALB
B6
-
Mode
e
inheritance
Dominant
Additive
Additive
Recessive
Additive
Dominant
of
Underdominance
Underdominance
Additive
Additive
Recessive
Additive
Additive
Additive
Dominant
Dominant
Recessive
Underdominance
Dominant
Additive
Additive
Additive
Additive
Underdominance
The newly identified QTLs were named if they were significant or if they replicated previously reported suggestive ones. The
nomenclature of Cath was for carotid atherosclerosis QTLs. The newly identified QTLs were underlined to easily distinguish them
a
from known ones.
b
LOD scores were obtained from genome-wide QTL analysis using J/qtl software. The significant LOD scores were highlighted in
bold. The suggestive and significant LOD score thresholds were determined by 1,000 permutation tests for each trait. Suggestive and
significant LOD scores were 2.064 and 3.410, respectively, for carotid atherosclerosis (nonparametric); 2.096 and 3.475 for squire
root-transformed carotid atherosclerosis (parametric); 2.090 and 3.600 for HDL cholesterol, 2.081 and 3.513 for NON-HDL
cholesterol, and 2.066 and 3.679 for triglyceride.
c
95% Confidence interval in cM defined by a whole genome QTL scan.
d
The p-values reported represent the level of genome-wide significance as they were generated based on genome-wide permutation
tests.
e
Mode of inheritance was defined according to allelic effect at the nearest marker of a QTL.
2
Table 2. Effects of B6 (B) and BALB (C) alleles in different QTLs on carotid atherosclerosis and plasma lipids in the intercross
between B6.Apoe−/− and BALB.Apoe−/− mouse strains.
Locus
name
Cath2
Cath1
Cath3
Cath2
Cath4
Cath1
Cath3
Hdlq5
Hdlq17
Lipq2
Hdlq29
Hdlq32
Nhdlq13
Cq1
Pnhdlc1
Tglq1
Tgq4
Tgl1
Chr
5
12
13
17
18
5
6
9
12
13
17
18
1
9
13
17
19
20
1
1
6
1
7
8
Trait
Carotid lesion (nonparametric)
Carotid lesion (nonparametric)
Carotid lesion (nonparametric)
Carotid lesion (nonparametric)
Carotid lesion (nonparametric)
Carotid lesion (parametric)
Carotid lesion (parametric)
Carotid lesion (parametric)
Carotid lesion (parametric)
Carotid lesion (parametric)
Carotid lesion (parametric)
Carotid lesion (parametric)
HDL
HDL
HDL
HDL
HDL
HDL
Non-HDL
Non-HDL
Non-HDL
Triglyceride
Triglyceride
Triglyceride
Peak
Marker
D5Mit41
D12Mit201
D13Mit147
D17Mit66
D18Mit35
D5Mit155
D6Mit243
D9Mit279
D12Mit201
D13Mit147
D17Mit66
D18Mit35
D1Mit354
D9Mit285
D13Mit148
D17Mit20
D19Mit90
DXMit84
D1Mit495
D1Mit354
D6Mit102
D1Mit354
D7NDS1
D8Mit13
Peaks
(cM)
56.68
32.59
48.99
22.14
30
48.68
35.5
69.87
32.59
50.99
22.14
30
82.31
23.8
59.69
29.73
40.3
51.49
60.31
80.32
53.5
74.31
41.37
69.7
BB
116832.9±109325.5 9 (n=68)
146489.2±110520.6 (n=52)
146242.1±104769.9 (n=58)
149831.4±114851.4 (n=65)
79168.0±75581.7 (n=65)
114473±108135 (n=72)
114825±101947 (n=64)
81594±76681 (n=62)
146489±110521 (n=52)
146242±104770 (n=58)
149831±114851 (n=65)
79168± 75582 (n=65)
65.3 ± 34.1 (n=57)
61.1 ± 37.9 (n=71)
63.5 ± 41.5 (n=56)
61.8 ± 35.8 (n=69)
67.6 ± 36.5 (n=64)
68.1 ± 35.9 (n=79)
845.3 ± 195.0 (n=65)
855.7 ± 199.6 (n=57)
1010.9 ± 197.1 (n=66)
117.2 ± 31.7 (n=57)
143.8 ± 33.2 (n=55)
128.3 ± 33.1 (n=65)
CC
71120.7±92371.5 (n=55)
72933.6±95294.4 (n=59)
79884.7±93992.1 (n=77)
102302.1±107115.5 (n=76)
133860.3±118030.6 (n=63)
64025±90979 (n=51)
145489±127531(n=80)
109173±99109 (n=59)
72934±95294 (n=59)
79885±93992 (n=77)
102302±107116 (n=76)
133860±118031 (n=63)
99.2 ± 31.6 (n=68)
100.5 ± 55.5 (n=52)
84.9 ± 52.2 (n=82)
84.5 ± 51.9 (n=66)
93.7 ± 60.3 (n=68)
68.7 ± 54.5 (n=43)
994.1 ± 196.5 (n=65)
1026.2 ± 215.8 (n=68)
895.2 ± 210.9 (n=73)
145.1 ± 38.0 (n=68)
124.2 ± 29.3 (n=64)
123.3 ± 29.7 (n=64)
BC
129914.7±104129.0 (n=131)
115870.9±100169.5 (n=154)
116396.0±103879.1 (n=130)
99280.7±90916.3 (n=115)
120239.4±105365.8 (n=134)
129348±101158 (n=137)
89273±78934 (n=121)
128345±112776 (n=142)
115871±100170 (n=154)
116396±103879 (n=130)
99281±90916 (n=115)
120239±105366 (n=134)
71.4 ± 12.7 (n=128)
74.8 ± 43.6 (n=135)
77.9 ± 43.6 (n=123)
80.8 ± 46.2 (n=121)
72.2 ± 39.9 (n=128)
84.5 ± 48.3 (n=138)
978.6 ± 215.1 (n=123)
945.2 ± 206.0 (n=128)
953.3 ± 217.5 (n=118)
135.2 ± 31.8 (n=128)
134.2 ± 36.5 (n=134)
140.1 ± 35.7 (n=127)
P-value
2.05E-03
6.66E-04
8.20E-04
3.92E-03
6.06E-03
5.38E-04
7.18E-04
1.14E-02
6.66E-04
8.20E-04
3.92E-03
6.06E-03
2.47E-05
3.76E-06
2.82E-02
6.12E-03
1.52E-03
1.92E-02
2.35E-05
4.20E-05
5.87E-03
2.82E-05
7.29E-03
2.62E-03
Measurements are expressed as means ± SD. The units for these measurements are: µm2/section for carotid atherosclerotic lesions and
mg/dl for plasma lipid levels. BB, homozygous for B6 alleles at the linked peak marker; CC, homozygous for BALB alleles; BC,
heterozygous for B6 and BALB alleles at the peak marker. The number in the bracket represents the number of progeny with a
specific genotype at a peak marker. ANOVA was used to determine the significance level (p value) of differences for a specific
3
phenotype among progeny with three different genotypes at a specific marker.
4
Table 3. Haplotype analysis to prioritize candidate genes for Cath1
High allele
Low allele
Gene
chr
position C57BL/6
BALB C3H
Egln3
Eapp
Gm16382
2700097O09Rik
Prps1l3
Mipol1
Foxa1
Ttc6
Clec14a
12
12
12
12
12
12
12
12
12
12
12
12
55304356
55304602
55304677
55771990
55772852
55773051
55774107
55774193
55774467
55796707
55802602
56146803
A
T
G
T
G
A
A
T
C
G
T
T
G
G
A
C
a
t
T
C
T
A
g
C
G
G
A
C
a
t
T
C
T
A
G
C
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
56149876
56181074
58331404
58331419
58404379
58426585
58426610
58558185
58567779
58597592
58642920
58643254
58677129
59365857
59366183
59366468
59368777
59369326
59369975
G
C
A
C
G
A
A
C
T
C
C
T
G
T
T
G
T
T
C
C
a
G
T
A
G
G
T
G
T
c/g
C
C
C
C
A
C
C
G
C
A
G
T
A
G
G
T
G
T
c/g
C
C
C
C
A
C
C
G
5
Ctage5
Fscb
Klhl28
Fancm
12
12
12
12
12
12
12
12
12
12
12
12
12
59369979
60232475
65572716
65573078
65573952
65574300
66043857
66043917
66043927
66044072
66044105
66051133
66214956
G
T
G
G
C
G
C
G
A
T
A
C
A
C
C
A
C
a
A
G
C
G
G
G
T
+
T
12
66231329
A
C
12
66231384
A
T
12
66231423
A
C
C
C
A
C
A
A
G
C
G
G
G
T
+
T
+
C
+
T
+
C
+
+
+
Mis18bp1
12
66249896
A
a/c
a/c
12
66249994
C
T
T
12
66253824
T
C
C
12
66253867
C
A
A
12
66253871
T
A
A
12
66273454
T
A
A
12
66273538
A
G
G
Analysis was performed using Sanger SNP database (http://www.sanger.ac.uk/cgi-bin/modelorgs/mousegenomes/snps.pl).
Yellow color denotes non-synonymous nucleotide substitution and blue denotes synonymous nucleotide substitution.
6