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Anthony P Kent, Ioannis M StylianouDepartment of Medicine and Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine, Philadelphia, PA, USAAbstract: Scavenger receptor class B member 1 (SR-BI, also known as SCARB1) is the primary receptor for the selective uptake of cholesterol from high-density lipoprotein (HDL). SR-BI is present in several key tissues; however, its presence and function in the liver is deemed the most relevant for protection against atherosclerosis. Cholesterol is transferred from HDL via SR-BI to the liver, which ultimately results in the excretion of cholesterol via bile and feces in what is known as the reverse cholesterol transport pathway. Much of our knowledge of SR-BI hepatic function and regulation is derived from mouse models and in vitro characterization. Multiple independent regulatory mechanisms of SR-BI have been discovered that operate at the transcriptional and post-transcriptional levels. In this review we summarize the critical discoveries relating to hepatic SR-BI cholesterol metabolism, atherosclerosis, and regulation of SR-BI, as well as alternative functions that may indirectly affect atherosclerosis.Keywords: SR-BI, SCARB1, lipids, atherosclerosis, CAD, mouse models

Gain-of-function variants in the voltage-gated sodium channel Nav1.7, encoded by the SCN9A gene, have previously been identified in patients with erythromelalgia, a clinical diagnosis defined by intermittent attacks of painful, hot, swollen, and red skin, predominantly involving the hands and feet. Symptoms are induced or aggravated by warming and relieved by cooling. In primary erythromelalgia there is no known underlying disease. This study investigated the frequency of SCN9A variants in a cohort of primary erythromelalgia patients collected at a single centre, and examined the clinical signs and symptoms associated with identified variants. One hundred patients with possible erythromelalgia were collected prospectively and evaluated by clinical examination. Thirty-five patients fulfilling the clinical criteria of primary erythromelalgia were screened for variants in SCN9A. Five were found to carry likely causal variants, including a variant found in 2 related individuals and a variant not previously described in patients with erythromelalgia. The clinical findings differed significantly between the patients. Overall, in this cohort only 4/34 (11.7%) of unrelated patients had erythromelalgia likely caused by gain-of-function variants in SCN9A. Variants in SCN9A are therefore likely to cause or contribute to primary erythromelalgia in only a small proportion of patients.

Background: Cluster headache is the most severe primary headache disorder. A genetic basis has long been suggested by family and twin studies; however, little is understood about the genetic variants that contribute to cluster headache susceptibility., Methods: We conducted a literature search of the MEDLINE database using the PubMed search engine to identify all human genetic studies for cluster headache. In this article we provide a review of those genetic studies, along with an overview of the pathophysiology of cluster headache and a brief review of migraine genetics, which have both been significant drivers of cluster headache candidate gene selection., Results: The investigation of cluster headache genetic etiology has been dominated by candidate gene studies. Candidate selection has largely been driven by the pathophysiology, such as the striking rhythmic nature of the attacks, which spurred close examination of the circadian rhythm genes CLOCK and HCRTR2 . More recently, unbiased genetic approaches such as genome-wide association studies (GWAS) have yielded new genetic avenues of interest including ADCYAP1R1 and MME ., Conclusions: The majority of candidate genes studied for cluster headache suffer from poor reproducibility. Broader genetic interrogation through larger unbiased GWAS, exome, and whole genome studies may provide more robust candidates, and in turn provide a clearer understanding of the causes of cluster headache.

Genome-wide association studies have struggled to identify functional genes and variants underlying complex phenotypes. We recruited a multi-ethnic cohort of healthy volunteers (n = 91) and used their tissue to generate induced pluripotent stem cells (iPSCs) and hepatocyte-like cells (HLCs) for genome-wide mapping of expression quantitative trait loci (eQTLs) and allele-specific expression (ASE). We identified many eQTL genes (eGenes) not observed in the comparably sized Genotype-Tissue Expression project's human liver cohort (n = 96). Focusing on blood lipid-associated loci, we performed massively parallel reporter assays to screen candidate functional variants and used genome-edited stem cells, CRISPR interference, and mouse modeling to establish rs2277862-CPNE1, rs10889356-DOCK7, rs10889356-ANGPTL3, and rs10872142-FRK as functional SNP-gene sets. We demonstrated HLC eGenes CPNE1, VKORC1, UBE2L3, and ANGPTL3 and HLC ASE gene ACAA2 to be lipid-functional genes in mouse models. These findings endorse an iPSC-based experimental framework to discover functional variants and genes contributing to complex human traits., (Copyright © 2017 Elsevier Inc. All rights reserved.)

While genetic determinants strongly influence HDL cholesterol (HDLc) levels, most genetic causes underlying variation in HDLc remain unknown. We aimed to identify novel rare mutations with large effects in candidate genes contributing to extreme HDLc in humans, utilizing family-based Mendelian genetics. We performed next-generation sequencing of 456 candidate HDLc-regulating genes in 200 unrelated probands with extremely low (≤10th percentile) or high (≥90th percentile) HDLc. Probands were excluded if known mutations existed in the established HDLc-regulating genes ABCA1, APOA1, LCAT, cholesteryl ester transfer protein (CETP), endothelial lipase (LIPG), and UDP-N-acetyl-α-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 2 (GALNT2). We identified 93 novel coding or splice-site variants in 72 candidate genes. Each variant was genotyped in the proband's family. Family-based association analyses were performed for variants with sufficient power to detect significance at P < 0.05 with a total of 627 family members being assessed. Mutations in the genes glucokinase regulatory protein (GCKR), RNase L (RNASEL), leukocyte immunoglobulin-like receptor 3 (LILRA3), and dynein axonemal heavy chain 10 (DNAH10) segregated with elevated HDLc levels in families, while no mutations associated with low HDLc. Taken together, we have identified mutations in four novel genes that may play a role in regulating HDLc levels in humans., (Copyright © 2014 by the American Society for Biochemistry and Molecular Biology, Inc.)

Human coding variants in scavenger receptor class B member 1 (SR-BI; gene name SCARB1) have recently been identified as being associated with plasma levels of HDL cholesterol. However, a link between coding variants and atherosclerosis has not yet been established. In this study we set out to examine the impact of a SR-BI coding variant in vivo. A mouse model with a coding variant in SR-BI (I179N), identified through a mutagenesis screen, was crossed with Ldlr (-/-) mice, and these mice were maintained on a Western-type diet to promote atherosclerosis. Mice showed 56 and 125 % increased atherosclerosis in female and male Ldlr (-/-) Scarb1 (I179N) mice, respectively, when compared to gender-matched Ldlr (-/-) control mice. As expected, HDL cholesteryl ester uptake was impaired in Ldlr (-/-) Scarb1 (I179N) mice compared to Ldlr (-/-) control mice, with a net effect of increased small and very small LDL cholesterol in Ldlr (-/-) Scarb1 (I179N) mice being the most probable cause of the observed increased atherosclerosis. Our data show that non-null coding variants in SR-BI can have a large significant impact on atherosclerosis, even if plasma lipid levels are not dramatically affected, and that human mutations in other candidate lipid genes could significantly impact atherosclerosis.

Atherosclerosis is a complex and heritable disease involving multiple cell types and the interactions of many different molecular pathways. The genetic and molecular mechanisms of atherosclerosis have, in part, been elucidated by mouse models; at least 100 different genes have been shown to influence atherosclerosis in mice. Importantly, unbiased genome-wide association studies have recently identified a number of novel loci robustly associated with atherosclerotic coronary artery disease. Here, we review the genetic data elucidated from mouse models of atherosclerosis, as well as significant associations for human coronary artery disease. Furthermore, we discuss in greater detail some of these novel human coronary artery disease loci. The combination of mouse and human genetics has the potential to identify and validate novel genes that influence atherosclerosis, some of which may be candidates for new therapeutic approaches.

Purpose of Review: Recent genome-wide association studies (GWAS) have identified approximately 100 genomic loci that are associated with plasma lipid traits, two-thirds of which had never been previously associated with lipoprotein metabolism. Identification of the causal genes and variants, functional validation of these genes and biological pathways, and elucidation of molecular mechanisms is required and poses a daunting task., Recent Findings: Human genetics have been used to recently 'validate' genes, such as LIPG, SCARB1 and ANGPTL3, which were previously implicated in lipoprotein metabolism through classical wet bench approaches. Additionally, many novel genes have been identified as associated with plasma lipid traits by GWAS, though only relatively few have been functionally validated through targeted sequencing and genetic manipulation in cells and animals. These types of studies have defined new roles in lipid metabolism for the novel lipid genes SORT1 and TRIB1. These examples demonstrate the ways in which human genetics can validate candidate genes, as well as provide a novel discovery that requires functional validation at the bench, and point towards a more complete understanding of the molecular physiology of lipoprotein metabolism., Summary: This review summarizes recent developments in the use of human genetics to validate candidate genes in lipoprotein metabolism as well as in the functional validation of novel GWAS loci associated with plasma lipid traits.

Aims: Two single-nucleotide polymorphisms (SNPs), rs1746048 and rs501120, from genome wide association studies of coronary artery disease (CAD) map to chromosome 10q11 ∼80 kb downstream of chemokine CXCL12. Therefore, we examined the relationship between these two SNPs and plasma CXCL12 levels., Methods and Results: We tested the association of two SNPs with plasma CXCL12 levels in a two-stage study (n= 2939): first in PennCath (n= 1182), a Caucasian, angiographic CAD case-control study, and second in PennCAC (n= 1757), a community-based study of CAD risk factors. Plasma CXCL12 levels increased with age and did not vary by gender. There was no linkage disequilibrium between these two SNPs and SNPs within CXCL12 gene. However, CAD risk alleles at rs1746048 (C allele, P= 0.034; CC 2.33 ± 0.49, CT 2.27 ± 0.46, and TT 2.21 ± 0.52 ng/mL) and rs501120 (T allele, P= 0.041; TT 2.34 ± 0.49, CT 2.28 ± 0.46, and CC 2.23 ± 0.53 ng/mL) were associated with higher plasma levels of CXCL12 in age and gender adjusted models. In Stage 2, we confirmed this association (rs501120, T allele, P= 0.007), and meta-analysis strengthened this finding (n= 2939, P= 6.0 × 10(-4)). Finally, in exploratory analysis, the rs1746048 risk allele tended to have higher transcript levels of CXCL12 in human natural killer cells and the liver., Conclusion: Coronary artery disease risk alleles downstream of CXCL12 are associated with plasma protein levels of CXCL12 and appear to be related to CXCL12 transcript levels in two human cell lines. This implicates CXCL12 as potentially causal and supports CXCL12 as a potential therapeutic target for CAD.

Background: Plasma levels of high-density lipoprotein cholesterol (HDL-C) are known to be heritable, but only a fraction of the heritability is explained. We used a high-density genotyping array containing single-nucleotide polymorphisms (SNPs) from HDL-C candidate genes selected on known biology of HDL-C metabolism, mouse genetic studies, and human genetic association studies. SNP selection was based on tagging SNPs and included low-frequency nonsynonymous SNPs., Methods and Results: Association analysis in a cohort containing extremes of HDL-C (case-control, n=1733) provided a discovery phase, with replication in 3 additional populations for a total meta-analysis in 7857 individuals. We replicated the majority of loci identified through genome-wide association studies and present on the array (including ABCA1, APOA1/C3/A4/A5, APOB, APOE/C1/C2, CETP, CTCF-PRMT8, FADS1/2/3, GALNT2, LCAT, LILRA3, LIPC, LIPG, LPL, LRP4, SCARB1, TRIB1, ZNF664) and provide evidence that suggests an association in several previously unreported candidate gene loci (including ABCG1, GPR109A/B/81, NFKB1, PON1/2/3/4). There was evidence for multiple, independent association signals in 5 loci, including association with low-frequency nonsynonymous variants., Conclusions: Genetic loci associated with HDL-C are likely to harbor multiple, independent causative variants, frequently with opposite effects on the HDL-C phenotype. Cohorts comprising subjects at the extremes of the HDL-C distribution may be efficiently used in a case-control discovery of quantitative traits.

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

Background: To assess the utility of haplotype association mapping (HAM) as a quantitative trait locus (QTL) discovery tool, we conducted HAM analyses for red blood cell count (RBC) and high density lipoprotein cholesterol (HDL) in mice. We then experimentally tested each HAM QTL using published crosses or new F2 intercrosses guided by the haplotype at the HAM peaks., Results: The HAM for RBC, using 33 classic inbred lines, revealed 8 QTLs; 2 of these were true positives as shown by published crosses. A HAM-guided (C57BL/6J x CBA/J)F2 intercross we carried out verified 2 more as true positives and 4 as false positives. The HAM for HDL, using 81 strains including recombinant inbred lines and chromosome substitution strains, detected 46 QTLs. Of these, 36 were true positives as shown by published crosses. A HAM-guided (C57BL/6J x A/J)F2 intercross that we carried out verified 2 more as true positives and 8 as false positives. By testing each HAM QTL for RBC and HDL, we demonstrated that 78% of the 54 HAM peaks were true positives and 22% were false positives. Interestingly, all false positives were in significant allelic association with one or more real QTL., Conclusion: Because type I errors (false positives) can be detected experimentally, we conclude that HAM is useful for QTL detection and narrowing. We advocate the powerful and economical combined approach demonstrated here: the use of HAM for QTL discovery, followed by mitigation of the false positive problem by testing the HAM-predicted QTLs with small HAM-guided experimental crosses.

Objective: Fish oil (FO), and specifically omega 3 fatty acids, has favorable effects on cardiovascular outcomes. The aim of this study was to investigate the effects of FO on the process of macrophage reverse cholesterol transport (RCT) in an in vivo mouse model., Methods and Results: C57BL/6J mice were fed a FO diet, whereas control mice were fed diets containing alternative sources of fats, soybean oil (SO), and coconut oil (CO) for 4 weeks. Macrophage RCT was assessed by injecting [(3)H]cholesterol-labeled J774 macrophages intraperitoneally into mice. After 48 hours, tissues were harvested and feces were collected. An increase in the excretion of macrophage-derived [(3)H]-tracer recovered in fecal neutral sterols for FO-fed mice was observed (273% versus SO and 182% versus CO). FO also decreased [(3)H]-tracer in hepatic cholesteryl ester compared to SO and CO by 76% and 56%, respectively. To specifically determine the effect of FO on the fate of HDL-derived cholesterol, mice fed FO or SO diets were injected with HDL labeled with [(3)H]cholesteryl oleate, and the disappearance of [(3)H]-tracer from blood and its excretion in feces was measured. There was no significant difference in the fractional catabolic rate of [(3)H]cholesteryl oleate-HDL between the 2 groups. However, there was a 242% increase in the excretion of HDL-derived [(3)H]-tracer recovered in fecal neutral sterols in FO-fed mice, concordant with significantly increased expression of hepatic Abcg5 and Abcg8 mRNA., Conclusions: As measured by this tracer-based assay, FO promoted reverse cholesterol transport, primarily by enhancement of the hepatic excretion of macrophage-derived and HDL-derived cholesterol.

To identify genes controlling plasma HDL and triglyceride levels, quantitative trait locus (QTL) analysis was performed in one backcross, (NZO/H1Lt x NON/LtJ) x NON/LtJ, and three intercrosses, C57BL/6J x DBA/2J, C57BL/6J x C3H/HeJ, and NZB/B1NJ x NZW/LacJ. HDL concentrations were affected by 25 QTL distributed on most chromosomes (Chrs); those on Chrs 1, 8, 12, and 16 were newly identified, and the remainder were replications of previously identified QTL. Triglyceride concentrations were controlled by nine loci; those on Chrs 1, 2, 3, 7, 16, and 18 were newly identified QTL, and the remainder were replications. Combining mouse crosses with haplotype analysis for the HDL QTL on Chr 18 reduced the list of candidates to six genes. Further expression analysis, sequencing, and quantitative complementation testing of these six genes identified Lipg as the HDL QTL gene on distal Chr 18. The data from these crosses further increase the ability to perform haplotype analyses that can lead to the identification of causal lipid genes.

Interindividual variability in response to chemicals and drugs is a common regulatory concern. It is assumed that xenobiotic-induced adverse reactions have a strong genetic basis, but many mechanism-based investigations have not been successful in identifying susceptible individuals. While recent advances in pharmacogenetics of adverse drug reactions show promise, the small size of the populations susceptible to important adverse events limits the utility of whole-genome association studies conducted entirely in humans. We present a strategy to identify genetic polymorphisms that may underlie susceptibility to adverse drug reactions. First, in a cohort of healthy adults who received the maximum recommended dose of acetaminophen (4 g/d x 7 d), we confirm that about one third of subjects develop elevations in serum alanine aminotransferase, indicative of liver injury. To identify the genetic basis for this susceptibility, a panel of 36 inbred mouse strains was used to model genetic diversity. Mice were treated with 300 mg/kg or a range of additional acetaminophen doses, and the extent of liver injury was quantified. We then employed whole-genome association analysis and targeted sequencing to determine that polymorphisms in Ly86, Cd44, Cd59a, and Capn8 correlate strongly with liver injury and demonstrated that dose-curves vary with background. Finally, we demonstrated that variation in the orthologous human gene, CD44, is associated with susceptibility to acetaminophen in two independent cohorts. Our results indicate a role for CD44 in modulation of susceptibility to acetaminophen hepatotoxicity. These studies demonstrate that a diverse mouse population can be used to understand and predict adverse toxicity in heterogeneous human populations through guided resequencing.

Cardiovascular disease (CVD) is the largest cause of premature death in human populations throughout the world. Circulating plasma lipid levels, specifically high levels of LDL or low levels of HDL, are predictive of susceptibility to CVD. The scavenger receptor class B member 1 (SCARB1) is the primary receptor for the selective uptake of HDL cholesterol by liver and steroidogenic tissues. Hepatic SCARB1 influences plasma HDL-cholesterol levels and is vital for reverse cholesterol transport. Here we describe the mapping of a novel N-ethyl-N-nitrosourea (ENU) induced point mutation in the Scarb1 gene identified in a C57BL/6J background. The mutation is located in a highly conserved amino acid in the extracellular loop and leads to the conversion of an isoleucine to an asparagine (I179N). Homozygous mutant mice express normal Scarb1 mRNA levels and are fertile. SCARB1 protein levels are markedly reduced in liver (approximately 90%), but not in steroidogenic tissues. This leads to approximately 70% increased plasma HDL levels due to reduced HDL cholesteryl ester selective uptake. Pdzk1 knockout mice have liver-specific reduction of SCARB1 protein as does this mutant; however, in vitro analysis of the mutation indicates that the regulation of SCARB1 protein in this mutant is independent of PDZK1. This new Scarb1 model may help further our understanding of post-translational and tissue-specific regulation of SCARB1 that may aid the important clinical goal of raising functional HDL.

Objective: To identify the gene responsible for the quantitative trait locus (QTL) Hdlq14, a high-density lipoprotein cholesterol (HDL) QTL previously identified in a C57BL/6Jx129S1/SvImJ cross., Methods and Results: Hdlq14 was first confirmed as an independent QTL by detecting it in an intercross between NZB/B1NJ and NZW/LacJ, 2 strains that had identical genotypes at nearby QTL genes on chromosome 1. Using the bioinformatics tools of combined cross data and haplotype analysis, we narrowed this QTL from a 45-Mb 225-gene region to 2 genes, Farp2 and Stk25. Sequencing and expression studies showed that Farp2 had an amino acid polymorphism in an important plekstrin domain and that Stk25 had a significant expression difference between the parental strains. These 2 genes are immediately adjacent to each other and share the same haplotype over 45 inbred strains. The haplotype was associated with a significant difference in HDL levels among these strains., Conclusions: We confirmed Hdlq14 as a separate independent QTL for HDL and narrowed the region to 2 genes, Farp2 and Stk25, with considerable evidence for both. Additional studies are needed to choose between these 2 genes or to show that both are important in determining HDL levels.

Recent advances in mouse genomics have revealed considerable variation in the form of single-nucleotide polymorphisms (SNPs) among common inbred strains. This has made it possible to characterize closely related strains and to identify genes that differ; such genes may be causal for quantitative phenotypes. The mouse strains DBA/1J and DBA/2J differ by just 5.6% at the SNP level. These strains exhibit differences in a number of metabolic and lipid phenotypes, such as plasma levels of triglycerides (TGs) and HDL. A cross between these strains revealed multiple quantitative trait loci (QTLs) in 294 progeny. We identified significant TG QTLs on chromosomes (Chrs) 1, 2, 3, 4, 8, 9, 10, 11, 12, 13, 14, 16, and 19, and significant HDL QTLs on Chrs 3, 9, and 16. Some QTLs mapped to chromosomes with limited variability between the two strains, thus facilitating the identification of candidate genes. We suggest that Tshr is the QTL gene for Chr 12 TG and HDL levels and that Ihh may account for the TG QTL on Chr 1. This cross highlights the advantage of crossing closely related strains for subsequent identification of QTL genes.

Identification of genes that regulate BMD will enhance our understanding of osteoporosis and could provide novel molecular targets for treatment or prevention. We generated a mouse intercross population and carried out a quantitative trait locus (QTL) analysis of 143 female and 124 male F(2) progeny from progenitor strains SM/J and NZB/BlNJ using whole body and vertebral areal BMD (aBMD) as measured by DXA. We found that both whole body and vertebral aBMD was affected by two loci on chromosome 9: one with a significant epistatic interaction on distal chromosome 8 and the other with a sex-specific effect. Two additional significant QTLs were identified on chromosome 12, and several suggestive ones were identified on chromosomes 5, 8, 15, and 19. The chromosome 9, 12, and 15 loci have been previously identified in other crosses. SNP-based haplotype analysis of the progenitor strains identified blocks within the QTL region that distinguish the low allele strains from the high allele strains, significantly narrowing the QTL region and reducing the possible candidate genes to 98 for chromosome 9, 31 for chromosome 12, and only 2 for chromosome 15. Trps1 is the most probable candidate gene for the chromosome 15 QTL. The sex-specific effects may help to elucidate the BMD differences between males and females. This study shows the power of statistical modeling to resolve linked QTLs and the use of haplotype analysis in narrowing the list of candidates.

Previous quantitative trait locus (QTL) analysis of an intercross involving the inbred mouse strains NZB/BlNJ and SM/J revealed QTL for a variety of complex traits. Many QTL have large intervals containing hundreds of genes, and methods are needed to rapidly sort through these genes for probable candidates. We chose nine QTL: the three most significant for high-density lipoprotein (HDL) cholesterol, gallstone formation, and obesity. We searched for candidate genes using three different approaches: mRNA microarray gene expression technology to assess >45,000 transcripts, publicly available SNPs to locate genes that are not identical by descent and that contain nonsynonymous coding differences, and a mass-spectrometry-based proteomics technology to interrogate nearly 1000 proteins for differential expression in the liver of the two parental inbred strains. This systematic approach reduced the number of candidate genes within each QTL from hundreds to a manageable list. Each of the three approaches selected candidates that the other two approaches missed. For example, candidate genes such as Apoa2 and Acads had differential protein levels although the mRNA levels were similar. We conclude that all three approaches are important and that focusing on a single approach such as mRNA expression may fail to identify a QTL gene.

An F(2) pedigree based on the mouse lines DU6i and DBA/2 with extremely different growth and obesity characteristics was generated to search for QTLs affecting serum concentrations of triglycerides (TG), total cholesterol (CHOL), HDL cholesterol (HDL-C), and LDL cholesterol (LDL-C). Compared with many other studies, we searched for spontaneous genetic variants contributing to high lipid levels under a standard breeding diet. Significant QTLs for CHOL were identified on chromosomes 4 and 6, and a female-specific locus on chromosome 3. QTLs for HDL-C were detected on chromosome 11 for both sexes, and on chromosome 1 for females. These QTLs are located in syntenic human regions that have QTLs that have not been previously confirmed in animal studies. LDL-C QTLs have been mapped for both sexes to chromosome 8 and in males on chromosome 13. Epistatic interactions that significantly accounted for the phenotypic variance of HDL-C, CHOL, and LDL-C serum concentrations were also detected with one interaction between chromosomes 8 and 15, accounting for 22% of the observed variance in LDL-C levels. The identified loci coincide in part with regions controlling growth and obesity. Thus, multiple genes or pleiotropic effects may be assumed. The identified QTLs for cholesterol and its transport proteins as subcomponents of risk for coronary heart disease will further improve our understanding of the genetic net controlling plasma lipid concentrations.

Intercrosses between inbred lines provide a traditional approach to analysis of polygenic inheritance in model organisms. Chromosome substitution strains (CSSs) have been developed as an alternative to accelerate the pace of gene identification in quantitative trait mapping. We compared a classical intercross and three CSS intercrosses to examine the genetic architecture underlying plasma high-density lipoprotein cholesterol (HDL) levels in the C57BL/6J (B) and A/J (A) mouse strains. The B x A intercross revealed significant quantitative trait loci (QTL) for HDL on chromosomes 1, 4, 8, 15, 17, 18, and 19. A CSS survey revealed that many have significantly different HDL levels compared to the background strain B, including chromosomes with no significant QTL in the intercross and, in some cases (CSS-1, CSS-17), effects that are opposite to those observed in the B x A intercross population. Intercrosses between B and three CSSs (CSS-3, CSS-11, and CSS-8) revealed significant QTL but with some unexpected differences from the B x A intercross. Our inability to predict the results of CSS intercrosses suggests that additional complexity will be revealed by further crosses and that the CSS mapping strategy should be viewed as a complement to, rather than a replacement for, classical intercross mapping.

We introduce a method for the analysis of multilocus, multitrait genetic data that provides an intuitive and precise characterization of genetic architecture. We show that it is possible to infer the magnitude and direction of causal relationships among multiple correlated phenotypes and illustrate the technique using body composition and bone density data from mouse intercross populations. Using these techniques we are able to distinguish genetic loci that affect adiposity from those that affect overall body size and thus reveal a shortcoming of standardized measures such as body mass index that are widely used in obesity research. The identification of causal networks sheds light on the nature of genetic heterogeneity and pleiotropy in complex genetic systems., Competing Interests: Competing interests. The authors have declared that no competing interests exist.

Obesity is a highly heritable and genetically complex trait with hundreds of potential loci identified. An intercross of 513 F2 progeny between the SM/J x NZB/BINJ inbred mouse strains was generated to identify quantitative trait loci (QTL) that are involved in the weight of four fat pads: mesenteric, inguinal, gonadal, and retroperitoneal. Sex and lean body weight were treated as covariates in the analysis of these fat pads. This analysis uncoupled genetic effects related to overall body size from those influencing the adiposity of a mouse. We identified multiple significant QTL. QTL alleles associated with increased lean body weight and individual fat pad weights are contributed by the NZB background. Adiposity loci are distinct from these body size QTLs and high-adiposity alleles are contributed by the SM background. An extended network of epistatic QTL is also observed. A QTL on Chr 19 is the center of a network of eight interacting QTL, Chr 4 is the center of six, and Chr 17 the center of four interacting QTL. We conclude that interacting networks of multiple genes characterize the regulation of fat pad depots and body weight. Haplotype patterns and a literature-driven approach were used to generate hypotheses regarding the identity of the genes and pathways underlying the QTL.

Quantitative trait locus (QTL) analysis is a powerful method for localizing disease genes, but identifying the causal gene remains difficult. Rodent models of disease facilitate QTL gene identification, and causal genes underlying rodent QTL are often associated with the corresponding human diseases. Recently developed bioinformatics methods, including comparative genomics, combined cross analysis, interval-specific and genome-wide haplotype analysis, followed by sequence and expression analysis, each facilitated by public databases, provide new tools for narrowing rodent QTLs. Here we discuss each tool, illustrate its application and generate a bioinformatics strategy for narrowing QTLs. Combining these bioinformatics tools with classical experimental methods should accelerate QTL gene identification.

Obesity-related diseases are poised to become the primary cause of death in developed nations. While a number of monogenic causes of obesity have recently been identified, these are responsible for only a small proportion of human cases of obesity. Quantitative trait locus (QTL) studies using animal models have revealed hundreds of potential loci that affect obesity; however, few have been further analyzed beyond the original QTL scan. We previously mapped four QTL in an F(2) between divergently selected Fat (F) and Lean (L) lines. A QTL of large effect on chromosome 15 (Fob3) was subsequently mapped to a higher resolution into two smaller-effect QTL (Fob3a and Fob3b) using crosses between the F-line and a congenic line containing L-line alleles at the Fob3 QTL region. Here we report the gene expression characterization of Fob3b. Microarray expression analysis using the NIA-NIH 15K cDNA array set containing 14,938 mouse ESTs was employed to identify candidate genes and pathways that are differentially expressed between the F-line and a congenic line containing only the Fob3b QTL (Fob3b-line). Our study suggests squalene epoxidase (Sqle), a cholesterol biosynthesis enzyme, as a strong positional candidate gene for Fob3b. Several other cholesterol biosynthesis pathway genes unlinked to Fob3b were found to be differentially expressed, suggesting that a perturbation of this pathway could be in part responsible for the phenotypic difference between the F-line and Fob3b-line mice.

Obesity is proving to be a serious health concern in the developed world as well as an unwanted component of growth in livestock production. While recent advances in genetics have identified a number of monogenic causes of obesity, these are responsible for only a small proportion of human cases of obesity. By divergent selection for high and low fat content over 60 generations, we have created Fat (F) and Lean (L) lines of mice that represent a model of polygenic obesity similar to the situation in human populations. From previous crosses of these lines, four body fat quantitative trait loci (QTL) were identified. We have created congenic lines (F(chr15L)), by recurrent marker-assisted backcrossing, to introgress the QTL region with the highest LOD score, Fob3 on Chr 15, from the L-Iine into the F-line background. We have further mapped this QTL by progeny testing of recombinants, produced from crosses between the F-line and congenic F(chrl5L) mice, showing that the Fob3 QTL region is a composite of at least two smaller effect QTL-the proximal QTL Fob3a is a late-onset obesity QTL, whereas the distal Fob3b is an early-onset obesity QTL.