Unraveling inflammatory responses using systems genetics and gene-environment interactions in macrophages.

Many common diseases have an important inflammatory component mediated in part by macrophages. Here we used a systems genetics strategy to examine the role of common genetic variation in macrophage responses to inflammatory stimuli. We examined genome-wide transcript levels in macrophages from 92 strains of the Hybrid Mouse Diversity Panel. We exposed macrophages to control media, bacterial lipopolysaccharide (LPS), or oxidized phospholipids. We performed association mapping under each condition and identified several thousand expression quantitative trait loci (eQTL), gene-by-environment interactions, and eQTL "hot spots" that specifically control LPS responses. We used siRNA knockdown of candidate genes to validate an eQTL hot spot in chromosome 8 and identified the gene 2310061C15Rik as a regulator of inflammatory responses in macrophages. We have created a public database where the data presented here can be used as a resource for understanding many common inflammatory traits that are modeled in the mouse and for the dissection of regulatory relationships between genes.

The Genetic Architecture of Coronary Artery Disease: Current Knowledge and Future Opportunities.

PURPOSE OF REVIEW: We provide an overview of our current understanding of the genetic architecture of coronary artery disease (CAD) and discuss areas of research that provide excellent opportunities for further exploration. RECENT FINDINGS: Large-scale studies in human populations, coupled with rapid advances in genetic technologies over the last decade, have clearly established the association of common genetic variation with risk of CAD. However, the effect sizes of the susceptibility alleles are for the most part modest and collectively explain only a small fraction of the overall heritability. By comparison, evidence that rare variants make a substantial contribution to risk of CAD has been somewhat disappointing thus far, suggesting that other biological mechanisms have yet to be discovered. Emerging data suggests that novel pathways involved in the development of CAD can be identified through complementary and integrative systems genetics strategies in mice or humans. There is also convincing evidence that gut bacteria play a previously unrecognized role in the development of CAD, particularly through metabolism of certain dietary nutrients that lead to proatherogenic metabolites in the circulation. A major effort is now underway to functionally understand the newly discovered genetic and biological associations for CAD, which could lead to the development of potentially novel therapeutic strategies. Other important areas of investigation for understanding the pathophysiology of CAD, including epistatic interactions between genes or with either sex and environmental factors, have not been studied on a broad scope and represent additional opportunities for future studies.

Expanding role of gut microbiota in lipid metabolism.

PURPOSE OF REVIEW: This article highlights recent advances in the emerging role that gut microbiota play in modulating metabolic phenotypes, with a particular focus on lipid metabolism. RECENT FINDINGS: Accumulating data from both human and animal studies demonstrate that intestinal microbes can affect host lipid metabolism through multiple direct and indirect biological mechanisms. These include a variety of signaling molecules produced by gut bacteria that have potent effects on hepatic lipid and bile metabolism and on reverse cholesterol transport, energy expenditure, and insulin sensitivity in peripheral tissues. Additionally, host genetic factors can modulate the abundance of bacterial taxa, which can subsequently affect various metabolic phenotypes. Proof of causality for identified microbial associations with host lipid-related phenotypes has been demonstrated in several animal studies, but remains a challenge in humans. Ultimately, selective manipulation of the gut microbial ecosystem for intervention will first require a better understanding of which specific bacteria, or alternatively, which bacterial metabolites, are appropriate targets. SUMMARY: Recent discoveries have broad implications for elucidating bacterially mediated pathophysiological mechanisms that alter lipid metabolism and other related metabolic traits. From a clinical perspective, this newly recognized endocrine organ system can be targeted for therapeutic benefit of dyslipidemia and cardiometabolic diseases.

Genetic regulation of mouse liver metabolite levels.

We profiled and analyzed 283 metabolites representing eight major classes of molecules including Lipids, Carbohydrates, Amino Acids, Peptides, Xenobiotics, Vitamins and Cofactors, Energy Metabolism, and Nucleotides in mouse liver of 104 inbred and recombinant inbred strains. We find that metabolites exhibit a wide range of variation, as has been previously observed with metabolites in blood serum. Using genome-wide association analysis, we mapped 40% of the quantified metabolites to at least one locus in the genome and for 75% of the loci mapped we identified at least one candidate gene by local expression QTL analysis of the transcripts. Moreover, we validated 2 of 3 of the significant loci examined by adenoviral overexpression of the genes in mice. In our GWAS results, we find that at significant loci the peak markers explained on average between 20 and 40% of variation in the metabolites. Moreover, 39% of loci found to be regulating liver metabolites in mice were also found in human GWAS results for serum metabolites, providing support for similarity in genetic regulation of metabolites between mice and human. We also integrated the metabolomic data with transcriptomic and clinical phenotypic data to evaluate the extent of co-variation across various biological scales.

Variations in DNA elucidate molecular networks that cause disease.

Identifying variations in DNA that increase susceptibility to disease is one of the primary aims of genetic studies using a forward genetics approach. However, identification of disease-susceptibility genes by means of such studies provides limited functional information on how genes lead to disease. In fact, in most cases there is an absence of functional information altogether, preventing a definitive identification of the susceptibility gene or genes. Here we develop an alternative to the classic forward genetics approach for dissecting complex disease traits where, instead of identifying susceptibility genes directly affected by variations in DNA, we identify gene networks that are perturbed by susceptibility loci and that in turn lead to disease. Application of this method to liver and adipose gene expression data generated from a segregating mouse population results in the identification of a macrophage-enriched network supported as having a causal relationship with disease traits associated with metabolic syndrome. Three genes in this network, lipoprotein lipase (Lpl), lactamase beta (Lactb) and protein phosphatase 1-like (Ppm1l), are validated as previously unknown obesity genes, strengthening the association between this network and metabolic disease traits. Our analysis provides direct experimental support that complex traits such as obesity are emergent properties of molecular networks that are modulated by complex genetic loci and environmental factors.

Mouse genome-wide association and systems genetics identify Asxl2 as a regulator of bone mineral density and osteoclastogenesis.

Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis were used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal, and femoral BMD revealed four significant associations (-log10P>5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12, and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism through which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cells of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits.

Comparative analysis of proteome and transcriptome variation in mouse.

The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography-Mass Spectrometry using O(18)-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript-mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels. Surprisingly, transcript levels were more strongly correlated with clinical traits than protein levels. In light of the widespread use of high-throughput technologies in both clinical and basic research, the results presented have practical as well as basic implications.

A high-resolution association mapping panel for the dissection of complex traits in mice.

Systems genetics relies on common genetic variants to elucidate biologic networks contributing to complex disease-related phenotypes. Mice are ideal model organisms for such approaches, but linkage analysis has been only modestly successful due to low mapping resolution. Association analysis in mice has the potential of much better resolution, but it is confounded by population structure and inadequate power to map traits that explain less than 10% of the variance, typical of mouse quantitative trait loci (QTL). We report a novel strategy for association mapping that combines classic inbred strains for mapping resolution and recombinant inbred strains for mapping power. Using a mixed model algorithm to correct for population structure, we validate the approach by mapping over 2500 cis-expression QTL with a resolution an order of magnitude narrower than traditional QTL analysis. We also report the fine mapping of metabolic traits such as plasma lipids. This resource, termed the Hybrid Mouse Diversity Panel, makes possible the integration of multiple data sets and should prove useful for systems-based approaches to complex traits and studies of gene-by-environment interactions.

Genetic locus on mouse chromosome 7 controls elevated heart rate.

Elevated heart rate (HR) is a risk factor for cardiovascular diseases. The goal of the study was to map HR trait in mice using quantitative trait locus (QTL) analysis followed by genome-wide association (GWA) analysis. The first approach provides mapping power and the second increases genome resolution. QTL analyses were performed in a C3HeB×SJL backcross. HR and systolic blood pressure (SBP) were measured by the tail-cuff plethysmography. HR was ∼80 beats/min higher in SJL compared with C3HeB. There was a wide distribution of the HR (536-763 beats/min) in N2 mice. We discovered a highly significant QTL (logarithm of odds = 6.7, P < 0.001) on chromosome 7 (41 cM) for HR in the C3HeB×SJL backcross. In the Hybrid Mouse Diversity Panel (58 strains, n = 5-6/strain) we found that HR (beats/min) ranged from 546 ± 12 in C58/J to 717 ± 7 in MA/MyJ mice. SBP (mmHg) ranged from 99 ± 6 in strain I/LnJ to 151 ± 4 in strain BXA4/PgnJ. GWA analyses were done using the HMDP, which revealed a locus (64.2-65.1 Mb) on chromosome 7 that colocalized with the QTL for elevated HR found in the C3HeB×SJL backcross. The peak association was observed for 17 SNPs that are localized within three GABA(A) receptor genes. In summary, we used a combined genetic approach to fine map a novel elevated HR locus on mouse chromosome 7.

Hybrid mouse diversity panel: a panel of inbred mouse strains suitable for analysis of complex genetic traits.

We have developed an association-based approach using classical inbred strains of mice in which we correct for population structure, which is very extensive in mice, using an efficient mixed-model algorithm. Our approach includes inbred parental strains as well as recombinant inbred strains in order to capture loci with effect sizes typical of complex traits in mice (in the range of 5% of total trait variance). Over the last few years, we have typed the hybrid mouse diversity panel (HMDP) strains for a variety of clinical traits as well as intermediate phenotypes and have shown that the HMDP has sufficient power to map genes for highly complex traits with resolution that is in most cases less than a megabase. In this essay, we review our experience with the HMDP, describe various ongoing projects, and discuss how the HMDP may fit into the larger picture of common diseases and different approaches.

Copy number variation influences gene expression and metabolic traits in mice.

Copy number variants (CNVs) are genomic segments which are duplicated or deleted among different individuals. CNVs have been implicated in both Mendelian and complex traits, including immune and behavioral disorders, but the study of the mechanisms by which CNVs influence gene expression and clinical phenotypes in humans is complicated by the limited access to tissues and by population heterogeneity. We now report studies of the effect of 19 CNVs on gene expression and metabolic traits in a mouse intercross between strains C57BL/6J and C3H/HeJ. We found that 83% of genes predicted to occur within CNVs were differentially expressed. The expression of most CNV genes was correlated with copy number, but we also observed evidence that gene expression was altered in genes flanking CNVs, suggesting that CNVs may contain regulatory elements for these genes. Several CNVs mapped to hotspots, genomic regions influencing expression of tens or hundreds of genes. Several metabolic traits including cholesterol, triglycerides, glucose and body weight mapped to three CNVs in the genome, in mouse chromosomes 1, 4 and 17. Predicted CNV genes, such as Itlna, Defcr-1, Trim12 and Trim34 were highly correlated with these traits. Our results suggest that CNVs have a significant impact on gene expression and that CNVs may be playing a role in the mechanisms underlying metabolic traits in mice.

High-resolution mapping of gene expression using association in an outbred mouse stock.

Quantitative trait locus (QTL) analysis is a powerful tool for mapping genes for complex traits in mice, but its utility is limited by poor resolution. A promising mapping approach is association analysis in outbred stocks or different inbred strains. As a proof of concept for the association approach, we applied whole-genome association analysis to hepatic gene expression traits in an outbred mouse population, the MF1 stock, and replicated expression QTL (eQTL) identified in previous studies of F2 intercross mice. We found that the mapping resolution of these eQTL was significantly greater in the outbred population. Through an example, we also showed how this precise mapping can be used to resolve previously identified loci (in intercross studies), which affect many different transcript levels (known as eQTL "hotspots"), into distinct regions. Our results also highlight the importance of correcting for population structure in whole-genome association studies in the outbred stock.

Integrating genetic and network analysis to characterize genes related to mouse weight.

Systems biology approaches that are based on the genetics of gene expression have been fruitful in identifying genetic regulatory loci related to complex traits. We use microarray and genetic marker data from an F2 mouse intercross to examine the large-scale organization of the gene co-expression network in liver, and annotate several gene modules in terms of 22 physiological traits. We identify chromosomal loci (referred to as module quantitative trait loci, mQTL) that perturb the modules and describe a novel approach that integrates network properties with genetic marker information to model gene/trait relationships. Specifically, using the mQTL and the intramodular connectivity of a body weight-related module, we describe which factors determine the relationship between gene expression profiles and weight. Our approach results in the identification of genetic targets that influence gene modules (pathways) that are related to the clinical phenotypes of interest.

Comprehensive molecular profiling of advanced/metastatic olfactory neuroblastomas.

Olfactory neuroblastoma (ONB) is a rare, locally aggressive, malignant neoplasm originating in the olfactory epithelium in the nasal vault. The recurrence rate of ONB remains high and there are no specific treatment guidelines for recurrent/metastatic ONBs. This study retrospectively evaluated 23 ONB samples profiled at Caris Life Sciences (Phoenix, Arizona) using DNA sequencing (Sanger/NGS [Illumina], n = 15) and gene fusions (Archer FusionPlex, n = 6), whole genome RNA microarray (HumanHT-12 v4 beadChip, Illumina, n = 4), gene copy number assays (chromogenic and fluorescent in situ hybridization), and immunohistochemistry. Mutations were detected in 63% ONBs including TP53, CTNNB1, EGFR, APC, cKIT, cMET, PDGFRA, CDH1, FH, and SMAD4 genes. Twenty-one genes were over-expressed and 19 genes under-expressed by microarray assay. Some of the upregulated genes included CD24, SCG2, and IGFBP-2. None of the cases harbored copy number variations of EGFR, HER2 and cMET genes, and no gene fusions were identified. Multiple protein biomarkers of potential response or resistance to classic chemotherapy drugs were identified, such as low ERCC1 [cisplatin sensitivity in 10/12], high TOPO1 [irinotecan sensitivity in 12/19], high TUBB3 [vincristine resistance in 13/14], and high MRP1 [multidrug resistance in 6/6 cases]. None of the cases (0/10) were positive for PD-L1 in tumor cells. Overexpression of pNTRK was observed in 67% (4/6) of the cases without underlying genetic alterations. Molecular alterations detected in our study (e.g., Wnt and cKIT/PDGFRA pathways) are potentially treatable using novel therapeutic approaches. Identified protein biomarkers of response or resistance to classic chemotherapy could be useful in optimizing existing chemotherapy treatment(s) in ONBs.

Complex inheritance of the 5-lipoxygenase locus influencing atherosclerosis in mice.

We previously mapped a locus on chromosome 6 with a large effect (LOD > 6) on aortic lesion size in a (C57BL/6J x CAST/Ei) F(2) cross and identified arachidonate 5-lipoxygenase (5LO) as a candidate gene in this region. Subsequent studies with the 5LO knockout model showed effects on atherosclerosis and aortic aneurysms. We now report detailed genetic analysis of the chromosome 6 locus. We created a panel of overlapping and reciprocal subcongenic lines from the B6.CAST Ldlr(-/-) chromosome 6 congenic strain (CON6.Ldlr(-/-)) and analyzed aortic lesion size in different subcongenic lines. Our results revealed that there are at least two subregions, designated as Ath37 and Ath38 that affect the size of aortic lesions independently of 5LO. We also showed that homozygote 5LO null mice develop smaller atherosclerotic lesions. We conclude that the relation between the mouse chromosome 6 locus and atherosclerosis is complex and is due to at least two genes with large effects within this region. This complexity should be considered when interpreting results of knockout studies.

Multiplatform molecular profiling identifies potentially targetable biomarkers in malignant phyllodes tumors of the breast.

Malignant phyllodes tumor is a rare breast malignancy with sarcomatous overgrowth and with limited effective treatment options for recurrent and metastatic cases. Recent clinical trials indicated a potential for anti-angiogenic, anti-EGFR and immunotherapeutic approaches for patients with sarcomas, which led us to investigate these and other targetable pathways in malignant phyllodes tumor of the breast. Thirty-six malignant phyllodes tumors (including 8 metastatic tumors with two cases having matched primary and metastatic tumors) were profiled using gene sequencing, gene copy number analysis, whole genome expression, and protein expression. Whole genome expression analysis demonstrated consistent over-expression of genes involved in angiogenesis including VEGFA, Angiopoietin-2, VCAM1, PDGFRA, and PTTG1. EGFR protein overexpression was observed in 26/27 (96%) of cases with amplification of the EGFR gene in 8/24 (33%) cases. Two EGFR mutations were identified including EGFRvIII and a presumed pathogenic V774M mutation, respectively. The most common pathogenic mutations included TP53 (50%) and PIK3CA (15%). Cases with matched primary and metastatic tumors harbored identical mutations in both sites (PIK3CA/KRAS and RB1 gene mutations, respectively). Tumor expression of PD-L1 immunoregulatory protein was observed in 3/22 (14%) of cases. Overexpression of molecular biomarkers of increased angiogenesis, EGFR and immune checkpoints provides novel targeted therapy options in malignant phyllodes tumors of the breast.

Multi-platform molecular profiling of a large cohort of glioblastomas reveals potential therapeutic strategies.

Glioblastomas (GBM) are the most aggressive and prevalent form of gliomas with abysmal prognosis and limited treatment options. We analyzed clinically relevant molecular aberrations suggestive of response to therapies in 1035 GBM tumors. Our analysis revealed mutations in 39 genes of 48 tested. IHC revealed expression of PD-L1 in 19% and PD-1 in 46%. MGMT-methylation was seen in 43%, EGFRvIII in 19% and 1p19q co-deletion in 2%. TP53 mutation was associated with concurrent mutations, while IDH1 mutation was associated with MGMT-methylation and TP53 mutation and was mutually exclusive of EGFRvIII mutation. Distinct biomarker profiles were seen in GBM compared with WHO grade III astrocytoma, suggesting different biology and potentially different treatment approaches. Analysis of 17 metachronous paired tumors showed frequent biomarker changes, including MGMT-methylation and EGFR aberrations, indicating the need for a re-biopsy for tumor profiling to direct subsequent therapy. MGMT-methylation, PR and TOPO1 appeared as significant prognostic markers in sub-cohorts of GBM defined by age. The current study represents the largest biomarker study on clinical GBM tumors using multiple technologies to detect gene mutation, amplification, protein expression and promoter methylation. These data will inform planning for future personalized biomarker-based clinical trials and identifying effective treatments based on tumor biomarkers.

Using mice to dissect genetic factors in atherosclerosis.

The genes that contribute to common, complex forms of atherosclerosis remain largely unknown. Genetic studies in humans have, for the most part, focused on identifying genes that predispose to the traditional risk factors, such as lipid levels and blood pressure, but apart from rare, single-gene disorders, there have been few successes to date. The use of mice to dissect the complex genetic etiology of atherosclerosis offers a viable alternative to human studies, because experimental parameters, such as environment, breeding scheme, and detailed phenotyping, can be controlled. Herein we review how mouse genetics can lead to the identification of genes, some of which would otherwise not have been considered as candidates for atherosclerosis, and provide an overview of the prospects for successful gene discovery in the future.

Mutations in the Kinase Domain of the HER2/ERBB2 Gene Identified in a Wide Variety of Human Cancers.

The HER2 (official name ERBB2) gene encodes a membrane receptor in the epidermal growth factor receptor family amplified and overexpressed in adenocarcinoma. Activating mutations also occur in several cancers. We report mutation analyses of the HER2 kinase domain in 7497 histologically diverse cancers. Forty-five genes, including the kinase domain of HER2 with HER2 IHC and dual in situ hybridization, were analyzed in tumors from 7497 patients with cancer, including 850 breast, 770 colorectal, 910 non-small cell lung, 823 uterine or cervical, 1372 ovarian, and 297 pancreatic cancers, as well as 323 melanomas and 2152 other solid tumors. Sixty-nine HER2 kinase domain mutations were identified in tumors from 68 patients (approximately 1% of all cases, ranging from absent in sarcomas to 4% in urothelial cancers), which included previously published activating mutations and 13 novel mutations. Fourteen cases with coexisting HER2 mutation and amplification and/or overexpression were identified. Fifty-two of 68 patients had additional mutations in other analyzed genes, whereas 16 patients (23%) had HER2 mutations identified as the sole driver mutation. HER2 mutations coexisted with HER2 gene amplification and overexpression and with mutations in other functionally important genes. HER2 mutations were identified as the only driver mutation in a significant proportion of solid cancers. Evaluation of anti-HER2 therapies in nonamplified, HER2-mutated cancers is warranted.

Epigenome-wide association of liver methylation patterns and complex metabolic traits in mice.

Heritable epigenetic factors can contribute to complex disease etiology. Here we examine the contribution of DNA methylation to complex traits that are precursors to heart disease, diabetes, and osteoporosis. We profiled DNA methylation in the liver using bisulfite sequencing in 90 mouse inbred strains, genome-wide expression levels, proteomics, metabolomics, and 68 clinical traits and performed epigenome-wide association studies (EWAS). We found associations with numerous clinical traits including bone density, insulin resistance, expression, and protein and metabolite levels. A large proportion of associations were unique to EWAS and were not identified using GWAS. Methylation levels were regulated by genetics largely in cis, but we also found evidence of trans regulation, and we demonstrate that genetic variation in the methionine synthase reductase gene Mtrr affects methylation of hundreds of CpGs throughout the genome. Our results indicate that natural variation in methylation levels contributes to the etiology of complex clinical traits.