Activation of inflammatory pathways plays a critical role in the development of abdominal aortic aneurysms (AAA). Notch1 signaling is a significant regulator of the inflammatory response; however, its role in AAA is unknown.
Methods and Results
In an angiotensin II (AngII)-induced mouse model of AAA, activation of Notch1 signaling was observed in the aortic aneurysmal tissue of Apoe−/− mice and a similar activation of Notch1 was observed in aneurysms of humans undergoing AAA repair. Notch1 haploinsufficiency significantly reduced the incidence of AAA in Apoe−/− mice in response to AngII. Reconstitution of bone marrow-derived cells from Notch1+/−; Apoe−/− mice (donor) in lethally irradiated Apoe−/− mice (recipient) decreased occurrence of aneurysm. Flow cytometry and immunohistochemistry demonstrated that Notch1 haploinsufficiency prevented the influx of inflammatory macrophages at the aneurysmal site by causing defects in macrophage migration and proliferation. Additionally, there was an overall reduction in the inflammatory burden in the aorta of the Notch1+/−;Apoe−/− mice as compared to the Apoe−/− mice. Lastly, pharmacologic inhibition of Notch1 signaling also prevented AAA formation and progression in Apoe−/− mice.
Our data suggest that decreased levels of Notch1 protect against the formation of AAA by preventing macrophage recruitment and attenuating the inflammatory response in the aorta.
aneurysm; Notch1 signaling; inflammation; macrophages
Intracranial aneurysms, also called cerebral aneurysms, are dilatations in the arteries that supply blood to the brain. Rupture of an intracranial aneurysm leads to a subarachnoid hemorrhage, which is fatal in about 50% of the cases. Intracranial aneurysms can be repaired surgically or endovascularly, or by combining these two treatment modalities. They are relatively common with an estimated prevalence of unruptured aneurysms of 2%–6% in the adult population, and are considered a complex disease with both genetic and environmental risk factors. Known risk factors include smoking, hypertension, increasing age, and positive family history for intracranial aneurysms. Identifying the molecular mechanisms underlying the pathogenesis of intracranial aneurysms is complex. Genome-wide approaches such as DNA linkage and genetic association studies, as well as microarray-based mRNA expression studies, provide unbiased approaches to identify genetic risk factors and dissecting the molecular pathobiology of intracranial aneurysms. The ultimate goal of these studies is to use the information in clinical practice to predict an individual's risk for developing an aneurysm or monitor its growth or rupture risk. Another important goal is to design new therapies based on the information on mechanisms of disease processes to prevent the development or halt the progression of intracranial aneurysms.
Berry aneurysm; candidate gene analyses; genetic association studies; intracranial aneurysms; linkage mapping; microarray analysis; subarachnoid hemorrhage
TGF-β signaling plays critical roles in the pathogenesis of aneurysms; however, it is still unclear whether its role is protective or destructive. In this study, we investigate the role of SMAD3 in the pathogenesis of calcium chloride (CaCl2)-induced abdominal aortic aneurysms (AAA) in Smad3−/−, Smad3+/− and Smad3+/+ mice. We find that loss of SMAD3 drastically increases wall thickening of the abdominal aorta. Histological analyses show significant vessel wall remodeling with elastic fiber fragmentation. Remarkably, under polarized light, collagen fibers in the hyperplastic adventitia of Smad3−/− mice show extensive reorganization accompanied by loosely packed thin and radial collagen fibers. The expressions of matrix metalloproteinases including MMP2, MMP9, and MMP12 and infiltration of macrophage/T cells are drastically enhanced in the vascular wall of Smad3−/− mice. We also observe marked increase of NF-κB and ERK1/2 signaling as well as the expression of nuclear Smad2, Smad4 and TGF-β1 in the vessel wall of Smad3−/− mice. In addition, we find that SMAD3 expression is reduced in the dedifferentiated medial smooth muscle-like cells of human AAA patients. These findings provide direct in vivo evidence to support the essential roles of SMAD3 in protecting vessel wall integrity and suppressing inflammation in the pathogenesis of AAAs.
Our previous analysis using genome-wide microarray expression data revealed extreme overrepresentation of immune related genes belonging the Natural Killer (NK) Cell Mediated Cytotoxicity pathway (hsa04650) in human abdominal aortic aneurysm (AAA). We followed up the microarray studies by immunohistochemical analyses using antibodies against nine members of the NK pathway (VAV1, VAV3, PLCG1, PLCG2, HCST, TYROBP, PTK2B, TNFA, and GZMB) and aortic tissue samples from AAA repair operations (n = 6) and control aortae (n = 8) from age-, sex- and ethnicity-matched donors from autopsies. The results confirmed the microarray results. Two different members of the NK pathway, HCST and GRZB, which act at different steps in the NK-pathway, were actively transcribed and translated into proteins in the same cells in the AAA tissue demonstrated by double staining. Furthermore, double staining with antibodies against CD68 or CD8 together with HCST, TYROBP, PTK2B or PLCG2 revealed that CD68 and CD8 positive cells expressed proteins of the NK-pathway but were not the only inflammatory cells involved in the NK-pathway in the AAA tissue. The results provide strong evidence that the NK Cell Mediated Cytotoxicity Pathway is activated in human AAA and valuable insight for future studies to dissect the pathogenesis of human AAA.
human aorta; immunohistochemistry; double-staining; AAA; aortic aneurysm
We investigated transcriptional control of gene expression in human abdominal aortic aneurysm (AAA). We previously identified 3274 differentially expressed genes in human AAA tissue compared to non-aneurysmal controls. Four expressed transcription factors (ELF1, ETS2, STAT5 and RUNX1) were selected for genome-wide chromatin immunoprecipitation. Transcription factor binding was enriched in 4760 distinct genes (FDR < 0.05), of which 713 were differentially expressed in AAA. Functional classification using Gene Ontology (GO), KEGG, and Network Analysis revealed enrichment in several biological processes including “leukocyte migration” (FDR = 3.09 × 10−05) and “intracellular protein kinase cascade” (FDR = 6.48 × 10−05). In the control aorta, the most significant GO categories differed from those in the AAA samples and included “cytoskeleton organization” (FDR = 1.24 × 10−06) and “small GTPase mediated signal transduction” (FDR = 1.24 × 10−06). Genes up-regulated in AAA tissue showed a highly significant enrichment for GO categories “leukocyte migration” (FDR = 1.62 × 10−11), “activation of immune response” (FDR = 8.44 × 10−11), “T cell activation” (FDR = 4.14 × 10−10) and “regulation of lymphocyte activation” (FDR = 2.45 × 10−09), whereas the down-regulated genes were enriched in GO categories “cytoskeleton organization” (FDR = 7.84 × 10−05), “muscle cell development” (FDR = 1.00 × 10−04), and “organ morphogenesis” (FDR = 3.00 × 10−04). Quantitative PCR assays confirmed a sub-set of the transcription factor binding sites including those in MTMR11, DUSP10, ITGAM, MARCH1, HDAC8, MMP14, MAGI1, THBD and SPOCK1.
aneurysm; aorta; genes; transcription factor; chromatin immunoprecipitation; gene expression; gene ontology; KEGG pathway; network
Abdominal aortic aneurysm (AAA) is a complex disorder that has a significant impact on the aging population. While both genetic and environmental risk factors have been implicated in AAA formation, the precise genetic markers involved and the factors influencing their expression remain an area of ongoing investigation. DNA methylation has been previously used to study gene silencing in other inflammatory disorders and since AAA has an extensive inflammatory component, we sought to examine the genome-wide DNA methylation profiles in mononuclear blood cells of AAA cases and matched non-AAA controls. To this end, we collected blood samples and isolated mononuclear cells for DNA and RNA extraction from four all male groups: AAA smokers (n = 11), AAA non-smokers (n = 9), control smokers (n = 10) and control non-smokers (n = 11). Methylation data were obtained using the Illumina 450k Human Methylation Bead Chip and analyzed using the R language and multiple Bioconductor packages. Principal component analysis and linear analysis of CpG island subsets identified four regions with significant differences in methylation with respect to AAA: kelch-like family member 35 (KLHL35), calponin 2 (CNN2), serpin peptidase inhibitor clade B (ovalbumin) member 9 (SERPINB9), and adenylate cyclase 10 pseudogene 1 (ADCY10P1). Follow-up studies included RT-PCR and immunostaining for CNN2 and SERPINB9. These findings are novel and suggest DNA methylation may play a role in AAA pathobiology.
DNA methylation; AAA; KLHL35; CNN2; SERPINB9; ADCY10P1; aortic aneurysm
The objectives were to answer the following questions using a well-characterized population in Liège, Belgium: 1) what percentage of abdominal aortic aneurysm (AAA) patients have a positive family history for AAA, 2) what is the prevalence of AAAs among relatives of AAA patients; and 3) do familial and sporadic AAA cases differ in clinical characteristics.
Methods and Results
Unrelated AAA patients diagnosed at the Cardiovascular Surgery Department, University Hospital of Liège, Belgium, between 1999 and 2012 were invited to the study. A detailed family history was obtained in interviews and recorded using Progeny software. In the initial interview 62 (10%) of the 618 AAA patients reported a positive family history for AAA. We divided the 618 patients into two study groups: Group I: 296 AAA patients (268; 91% males) were followed up with computerized tomography combined with positron emission tomography, and Group II: 322 AAA patients (295; 92% males) whose families were invited to ultrasonography screening. Ultrasonography screening identified 24 new AAAs among 186 relatives (≥ 50 years) of 144 families yielding a prevalence of 13%. The highest prevalence (25%) was found among brothers. By combining the number of AAAs found by ultrasonography screening with those diagnosed previously the observed lifetime prevalence of AAA was estimated to be 32% in brothers. The familial AAA cases were more likely to have a ruptured AAA than the sporadic cases (8% vs. 2.4%; P<0.0001).
The findings confirm previously found high prevalence of AAA among brothers, support genetic contribution to AAA pathogenesis and provide rationale for targeted screening of relatives of AAA patients.
abdominal aortic aneurysm; ultrasonography screening; family study; risk factors; family history
Rupture of abdominal aortic aneurysm (AAA) is a cause of significant mortality and morbidity in aging populations. Uptake of 18-fluorodeoxyglucose (FDG) detected by positron emission tomography (PET) is observed in the wall of 12% of AAA (A+), with most of them being symptomatic. We previously showed that the metabolically active areas displayed adventitial inflammation, medial degeneration and molecular alterations prefacing wall rupture. The aim of this study was to identify new factors predictive of rupture. Transcriptomic analyses were performed in the media and adventitia layers from three types of samples: AAA with-out FDG uptake (A0) and with FDG uptake (A+), both at the positive spot (A+Pos) and at a paired distant negative site (A+Neg) of the same aneurysm. Follow-up studies included reverse-transcriptase–polymerase chain reaction (RT-PCR), immunohistochemical staining and enzyme-linked immunosorbent assay (ELISA). A large number of genes, including matrix metalloproteinases, collagens and cytokines as well as genes involved in osteochondral development, were differentially expressed in the A+Pos compared with A+Neg. Moreover, a series of genes (notably CCL18 ) was differentially expressed both in the A+Neg and A+Pos compared with the A0. A significant increase of CCL18 was also found at the protein level in the aortic wall and in peripheral blood of A+ patients compared with A0. In conclusion, new factors, including CCL18, involved in the progression of AAA and, potentially, in their rupture were identified by a genome-wide analysis of PET-positive and -negative human aortic tissue samples. Further work is needed to study their role in AAA destabilization and weakening.
electronic health records; precision medicine; genomic medicine; EHR; genomics
The electronic MEdical Records and GEnomics (eMERGE) network brings together DNA biobanks linked to electronic health records (EHRs) from multiple institutions. Approximately 51,000 DNA samples from distinct individuals have been genotyped using genome-wide SNP arrays across the nine sites of the network. The eMERGE Coordinating Center and the Genomics Workgroup developed a pipeline to impute and merge genomic data across the different SNP arrays to maximize sample size and power to detect associations with a variety of clinical endpoints. The 1000 Genomes cosmopolitan reference panel was used for imputation. Imputation results were evaluated using the following metrics: accuracy of imputation, allelic R2 (estimated correlation between the imputed and true genotypes), and the relationship between allelic R2 and minor allele frequency. Computation time and memory resources required by two different software packages (BEAGLE and IMPUTE2) were also evaluated. A number of challenges were encountered due to the complexity of using two different imputation software packages, multiple ancestral populations, and many different genotyping platforms. We present lessons learned and describe the pipeline implemented here to impute and merge genomic data sets. The eMERGE imputed dataset will serve as a valuable resource for discovery, leveraging the clinical data that can be mined from the EHR.
imputation; genome-wide association; eMERGE; electronic health records
Using abdominal aortic aneurysm (AAA) as a model, this case–control study used electronic medical record (EMR) data to assess known risk factors and identify new associations.
The study population consisted of cases with AAA (n =888) and controls (n =10,523) from the Geisinger Health System EMR in Central and Northeastern Pennsylvania. We extracted all clinical and diagnostic data for these patients from January 2004 to December 2009 from the EMR. From this sample set, bootstrap replication procedures were used to randomly generate 2,500 iterations of data sets, each with 500 cases and 2000 controls. Estimates of risk factor effect sizes were obtained by stepwise logistic regression followed by bootstrap aggregation. Variables were ranked using the number of inclusions in iterations and P values.
The benign neoplasm diagnosis was negatively associated with AAA, a novel finding. Similarly, type 2 diabetes, diastolic blood pressure, weight and myelogenous neoplasms were negatively associated with AAA. Peripheral artery disease, smoking, age, coronary stenosis, systolic blood pressure, age, height, male sex, pulmonary disease and hypertension were associated with an increased risk for AAA.
This study utilized EMR data, retrospectively, for risk factor assessment of a complex disease. Known risk factors for AAA were replicated in magnitude and direction. A novel negative association of benign neoplasms was identified. EMRs allow researchers to rapidly and inexpensively use clinical data to expand cohort size and derive better risk estimates for AAA as well as other complex diseases.
Aortic Aneurysm; Abdominal; Electronic medical record; Neoplasms; Benign; Risk factors; Blood pressure; Diabetes mellitus; Type 2; Case–control studies
The progression of abdominal aortic aneurysm (AAA) involves a sustained influx of proinflammatory macrophages, which exacerbate tissue injury by releasing cytokines, chemokines, and matrix metalloproteinases. Previously, we showed that Notch deficiency reduces the development of AAA in the angiotensin II–induced mouse model by preventing infiltration of macrophages. Here, we examined whether Notch inhibition in this mouse model prevents progression of small AAA and whether these effects are associated with altered macrophage differentiation.
Methods and Results
Treatment with pharmacological Notch inhibitor (DAPT [N‐(N‐[3,5‐difluorophenacetyl]‐L‐alanyl)‐S‐phenylglycine t‐butyl ester]) at day 3 or 8 of angiotensin II infusion arrested the progression of AAA in Apoe−/− mice, as demonstrated by a decreased luminal diameter and aortic width. The abdominal aortas of Apoe−/− mice treated with DAPT showed decreased expression of matrix metalloproteinases and presence of elastin precursors including tropoelastin and hyaluronic acid. Marginal adventitial thickening observed in the aorta of DAPT‐treated Apoe−/− mice was not associated with increased macrophage content, as observed in the mice treated with angiotensin II alone. Instead, DAPT‐treated abdominal aortas showed increased expression of Cd206‐positive M2 macrophages and decreased expression of Il12‐positive M1 macrophages. Notch1 deficiency promoted M2 differentiation of macrophages by upregulating transforming growth factor β2 in bone marrow–derived macrophages at basal levels and in response to IL4. Protein expression of transforming growth factor β2 and its downstream effector pSmad2 also increased in DAPT‐treated Apoe−/− mice, indicating a potential link between Notch and transforming growth factor β2 signaling in the M2 differentiation of macrophages.
Pharmacological inhibitor of Notch signaling prevents the progression of AAA by macrophage differentiation–dependent mechanisms. The study also provides insights for novel therapeutic strategies to prevent the progression of small AAA.
abdominal aortic aneurysm; macrophage differentiation; Notch1; Tgfβ2
Combining samples across multiple cohorts in large-scale scientific research programs is often required to achieve the necessary power for genome-wide association studies. Controlling for genomic ancestry through principal component analysis (PCA) to address the effect of population stratification is a common practice. In addition to local genomic variation, such as copy number variation and inversions, other factors directly related to combining multiple studies, such as platform and site recruitment bias, can drive the correlation patterns in PCA. In this report, we describe the combination and analysis of multi-ethnic cohort with biobanks linked to electronic health records for large-scale genomic association discovery analyses. First, we outline the observed site and platform bias, in addition to ancestry differences. Second, we outline a general protocol for selecting variants for input into the subject variance-covariance matrix, the conventional PCA approach. Finally, we introduce an alternative approach to PCA by deriving components from subject loadings calculated from a reference sample. This alternative approach of generating principal components controlled for site and platform bias, in addition to ancestry differences, has the advantage of fewer covariates and degrees of freedom.
principal component analysis; ancestry; biobank; loadings; genetic association study
We performed a genome-wide association study on 1,292 individuals with abdominal aortic aneurysms (AAAs) and 30,503 controls from Iceland and The Netherlands, with a follow-up of top markers in up to 3,267 individuals with AAAs and 7,451 controls. The A allele of rs7025486 on 9q33 was found to associate with AAA, with an odds ratio (OR) of 1.21 and P = 4.6 × 10−10. In tests for association with other vascular diseases, we found that rs7025486[A] is associated with early onset myocardial infarction (OR = 1.18, P = 3.1 × 10−5), peripheral arterial disease (OR = 1.14, P = 3.9 × 10−5) and pulmonary embolism (OR = 1.20, P = 0.00030), but not with intracranial aneurysm or ischemic stroke. No association was observed between rs7025486[A] and common risk factors for arterial and venous diseases—that is, smoking, lipid levels, obesity, type 2 diabetes and hypertension. Rs7025486 is located within DAB2IP, which encodes an inhibitor of cell growth and survival.
Abdominal aortic aneurysm (AAA) is a common human disease with a high estimated heritability (0.7); however, only a small number of associated genetic loci have been reported to date. In contrast, over 100 loci have now been reproducibly associated with either blood lipid profile and/or coronary artery disease (CAD) (both risk factors for AAA) in large-scale meta-analyses. This study employed a staged design to investigate whether the loci for these two phenotypes are also associated with AAA. Validated CAD and dyslipidaemia loci underwent screening using the Otago AAA genome-wide association data set. Putative associations underwent staged secondary validation in 10 additional cohorts. A novel association between the SORT1 (1p13.3) locus and AAA was identified. The rs599839 G allele, which has been previously associated with both dyslipidaemia and CAD, reached genome-wide significance in 11 combined independent cohorts (meta-analysis with 7048 AAA cases and 75 976 controls: G allele OR 0.81, 95% CI 0.76–0.85, P = 7.2 × 10−14). Modelling for confounding interactions of concurrent dyslipidaemia, heart disease and other risk factors suggested that this marker is an independent predictor of AAA susceptibility. In conclusion, a genetic marker associated with cardiovascular risk factors, and in particular concurrent vascular disease, appeared to independently contribute to susceptibility for AAA. Given the potential genetic overlap between risk factor and disease phenotypes, the use of well-characterized case–control cohorts allowing for modelling of cardiovascular disease risk confounders will be an important component in the future discovery of genetic markers for conditions such as AAA.
The electronic MEdical Records & GEnomics (eMERGE) network was established in 2007 by the National Human Genome Research Institute (NHGRI) of the National Institutes of Health (NIH) in part to explore the utility of electronic medical records (EMRs) in genome science. The initial focus was on discovery primarily using the genome-wide association paradigm, but more recently, the network has begun evaluating mechanisms to implement new genomic information coupled to clinical decision support into EMRs. Herein, we describe this evolution including the development of the individual and merged eMERGE genomic datasets, the contribution the network has made toward genomic discovery and human health, and the steps taken toward the next generation genotype-phenotype association studies and clinical implementation.
biobanks; genome-wide association studies; pharmacogenomics; electronic medical records
The electronic Medical Records and Genomics (eMERGE) (Phase I) network was established in 2007 to further genomic discovery using biorepositories linked to the electronic health record (EHR). In Phase II, which began in 2011, genomic discovery efforts continue and in addition the network is investigating best practices for implementing genomic medicine, in particular, the return of genomic results in the EHR for use by physicians at point-of-care. To develop strategies for addressing the challenges of implementing genomic medicine in the clinical setting, the eMERGE network is conducting studies that return clinically-relevant genomic results to research participants and their health care providers. These genomic medicine pilot studies include returning individual genetic variants associated with disease susceptibility or drug response, as well as genetic risk scores for common “complex” disorders. Additionally, as part of a network-wide pharmacogenomics-related project, targeted resequencing of 84 pharmacogenes is being performed and select genotypes of pharmacogenetic relevance are being placed in the EHR to guide individualized drug therapy. Individual sites within the eMERGE network are exploring mechanisms to address incidental findings generated by resequencing of the 84 pharmacogenes. In this paper, we describe studies being conducted within the eMERGE network to develop best practices for integrating genomic findings into the EHR, and the challenges associated with such work.
genomics; electronic health records; incidental findings; implementation; genetic counseling; next generation sequencing; pharmacogenetics
Abdominal aortic aneurysm (AAA), a dilatation of the infrarenal aorta, typically affects males > 65 years. The pathobiological mechanisms of human AAA are poorly understood. The goal of this study was to identify novel pathways involved in the development of AAAs.
A custom-designed “AAA-chip” was used to assay 43 of the differentially expressed genes identified in a previously published microarray study between AAA (n = 15) and control (n = 15) infrarenal abdominal aorta. Protein analyses were performed on selected genes.
Altogether 38 of the 43 genes on the “AAA-chip” showed significantly different expression. Novel validated genes in AAA pathobiology included ADCY7, ARL4C, BLNK, FOSB, GATM, LYZ, MFGE8, PRUNE2, PTPRC, SMTN, TMODI and TPM2. These genes represent a wide range of biological functions, such as calcium signaling, development and differentiation, as well as cell adhesion not previously implicated in AAA pathobiology. Protein analyses for GATM, CD4, CXCR4, BLNK, PLEK, LYZ, FOSB, DUSP6, ITGA5 and PTPRC confirmed the mRNA findings.
The results provide new directions for future research into AAA pathogenesis to study the role of novel genes confirmed here. New treatments and diagnostic tools for AAA could potentially be identified by studying these novel pathways.
gene expression; vascular biology; aorta; abdominal aortic aneurysm
An abdominal aortic aneurysm (AAA) is a dilatation of the abdominal aorta with a diameter of at least 3.0 cm. AAAs are often asymptomatic and are discovered as incidental findings in imaging studies or when the AAA ruptures leading to a medical emergency. AAAs are more common in males than females, in individuals of European ancestry, and in those over 65 years of age. Smoking is the most important environmental risk factor. In addition, a positive family history of AAA increases the person's risk for AAA. Interestingly, diabetes has been shown to be a protective factor for AAA in many large studies. Hallmarks of AAA pathogenesis include inflammation, vascular smooth muscle cell apoptosis, extracellular matrix degradation, and oxidative stress. Autoimmunity may also play a role in AAA development and progression. In this Outlook paper, we summarize our recent studies on AAA including clinical studies related to surgical repair of AAA and genetic risk factor and large-scale gene expression studies. We conclude with a discussion on our research projects using large data sets available through electronic medical records and biobanks.
A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency (MAF<0.1) non-synonymous SNPs (nsSNPs) associated with “mechanistic phenotypes”, comprised of collections of related diagnoses. We studied two mechanistic phenotypes: (1) thrombosis, evaluated in a population of 1,655 African Americans; and (2) four groupings of cancer diagnoses, evaluated in 3,009 white European Americans. We tested associations between nsSNPs represented on GWAS platforms and mechanistic phenotypes ascertained from electronic medical records (EMRs), and sought enrichment in functional ontologies across the top-ranked associations. We used a two-step analytic approach whereby nsSNPs were first sorted by the strength of their association with a phenotype. We tested associations using two reverse genetic models and standard additive and recessive models. In the second step, we employed a hypothesis-free ontological enrichment analysis using the sorted nsSNPs to identify functional mechanisms underlying the diagnoses comprising the mechanistic phenotypes. The thrombosis phenotype was solely associated with ontologies related to blood coagulation (Fisher's p = 0.0001, FDR p = 0.03), driven by the F5, P2RY12 and F2RL2 genes. For the cancer phenotypes, the reverse genetics models were enriched in DNA repair functions (p = 2×10−5, FDR p = 0.03) (POLG/FANCI, SLX4/FANCP, XRCC1, BRCA1, FANCA, CHD1L) while the additive model showed enrichment related to chromatid segregation (p = 4×10−6, FDR p = 0.005) (KIF25, PINX1). We were able to replicate nsSNP associations for POLG/FANCI, BRCA1, FANCA and CHD1L in independent data sets. Mechanism-oriented phenotyping using collections of EMR-derived diagnoses can elucidate fundamental disease mechanisms.
The Electronic Medical Records and Genomics (eMERGE) Network is a National Human Genome Research Institute (NHGRI)-funded consortium engaged in the development of methods and best-practices for utilizing the Electronic Medical Record (EMR) as a tool for genomic research. Now in its sixth year, its second funding cycle and comprising nine research groups and a coordinating center, the network has played a major role in validating the concept that clinical data derived from EMRs can be used successfully for genomic research. Current work is advancing knowledge in multiple disciplines at the intersection of genomics and healthcare informatics, particularly electronic phenotyping, genome-wide association studies, genomic medicine implementation and the ethical and regulatory issues associated with genomics research and returning results to study participants. Here we describe the evolution, accomplishments, opportunities and challenges of the network since its inception as a five-group consortium focused on genotype-phenotype associations for genomic discovery to its current form as a nine-group consortium pivoting towards implementation of genomic medicine.
electronic medical records; personalized medicine; genome-wide association studies; genetics and genomics; collaborative research
The goal of this study was to investigate the role of complement cascade genes in the pathobiology of human abdominal aortic aneurysms (AAAs).
Methods and Results
Results of a genome-wide microarray expression profiling revealed 3,274 differentially expressed genes between aneurysmal and control aortic tissue. Interestingly, 13 genes in the complement cascade were significantly differentially expressed between AAA and the controls. In silico analysis of the promoters of the 13 complement cascade genes showed enrichment for transcription factor binding sites for STAT5A. Chromatin-immunoprecipitation experiments demonstrated binding of transcription factor STAT5A to the promoters of the majority of the complement cascade genes. Immunohistochemical analysis showed strong staining for C2 in AAA tissues.
These results provide strong evidence that the complement cascade plays a role in human AAA. Based on our microarray studies, the pathway is activated in AAA, particularly via the lectin and classical pathways. The overrepresented binding sites of transcription factor STAT5A in the complement cascade gene promoters suggest a role for STAT5A in the coordinated regulation of complement cascade gene expression.
Abdominal aortic aneurysm; complement cascade; genetic association study; STAT5; chromatin immunoprecipitation
Abdominal aortic aneurysm (AAA) is a dilatation of the aorta affecting most frequently elderly men. Histologically AAAs are characterized by inflammation, vascular smooth muscle cell apoptosis, and extracellular matrix degradation. The mechanisms of AAA formation, progression, and rupture are currently poorly understood. A previous mRNA expression study revealed a large number of differentially expressed genes between AAA and non-aneurysmal control aortas. MicroRNAs (miRNAs), small non-coding RNAs that are post-transcriptional regulators of gene expression, could provide a mechanism for the differential expression of genes in AAA.
To determine differences in miRNA levels between AAA (n = 5) and control (n = 5) infrarenal aortic tissues, a microarray study was carried out. Results were adjusted using Benjamini-Hochberg correction (adjusted p < 0.05). Real-time quantitative RT-PCR (qRT-PCR) assays with an independent set of 36 AAA and seven control tissues were used for validation. Potential gene targets were retrieved from miRNA target prediction databases Pictar, TargetScan, and MiRTarget2. Networks from the target gene set were generated and examined using the network analysis programs, CytoScape® and Ingenuity Pathway Core Analysis®.
A microarray study identified eight miRNAs with significantly different expression levels between AAA and controls (adjusted p < 0.05). Real-time qRT-PCR assays validated the findings for five of the eight miRNAs. A total of 222 predicted miRNA target genes known to be differentially expressed in AAA based on a prior mRNA microarray study were identified. Bioinformatic analyses revealed that several target genes are involved in apoptosis and activation of T cells.
Our genome-wide approach revealed several differentially expressed miRNAs in human AAA tissue suggesting that miRNAs play a role in AAA pathogenesis.
Apoptosis; Microarray analysis; Vascular biology; miRNA-mRNA analysis; Network analysis
Abdominal aortic aneurysm (AAA) is a multifactorial disease with a strong genetic component. Since first candidate gene studies were published 20 years ago, nearly 100 genetic association studies using single nucleotide polymorphisms (SNPs) in biologically relevant genes have been reported on AAA. The studies investigated SNPs in genes of the extracellular matrix, the cardiovascular system, the immune system, and signaling pathways. Very few studies were large enough to draw firm conclusions and very few results could be replicated in another sample set. The more recent unbiased approaches are family-based DNA linkage studies and genome-wide genetic association studies, which have the potential of identifying the genetic basis for AAA, if appropriately powered and well-characterized large AAA cohorts are used. SNPs associated with AAA have already been identified in these large multicenter studies. One significant association was of a variant in a gene called CNTN3 which is located on chromosome 3p12.3. Two follow-up studies, however, could not replicate the association. Two other SNPs, which are located on chromosome 9p21 and 9q33 were replicated in other samples. The two genes with the strongest supporting evidence of contribution to the genetic risk for AAA are the CDKN2BAS gene, also known as ANRIL, which encodes an antisense RNA that regulates expression of the cyclin-dependent kinase inhibitors CDKN2A and CDKN2B, and DAB2IP, which encodes an inhibitor of cell growth and survival. Functional studies are now needed to establish the mechanisms by which these genes contribute to AAA pathogenesis.
The infrarenal abdominal aorta exhibits increased disease susceptibility relative to other aortic regions. Allograft studies exchanging thoracic and abdominal segments showed that regional susceptibility is maintained regardless of location, suggesting substantial roles for embryological origin, tissue composition and site-specific gene expression.
We analyzed gene expression with microarrays in baboon aortas, and found that members of the HOX gene family exhibited spatial expression differences. HOXA4 was chosen for further study, since it had decreased expression in the abdominal compared to the thoracic aorta. Western blot analysis from 24 human aortas demonstrated significantly higher HOXA4 protein levels in thoracic compared to abdominal tissues (P < 0.001). Immunohistochemical staining for HOXA4 showed nuclear and perinuclear staining in endothelial and smooth muscle cells in aorta. The HOXA4 transcript levels were significantly decreased in human abdominal aortic aneurysms (AAAs) compared to age-matched non-aneurysmal controls (P < 0.00004). Cultured human aortic endothelial and smooth muscle cells stimulated with INF-γ (an important inflammatory cytokine in AAA pathogenesis) showed decreased levels of HOXA4 protein (P < 0.0007).
Our results demonstrated spatial variation in expression of HOXA4 in human aortas that persisted into adulthood and that downregulation of HOXA4 expression was associated with AAAs, an important aortic disease of the ageing population.