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
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.
Phenome-wide association studies (PheWAS) have demonstrated utility in validating genetic associations derived from traditional genetic studies as well as identifying novel genetic associations. Here we used an electronic health record (EHR)-based PheWAS to explore pleiotropy of genetic variants in the fat mass and obesity associated gene (FTO), some of which have been previously associated with obesity and type 2 diabetes (T2D). We used a population of 10,487 individuals of European ancestry with genome-wide genotyping from the Electronic Medical Records and Genomics (eMERGE) Network and another population of 13,711 individuals of European ancestry from the BioVU DNA biobank at Vanderbilt genotyped using Illumina HumanExome BeadChip. A meta-analysis of the two study populations replicated the well-described associations between FTO variants and obesity (odds ratio [OR] = 1.25, 95% Confidence Interval = 1.11–1.24, p = 2.10 × 10−9) and FTO variants and T2D (OR = 1.14, 95% CI = 1.08–1.21, p = 2.34 × 10−6). The meta-analysis also demonstrated that FTO variant rs8050136 was significantly associated with sleep apnea (OR = 1.14, 95% CI = 1.07–1.22, p = 3.33 × 10−5); however, the association was attenuated after adjustment for body mass index (BMI). Novel phenotype associations with obesity-associated FTO variants included fibrocystic breast disease (rs9941349, OR = 0.81, 95% CI = 0.74–0.91, p = 5.41 × 10−5) and trends toward associations with non-alcoholic liver disease and gram-positive bacterial infections. FTO variants not associated with obesity demonstrated other potential disease associations including non-inflammatory disorders of the cervix and chronic periodontitis. These results suggest that genetic variants in FTO may have pleiotropic associations, some of which are not mediated by obesity.
PheWAS; genetic association; pleiotropy; Exome chip; FTO; BMI
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
Translation of results from genetic findings to inform medical practice is a highly anticipated goal of human genetics. The aim of this paper is to review and discuss the role of genetics in medically-relevant prediction. Germline genetics presages disease onset and therefore can contribute prognostic signals that augment laboratory tests and clinical features. As such, the impact of genetic-based predictive models on clinical decisions and therapy choice could be profound. However, given that (i) medical traits result from a complex interplay between genetic and environmental factors, (ii) the underlying genetic architectures for susceptibility to common diseases are not well-understood, and (iii) replicable susceptibility alleles, in combination, account for only a moderate amount of disease heritability, there are substantial challenges to constructing and implementing genetic risk prediction models with high utility. In spite of these challenges, concerted progress has continued in this area with an ongoing accumulation of studies that identify disease predisposing genotypes. Several statistical approaches with the aim of predicting disease have been published. Here we summarize the current state of disease susceptibility mapping and pharmacogenetics efforts for risk prediction, describe methods used to construct and evaluate genetic-based predictive models, and discuss applications.
predictive model; genetic risk; human genetics; prognosis; clinical utility
There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance.
A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization.
The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.
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 YAP1 gene encodes a potent new oncogene and stem cell factor. However, in some cancers, the YAP1 gene plays a role of tumor suppressor. At present, the gene and its products are intensely studied and its cDNAs are used as transgenes in cellular and animal models. Here, we report 4 new potential mRNA splicing isoforms of the YAP1 gene, bringing the total number of isoforms to 8. We detected all 8 YAP1 isoforms in a panel of human tissues and evaluated the expression of the longest isoform of YAP1 (YAP1-2δ) using Real Time PCR. All YAP1 isoforms are barely detectable in human leukocytes compared to fair levels of expression found in other human tissues. We analyzed the structure of the genomic region that gave rise to alternatively spliced YAP1 transcripts in different metazoans. We found that YAP1 isoforms, which utilize exon 6 emerged in evolution with the appearance of amniotes. Interestingly, 6 YAP1 isoforms, which contain the exon 5 extension, exon 6 or both would have their leucine zipper region disrupted in the predicted protein product, compared to the intact leucine zipper found in two YAP1 (α) isoforms. This observation has direct functional ramifications for YAP1 signaling. We also propose a normalized nomenclature for the mRNA splice variants of YAP1 gene, which should aid in the characterization of signaling differences among the potential protein products of the YAP1 gene.
Alternative splicing; WW domains; Leucine Zipper; Quantitative RT-PCR
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 heterogeneous histological features of melanoma may often overlap with melanocytic nevi. For this reason, pathologists have sought after immunohistochemistry to assist with difficult cases. Recently, Wilms’ tumor 1 protein (WT1) has been suggested to differentiate between melanoma and melanocytic nevi.
Our objective was to determine whether immunohistochemistry analysis of WT1 expression is a reliable tool in differentiating cutaneous melanoma from melanocytic nevi.
Forty-five melanoma and 43 melanocytic nevi were immunostained with anti-WT1 monoclonal antibody (clone 6F-H2).
Forty of the 45 cutaneous melanoma (89%) and 22 of the 43 melanocytic nevi (51%) stained (> 10% cells) for WT1. The highest sensitivity for WT1 was expressed by nodular melanoma (19/20), superficial spreading melanoma (8/10) and Spitz nevi (9/11). At the threshold of above 75% WT1-stained cells, the specificity for melanoma was 95% but the sensitivity was only 31%. At the threshold of 10%, the sensitivity increased to 89% but the specificity decreased to only 49%. Finally, at the threshold of 25% and 50%, the sensitivity and specificity were 71%, 61% and 64%, 77%, respectively.
Our data suggest that melanoma is associated with increased WT1 expression. However, as a single immunostaining marker, WT1 is not sufficient for distinguishing melanoma from melanocytic nevi.
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
To determine whether maternal/fetal SNPs in candidate genes are associated with spontaneous preterm labor/delivery.
A genetic association study was conducted in 223 mothers and 179 fetuses [preterm labor with intact membranes who delivered <37 weeks (PTB)], and 599 mothers and 628 fetuses (normal pregnancy): 190 candidate genes and 775 SNPs were studied. Single locus/haplotype association analyses were performed; FDR was used to correct for multiple testing (q*=0.15)].
1) The strongest single locus associations with PTB were IL6R (fetus: p=0.000148) and TIMP2 (mother: p=0.000197), remaining significant after correction for multiple comparisons; 2) Global haplotype analysis indicated an association between a fetal DNA variant in IGF2 and maternal COL4A3 (global p=0.004 and 0.007, respectively).
A SNP involved in controlling fetal inflammation (IL6R) and DNA variants in maternal genes encoding for proteins involved in extracellular matrix biology approximately doubled the risk of PTB.
Chorioamnionitis; DNA variants; extracellular matrix; genetic association study; genomics; genotype; haplotype; high dimensional biology; IL-6; parturition; prematurity; SNP
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.
To determine whether maternal/fetal SNPs in candidate genes are associated with preterm prelabor rupture of membranes (pPROM).
A case-control study was conducted in patients with pPROM (225 mothers and 155 fetuses) and 599 mothers and 628 fetuses with a normal pregnancy; 190 candidate genes and 775 SNPs were studied. Single locus/haplotype association analyses were performed; FDR was used to correct for multiple testing (q*=0.15)].
1) A SNP in TIMP2 in mothers was significantly associated with pPROM(OR=2.12 95% CI [1.47-3.07], p = 0.000068), and this association remained significant after correction for multiple comparisons; 2) Haplotypes for COL4A3 in the mother were associated with pPROM (global p = 0.003); 3) Multilocus analysis identified a three locus model, which included maternal SNPs in COL1A2, DEFA5, and EDN1.
DNA variants in a maternal gene involved in extracellular matrix metabolism doubled the risk of pPROM.
Chorioamnionitis; DNA variants; extracellular matrix; genetic association study; genomics; genotype; haplotype; high dimensional biology; MMP; parturition; pPROM; prematurity; SNP
To examine the association between maternal and fetal genetic variants and small-for-gestational-age (SGA).
A case-control study was conducted in patients with SGA neonates (530 maternal and 436 fetal) and controls (599 maternal and 628 fetal); 190 candidate genes and 775 SNPs were studied. Single locus, multilocus and haplotype association analyses were performed on maternal and fetal data with logistic regression, multifactor dimensionality reduction (MDR) analysis, and haplotype-based association with 2 and 3 marker sliding windows, respectively. Ingenuity Pathway Analysis (IPA) software was used to assess pathways that associate with SGA.
The most significant single locus association in maternal data was with a SNP in tissue inhibitor of metalloproteinase 2 (TIMP2) (rs2277698 OR = 1.71 95% CI [1.26-2.32], p = 0.0006) while in the fetus it was with a SNP in fibronectin 1 isoform 3 preproprotein (FN1) (rs3796123, OR = 1.46 95% CI [1.20-1.78], p = 0.0001). Both SNPs were adjusted for potential confounders (maternal body mass index and fetal sex). Haplotype analyses resulted in associations in alpha 1 type I collagen preproprotein (COL1A1, rs1007086-rs2141279-rs17639446, global p = 0.006) in mothers and FN1 (rs2304573-rs1250204-rs1250215, global p = 0.045) in fetuses. Multilocus analyses with MDR identified a two SNP model with maternal variants collagen type V alpha 2 (COL5A2) and plasminogen activator urokinase (PLAU) predicting SGA outcome correctly 59% of the time (p = 0.035).
Genetic variants in extracellular matrix related genes showed significant single locus association with SGA. These data are consistent with other studies that have observed elevated circulating fibronectin concentrations in association with increased risk of SGA. The present study supports the hypothesis that DNA variants can partially explain risk of SGA in a cohort of Hispanic women.
DNA variants; extracellular matrix; genetic association study; genomics; genotype; haplotype; high dimensional biology; SNP; intrauterine growth restriction; genetic epidemiology; complex disease
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.
Previously, we identified 3,274 distinct differentially expressed genes in abdominal aortic aneurysm (AAA) tissue compared to non-aneurysmal controls. As transcriptional control is responsible for these expression changes, we sought to find common transcriptional elements in the promoter regions of the differentially expressed genes.
Methods and Results
We analyzed the up- and downregulated gene sets with Whole Genome rVISTA to determine the transcription factor binding sites (TFBSs) overrepresented in the 5 kb promoter regions of the 3,274 genes. The downregulated gene set yielded 144 TFBSs that were overrepresented in the subset when compared to the entire genome. In contrast, the upregulated gene set yielded only 13 distinct overrepresented TFBSs. Interestingly, as classified by TRANSFAC®, 8 of the 13 transcription factors (TFs) binding to these regions belong to the ETS family. Additionally, NFKB and its subunits p50 and p65 showed enrichment. Immunohistochemical analyses in 10 of the TFs from the upregulated analysis showed 9 to be present in AAA tissue. Based on Gene Ontology analysis of biological process categories of the upregulated target genes of enriched TFs, 10 TFs had enrichment in immune system process among their target genes.
Our genome-wide analysis provides further evidence of ETS and NFKB involvement in AAA. Additionally, our results provide novel insight for future studies aiming to dissect the pathogenesis of AAA and have uncovered potential therapeutic targets for AAA prevention.
Aneurysm; Aorta; Genomics; Transcription Factors
Abdominal aortic aneurysm (AAA) is a complex disorder with multiple genetic risk factors. Using affected relative pair linkage analysis, we previously identified an AAA susceptibility locus on chromosome 19q13. This locus has been designated as the AAA1 susceptibility locus in the Online Mendelian Inheritance in Man (OMIM) database.
Nine candidate genes were selected from the AAA1 locus based on their function, as well as mRNA expression levels in the aorta. A sample of 394 cases and 419 controls was genotyped for 41 SNPs located in or around the selected nine candidate genes using the Illumina GoldenGate platform. Single marker and haplotype analyses were performed. Three genes (CEBPG, PEPD and CD22) were selected for DNA sequencing based on the association study results, and exonic regions were analyzed. Immunohistochemical staining of aortic tissue sections from AAA and control individuals was carried out for the CD22 and PEPD proteins with specific antibodies.
Several SNPs were nominally associated with AAA (p < 0.05). The SNPs with most significant p-values were located near the CCAAT enhancer binding protein (CEBPG), peptidase D (PEPD), and CD22. Haplotype analysis found a nominally associated 5-SNP haplotype in the CEBPG/PEPD locus, as well as a nominally associated 2-SNP haplotype in the CD22 locus. DNA sequencing of the coding regions revealed no variation in CEBPG. Seven sequence variants were identified in PEPD, including three not present in the NCBI SNP (dbSNP) database. Sequencing of all 14 exons of CD22 identified 20 sequence variants, five of which were in the coding region and six were in the 3'-untranslated region. Five variants were not present in dbSNP. Immunohistochemical staining for CD22 revealed protein expression in lymphocytes present in the aneurysmal aortic wall only and no detectable expression in control aorta. PEPD protein was expressed in fibroblasts and myofibroblasts in the media-adventitia border in both aneurysmal and non-aneurysmal tissue samples.
Association testing of the functional positional candidate genes on the AAA1 locus on chromosome 19q13 demonstrated nominal association in three genes. PEPD and CD22 were considered the most promising candidate genes for altering AAA risk, based on gene function, association evidence, gene expression, and protein expression.
Human parturition is characterized by the activation of genes involved in acute inflammatory in the fetal membranes. Manganese superoxide dismutase (MnSOD) is a mitochondrial enzyme that scavenges reactive oxygen species (ROS). MnSOD is up-regulated in sites of inflammation and has an important role in the down-regulation of acute inflammatory processes. Therefore, the aim of this study was to determine the differences in MnSOD mRNA expression in the fetal membranes in patients with term and preterm labor as well as in acute chorioamnionitis.
Fetal membranes were obtained from patients in the following groups: 1) term not in labor (n=29); 2) term in labor (n=29); 3) spontaneous preterm labor with intact mebranes (n=16); 4) PTL with histological chorioamnionitis (n=12); 5) preterm prelabor rupture of membranes (PPROM; n=17); and 6) PPROM with histological chorioamnionitis (n=21). MnSOD mRNA expression in the membranes was determined by quantitative real-time RT-PCR.
1) MnSOD mRNA expression was higher in the fetal membranes of patients at term in labor than those not in labor (2.4-fold; p=0.02); 2) the amount of MnSOD mRNA in the fetal membranes was higher in PTL than in term labor or in PPROM (7.2-fold, p=0.03; 3.2-fold, p=0.03, respectively); 3) MnSOD mRNA expression was higher when histological chorioamnionitis was present both among patients with PPROM (3.8-fold, p=0.02) and with PTL (5.4-fold, p=0.02) than in patients with these conditions without histological chorioamnionitis; 4) expression of MnSOD mRNA was higher in PTL with chorioamnionitis than in PPROM with chorioamnionitis (4.3-fold, p=0.03);
The increase in MnSOD mRNA expression by fetal membranes in term labor and in histological chorioamnionitis in PTL and PPROM suggests that the fetus deploys anti-oxidant mechanisms to constrain the inflammatory processes in the chorioamniotic membranes.
fetal gender; gene expression; preterm delivery; preterm labor; preterm prelabor rupture of the membranes; reactive oxygen species; scavenger