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.
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.
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.
Current therapies for diseases of heart muscle (cardiomyopathy) and aorta (aortopathy) include inhibitors of the renin-angiotensin system, β-adrenergic antagonists, and the statin class of cholesterol-lowering agents. These therapies have limited efficacy, as adverse cardiovascular events continue to occur with some frequency in patients taking these drugs. Although cardiomyopathy and aortopathy can coexist in a number of conditions (for example, Marfan’s syndrome, acromegaly, pregnancy, and aging), pathogenetic molecular links between the two diseases remain poorly understood. We reasoned that identification of common molecular perturbations in these two tissues could point to therapies for both conditions. Here, we show that deficiency of the transcriptional regulator Kruppel-like factor 15 (Klf15) in mice leads to both heart failure and aortic aneurysm formation through a shared molecular mechanism. Klf15 concentrations are markedly reduced in failing human hearts and in human aortic aneurysm tissues. Mice deficient in Klf15 develop heart failure and aortic aneurysms in a p53-dependent and p300 acetyltransferase–dependent fashion. KLF15 activation inhibits p300-mediated acetylation of p53. Conversely, Klf15 deficiency leads to hyperacetylation of p53 in the heart and aorta, a finding that is recapitulated in human tissues. Finally, Klf15-deficient mice are rescued by p53 deletion or p300 inhibition. These findings highlight a molecular perturbation common to the pathobiology of heart failure and aortic aneurysm formation and suggest that manipulation of KLF15 function may be a productive approach to treat these morbid diseases.
In utero interactions between incompatible maternal and fetal genotypes are a potential mechanism for the onset or progression of pregnancy related diseases such as pre-eclampsia (PE). However, the optimal analytical approach and study design for evaluating incompatible maternal/offspring genotype combinations is unclear.
Using simulation, we estimated the type I error and power of incompatible maternal/offspring genotype models for two analytical approaches: logistic regression used with case-control mother/offspring pairs and the log-linear regression used with case-parent triads. We evaluated a real dataset consisting of maternal/offspring pairs with and without PE for incompatibility effects using the optimal analysis based on the results of the simulation study.
We identified a single coding scheme for the incompatibility effect that was equally or more powerful than all of the alternative analysis models evaluated, regardless of the true underlying model for the incompatibility effect. In addition, the log-linear regression was more powerful than the logistic regression when the heritability was low, and more robust to adjustment for maternal or fetal effects. For the PE data, this analysis revealed three genes, lymphotoxin alpha (LTA), von Willebrand factor (VWF), and alpha 2 chain of type IV collagen (COL4A2) with possible incompatibility effects.
The incompatibility model should be evaluated for complications of pregnancy, such as PE, where the genotypes of two individuals may contribute to the presence of disease.
Abdominal aortic aneurysm (AAA) is a significant health problem in the United States with approximately 30,000 repair operations annually. Treatment of AAA is associated with more than 150,000 hospital admissions per year. The development of AAA is characterized by destruction of the elastic media of the aortic wall. A large body of evidence suggests that a group of enzymes called matrix metalloproteinases (MMPs) plays a significant role in the destruction of extracellular matrix in the aortic wall. MMP inhibition has, therefore, been viewed as an alternative pharmacotherapeutic approach to slow down the development and progression of small AAAs thus reducing the need for surgical intervention.
Abdominal Aortic Aneurysm; Matrix Metalloproteinases; Matrix Metalloproteinase Inhibitors; Doxycycline; Small Molecule Inhibitors
The purpose of this study was to identify which biological processes may be involved in normal labor.
Transcriptional profiles for chorioamniotic membranes (n=24) and blood (n=20) were generated from patients at term with no labor (TNL) and in labor (TIL).
Expression of 197 transcripts (P≤0.02) differentiated TIL and TNL chorioamniotic membrane samples. Gene Ontology analysis indicated that TIL samples had increased expression of multiple chemokines and transcripts associated with neutrophil and monocyte recruitment. Microarray results were verified using quantitative real-time RT-PCR with independent samples. Transcriptional profiles from blood RNA revealed no Gene Ontology category enrichment of discriminant probe sets.
Labor induces gene expression changes consistent with localized inflammation, despite the absence of histologically detectable inflammation.
chorioamniotic membrane; blood, transcriptional profile; microarray; acute inflammation; parturition; chorioamnionitis; chemokines; cytokines
Macrophage migration inhibitory factor (MIF) has emerged as an important mediator of septic shock. The administration of MIF increases lethality during endotoxemia, whereas neutralization of this cytokine prevents endotoxic shock and death associated with bacterial infection. The objective of this study was to determine whether there is a change in the amniotic fluid concentration of MIF in intra-amniotic infection and human parturition.
A cross-sectional study was conducted in women in the following categories: 1) midtrimester (n=84); 2) preterm labor and intact membranes who delivered at term (n=33), who delivered preterm (n=53), and preterm labor with intra-amniotic infection (n=23); 3) preterm premature rupture of membranes (PROM) with (n=25) and without intra-amniotic infection (n=26); and 4) term with intact membranes, in labor (n=52), and not in labor (n=31). MIF concentrations in amniotic fluid were determined using a sensitive and specific immunoassay. MIF concentrations in maternal plasma were also determined in patients with preterm labor and intact membranes. Immunohistochemistry was conducted in chorioamniotic membranes obtained from a different set of patients presenting with preterm labor with (n=18) and without (n=20) histologic chorioamnionitis. Quantitative RT-PCR was used to measure MIF mRNA expression in chorioamniotic membranes of patients with preterm labor with (n=13) and without (n=13) histologic chorioamnionitis. Parametric and non-parametric, receiver-operating characteristic (ROC) curve, survival analysis, and Cox regression model were used for analysis.
Immunoreactive MIF was detectable in 96% (313/327) of amniotic fluid samples. The concentration of amniotic fluid MIF at term was higher than that in the midtrimester (p=0.004). Intra-amniotic infection in women with preterm labor and preterm PROM was associated with a significant increase in median amniotic fluid MIF concentration (p<0.001 and 0.004, respectively). Patients with preterm labor with sterile amniotic fluid who delivered preterm had a significantly higher median amniotic fluid MIF concentration than those who delivered at term (p=0.007). Among patients with preterm labor with intact membranes, survival analysis indicated that the median amniocentesis-to-delivery interval was significantly shorter in patients whose amniotic fluid concentrations of MIF were above 302 ng/ml than those below this cutoff value (p<0.001). Human parturition at term was not associated with changes in the amniotic fluid MIF concentrations (p>0.05). There was no significant difference in median maternal plasma MIF concentrations among patients with preterm labor and intact membranes who delivered at term, those who delivered preterm, and those who had intra-amniotic infection (p>0.05 for all comparisons). Immunohistochemistry demonstrated that MIF protein was present in amniotic epithelial cells, and the mean percentage of immunoreactive MIF-staining cells was higher in patients with histologic chorioamnionitis than in those without this lesion (p=0.03). Similarly, the mean MIF mRNA expression was higher in chorioamniotic membranes obtained from patients with histologic chorioamnionitis than in those without this lesion (p=0.03).
Intra-amniotic infection and preterm parturition, but not term parturition, are associated with a significant increase in amniotic fluid MIF concentrations. Among patients with preterm labor with intact membranes, elevated amniotic fluid concentrations of MIF are associated with intra-amniotic inflammation, histologic chorioamnionitis, and shorter amniocentesis-to-delivery interval. These changes in amniotic fluid were not reflected in maternal plasma. An increased expression of MIF protein and mRNA in chorioamniotic membranes was observed in patients with histologic chorioamnionitis.
Amniotic fluid; immunohistochemistry; intrauterine infection; macrophage migration inhibitory factor; MIF; MIF gene expression; parturition; placenta; preterm labor
Abdominal aortic aneurysms (AAAs) are frequently familial. The aim of this study was to compare the prevalence of AAA among the siblings of AAA patients to that in the spouses’ siblings.
The siblings of 375 AAA patients and the siblings of the spouses of the AAA patients were included in this study and offered ultrasonography screening for AAA. Participants were asked to complete a questionnaire to collect demographic and general health information. Statistical analysis was carried out using Fisher’s exact test. Odds ratios and 95% confidence intervals were also calculated.
Abdominal ultrasonography examination was carried out for 309 individuals. The results indicated that 11 of 98 (11.2%) brothers of AAA patients, 4 of 147 (2.7%) sisters, and none of the 64 siblings of the spouses of the AAA patients were found to have an AAA. Combining the information from the ultrasonography screening and medical records on already known cases of AAA in these families, altogether 29.0% (44/152) of the brothers of AAA patients, 11.1% (20/181) of the sisters of AAA patients, and 2.3% (2/88) of the siblings of the spouses had an AAA.
There was a significant difference between the siblings of the AAA patients and those of the spouses both in the frequency of AAA detected by ultrasonography screening and in the overall prevalence of AAA. The overall prevalence of AAA in the siblings of AAA patients was about 8 times that observed among the siblings of their spouses (19.2% vs. 2.3%). These findings confirmed previous reports on high prevalence of AAA among siblings of AAA patients and emphasized the importance of an ultrasonography screening program for siblings of AAA patients.
Genome-wide screening studies of the chorioamniotic membranes have unexpectedly identified an increase in the expression of bone morphogenetic protein 2 (BMP2) in spontaneous labor at term. The objective of this study was to determine whether BMP2 mRNA and protein expression are altered in the chorioamniotic membranes of patients with term labor, preterm labor, and preterm premature rupture of membranes (PPROM).
Chorioamniotic membranes were obtained from patients at term (with and without labor), with preterm labor (with and without histologic chorioamnionitis), and with PPROM (with and without histologic chorioamnionitis). The expression of BMP2 was studied by real-time quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR; n=88) and immunohistochemistry (IHC; n=124). Non-parametric statistics were used for analysis. Primary amnion cells obtained from women at term not in labor were treated with BMP2 to examine whether there was increased prostaglandin E2 expression.
1) The median BMP2 mRNA and protein expression were significantly higher in the membranes of patients with spontaneous labor at term than in those of patients not in labor at term (P < 0.001 for both). 2) BMP2 mRNA and protein expression were increased in patients with preterm labor with histologic chorioamnionitis than in those without histologic chorioamnionitis (P < 0.05 and P < 0.001, respectively). 3) There was no difference in BMP2 mRNA and protein expression in patients with PPROM, regardless of chorioamnionitis (P = 0.13 and P = 0.08). 4) There was a correlation between BMP2 and cyclooxygenase 2 protein expression in chorioamniotic membranes (R = 0.34; P < 0.001).
BMP2 mRNA and protein expression are increased in the chorioamniotic membranes of patients with spontaneous labor at term and patients with preterm labor associated with histologic chorioamnionitis. Its expression pattern and biologic effects strongly suggest that BMP2 is involved in human parturition.
parturition; chorioamniotic membrane; immunohistochemistry; real-time quantitative reverse-transcriptase PCR; BMP-2; Preterm labor; Preterm premature rupture of membranes; PPROM