Eric Farber-Eger

Hemodynamic Evidence of Vascular Remodeling in Combined Post- and Precapillary Pulmonary Hypertension

Although commonly encountered, patients with combined postcapillary and precapillary pulmonary hypertension (Cpc-PH) have poorly understood pulmonary vascular properties. The product of pulmonary vascular resistance and compliance, resistance-compliance (RC) time, is a measure of pulmonary vascular physiology. While RC time is lower in postcapillary PH than in precapillary PH, the RC time in Cpc-PH and the effect of pulmonary wedge pressure (PWP) on RC time are unknown. We tested the hypothesis that Cpc-PH has an RC time that resembles that in pulmonary arterial hypertension (PAH) more than that in isolated postcapillary PH (Ipc-PH). We analyzed the hemodynamics of 282 consecutive patients with PH referred for right heart catheterization (RHC) with a fluid challenge from 2004 to 2013 (cohort A) and 4,382 patients who underwent RHC between 1998 and 2014 for validation (cohort B). Baseline RC time in Cpc-PH was higher than that in Ipc-PH and lower than that in PAH in both cohorts (P < 0.001). In cohort A, RC time decreased after fluid challenge in patients with Ipc-PH but not in those with PAH or Cpc-PH (P < 0.001). In cohort B, the inverse relationship of pulmonary vascular compliance and resistance, as well as that of RC time and PWP, in Cpc-PH was similar to that in PAH and distinct from that in Ipc-PH. Our findings demonstrate that patients with Cpc-PH have pulmonary vascular physiology that resembles that of patients with PAH more than that of Ipc-PH patients. Further study is warranted to identify determinants of vascular remodeling and assess therapeutic response in this subset of PH.

Extraction of echocardiographic data from the electronic medical record is a rapid and efficient method for study of cardiac structure and function

BackgroundMeasures of cardiac structure and function are important human phenotypes that are associated with a range of clinical outcomes. Studying these traits in large populations can be time consuming and costly. Utilizing data from large electronic medical records (EMRs) is one possible solution to this problem. We describe the extraction and filtering of quantitative transthoracic echocardiographic data from the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study, a large, racially diverse, EMR-based cohort (n = 15,863).ResultsThere were 6,076 echocardiography reports for 2,834 unique adult subjects. Missing data were uncommon with over 90% of data points present. Data irregularities are primarily related to inconsistent use of measurement units and transcriptional errors. The reported filtering method requires manual review of very few data points (<1%), and filtered echocardiographic parameters are similar to published data from epidemiologic populations of similar ethnicity. Moreover, the cohort is comparable in size, and in some cases larger than community-based cohorts of similar race/ethnicity.ConclusionsThese results demonstrate that echocardiographic data can be efficiently extracted from EMRs, and suggest that EMR-based cohorts have the potential to make major contributions toward the study of epidemiologic and genotype-phenotype associations for cardiac structure and function in diverse populations.

Investigating the relationship between mitochondrial genetic variation and cardiovascular-related traits to develop a framework for mitochondrial phenome-wide association studies

BackgroundMitochondria play a critical role in the cell and have DNA independent of the nuclear genome. There is much evidence that mitochondrial DNA (mtDNA) variation plays a role in human health and disease, however, this area of investigation has lagged behind research into the role of nuclear genetic variation on complex traits and phenotypic outcomes. Phenome-wide association studies (PheWAS) investigate the association between a wide range of traits and genetic variation. To date, this approach has not been used to investigate the relationship between mtDNA variants and phenotypic variation. Herein, we describe the development of a PheWAS framework for mtDNA variants (mt-PheWAS). Using the Metabochip custom genotyping array, nuclear and mitochondrial DNA variants were genotyped in 11,519 African Americans from the Vanderbilt University biorepository, BioVU. We employed both polygenic modeling and association testing with mitochondrial single nucleotide polymorphisms (mtSNPs) to explore the relationship between mtDNA variants and a group of eight cardiovascular-related traits obtained from de-identified electronic medical records within BioVU.ResultsUsing polygenic modeling we found evidence for an effect of mtDNA variation on total cholesterol and type 2 diabetes (T2D). After performing comprehensive mitochondrial single SNP associations, we identified an increased number of single mtSNP associations with total cholesterol and T2D compared to the other phenotypes examined, which did not have more significantly associated SNPs than would be expected by chance. Among the mtSNPs significantly associated with T2D we identified variant mt16189, an association previously reported only in Asian and European-descent populations.ConclusionsOur replication of previous findings and identification of novel associations from this initial study suggest that our mt-PheWAS approach is robust for investigating the relationship between mitochondrial genetic variation and a range of phenotypes, providing a framework for future mt-PheWAS.

Leveraging Epidemiologic and Clinical Collections for Genomic Studies of Complex Traits

Background/Aims: Present-day limited resources demand DNA and phenotyping alternatives to the traditional prospective population-based epidemiologic collections. Methods: To accelerate genomic discovery with an emphasis on diverse populations, we - as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study - accessed all non-European American samples (n = 15,863) available in BioVU, the Vanderbilt University biorepository linked to de-identified electronic medical records, for genomic studies as part of the larger Population Architecture using Genomics and Epidemiology (PAGE) I study. Given previous studies have cautioned against the secondary use of clinically collected data compared with epidemiologically collected data, we present here a characterization of EAGLE BioVU, including the billing and diagnostic (ICD-9) code distributions for adult and pediatric patients as well as comparisons made for select health metrics (body mass index, glucose, HbA1c, HDL-C, LDL-C, and triglycerides) with the population-based National Health and Nutrition Examination Surveys (NHANES) linked to DNA samples (NHANES III, n = 7,159; NHANES 1999-2002, n = 7,839). Results: Overall, the distributions of billing and diagnostic codes suggest this clinical sample is a mixture of healthy and sick patients like that expected for a contemporary American population. Conclusion: Little bias is observed among health metrics, suggesting this clinical collection is suitable for genomic studies along with traditional epidemiologic cohorts.

Prognostic Effect and Longitudinal Hemodynamic Assessment of Borderline Pulmonary Hypertension

Importance Pulmonary hypertension (PH) is diagnosed by a mean pulmonary arterial pressure (mPAP) value of at least 25 mm Hg during right heart catheterization (RHC). While several studies have demonstrated increased mortality in patients with mPAP less than that threshold, little is known about the natural history of borderline PH. Objective To test the hypothesis that patients with borderline PH have decreased survival compared with patients with lower mPAP and frequently develop overt PH and to identify clinical correlates of borderline PH. Design, Setting, and Participants Retrospective cohort study from 1998 to 2014 at Vanderbilt University Medical Center, comprising all patients undergoing routine RHC for clinical indication. We extracted demographics, clinical data, invasive hemodynamics, echocardiography, and vital status for all patients. Patients with mPAP values of 18 mm Hg or less, 19 to 24 mm Hg, and at least 25 mm Hg were classified as reference, borderline PH, and PH, respectively. Exposures Mean pulmonary arterial pressure. Main Outcome and Measures Our primary outcome was all-cause mortality after adjusting for clinically relevant covariates in a Cox proportional hazards model. Our secondary outcome was the diagnosis of overt PH in patients initially diagnosed with borderline PH. Both outcomes were determined prior to data analysis. Results We identified 4343 patients (mean [SD] age, 59 [15] years, 51% women, and 86% white) among whom the prevalence of PH and borderline PH was 62% and 18%, respectively. Advanced age, features of the metabolic syndrome, and chronic heart and lung disease were independently associated with a higher likelihood of borderline PH compared with reference patients in a logistic regression model. After adjusting for 34 covariates in a Cox proportional hazards model, borderline PH was associated with increased mortality compared with reference patients (hazard ratio, 1.31; 95% CI, 1.04-1.65; P = .001). The hazard of death increased incrementally with higher mPAP, without an observed threshold. In the 70 patients with borderline PH who underwent a repeated RHC, 43 (61%) had developed overt PH, with a median increase in mPAP of 5 mm Hg (interquartile range, −1 to 11 mm Hg; P < .001). Conclusions and Relevance Borderline PH is common in patients undergoing RHC and is associated with significant comorbidities, progression to overt PH, and decreased survival. Small increases in mPAP, even at values currently considered normal, are independently associated with increased mortality. Prospective studies are warranted to determine whether early intervention or closer monitoring improves clinical outcomes in these patients.

Towards a phenome-wide catalog of human clinical traits impacted by genetic ancestry

BackgroundRacial/ethnic differences for commonly measured clinical variables are well documented, and it has been postulated that population-specific genetic factors may play a role. The genetic heterogeneity of admixed populations, such as African Americans, provides a unique opportunity to identify genomic regions and variants associated with the clinical variability observed for diseases and traits across populations.MethodTo begin a systematic search for these population-specific genomic regions at the phenome-wide scale, we determined the relationship between global genetic ancestry, specifically European and African ancestry, and clinical variables measured in a population of African Americans from BioVU, Vanderbilt University’s biorepository linked to de-identified electronic medical records (EMRs) as part of the Epidemiologic Architecture using Genomics and Epidemiology (EAGLE) study. Through billing (ICD-9) codes, procedure codes, labs, and clinical notes, 36 common clinical and laboratory variables were mined from the EMR, including body mass index (BMI), kidney traits, lipid levels, blood pressure, and electrocardiographic measurements. A total of 15,863 DNA samples from non-European Americans were genotyped on the Illumina Metabochip containing ~200,000 variants, of which 11,166 were from African Americans. Tests of association were performed to examine associations between global ancestry and the phenotype of interest.ResultsIncreased European ancestry, and conversely decreased African ancestry, was most strongly correlated with an increase in QRS duration, consistent with previous observations that African Americans tend to have shorter a QRS duration compared with European Americans. Despite known racial/ethnic disparities in blood pressure, European and African ancestry was neither associated with diastolic nor systolic blood pressure measurements.ConclusionCollectively, these results suggest that this clinical population can be used to identify traits in which population differences may be due, in part, to population-specific genetics.

Pre-existing Psychiatric Illness is Associated With Increased Risk of Recurrent Takotsubo Cardiomyopathy

BACKGROUND The increased prevalence of psychiatric illness among patients with takotsubo cardiomyopathy (TC) has been previously described. OBJECTIVES We sought to assess the effect of pre-existing psychiatric illness on clinical outcomes following the diagnosis of TC. METHODS Adults diagnosed with TC at Vanderbilt University Medical Center between 1999 and 2015 were included in the study. Medical records were retrospectively reviewed to identify any pre-existing mood, anxiety, or schizophrenia-spectrum illness before TC presentation. Multivariable logistic regression was used to test for independent association of pre-existing psychiatric illness with 30-day mortality and recurrent TC; Cox proportional hazard analysis was used to evaluate for association with long-term mortality. RESULTS Among 306 patients diagnosed with TC during the study period, 114 (37%) had a pre-existing psychiatric illness. In all, 43 (14%) and 88 (29%) patients died within 30 days of index diagnosis and as of last medical record review, respectively. Of the 269 who survived their index hospitalization, 19 (7%) had a confirmed recurrent episode of TC. In multivariable analyses, pre-existing psychiatric illness was not associated with increased 30-day (P = 0.320) or long-term (P = 0.621) mortality. Pre-existing psychiatric illness was associated with higher risk of recurrent TC (odds ratio = 7.44, 95% CI: 2.30-24.01, P < 0.001). CONCLUSIONS Pre-existing psychiatric illness was associated with an increased risk of recurrent TC. No significant association was noted between pre-existing psychiatric illness and survival.

Extracting Primary Open-Angle Glaucoma from Electronic Medical Records for Genetic Association Studies.

Electronic medical records (EMRs) are being widely implemented for use in genetic and genomic studies. As a phenotypic rich resource, EMRs provide researchers with the opportunity to identify disease cohorts and perform genotype-phenotype association studies. The Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study, as part of the Population Architecture using Genomics and Epidemiology (PAGE) I study, has genotyped more than 15,000 individuals of diverse genetic ancestry in BioVU, the Vanderbilt University Medical Center’s biorepository linked to a de-identified version of the EMR (EAGLE BioVU). Here we develop and deploy an algorithm utilizing data mining techniques to identify primary open-angle glaucoma (POAG) in African Americans from EAGLE BioVU for genetic association studies. The algorithm described here was designed using a combination of diagnostic codes, current procedural terminology billing codes, and free text searches to identify POAG status in situations where gold-standard digital photography cannot be accessed. The case algorithm identified 267 potential POAG subjects but underperformed after manual review with a positive predictive value of 51.6% and an accuracy of 76.3%. The control algorithm identified controls with a negative predictive value of 98.3%. Although the case algorithm requires more downstream manual review for use in large-scale studies, it provides a basis by which to extract a specific clinical subtype of glaucoma from EMRs in the absence of digital photographs.

Oestrogen inhibition reverses pulmonary arterial hypertension and associated metabolic defects

Increased oestrogen is a strong epidemiological risk factor for development of pulmonary arterial hypertension (PAH) in patients, associated with metabolic defects. In addition, oestrogens drive penetrance in mice carrying mutations in bone morphogenetic protein receptor type II (BMPR2), the cause of most heritable PAH. The goal of the present study was to determine whether inhibition of oestrogens was effective in the treatment of PAH in these mice. The oestrogen inhibitors fulvestrant and anastrozole were used in a prevention and treatment paradigm in BMPR2 mutant mice, and tamoxifen was used for treatment. In addition, BMPR2 mutant mice were crossed onto oestrogen receptor (ESR)1 and ESR2 knockout backgrounds to assess receptor specificity. Haemodynamic and metabolic outcomes were measured. Oestrogen inhibition both prevented and treated PAH in BMPR2 mutant mice. This was associated with reduction in metabolic defects including oxidised lipid formation, insulin resistance and rescue of peroxisome proliferator-activated receptor-γ and CD36. The effect was mediated primarily through ESR2, but partially through ESR1. Our data suggest that trials of oestrogen inhibition in human PAH are warranted, and may improve pulmonary vascular disease through amelioration of metabolic defects. Although fulvestrant and anastrozole were more effective than tamoxifen, tamoxifen may be useful in premenopausal females, because of a reduced risk of induction of menopause. Oestrogen inhibition reverses BMPR2-related pulmonary arterial hypertension and associated metabolic defects http://ow.ly/ir6Y30b2WLH

The effects of electronic medical record phenotyping details on genetic association studies: HDL-C as a case study

BackgroundBiorepositories linked to de-identified electronic medical records (EMRs) have the potential to complement traditional epidemiologic studies in genotype-phenotype studies of complex human diseases and traits. A major challenge in meeting this potential is the use of EMR-derived data to extract phenotypes and covariates for genetic association studies. Unlike traditional epidemiologic data, EMR-derived data are collected for clinical care and are therefore highly variable across patients. The variability of clinical data coupled with the challenges associated with searching unstructured clinical notes requires the development of algorithms to extract phenotypes for analysis. Given the number of possible algorithms that could be developed for any one EMR-derived phenotype, we explored here the impact algorithm decision logic has on genetic association study results for a single quantitative trait, high density lipoprotein cholesterol (HDL-C).ResultsWe used five different algorithms to extract HDL-C from African American subjects genotyped on the Illumina Metabochip (n = 11,519) as part of Epidemiologic Architecture for Genes Linked to Environment (EAGLE). Tests of association between HDL-C and genetic risk scores for HDL-C associated variants suggest that the genetic effect size does not vary substantially across the five HDL-C definitions.ConclusionsThese data collectively suggest that, at least for this quantitative trait, algorithm decision logic and phenotyping details do not appreciably impact genetic association study test statistics.