A missense variant in human perilipin 2 (PLIN2 Ser251Pro) reduces hepatic steatosis in mice.

Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is characterised by the accumulation of lipid droplets (LDs) within hepatocytes. Perilipin 2 (PLIN2) is the most abundant protein in hepatic LDs and its expression correlates with intracellular lipid accumulation. A recently discovered PLIN2 coding variant, Ser251Pro (rs35568725), was found to promote the accumulation of small LDs in embryonic kidney cells. In this study, we investigate the role of PLIN2-Ser251Pro (PLIN2-Pro251) on hepatic LD metabolism in vivo and research the metabolic phenotypes associated with this variant in humans. Methods: For our animal model, we used Plin2 knockout mice in which we expressed either human PLIN2-Pro251 (Pro251 mice) or wild-type human PLIN2-Ser251 (Ser251 mice) in a hepatocyte-specific manner. We fed both cohorts a lipogenic high-fat, high-cholesterol, high-fructose diet for 12 weeks. Results: Pro251 mice were associated with reduced liver triglycerides (TGs) and had lower mRNA expression of fatty acid synthase and diacylglycerol O-acyltransferase-2 compared with Ser251 mice. Moreover, Pro251 mice had a reduction of polyunsaturated fatty acids-TGs and reduced expression of epoxygenase genes. For our human study, we analysed the Penn Medicine BioBank, the Million Veteran Program, and UK Biobank. Across these databases, the minor allele frequency of PLIN2-Pro251 was approximately 5%. There was no association with the clinical diagnosis of NAFLD, however, there was a trend toward reduced liver fat in PLIN2-Pro251 carriers by MRI-spectroscopy in UK Biobank subjects. Conclusions: In mice lacking endogenous Plin2, expression of human PLIN2-Pro251 attenuated high-fat, high-fructose, high-cholesterol, diet-induced hepatic steatosis compared with human wild-type PLIN2-Ser251. Moreover, Pro251 mice had lower polyunsaturated fatty acids-TGs and epoxygenase genes expression, suggesting less liver oxidative stress. In humans, PLIN2-Pro251 is not associated with NAFLD. Impact and Implications: Lipid droplet accumulation in hepatocytes is the distinctive characteristic of non-alcoholic fatty liver disease. Perilipin 2 (PLIN2) is the most abundant protein in hepatic lipid droplets; however, little is known on the role of a specific polymorphism PLIN2-Pro251 on hepatic lipid droplet metabolism. PLIN2-Pro251 attenuates liver triglycerides accumulation after a high-fat-high-glucose-diet. PLIN2-Pro251 may be a novel lipid droplet protein target for the treatment of liver steatosis.

DETECT: Feature extraction method for disease trajectory modeling in electronic health records.

Modeling with longitudinal electronic health record (EHR) data proves challenging given the high dimensionality, redundancy, and noise captured in EHR. In order to improve precision medicine strategies and identify predictors of disease risk in advance, evaluating meaningful patient disease trajectories is essential. In this study, we develop the algorithm DiseasE Trajectory fEature extraCTion (DETECT) for feature extraction and trajectory generation in high-throughput temporal EHR data. This algorithm can 1) simulate longitudinal individual-level EHR data, specified to user parameters of scale, complexity, and noise and 2) use a convergent relative risk framework to test intermediate codes occurring between specified index code(s) and outcome code(s) to determine if they are predictive features of the outcome. Temporal range can be specified to investigate predictors occurring during a specific period of time prior to onset of the outcome. We benchmarked our method on simulated data and generated real-world disease trajectories using DETECT in a cohort of 145,575 individuals diagnosed with hypertension in Penn Medicine EHR for severe cardiometabolic outcomes.

Incremental prognostic value of visually estimated coronary artery calcium in patients undergoing positron emission tomography imaging.

OBJECTIVE: Visually estimated coronary artery calcium (VECAC) from chest CT or attenuation correction (AC)/CT obtained during positron emission tomography (PET)-myocardial perfusion imaging (MPI) is feasible. Our aim was to determine the prognostic value of VECAC beyond conventional risk factors and PET imaging parameters, including coronary flow reserve (CFR). METHODS: We analysed 608 patients without known coronary artery disease who underwent PET-MPI between 2012 and 2016 and had AC/CT and/or chest CT images. We used Cox regression to estimate the association of VECAC categories (≤10, 11-400, >400 Agatston units (AU)) with the primary outcome of all-cause death, acute coronary syndrome or stroke (mean follow-up 4.3±1.8 years). C-statistics assessed the relationship between PET parameters and VECAC with the primary outcome. RESULTS: Mean age was 58±11 years, 65% were women and 67% were black. VECAC ≤10, 11-400 and >400 AU was observed in 68%, 12% and 20% of subjects, respectively. Compared with VECAC ≤10, VECAC categories 11-400 (HR 2.25, 95% CI 1.24 to 4.08) and >400 AU (HR 3.05, 95% CI 1.87 to 4.98) were associated with the primary outcome after adjusting for traditional risk factors, MPI findings and CFR. Adding VECAC to a model that included PET-MPI, CFR and clinical risk factors improved the prognostic value for the primary outcomes (c-statistic 0.71 to 0.75 with VECAC, p=0.01). CONCLUSIONS: VECAC is a potent predictor of events beyond traditional risk factors and PET imaging markers, including CFR. These data further support the importance for routine VECAC implementation.

Advances in translational imaging of the microcirculation.

The past few decades have seen an explosion in the development and use of methods for imaging the human microcirculation during health and disease. The confluence of innovative imaging technologies, affordable computing power, and economies of scale have ushered in a new era of "translational" imaging that permit us to peer into blood vessels of various organs in the human body. These imaging techniques include near-infrared spectroscopy (NIRS), positron emission tomography (PET), and magnetic resonance imaging (MRI) that are sensitive to microvascular-derived signals, as well as computed tomography (CT), optical imaging, and ultrasound (US) imaging that are capable of directly acquiring images at, or close to microvascular spatial resolution. Collectively, these imaging modalities enable us to characterize the morphological and functional changes in a tissue's microcirculation that are known to accompany the initiation and progression of numerous pathologies. Although there have been significant advances for imaging the microcirculation in preclinical models, this review focuses on developments in the assessment of the microcirculation in patients with optical imaging, NIRS, PET, US, MRI, and CT, to name a few. The goal of this review is to serve as a springboard for exploring the burgeoning role of translational imaging technologies for interrogating the structural and functional status of the microcirculation in humans, and highlight the breadth of current clinical applications. Making the human microcirculation "visible" in vivo to clinicians and researchers alike will facilitate bench-to-bedside discoveries and enhance the diagnosis and management of disease.

Diagnostic accuracy of SPECT and PET myocardial perfusion imaging in patients with left bundle branch block or ventricular-paced rhythm.

BACKGROUND: The difference in diagnostic accuracy of coronary artery disease (CAD) between vasodilator SPECT and PET myocardial perfusion imaging (MPI) in patients with left bundle branch block (LBBB) or ventricular-paced rhythm (VPR) is unknown. METHODS: We identified patients with LBBB or VPR who underwent either vasodilator SPECT or PET MPI and subsequent coronary angiography. LBBB/VPR-related septal and anteroseptal defects were defined as perfusion defects involving those regions in the absence of obstructive CAD in the left anterior descending artery or left main coronary artery. RESULTS: Of the 55 patients who underwent coronary angiography, 38 (69%) underwent SPECT and 17 patients (31%) underwent PET. PET compared to SPECT demonstrated higher sensitivity (88% vs 60%), specificity (56% vs 14%), positive predictive value (64% vs 20%), negative predictive value (83% vs 50%), and overall superior diagnostic accuracy (AUC .72 (95% CI .50-.93) vs .37 (95% CI .20-.54), P = .01) to detect obstructive CAD. LBBB/VPR-related septal and anteroseptal defects were more common with SPECT compared to PET (septal: 72% vs 17%, P = .001; anteroseptal: 47% vs 8%, P = .02). CONCLUSIONS: PET has higher diagnostic accuracy when compared to SPECT for the detection of obstructive CAD in patients with LBBB or VPR.

Quantification of defect contrast in microSPECT imaging of a myocardial phantom.

Ischemic heart disease remains a significant public health concern, accentuating the importance of basic research and therapeutic studies of small animals in which myocardial changes can be reproducibly detected and quantified. Few or no studies have investigated the performance of microSPECT in quantifying myocardial lesions. We utilized three versions of a multi-compartment phantom containing two left ventricular myocardial compartments (one uniform and one with a transmural 'cold' defect), a ventricular blood pool, and a background compartment, where each version had a different myocardial wall thickness (0.75, 1.0 and 1.25 mm). Each compartment was imaged separately while acquiring list-mode data. The separate compartment data were manipulated into a single data set with a known defect contrast, blood-pool and background activity. Data were processed with background-free defect-contrast values of 0 (no defect), -0.25, -0.5, -0.75, and -1.0 (all defect), three ratios of blood-pool to myocardial activity, 0 (no blood pool activity), 0.1, and 0.2 (20% of the activity in the healthy myocardial compartment), and three ratios of uniform background 0 (no background activity), 0.1 and 0.2, relative to the healthy myocardial compartment. For each wall thickness, defect contrast, blood-pool, and background activity combination, 25 list-mode noise realizations were generated and reconstructed. Volumes of interest were drawn and used to determine mean contrast recovery coefficients (CRCs) over the noise ensembles. We developed a slope-analysis procedure to estimate a single CRC over all contrast levels, with resulting CRC values (for no blood-pool and no background) of 0.848, 0.946, and 0.834 for the 0.75, 1.0, and 1.25 mm wall thicknesses, respectively. We also determined and validated a reprocessing method to calculate an ideal CRC. This work demonstrates the quantitative abilities of microSPECT for myocardial-defect imaging utilizing CRC and establishes a framework for evaluating defect-imaging capabilities in other systems.

The role of resting myocardial blood flow and myocardial blood flow reserve as a predictor of major adverse cardiovascular outcomes.

Cardiac perfusion PET is increasingly used to assess ischemia and cardiovascular risk and can also provide quantitative myocardial blood flow (MBF) and flow reserve (MBFR) values. These have been shown to be prognostic biomarkers of adverse outcomes, yet MBF and MBFR quantification remains underutilized in clinical settings. We compare MBFR to traditional cardiovascular risk factors in a large and diverse clinical population (60% African-American, 35.3% Caucasian) to rank its relative contribution to cardiovascular outcomes. Major adverse cardiovascular events (MACE), including unstable angina, non-ST and ST-elevation myocardial infarction, stroke, and death, were assessed for consecutive patients who underwent rest-dipyridamole stress 82Rb PET cardiac imaging from 2012-2015 at the Hospital of the University of Pennsylvania (n = 1283, mean follow-up 2.3 years). Resting MBF (1.1 ± 0.4 ml/min/g) was associated with adverse cardiovascular outcomes. MBFR (2.1 ± 0.8) was independently and inversely associated with MACE. Furthermore, MBFR was more strongly associated with MACE than both traditional cardiovascular risk factors and the presence of perfusion defects in regression analysis. Decision tree analysis identified MBFR as superior to established cardiovascular risk factors in predicting outcomes. Incorporating resting MBF and MBFR in CAD assessment may improve clinical decision making.

Genomic profiling of human vascular cells identifies TWIST1 as a causal gene for common vascular diseases.

Genome-wide association studies have identified multiple novel genomic loci associated with vascular diseases. Many of these loci are common non-coding variants that affect the expression of disease-relevant genes within coronary vascular cells. To identify such genes on a genome-wide level, we performed deep transcriptomic analysis of genotyped primary human coronary artery smooth muscle cells (HCASMCs) and coronary endothelial cells (HCAECs) from the same subjects, including splicing Quantitative Trait Loci (sQTL), allele-specific expression (ASE), and colocalization analyses. We identified sQTLs for TARS2, YAP1, CFDP1, and STAT6 in HCASMCs and HCAECs, and 233 ASE genes, a subset of which are also GTEx eGenes in arterial tissues. Colocalization of GWAS association signals for coronary artery disease (CAD), migraine, stroke and abdominal aortic aneurysm with GTEx eGenes in aorta, coronary artery and tibial artery discovered novel candidate risk genes for these diseases. At the CAD and stroke locus tagged by rs2107595 we demonstrate colocalization with expression of the proximal gene TWIST1. We show that disrupting the rs2107595 locus alters TWIST1 expression and that the risk allele has increased binding of the NOTCH signaling protein RBPJ. Finally, we provide data that TWIST1 expression influences vascular SMC phenotypes, including proliferation and calcification, as a potential mechanism supporting a role for TWIST1 in CAD.

Association of the V122I Hereditary Transthyretin Amyloidosis Genetic Variant With Heart Failure Among Individuals of African or Hispanic/Latino Ancestry.

Importance: Hereditary transthyretin (TTR) amyloid cardiomyopathy (hATTR-CM) due to the TTR V122I variant is an autosomal-dominant disorder that causes heart failure in elderly individuals of African ancestry. The clinical associations of carrying the variant, its effect in other African ancestry populations including Hispanic/Latino individuals, and the rates of achieving a clinical diagnosis in carriers are unknown. Objective: To assess the association between the TTR V122I variant and heart failure and identify rates of hATTR-CM diagnosis among carriers with heart failure. Design, Setting, and Participants: Cross-sectional analysis of carriers and noncarriers of TTR V122I of African ancestry aged 50 years or older enrolled in the Penn Medicine Biobank between 2008 and 2017 using electronic health record data from 1996 to 2017. Case-control study in participants of African and Hispanic/Latino ancestry with and without heart failure in the Mount Sinai BioMe Biobank enrolled between 2007 and 2015 using electronic health record data from 2007 to 2018. Exposures: TTR V122I carrier status. Main Outcomes and Measures: The primary outcome was prevalent heart failure. The rate of diagnosis with hATTR-CM among TTR V122I carriers with heart failure was measured. Results: The cross-sectional cohort included 3724 individuals of African ancestry with a median age of 64 years (interquartile range, 57-71); 1755 (47%) were male, 2896 (78%) had a diagnosis of hypertension, and 753 (20%) had a history of myocardial infarction or coronary revascularization. There were 116 TTR V122I carriers (3.1%); 1121 participants (30%) had heart failure. The case-control study consisted of 2307 individuals of African ancestry and 3663 Hispanic/Latino individuals; the median age was 73 years (interquartile range, 68-80), 2271 (38%) were male, 4709 (79%) had a diagnosis of hypertension, and 1008 (17%) had a history of myocardial infarction or coronary revascularization. There were 1376 cases of heart failure. TTR V122I was associated with higher rates of heart failure (cross-sectional cohort: n = 51/116 TTR V122I carriers [44%], n = 1070/3608 noncarriers [30%], adjusted odds ratio, 1.7 [95% CI, 1.2-2.4], P = .006; case-control study: n = 36/1376 heart failure cases [2.6%], n = 82/4594 controls [1.8%], adjusted odds ratio, 1.8 [95% CI, 1.2-2.7], P = .008). Ten of 92 TTR V122I carriers with heart failure (11%) were diagnosed as having hATTR-CM; the median time from onset of symptoms to clinical diagnosis was 3 years. Conclusions and Relevance: Among individuals of African or Hispanic/Latino ancestry enrolled in 2 academic medical center-based biobanks, the TTR V122I genetic variant was significantly associated with heart failure.

Quantification of myocardial uptake rate constants in dynamic small-animal SPECT using a cardiac phantom.

Myocardial blood flow and myocardial blood flow reserve (MBFR) measurements are often used clinically to quantify coronary microvascular function. Developing imaging-based methods to measure MBFR for research in mice would be advantageous for evaluating new treatment methods for coronary microvascular disease (CMVD), yet this is more challenging in mice than in humans. This work investigates microSPECT's quantitative capabilities of cardiac imaging by utilizing a multi-part cardiac phantom and applying a known kinetic model to synthesize kinetic data from static data, allowing for assessment of kinetic modeling accuracy. The phantom was designed with four main components: two left-ventricular (LV) myocardial sections and two LV blood-pool sections, sized for end-systole (ES) and end-diastole (ED). Each section of the phantom was imaged separately while acquiring list-mode data. These static, separate-compartment data were manipulated into synthetic dynamic data using a kinetic model representing the myocardium and blood-pool activity concentrations over time and then combined into a set of dynamic image frames and reconstructed. Regions of interest were drawn on the resulting images, and kinetic parameters were estimated. This process was performed for three tracer uptake values (K 1), three myocardial wall thicknesses, ten filter parameters, and 20 iterations for 25 noise ensembles. The degree of filtering and iteration number were optimized to minimize the root mean-squared error (RMSE) of K 1 values, with the largest number of iterations and minimal filtering yielding the lowest error. Using the optimized parameters, K 1 was determined with reasonable error (~3% RMSE) over all wall thicknesses and K 1 input values. This work demonstrates that accurate and precise measurements of K 1 are possible for the U-SPECT+ system used in this study, for several different uptake rates and LV dimensions. Additionally, it allows for future investigation utilizing other imaging systems, including PET studies with any radiotracer, as well as with additional phantom parts containing lesions.

Genomic Risk Stratification Predicts All-Cause Mortality After Cardiac Catheterization.

BACKGROUND: Coronary artery disease (CAD) is influenced by genetic variation and traditional risk factors. Polygenic risk scores (PRS), which can be ascertained before the development of traditional risk factors, have been shown to identify individuals at elevated risk of CAD. Here, we demonstrate that a genome-wide PRS for CAD predicts all-cause mortality after accounting for not only traditional cardiovascular risk factors but also angiographic CAD itself. METHODS: Individuals who underwent coronary angiography and were enrolled in an institutional biobank were included; those with prior myocardial infarction or heart transplant were excluded. Using a pruning-and-thresholding approach, a genome-wide PRS comprised of 139 239 variants was calculated for 1503 participants who underwent coronary angiography and genotyping. Individuals were categorized into high PRS (hiPRS) and low-PRS control groups using the maximally selected rank statistic. Stratified analysis based on angiographic findings was also performed. The primary outcome was all-cause mortality following the index coronary angiogram. RESULTS: Individuals with hiPRS were younger than controls (66 years versus 69 years; P=2.1×10-5) but did not differ by sex, body mass index, or traditional risk-factor profiles. Individuals with hiPRS were at significantly increased risk of all-cause mortality after cardiac catheterization, adjusting for traditional risk factors and angiographic extent of CAD (hazard ratio, 1.6; 95% CI, 1.2-2.2; P=0.004). The strongest increase in risk of all-cause mortality conferred by hiPRS was seen among individuals without angiographic CAD (hazard ratio, 2.4; 95% CI, 1.1-5.5; P=0.04). In the overall cohort, adding hiPRS to traditional risk assessment improved prediction of 5-year all-cause mortality (area under the receiver-operating curve 0.70; 95% CI, 0.66-0.75 versus 0.66; 95% CI, 0.61-0.70; P=0.001). CONCLUSIONS: A genome-wide PRS improves risk stratification when added to traditional risk factors and coronary angiography. Individuals without angiographic CAD but with hiPRS remain at significantly elevated risk of mortality.

Text mining applied to electronic cardiovascular procedure reports to identify patients with trileaflet aortic stenosis and coronary artery disease.

BACKGROUND: Interrogation of the electronic health record (EHR) using billing codes as a surrogate for diagnoses of interest has been widely used for clinical research. However, the accuracy of this methodology is variable, as it reflects billing codes rather than severity of disease, and depends on the disease and the accuracy of the coding practitioner. Systematic application of text mining to the EHR has had variable success for the detection of cardiovascular phenotypes. We hypothesize that the application of text mining algorithms to cardiovascular procedure reports may be a superior method to identify patients with cardiovascular conditions of interest. METHODS: We adapted the Oracle product Endeca, which utilizes text mining to identify terms of interest from a NoSQL-like database, for purposes of searching cardiovascular procedure reports and termed the tool "PennSeek". We imported 282,569 echocardiography reports representing 81,164 individuals and 27,205 cardiac catheterization reports representing 14,567 individuals from non-searchable databases into PennSeek. We then applied clinical criteria to these reports in PennSeek to identify patients with trileaflet aortic stenosis (TAS) and coronary artery disease (CAD). Accuracy of patient identification by text mining through PennSeek was compared with ICD-9 billing codes. RESULTS: Text mining identified 7115 patients with TAS and 9247 patients with CAD. ICD-9 codes identified 8272 patients with TAS and 6913 patients with CAD. 4346 patients with AS and 6024 patients with CAD were identified by both approaches. A randomly selected sample of 200-250 patients uniquely identified by text mining was compared with 200-250 patients uniquely identified by billing codes for both diseases. We demonstrate that text mining was superior, with a positive predictive value (PPV) of 0.95 compared to 0.53 by ICD-9 for TAS, and a PPV of 0.97 compared to 0.86 for CAD. CONCLUSION: These results highlight the superiority of text mining algorithms applied to electronic cardiovascular procedure reports in the identification of phenotypes of interest for cardiovascular research.

Biomarkers of Calcific Aortic Valve Disease.

Calcific aortic valve disease (CAVD) is a highly prevalent cardiovascular disorder accounting for a rising economic and social burden on aging populations. In spite of continuing study on the pathophysiology of disease, there remain no medical therapies to prevent the progression of CAVD. The discovery of biomarkers represents a potentially complementary approach in stratifying risk and timing of intervention in CAVD and has the advantage of providing insight into causal factors for the disease. Biomarkers have been studied extensively in atherosclerotic cardiovascular disease, with success as additive for clinical and scientific purposes. Similar research in CAVD is less robust; however, the available studies of biomarkers in CAVD show promise for enhanced clinical decision making and identification of causal factors for the disease. This comprehensive review summarizes available established and novel biomarkers in CAVD, their contributions toward an understanding of pathophysiology, their potential clinical utility, and provides an outline to direct future research in the field.