Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery

The electrocardiogram or ECG has been in use for over 100 years and remains the most widely performed diagnostic test to characterize cardiac structure and electrical activity. We hypothesized that parallel advances in computing power, innovations in machine learning algorithms, and availability of large-scale digitized ECG data would enable extending the utility of the ECG beyond its current limitations, while at the same time preserving interpretability, which is fundamental to medical decision-making. We identified 36,186 ECGs from the UCSF database that were 1) in normal sinus rhythm and 2) would enable training of specific models for estimation of cardiac structure or function or detection of disease. We derived a novel model for ECG segmentation using convolutional neural networks (CNN) and Hidden Markov Models (HMM) and evaluated its output by comparing electrical interval estimates to 141,864 measurements from the clinical workflow. We built a 725-element patient-level ECG profile using downsampled segmentation data and trained machine learning models to estimate left ventricular mass, left atrial volume, mitral annulus e' and to detect and track four diseases: pulmonary arterial hypertension (PAH), hypertrophic cardiomyopathy (HCM), cardiac amyloid (CA), and mitral valve prolapse (MVP). CNN-HMM derived ECG segmentation agreed with clinical estimates, with median absolute deviations (MAD) as a fraction of observed value of 0.6% for heart rate and 4% for QT interval. Patient-level ECG profiles enabled quantitative estimates of left ventricular and mitral annulus e' velocity with good discrimination in binary classification models of left ventricular hypertrophy and diastolic function. Models for disease detection ranged from AUROC of 0.94 to 0.77 for MVP. Top-ranked variables for all models included known ECG characteristics along with novel predictors of these traits/diseases.Comment: 13 pages, 6 figures, 1 Table + Supplemen

Westward propagating twin gyres in the equatorial Indian Ocean

A reduced-gravity (11/2-layer) model forced by daily climatological winds simulates twin, anticyclonic gyres, which propagate westward on either side of the equator. The gyres form at the beginning of both the Southwest Monsoon and the Northeast monsoon in the equatorial eastern Indian Ocean, and subsequently propagate across the basin. Their existence is supported by velocity observations taken during WOCE in 1995 and by TOPEX/Poseidon sea-level observations during 1993. They are also present in the ECCO model/data product. They form at the front of a Rossby-wave packet generated by the reflection of the equatorial jet (EJ) from the eastern boundary of the basin. They are likely either Rossby solitons or result from the nonlinear interaction between the EJ and the Rossby-wave front

Recognition of Polyadenylate RNA by the Poly(A)-Binding Protein

AbstractThe cocrystal structure of human poly(A)-binding protein (PABP) has been determined at 2.6 Å resolution. PABP recognizes the 3′ mRNA poly(A) tail and plays critical roles in eukaryotic translation initiation and mRNA stabilization/degradation. The minimal PABP used in this study consists of the N-terminal two RRM-type RNA-binding domains connected by a short linker (RRM1/2). These two RRMs form a continuous RNA-binding trough, lined by an antiparallel β sheet backed by four α helices. The polyadenylate RNA adopts an extended conformation running the length of the molecular trough. Adenine recognition is primarily mediated by contacts with conserved residues found in the RNP motifs of the two RRMs. The convex dorsum of RRM1/2 displays a phylogenetically conserved hydrophobic/acidic portion, which may interact with translation initiation factors and regulatory proteins

Phase transformation, Mechanical Properties and Corrosion Behavior of 304L Austenitic Stainless Steel Rolled at Room and Cryo Temperatures

The present work investigates the effect of rolling (90% thickness reduction) on phase transformation, mechanical properties, and corrosion behaviour of 304L-austenitic stainless steel through cryorolling and room temperature rolling. The processed steel sheets were characterised through X-ray diffraction (XRD), electron backscattered diffraction (EBSD), and vibrating sample magnetometer (VSM). The analysis of XRD patterns, EBSD scan, and vibrating sample magnetometer results confirmed the transformation of the austenitic phase to the martensitic phase during rolling. Cryorolling resulted in improved tensile strength and microhardness of 1808 MPa and 538 VHN, respectively, as compared to 1566 MPa and 504 VHN for room temperature rolling. The enhancement in properties of cryorolled steel is attributed to its higher dislocation density compared to room temperature rolled steel. The corrosion behaviour was assessed via linear polarisation corrosion tests. Corrosion resistance was found to decrease with increasing rolling reduction in both room temperature rolled and cryorolled specimens

Adipocyte JAK2 Regulates Hepatic Insulin Sensitivity Independently of Body Composition, Liver Lipid Content, and Hepatic Insulin Signaling.

Disruption of hepatocyte growth hormone (GH) signaling through disruption of Jak2 (JAK2L) leads to fatty liver. Previously, we demonstrated that development of fatty liver depends on adipocyte GH signaling. We sought to determine the individual roles of hepatocyte and adipocyte Jak2 on whole-body and tissue insulin sensitivity and liver metabolism. On chow, JAK2L mice had hepatic steatosis and severe whole-body and hepatic insulin resistance. However, concomitant deletion of Jak2 in hepatocytes and adipocytes (JAK2LA) completely normalized insulin sensitivity while reducing liver lipid content. On high-fat diet, JAK2L mice had hepatic steatosis and insulin resistance despite protection from diet-induced obesity. JAK2LA mice had higher liver lipid content and no protection from obesity but retained exquisite hepatic insulin sensitivity. AKT activity was selectively attenuated in JAK2L adipose tissue, whereas hepatic insulin signaling remained intact despite profound hepatic insulin resistance. Therefore, JAK2 in adipose tissue is epistatic to liver with regard to insulin sensitivity and responsiveness, despite fatty liver and obesity. However, hepatocyte autonomous JAK2 signaling regulates liver lipid deposition under conditions of excess dietary fat. This work demonstrates how various tissues integrate JAK2 signals to regulate insulin/glucose and lipid metabolism

Pattern Specification and Immune Response Transcriptional Signatures of Pericardial and Subcutaneous Adipose Tissue

Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality in the United States. Recent studies suggest that pericardial adipose tissue (PCAT) secretes inflammatory factors that contribute to the development of CVD. To better characterize the role of PCAT in the pathogenesis of disease, we performed a large-scale unbiased analysis of the transcriptional differences between PCAT and subcutaneous adipose tissue, analysing 53 microarrays across 19 individuals. As it was unknown whether PCAT-secreted factors are produced by adipocytes or cells in the supporting stromal fraction, we also sought to identify differentially expressed genes in isolated pericardial adipocytes vs. isolated subcutaneous adipocytes. Using microarray analysis, we found that: 1) pericardial adipose tissue and isolated pericardial adipocytes both overexpress atherosclerosis-promoting chemokines and 2) pericardial and subcutaneous fat depots, as well as isolated pericardial adipocytes and subcutaneous adipocytes, express specific patterns of homeobox genes. In contrast, a core set of lipid processing genes showed no significant overlap with differentially expressed transcripts. These depot-specific homeobox signatures and transcriptional profiles strongly suggest different functional roles for the pericardial and subcutaneous adipose depots. Further characterization of these inter-depot differences should be a research priority

A High-Density Admixture Scan in 1,670 African Americans with Hypertension

Hypertension (HTN) is a devastating disease with a higher incidence in African Americans than European Americans, inspiring searches for genetic variants that contribute to this difference. We report the results of a large-scale admixture scan for genes contributing HTN risk, in which we screened 1,670 African Americans with HTN and 387 control individuals for regions of the genome with elevated proportion of African or European ancestry. No loci were identified that were significantly associated with HTN. We also searched for evidence of an admixture signal at 40 candidate genes and eight previously reported linkage peaks, but none appears to contribute substantially to the differential HTN risk between African and European Americans. Finally, we observed nominal association at one of the loci detected in the admixture scan of Zhu et al. 2005 (p = 0.016 at 6q24.3 correcting for four hypotheses tested), although we caution that the significance is marginal and the estimated odds ratio of 1.19 per African allele is less than what would be expected from the original report; thus, further work is needed to follow up this locus

Single-Nucleotide Polymorphisms in LPA Explain Most of the Ancestry-Specific Variation in Lp(a) Levels in African Americans

Lipoprotein(a) (Lp(a)) is an important causal cardiovascular risk factor, with serum Lp(a) levels predicting atherosclerotic heart disease and genetic determinants of Lp(a) levels showing association with myocardial infarction. Lp(a) levels vary widely between populations, with African-derived populations having nearly 2-fold higher Lp(a) levels than European Americans. We investigated the genetic basis of this difference in 4464 African Americans from the Jackson Heart Study (JHS) using a panel of up to 1447 ancestry informative markers, allowing us to accurately estimate the African ancestry proportion of each individual at each position in the genome. In an unbiased genome-wide admixture scan for frequency-differentiated genetic determinants of Lp(a) level, we found a convincing peak (LOD = 13.6) at 6q25.3, which spans the LPA locus. Dense fine-mapping of the LPA locus identified a number of strongly associated, common biallelic SNPs, a subset of which can account for up to 7% of the variation in Lp(a) level, as well as >70% of the African-European population differences in Lp(a) level. We replicated the association of the most strongly associated SNP, rs9457951 (p = 6×10−22, 27% change in Lp(a) per allele, ∼5% of Lp(a) variance explained in JHS), in 1,726 African Americans from the Dallas Heart Study and found an even stronger association after adjustment for the kringle(IV) repeat copy number. Despite the strong association with Lp(a) levels, we find no association of any LPA SNP with incident coronary heart disease in 3,225 African Americans from the Atherosclerosis Risk in Communities Study

Prioritizing causal disease genes using unbiased genomic features

Background: Cardiovascular disease (CVD) is the leading cause of death in the developed world. Human genetic studies, including genome-wide sequencing and SNP-array approaches, promise to reveal disease genes and mechanisms representing new therapeutic targets. In practice, however, identification of the actual genes contributing to disease pathogenesis has lagged behind identification of associated loci, thus limiting the clinical benefits. Results: To aid in localizing causal genes, we develop a machine learning approach, Objective Prioritization for Enhanced Novelty (OPEN), which quantitatively prioritizes gene-disease associations based on a diverse group of genomic features. This approach uses only unbiased predictive features and thus is not hampered by a preference towards previously well-characterized genes. We demonstrate success in identifying genetic determinants for CVD-related traits, including cholesterol levels, blood pressure, and conduction system and cardiomyopathy phenotypes. Using OPEN, we prioritize genes, including FLNC, for association with increased left ventricular diameter, which is a defining feature of a prevalent cardiovascular disorder, dilated cardiomyopathy or DCM. Using a zebrafish model, we experimentally validate FLNC and identify a novel FLNC splice-site mutation in a patient with severe DCM. Conclusion: Our approach stands to assist interpretation of large-scale genetic studies without compromising their fundamentally unbiased nature. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0534-8) contains supplementary material, which is available to authorized users

Comprehensive mutations analyses of FTO (fat mass and obesity-associated gene) and their effects on FTO’s substrate binding implicated in obesity

An excessive amount of fat deposition in the body leads to obesity which is a complex disease and poses a generic threat to human health. It increases the risk of various other diseases like diabetes, cardiovascular disease, and multiple types of cancer. Genomic studies have shown that the expression of the fat mass obesity (FTO) gene was highly altered and identified as one of the key biomarkers for obesity. This study has been undertaken to investigate the mutational profile of the FTO gene and elucidates its effect on the protein structure and function. Harmful effects of various missense mutations were predicted using different independent tools and it was observed that all mutations were highly pathogenic. Molecular dynamics (MD) simulations were performed to study the structure and function of FTO protein upon different mutations and it was found that mutations decreased the structure stability and affected protein conformation. Furthermore, a protein residue network analysis suggested that the mutations affected the overall residues bonding and topology. Finally, molecular docking coupled with MD simulation suggested that mutations affected FTO substrate binding by changing the protein-ligand affinity. Hence, the results of this finding would help in an in-depth understanding of the molecular biology of the FTO gene and its variants and lead to the development of effective therapeutics against associated diseases and disorders