Markov Chain Ontology Analysis (MCOA)

<p>Abstract</p> <p>Background</p> <p>Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research. Of particular relevance are methods, such as enrichment analysis, that quantify the importance of ontology classes relative to a collection of domain data. Current analytical techniques, however, remain limited in their ability to handle many important types of structural complexity encountered in real biological systems including class overlaps, continuously valued data, inter-instance relationships, non-hierarchical relationships between classes, semantic distance and sparse data.</p> <p>Results</p> <p>In this paper, we describe a methodology called Markov Chain Ontology Analysis (MCOA) and illustrate its use through a MCOA-based enrichment analysis application based on a generative model of gene activation. MCOA models the classes in an ontology, the instances from an associated dataset and all directional inter-class, class-to-instance and inter-instance relationships as a single finite ergodic Markov chain. The adjusted transition probability matrix for this Markov chain enables the calculation of eigenvector values that quantify the importance of each ontology class relative to other classes and the associated data set members. On both controlled Gene Ontology (GO) data sets created with Escherichia coli, Drosophila melanogaster and Homo sapiens annotations and real gene expression data extracted from the Gene Expression Omnibus (GEO), the MCOA enrichment analysis approach provides the best performance of comparable state-of-the-art methods.</p> <p>Conclusion</p> <p>A methodology based on Markov chain models and network analytic metrics can help detect the relevant signal within large, highly interdependent and noisy data sets and, for applications such as enrichment analysis, has been shown to generate superior performance on both real and simulated data relative to existing state-of-the-art approaches.</p

The American Heart Association 2030 Impact Goal: A Presidential Advisory From the American Heart Association

Each decade, the American Heart Association (AHA) develops an Impact Goal to guide its overall strategic direction and investments in its research, quality improvement, advocacy, and public health programs. Guided by the AHA’s new Mission Statement, to be a relentless force for a world of longer, healthier lives, the 2030 Impact Goal is anchored in an understanding that to achieve cardiovascular health for all, the AHA must include a broader vision of health and well-being and emphasize health equity. In the next decade, by 2030, the AHA will strive to equitably increase healthy life expectancy beyond current projections, with global and local collaborators, from 66 years of age to at least 68 years of age across the United States and from 64 years of age to at least 67 years of age worldwide. The AHA commits to developing additional targets for equity and well-being to accompany this overarching Impact Goal. To attain the 2030 Impact Goal, we recommend a thoughtful evaluation of interventions available to the public, patients, providers, healthcare delivery systems, communities, policy makers, and legislators. This presidential advisory summarizes the task force’s main considerations in determining the 2030 Impact Goal and the metrics to monitor progress. It describes the aspiration that these goals will be achieved by working with a diverse community of volunteers, patients, scientists, healthcare professionals, and partner organizations needed to ensure success

Effect of Genetic Diagnosis on Patients with Previously Undiagnosed Disease

BackgroundMany patients remain without a diagnosis despite extensive medical evaluation. The Undiagnosed Diseases Network (UDN) was established to apply a multidisciplinary model in the evaluation of the most challenging cases and to identify the biologic characteristics of newly discovered diseases. The UDN, which is funded by the National Institutes of Health, was formed in 2014 as a network of seven clinical sites, two sequencing cores, and a coordinating center. Later, a central biorepository, a metabolomics core, and a model organisms screening center were added.MethodsWe evaluated patients who were referred to the UDN over a period of 20 months. The patients were required to have an undiagnosed condition despite thorough evaluation by a health care provider. We determined the rate of diagnosis among patients who subsequently had a complete evaluation, and we observed the effect of diagnosis on medical care.ResultsA total of 1519 patients (53% female) were referred to the UDN, of whom 601 (40%) were accepted for evaluation. Of the accepted patients, 192 (32%) had previously undergone exome sequencing. Symptoms were neurologic in 40% of the applicants, musculoskeletal in 10%, immunologic in 7%, gastrointestinal in 7%, and rheumatologic in 6%. Of the 382 patients who had a complete evaluation, 132 received a diagnosis, yielding a rate of diagnosis of 35%. A total of 15 diagnoses (11%) were made by clinical review alone, and 98 (74%) were made by exome or genome sequencing. Of the diagnoses, 21% led to recommendations regarding changes in therapy, 37% led to changes in diagnostic testing, and 36% led to variant-specific genetic counseling. We defined 31 new syndromes.ConclusionsThe UDN established a diagnosis in 132 of the 382 patients who had a complete evaluation, yielding a rate of diagnosis of 35%. (Funded by the National Institutes of Health Common Fund.)

Spectrum of neurodevelopmental disease associated with the GNAO1 guanosine triphosphate-binding region

Objective To characterize the phenotypic spectrum associated with GNAO1 variants and establish genotype-protein structure-phenotype relationships. Methods We evaluated the phenotypes of 14 patients with GNAO1 variants, analyzed their variants for potential pathogenicity, and mapped them, along with those in the literature, on a three-dimensional structural protein model. Results The 14 patients in our cohort, including one sibling pair, had 13 distinct, heterozygous GNAO1 variants classified as pathogenic or likely pathogenic. We attributed the same variant in two siblings to parental mosaicism. Patients initially presented with seizures beginning in the first 3 months of life (8/14), developmental delay (4/14), hypotonia (1/14), or movement disorder (1/14). All patients had hypotonia and developmental delay ranging from mild to severe. Nine had epilepsy, and nine had movement disorders, including dystonia, ataxia, chorea, and dyskinesia. The 13 GNAO1 variants in our patients are predicted to result in amino acid substitutions or deletions in the GNAO1 guanosine triphosphate (GTP)-binding region, analogous to those in previous publications. Patients with variants affecting amino acids 207-221 had only movement disorder and hypotonia. Patients with variants affecting the C-terminal region had the mildest phenotypes.

Spectrum of neurodevelopmental disease associated with the GNAO1 guanosine triphosphate-binding region

OBJECTIVE: To characterize the phenotypic spectrum associated with GNAO1 variants and establish genotype-protein structure-phenotype relationships. METHODS: We evaluated the phenotypes of 14 patients with GNAO1 variants, analyzed their variants for potential pathogenicity, and mapped them, along with those in the literature, on a three-dimensional structural protein model. RESULTS: The 14 patients in our cohort, including one sibling pair, had 13 distinct, heterozygous GNAO1 variants classified as pathogenic or likely pathogenic. We attributed the same variant in two siblings to parental mosaicism. Patients initially presented with seizures beginning in the first 3 months of life (8/14), developmental delay (4/14), hypotonia (1/14), or movement disorder (1/14). All patients had hypotonia and developmental delay ranging from mild to severe. Nine had epilepsy, and nine had movement disorders, including dystonia, ataxia, chorea, and dyskinesia. The 13 GNAO1 variants in our patients are predicted to result in amino acid substitutions or deletions in the GNAO1 guanosine triphosphate (GTP)-binding region, analogous to those in previous publications. Patients with variants affecting amino acids 207-221 had only movement disorder and hypotonia. Patients with variants affecting the C-terminal region had the mildest phenotypes. SIGNIFICANCE: GNAO1 encephalopathy most frequently presents with seizures beginning in the first 3 months of life. Concurrent movement disorders are also a prominent feature in the spectrum of GNAO1 encephalopathy. All variants affected the GTP-binding domain of GNAO1, highlighting the importance of this region for G-protein signaling and neurodevelopment.status: publishe