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Kitzmiller, J. A.

Publications and source records attributed to Kitzmiller, J. A..

3 recordsLinked to original sources

Role of Forkhead box F1 in the Pathobiology of Pulmonary Arterial Hypertension

RationaleApproximately 80% of patients with non-familial pulmonary arterial hypertension (PAH) lack identifiable pathogenic genetic variants. While most genetic studies of PAH have focused on predicted loss-of-function variants, recent approaches have identified ultra-rare missense variants associated with the disease. FOXF1 encodes a highly conserved transcription factor, essential for angiogenesis and vasculogenesis in human and mouse lungs. ObjectivesWe identified a rare FOXF1 missense coding variant in two unrelated probands with PAH. FOXF1 is an evolutionarily conserved transcription factor required for lung vascular development and vascular integrity. Our aims were to determine the frequency of FOXF1 variants in larger PAH cohorts compared to the general population, study FOXF1 expression in explanted lung tissue from PAH patients versus control (failed-donor) lungs, and define potential downstream targets linked to PAH development. MethodsThree independent, international, multicenter cohorts were analyzed to evaluate the frequency of FOXF1 rare variants. Various composite prediction models assessed the deleteriousness of individual variants. Bulk RNA sequencing datasets from human explanted lung tissues were compared to failed-donor controls to determine FOXF1 expression. Bioinformatic tools identified putative FOXF1 binding targets, which were orthogonally validated using mouse ChIP-seq datasets. Measurements and Main ResultsSeven novel or ultra-rare missense coding variants were identified across three patient cohorts in different regions of the FOXF1 gene, including the DNA binding domain. FOXF1 expression was dysregulated in PAH lungs, correlating with disease severity. Histological analysis showed heterogeneous FOXF1 expression, with the lowest levels in phenotypically abnormal endothelial cells within complex vascular lesions in PAH samples. A hybrid bioinformatic approach identified FOXF1 downstream targets potentially involved in PAH pathogenesis, including BMPR2. ConclusionsLarge genomic and transcriptomic datasets suggest that decreased FOXF1 expression or predicted dysfunction is associated with PAH.

genomics↗

Guided construction of single cell reference for human and mouse lung

Accurate cell type identification is a key and rate-limiting step in single cell data analysis. Single cell references with comprehensive cell types, reproducible and functional validated cell identities, and common nomenclatures are much needed by the research community to optimize automated cell type annotation and facilitate data integration, sharing, and collaboration. In the present study, we developed a novel computational pipeline to utilize the LungMAP CellCards as a dictionary to consolidate single-cell transcriptomic datasets of 104 human lungs and 17 mouse lung samples and constructed "LungMAP CellRef" and "LungMAP CellRef Seed" for both normal human and mouse lungs. "CellRef Seed" has an equivalent prediction power and produces consistent cell annotation as does "CellRef" but improves computational efficiency and simplifies its utilization for fast automated cell type annotation and online visualization. This atlas set incorporates 48 human and 40 mouse well-defined lung cell types catalogued from diverse anatomic locations and developmental time points. Using independent datasets, we demonstrated the utility of our CellRefs for automated cell type annotation analysis of both normal and disease lungs. User-friendly web interfaces were developed to support easy access and maximal utilization of the LungMAP CellRefs. LungMAP CellRefs are freely available to the pulmonary research community through fast interactive web interfaces to facilitate hypothesis generation, research discovery, and identification of cell type alterations in disease conditions.

bioinformatics↗

LungMAP Portal Ecosystem: Systems-Level Exploration of the Lung

An improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular, imaging and pathological datasets. To centralize and standardize information across broad lung research efforts we expanded the LungMAP.net website into a gateway portal. This portal connects a broad-spectrum of research networks, bulk and single-cell multi-omics data and a diverse collection of image data that span mammalian lung development and disease. The data are standardized across species and technologies using harmonized data and metadata models that leverage recent advances including those from the Human Cell Atlas, diverse ontologies, and the LungMAP CellCards initiative. To cultivate future discoveries, we have aggregated a diverse collection of single-cell atlases for multiple species (human, rhesus, mouse), to enable consistent queries across technologies, cohorts, age, disease and drug treatment. These atlases are provided as independent and integrated queriable datasets, with an emphasis on dynamic visualization, figure generation and reference-based classification of user-provided datasets (Azimuth). As this resource grows, we intend to increase the breadth of available interactive interfaces, data portals and datasets from LungMAP and external research efforts.

systems biology↗