Virus-Induced Acute Respiratory Distress Syndrome Causes Cardiomyopathy Through Eliciting Inflammatory Responses in the Heart.

BACKGROUND: Viral infections can cause acute respiratory distress syndrome (ARDS), systemic inflammation, and secondary cardiovascular complications. Lung macrophage subsets change during ARDS, but the role of heart macrophages in cardiac injury during viral ARDS remains unknown. Here we investigate how immune signals typical for viral ARDS affect cardiac macrophage subsets, cardiovascular health, and systemic inflammation. METHODS: We assessed cardiac macrophage subsets using immunofluorescence histology of autopsy specimens from 21 patients with COVID-19 with SARS-CoV-2-associated ARDS and 33 patients who died from other causes. In mice, we compared cardiac immune cell dynamics after SARS-CoV-2 infection with ARDS induced by intratracheal instillation of Toll-like receptor ligands and an ACE2 (angiotensin-converting enzyme 2) inhibitor. RESULTS: In humans, SARS-CoV-2 increased total cardiac macrophage counts and led to a higher proportion of CCR2+ (C-C chemokine receptor type 2 positive) macrophages. In mice, SARS-CoV-2 and virus-free lung injury triggered profound remodeling of cardiac resident macrophages, recapitulating the clinical expansion of CCR2+ macrophages. Treating mice exposed to virus-like ARDS with a tumor necrosis factor α-neutralizing antibody reduced cardiac monocytes and inflammatory MHCIIlo CCR2+ macrophages while also preserving cardiac function. Virus-like ARDS elevated mortality in mice with pre-existing heart failure. CONCLUSIONS: Our data suggest that viral ARDS promotes cardiac inflammation by expanding the CCR2+ macrophage subset, and the associated cardiac phenotypes in mice can be elicited by activating the host immune system even without viral presence in the heart.

Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models.

This work puts forth and demonstrates the utility of a reporting framework for collecting and evaluating annotations of medical images used for training and testing artificial intelligence (AI) models in assisting detection and diagnosis. AI has unique reporting requirements, as shown by the AI extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklists and the proposed AI extensions to the Standards for Reporting Diagnostic Accuracy (STARD) and Transparent Reporting of a Multivariable Prediction model for Individual Prognosis or Diagnosis (TRIPOD) checklists. AI for detection and/or diagnostic image analysis requires complete, reproducible, and transparent reporting of the annotations and metadata used in training and testing data sets. In an earlier work by other researchers, an annotation workflow and quality checklist for computational pathology annotations were proposed. In this manuscript, we operationalize this workflow into an evaluable quality checklist that applies to any reader-interpreted medical images, and we demonstrate its use for an annotation effort in digital pathology. We refer to this quality framework as the Collection and Evaluation of Annotations for Reproducible Reporting of Artificial Intelligence (CLEARR-AI).

Recruited macrophages elicit atrial fibrillation.

Atrial fibrillation disrupts contraction of the atria, leading to stroke and heart failure. We deciphered how immune and stromal cells contribute to atrial fibrillation. Single-cell transcriptomes from human atria documented inflammatory monocyte and SPP1+ macrophage expansion in atrial fibrillation. Combining hypertension, obesity, and mitral valve regurgitation (HOMER) in mice elicited enlarged, fibrosed, and fibrillation-prone atria. Single-cell transcriptomes from HOMER mouse atria recapitulated cell composition and transcriptome changes observed in patients. Inhibiting monocyte migration reduced arrhythmia in Ccr2-∕- HOMER mice. Cell-cell interaction analysis identified SPP1 as a pleiotropic signal that promotes atrial fibrillation through cross-talk with local immune and stromal cells. Deleting Spp1 reduced atrial fibrillation in HOMER mice. These results identify SPP1+ macrophages as targets for immunotherapy in atrial fibrillation.

Harmonized cross-species cell atlases of trigeminal and dorsal root ganglia.

Peripheral sensory neurons in the dorsal root ganglion (DRG) and trigeminal ganglion (TG) are specialized to detect and transduce diverse environmental stimuli including touch, temperature, and pain to the central nervous system. Recent advances in single-cell RNA-sequencing (scRNA-seq) have provided new insights into the diversity of sensory ganglia cell types in rodents, non-human primates, and humans, but it remains difficult to compare transcriptomically defined cell types across studies and species. Here, we built cross-species harmonized atlases of DRG and TG cell types that describe 18 neuronal and 11 non-neuronal cell types across 6 species and 19 studies. We then demonstrate the utility of this harmonized reference atlas by using it to annotate newly profiled DRG nuclei/cells from both human and the highly regenerative axolotl. We observe that the transcriptomic profiles of sensory neuron subtypes are broadly similar across vertebrates, but the expression of functionally important neuropeptides and channels can vary notably. The new resources and data presented here can guide future studies in comparative transcriptomics, simplify cell type nomenclature differences across studies, and help prioritize targets for future pain therapy development.

Human and mouse trigeminal ganglia cell atlas implicates multiple cell types in migraine.

Sensitization of trigeminal ganglion neurons contributes to primary headache disorders such as migraine, but the specific neuronal and non-neuronal trigeminal subtypes that are involved remain unclear. We thus developed a cell atlas in which human and mouse trigeminal ganglia are transcriptionally and epigenomically profiled at single-cell resolution. These data describe evolutionarily conserved and human-specific gene expression patterns within each trigeminal ganglion cell type, as well as the transcription factors and gene regulatory elements that contribute to cell-type-specific gene expression. We then leveraged these data to identify trigeminal ganglion cell types that are implicated both by human genetic variation associated with migraine and two mouse models of headache. This trigeminal ganglion cell atlas improves our understanding of the cell types, genes, and epigenomic features involved in headache pathophysiology and establishes a rich resource of cell-type-specific molecular features to guide the development of more selective treatments for headache and facial pain.