Lori Morton

Abstract Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disorder driven by unrelenting extracellular matrix deposition. Fibroblasts are recognized as the central mediators of extracellular matrix production in IPF; however, the characteristics of the underlying fibroblast cell populations in IPF remain poorly understood. Here, we use an unbiased single-cell RNA sequencing analysis of a bleomycin-induced pulmonary fibrosis model to characterize molecular responses to fibrotic injury. Lung cells were isolated on Day 11 to capture emerging fibrosis and gene expression was analyzed by three complementary techniques, which, together, generated a 49-gene signature that defined an activated subpopulation of fibroblasts. However, none of the identified genes were specific to the activated cells or to the disease setting, implying that the activated fibroblasts are not uniquely defined, but exhibit a similar, yet amplified, gene expression pattern to control cells. Our findings have important implications for fibrosis research, including: 1) defining myofibroblasts with any single marker will fail to capture much of the underlying biology; 2) fibroblast activation is poorly correlated with expression of transforming growth factor-β pathway genes; 3) single-cell analysis provides insight into the mechanism of action of effective therapies (nintedanib); 4) early events in lung fibrosis need not involve significant changes in fibroblast number; populations that do increase in number, such as macrophages, dendritic cells, and proliferating myeloid cells, may merit closer examination for their role in pathogenesis.

Significance Statement Microscopic analysis of urinary sediment is one of the most fundamental tests in nephrology. Urinary cells, however, have not been characterized in a standardized, unbiased manner. Single-cell transcriptomics of urine, of subjects with diabetic kidney disease and controls, were used to characterize 23,082 urinary cells in an unbiased manner. Combined analysis of urinary, kidney, and bladder cells indicated the technique can detect almost all kidney cell types and a variety of bladder cell types in human urine. This pilot study provides a reference dataset for future urinary single-cell characterization. Background Microscopic analysis of urine sediment is probably the most commonly used diagnostic procedure in nephrology. The urinary cells, however, have not yet undergone careful unbiased characterization. Methods Single-cell transcriptomic analysis was performed on 17 urine samples obtained from five subjects at two different occasions, using both spot and 24-hour urine collection. A pooled urine sample from multiple healthy individuals served as a reference control. In total 23,082 cells were analyzed. Urinary cells were compared with human kidney and human bladder datasets to understand similarities and differences among the observed cell types. Results Almost all kidney cell types can be identified in urine, such as podocyte, proximal tubule, loop of Henle, and collecting duct, in addition to macrophages, lymphocytes, and bladder cells. The urinary cell–type composition was subject specific and reasonably stable using different collection methods and over time. Urinary cells clustered with kidney and bladder cells, such as urinary podocytes with kidney podocytes, and principal cells of the kidney and urine, indicating their similarities in gene expression. Conclusions A reference dataset for cells in human urine was generated. Single-cell transcriptomics enables detection and quantification of almost all types of cells in the kidney and urinary tract.

Dilated cardiomyopathy (DCM) is a leading cause of heart failure and cardiac transplantation. We report a genome-wide association study and multi-trait analysis of DCM (14,256 cases) and three left ventricular traits (36,203 UK Biobank participants). We identified 80 genomic risk loci and prioritized 62 putative effector genes, including several with rare variant DCM associations (MAP3K7, NEDD4L and SSPN). Using single-nucleus transcriptomics, we identify cellular states, biological pathways, and intracellular communications that drive pathogenesis. We demonstrate that polygenic scores predict DCM in the general population and modify penetrance in carriers of rare DCM variants. Our findings may inform the design of genetic testing strategies that incorporate polygenic background. They also provide insights into the molecular etiology of DCM that may facilitate the development of targeted therapeutics.

Complement is a key component of the innate immune system. Inappropriate complement activation underlies the pathophysiology of a variety of diseases. Complement component 5 (C5) is a validated therapeutic target for complement-mediated diseases, but the development of new therapeutics has been limited by a paucity of preclinical models to evaluate the pharmacokinetic (PK) and pharmacodynamic (PD) properties of candidate therapies. The present report describes a novel humanized C5 mouse and its utility in evaluating a panel of fully human anti-C5 antibodies. Surprisingly, humanized C5 mice revealed marked differences in clearance rates amongst a panel of anti-C5 antibodies. One antibody, pozelimab (REGN3918), bound C5 and C5 variants with high affinity and potently blocked complement-mediated hemolysis in vitro. In studies conducted in both humanized C5 mice and cynomolgus monkeys, pozelimab demonstrated prolonged PK and durable suppression of hemolytic activity ex vivo. In humanized C5 mice, a switch in dosing from in-house eculizumab to pozelimab was associated with normalization of serum C5 concentrations, sustained suppression of hemolytic activity ex vivo, and no overt toxicity. Our findings demonstrate the value of humanized C5 mice in identifying new therapeutic candidates and treatment options for complement-mediated diseases.