Biology subjects

Damm, I.

Publications and source records attributed to Damm, I..

4 recordsLinked to original sources

bioRxiv2022

Genetic deletion and pharmacologic inhibition of FcER1 reduces renal injury in mouse models of diabetic nephropathy.

FcER1 forms a high affinity multimeric cell-surface receptor for the Fc region of immunoglobulin E (IgE) and controls the activation of mast cells and basophils. Antigen binding and cross-linking of FcER1 associated IgE induces several downstream signaling pathways that result in diverse outcomes. Canonical signaling through IgE-FcER1 has been related to allergic responses, however, recent studies have identified that their function in mast cell and basophils contribute to other pathogenic conditions such as cancer and diabetes. Previous studies have demonstrated that FcER1 protein is upregulated in advanced diabetic kidney disease (DKD) making it a targetable molecule for the treatment of DKD. This study presents evidence that loss of FcER1 signaling reduces proteinuria and renal injury in two pre-clinical mouse models of diabetes. Mice deficient for fcer1 are protected from streptozotocin mediated induction of proteinuria and display reduced fibrosis and mast cell infiltration in kidney. Furthermore, inhibition of FcER1 signaling with an antibody directed against the {gamma}-subunit reduces proteinuria in a spontaneous model of type II diabetes. Our results show significant reduction of proteinuria and tissue damage in pre-clinical DKD models demonstrating the potential of FcER1 inhibitory approaches for developing new therapies in DKD.

immunology↗

bioRxiv2022

Perturbations in podocyte transcriptome and biological pathways induced by FSGS associated circulating factors.

Focal segmental glomerulosclerosis (FSGS) is frequently associated with heavy proteinuria and progressive renal failure requiring dialysis or kidney transplantation. However, primary FSGS also has 40-80% risk of recurrence of disease in the transplanted kidney (rFSGS). Multiple circulating factors have been proposed to contribute to the pathogenesis of primary and rFSGS. However, neither the factors nor the downstream effectors specific to individual factors have been identified. The tumor necrosis factor, TNF pathway activation by one or more circulating factors present in the sera of patients with FSGS has been supported by multiple studies. The proposed circulating factors include soluble urokinase-type plasminogen activator receptor (suPAR) and patient derived CD40 autoantibody (CD40autoAb) in the development and recurrence of FSGS. In a human in vitro model, using two novel human antibodies-anti uPAR (2G10) and anti CD40 antibody, we show that the podocyte injury caused by sera from FSGS patients is at least in part mediated by CD40 and suPAR. Additionally, we employ gene expression studies to compare the molecules and pathways activated in response to CD40 autoantibody from rFSGS patients (rFSGS/CD40autoAb) and suPAR, and delineate the unique pathways associated with FSGS injury and transcriptional podocyte alterations with targeted blockade of suPAR and CD40 pathways. Clinical ImpactFocal Segmental Glomerulosclerosis remains a disease without specific therapy for primary disease and high rate of recurrence after kidney transplantation. Circulating factors are implicated in the pathogenesis of FSGS but targeting them for therapy has remained elusive. We propose two potential therapeutic molecules for rFSGS treatment-a human anti-uPAR antibody (2G10) and a humanized anti-CD40 blocking antibody (Bristol Meyer Squibb, 986090) that reverse podocyte injury associated with FSGS in cultured podocytes and can be further tested in pre-clinical and clinical models. Furthermore, we use microarray profiling to identify transcriptional pathways specific to podocyte injury from patient-derived CD40 autoantibodies (rFSGS/CD40autoAb) and suPAR and selective blockade of these pathways to abrogate podocyte injury.

immunology↗

bioRxiv2022

Perturbations of the T-cell immune repertoire in kidney transplant rejection

In this cross-sectional and longitudinal analysis of mapping the T-cell repertoire in kidney transplant recipients, we have investigated and validated T-cell clonality, immune repertoire chronology at rejection, and contemporaneous allograft biopsy quantitative tissue injury, to better understand the pathobiology of acute T cell and antibody-mediated kidney transplant rejection. To follow the dynamic evolution of T-cell repertoire changes before and after engraftment and during biopsy-confirmed acute rejection, we sequenced 323 peripheral blood samples from 200 unique kidney transplant recipients, with (n=100) and without (n=100) biopsyconfirmed acute rejection. The results of these studies highlight, for the first time, that patients who develop acute allograft rejection, have lower (p=0.01) T cell fraction even before transplantation, followed by its rise after transplantation and at the time of acute rejection accompanied by high TCR repertoire turnover (p=0.004). Acute rejection episodes occurring after the first 6 months post-transplantation, and those with a component of antibody-mediated rejection, had the highest turnover; p=0.0016) of their TCRs. In conclusion, further prospective validation studies are needed to evaluate the clinical utility of peripheral blood TCR analysis for both pre- and post-transplant immune risk assessment and prediction of different mechanisms of graft rejection.

immunology↗

bioRxiv2020

Novel Human Kidney Cell Subsets Identified by Mux-Seq

BackgroundThe kidney is a highly complex organ that performs multiple functions necessary to maintain systemic homeostasis, with complex interplay from different kidney sub-structures and the coordinated response of diverse cell types, few known and likely many others, as yet undiscovered. Traditional global sequencing techniques are limited in their ability to identify unique and functionally diverse cell types in complex tissues. MethodsHerein we characterize over 45,000 cells from 10 normal human kidneys using unbiased single-cell RNA sequencing. We also apply, for the first time, an approach of multiplexing kidney samples (Mux-Seq), pooled from different individuals, to save input sample amount and cost. We applied the computational tool Demuxlet to assess differential expression across multiple individuals by pooling human kidney cells for scRNA sequencing, utilizing individual genetic variability to determine the identity of each cell. ResultsMultiplexed droplet single-cell RNA sequencing results were highly correlated with the singleplexed sample run data. One hundred distinct cell cluster populations in total were identified across the major cell types of the kidney, with varied functional states. Proximal tubular and collecting duct cells were the most heterogeneous, displaying multiple clusters with unique ontologies. Novel proximal tubular cell subsets were identified with regenerative potential. Trajectory analysis demonstrated evolution of cell states between intercalated and principal cells in the collecting duct. ConclusionsHealthy kidney tissue has been successfully analyzed to detect all known renal cell types, inclusive of resident and infiltrating immune cells in the kidney. Mux-Seq is a unique method that allows for rapid and cost-effective single cell, in depth, transcriptional analysis of human kidney tissue. Significance StatementUse of renal biopsies for single cell transcriptomics is limited by small tissue availability and batch effects. In this study, we have successfully employed the use of Mux-Seq for the first time in kidney. Mux-Seq allows the use of single cell technology at a much more cost-effective manner by pooling samples from multiple individuals for a single sequencing run. This is even more relevant in the case of patient biopsies where the input of tissue is significantly limited. We show that the data from overlapping tissue samples are highly correlated between Mux-Seq and traditional Singleplexed RNA seq. Furthermore, the results from Mux-Seq of 4 pooled samples are highly correlated with singleplexed data from 10 singleplex samples despite the inherent variability among individuals.

genomics↗