Autoimmunity Research Spotlight: Vladimir Liarski, MD, MS, and Translational Research in Idiopathic Inflammatory Myopathies

Vladimir Liarski, MD, MS, is an assistant professor of Medicine in the Division of Rheumatology and Clinical Immunology at the University of Pittsburgh School of Medicine. Dr. Liarski joined the Division in 2022. Before joining UPMC and the University of Pittsburgh, he conducted his research and clinical work at the University of Chicago.

"UPMC and Pitt are one of the top centers in the world for the study of myositis, and with its combined resources, expertise, and ability for multidisciplinary collaborative research, it was the perfect match and location to continue my clinical practice and translational research," says Dr. Liarski.

Research Overview

While a significant amount of Dr. Liarski’s prior research involved lupus and lupus nephritis, his laboratory has shifted focus to human translational research of the idiopathic inflammatory myopathies, with a specific emphasis on dermatomyositis (DM) and inclusion body myositis (IBM).

Within its prior studies involving lupus, and its current work on myopathies, Dr. Liarski’s research has primarily involved understanding the role of inflammation – its cellular makeup and processes, and the importance of cognate versus noncognate immune interactions between T cells and B cells during the immune response.

Cognate immune interactions occur between T cells and antigen-specific B cells, where both cells recognize the same antigen. Noncognate interactions involve T cells providing help to B cells independent of antigen specificity, supporting the overall antibody response. Both types of interactions play important roles in the immune response and the generation of effective humoral immunity.

Dr. Liarski's explorations of cognate and noncognate cellular interactions are conducted using high-throughput, computerized, and objective techniques based on image analysis of multichannel immunofluorescent confocal microscopy images. Along with his prior collaborators, he has developed new approaches to the segmentation and analysis of in vivo cellular interactions using Convolutional Neural Networks and Deep Learning.

His work has also involved the development of a new technique to digest frozen clinical muscle biopsies to obtain intact immune cells for use in flow cytometry and downstream single-cell applications.

"This advance in the use of frozen biopsy tissue significantly expands our ability to conduct more robust studies on very rare diseases like dermatomyositis and those for which animal models do not exist. It advances our ability to collect and use fresh tissue samples challenged both by the rarity of the disease or the physical/anatomical difficulties in getting biopsies," says Dr. Liarski. "Our technique gives us RNA sequencing data from frozen biopsy samples that are indistinguishable from what you derive from fresh cellular material. It’s a game-changing advance.”

Prior Scientific Contribution Highlights

Dr. Liarski and colleagues' prior research has made numerous important findings in understanding immune cell interactions in the context of autoimmune diseases (e.g., lupus/lupus nephritis.)

In the journal Science Translational Medicine, Dr. Liarski and colleagues published their findings of a study, "Cell Distance Mapping identifies functional T follicular Helper Cells in Inflamed Human Renal Tissue,"¹ in which they employed their newly developed technique called Cell Distance Mapping (CDM) to identify functional T follicular helper cells in inflamed human renal tissue. T follicular helper cells are a subset of T cells that play a crucial role in the adaptive immune system, particularly in aiding B cells to produce antibodies in response to infection.

Cell Distance Mapping is a method that quantifies interactions between different immune cells.

Cognate recognition between a T cell and a B cell is essential for the T cell to provide "help" to the B cell, enabling it to mount an immune response. Dr. Liarski's team hypothesized that by visually quantifying these interactions in situ, they could directly assess the functional competency of TFH cells. With the developed CDM approach, they were able to analyze inflamed human tissues and found that the internuclear distances between TFH cells and B cells could be used to differentiate between cognate and noncognate interactions.

The fact that the study was focused on inflamed kidney tissue suggests that it might have implications for understanding and potentially treating kidney diseases that involve inflammation and immune response, such as lupus nephritis or other forms of glomerulonephritis.

In a paper published in Nature Immunology in 2019 under the title "Quantifying In Situ Adaptive Immune Cell Cognate Interactions In Humans,"² they explored adaptive immunity within the context of human disease, a subject that has been challenging to investigate due to the limitations of existing analytic techniques.

The study details a new methodology to quantify in situ adaptive immunity using a deep convolutional neural network, a type of artificial intelligence technology, and cell distance mapping to effectively discern between cognate T cell interactions and noncognate interactions.

This approach could have broad implications and applicability for understanding various conditions, including autoimmune diseases, infections, and cancers.

R21 Grant: Probing the Basic Immune System Mechanisms That Drive Dermatomyositis

Dr. Liarski’s current NIH-funded R21 grant, “Leveraging Single Index Cell RNA Sequencing to Study Macrophage Populations in Frozen Biopsies of Dermatomyositis,” is designed to investigate the underlying causes of dermatomyositis and identify predictive markers for disease progression.

"Our understanding of the basic cellular mechanisms and the pathophysiology of dermatomyositis is minimal, partially due to the rarity of the disease," says Dr. Liarski. "But with some of our recent understandings and the new technologies we have developed around frozen tissue analysis and computational modeling, we're positioned to begin interrogating and uncovering the disease's cellular drivers."

Specifically, Dr. Liarski’s research is focused on macrophages and whether and to what degree they may be responsible for inflammatory processes and inflammation within muscle tissue in DM.

By identifying the specific macrophage populations involved in the disease and their signatures of disease severity, Dr. Liarski's research may uncover new targets for therapy but also clinically applicable methods to identify macrophages associated with more severe DM disease activity in individual patients.

References

1. Liarski VM, Kaverina N, Chang A, et al. Cell Distance Mapping Identifies Functional T Follicular Helper Cells in Inflamed Human Renal Tissues. Sci Transl Med. 2014; 6(230): 230ra46.

    

2. Liarski VM, Sibley A, van Panhuys N, et al. Quantifying In Situ Adaptive Immune Cell Cognate Interactions in Humans. Nat Immunol. 2019; 20(4): 503-513.