CD8 T cells slow tauopathy progression by targeting microglia – Nature

Report on the Role of Granzyme K⁺ CD8⁺ T Cells in Slowing Tauopathy Progression by Targeting Microglia

Introduction

Neurodegenerative diseases, including tauopathies such as Alzheimer’s disease and chronic traumatic encephalopathy, involve activation of innate and adaptive immune responses. These immune responses can either mitigate or exacerbate disease progression. This report focuses on the beneficial immune mechanisms that emerge during tauopathy development, emphasizing their alignment with the Sustainable Development Goals (SDGs), particularly SDG 3: Good Health and Well-being.

Study Overview

The study utilized mouse models expressing mutant human tau protein in neurons to investigate immune interactions during tauopathy. Key findings were also validated in human brain tissue affected by tauopathies.

Key Findings

Microglia Function in Tauopathy

• Microglia initially slow tauopathy progression by controlling the spread of phosphorylated tau (pTau) within the central nervous system and bloodstream.
• Over time, microglia transform into distressed antigen-presenting cells, acquiring neuronal transcripts.

Role of CD8⁺ T Cells

• Resident, clonally expanded CD8⁺ T cells target distressed microglia.
• These CD8⁺ T cells express granzyme K (GZMK) rather than traditional effector molecules such as IFNγ, TNF, or granzymes a/b/c.
• Immune checkpoint proteins TIGIT and PD-1 regulate these T cells; blockade of these checkpoints accelerates disease progression.
• GZMK⁺ CD8⁺ T cells were also observed targeting microglia in pTau-rich lesions in human brains from aging, Alzheimer’s disease, and chronic traumatic encephalopathy cases.

Impact of CD8⁺ T Cell Deletion

• Removal of CD8⁺ T cells in mice led to increased emergence of distressed microglia containing neuronal transcripts.
• This deletion markedly enhanced pTau spread and accelerated neurological decline.

Implications for Sustainable Development Goals (SDGs)

SDG 3: Good Health and Well-being

1. Advancement in Understanding Neurodegenerative Diseases: The study provides insights into immune mechanisms that can be harnessed to slow tauopathy progression, contributing to improved health outcomes.
2. Potential Therapeutic Targets: Identification of GZMK⁺ CD8⁺ T cells and immune checkpoint pathways offers novel avenues for therapeutic interventions to combat neurodegeneration.
3. Promotion of Healthy Aging: By addressing mechanisms underlying diseases like Alzheimer’s, the research supports efforts to enhance the quality of life for aging populations.

SDG 9: Industry, Innovation, and Infrastructure

• Utilization of advanced techniques such as bulk and single-cell RNA sequencing and computational analyses exemplifies innovation in biomedical research infrastructure.

SDG 17: Partnerships for the Goals

• The study was supported by multiple institutions including the National Institutes of Health and The Defense Health Agency, demonstrating collaborative efforts in advancing health research.

Methodological Highlights

• Mouse models expressing mutant human tau protein were used to simulate tauopathy development.
• Immune cell populations were characterized using flow cytometry and immunohistochemistry.
• Bulk and single-cell RNA sequencing provided transcriptomic insights into microglia and T cell states.
• Computational tools such as Automated Immune Molecule Separator (AIMS) were employed to analyze T cell receptor (TCR) clusters.

Conclusions

The presence of GZMK⁺ CD8⁺ T cells represents a signature immune response that slows tauopathy progression by targeting distressed microglia. These findings highlight the dual role of the immune system in neurodegeneration and underscore the potential for immunomodulatory therapies. Aligning with SDG 3, this research contributes to the global objective of reducing the burden of neurological diseases and promoting well-being across all ages.

Data Availability

All bulk and single-cell RNA sequencing data generated in this study are publicly accessible via the NCBI Gene Expression Omnibus (GEO) under accession codes GSE273752, GSE273753, and GSE273757, supporting transparency and further research collaboration.

Acknowledgements

This work was supported by the intramural programs of the National Institute of Neurological Disorders & Stroke (NINDS), the National Institute of Allergy & Infectious Diseases (NIAID), and The Defense Health Agency. The study utilized computational resources of the NIH HPC Biowulf cluster. The authors acknowledge assistance from various core facilities and collaborators.

1. Relevant Sustainable Development Goals (SDGs)

1. SDG 3: Good Health and Well-being
   • The article focuses on neurodegenerative diseases, specifically tauopathies such as Alzheimer’s disease, which directly relates to ensuring healthy lives and promoting well-being for all ages.
2. SDG 9: Industry, Innovation and Infrastructure
   • The research involves advanced scientific methods including single-cell RNA sequencing and computational biology, reflecting innovation in health research infrastructure.
3. SDG 17: Partnerships for the Goals
   • The article acknowledges collaboration among multiple institutions and use of shared data resources, highlighting partnerships in scientific research.

2. Specific Targets Under the Identified SDGs

1. SDG 3: Good Health and Well-being
   • Target 3.4: By 2030, reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-being.
   • Target 3.b: Support the research and development of vaccines and medicines for the communicable and non-communicable diseases that primarily affect developing countries.
2. SDG 9: Industry, Innovation and Infrastructure
   • Target 9.5: Enhance scientific research, upgrade the technological capabilities of industrial sectors, including encouraging innovation and substantially increasing the number of research and development workers.
3. SDG 17: Partnerships for the Goals
   • Target 17.6: Enhance North-South, South-South and triangular regional and international cooperation on and access to science, technology and innovation.

3. Indicators Mentioned or Implied to Measure Progress

1. Indicators Related to SDG 3
   • Measurement of phosphorylated tau (pTau) spread in the central nervous system and blood as a biomarker for disease progression.
   • Neurological decline assessment in mouse models as a functional indicator of disease impact.
   • Quantification of immune cell populations such as microglia and CD8⁺ T cells in brain tissue to evaluate immune response.
   • Levels of proteins like GFAP and NF-L in blood as markers of neurodegeneration.
2. Indicators Related to SDG 9
   • Use of bulk and single-cell RNA sequencing data (GEO accession codes provided) to monitor molecular changes during disease progression.
   • Application of computational methods such as AIMS analysis and UMAP for immune repertoire characterization.
3. Indicators Related to SDG 17
   • Availability and sharing of data through public repositories (NCBI GEO), reflecting cooperation and data accessibility.

4. Table of SDGs, Targets, and Indicators

Source: nature.com