Towards precision therapeutics for macrophages: developing a multi-organ understanding of macrophage control by TGF-β

Background

Transforming growth factor-β (TGF-β) is a potent growth factor and immune modulator involved in tissue development, homeostasis, and repair across the body¹. Macrophages are resident immune cells that occupy most organs and are key producers of TGF-β².

Disturbed TGF-β and macrophage activity are associated with multiple chronic diseases - including neurological, fibrotic, autoimmune and cancers - hence the TGF-β pathway is a major drug target. However, most cells in the body can produce and respond to TGF-β which creates challenges to achieve sufficient selectivity; indeed, current TGF-β-blocking drugs are limited by major side effects.  Understanding how macrophage TGF-β activity is controlled between and within organs is crucial to guide design of more precise therapeutics targeting only disease-relevant macrophages.

TGF-β activity is regulated at multiple levels, including by molecules that help convert the inactive TGF-β precursor to its bioactive form. Macrophages located in different tissues and sub-tissue niches express different versions of these activation-enabling molecules. We recently described mutations in one of these, LRRC33/NRROS as the genetic cause of a childhood neurodegenerative disease³, likely through abnormal TGF-β function in microglia (the macrophages of the brain). 

Ongoing work in our labs suggests that LRRC33/TGF-β expression and function is sub-tissue compartment-restricted in the brain and that this pattern extends to selected systemic organs, such as the intestine. This suggests (1) that LRRC33 may have important physiological roles in macrophages outside the CNS, and (2) that LRRC33 could be a more selective target for modulating TGF-β activity in certain diseases. compared with existing therapies that target TGF-β signalling in all cells of the body. 

Aims

The overall project goal is to develop a multi-organ understanding of how dysregulated TGF-β activation, through loss of LRRC33 function, affects macrophages and health outcomes.

Specific aims, as follows, are complementary but independent of one another and intended to address the overall goal from different perspectives.

1. Compare effects of LRRC33 deficiency on macrophage transcriptome profiles in different organs and sub-organ niches using preclinical model datasets and tissues.

Working with macrophage single-cell RNA sequencing (scRNAseq) datasets from multiple organs generated previously in our labs, you will use established computational workflows to identify organ-specific/common macrophage phenotypes. Signatures will be mapped to a human macrophage expression atlas and key marker genes examined in situ for spatial validation. 

2. Determine if effects of LRRC33 deficiency are replicated by disruption to other components of the TGF-β pathway in macrophages within and across organs.

Our recent findings suggest similar, but not identical, clinical neurological signs resulting from disruption to LRRC33 and other components of TGF-β signaling. The comparative effects of targeting different components of the TGF-β signalling pathway on microglia are unknown. Analysis of altered microglial states using integrated scRNAseq datasets from genetic knockout of differing TGF-β pathway components will be conducted to understand how modulating LRRC33 compares to more broadly-acting TGF-β interventions. This approach may extend to other organs as new datasets are generated within our labs.

3. Assess if LRRC33 gene variants associate with adverse health outcomes related to TGF-β function in a large population cohort.

LRRC33 variants will be identified from exome sequencing data in UK Biobank. Associations between heterozygous variants with outcomes relating to TGF-β function, both for disease (including fibrotic diseases, autoimmune disease, cancer, cardiovascular remodeling disease, neurodegenerative disease) and quantitative biomarkers, will be determined.

Training outcomes

Knowledge

You will gain knowledge and understanding of tissue macrophage and TGF-β biology, immune-mediated mechanisms of chronic disease, genomics, transcriptomics and molecular epidemiology, and how to apply integrative data-driven -omics and population health data science approaches to tackle questions on disease mechanisms and targets. 

Skills

You will gain skills in a full package of bioinformatics methods for processing, analyzing, visualising and interpretating multi-omics datasets. Opportunities to acquire selected lab skills in tissue-based techniques important for validation of -omics profiles will be available. Further quantitative and statistical skills will be gained in curating and analysing genetic and population health data (from UK Biobank and related population health resources). Gaining transferable skills in experimental design, written and oral presentation of data, network building and collaboration will be embedded in the training.

References

1. Park et al., Cell 2022: https://doi.org/10.1016/j.cell.2022.10.007 

2. Deng et al., Sig Transduct Target Ther 2024:  https://doi.org/10.1038/s41392-024-01764-w 

3. Smith et al., Acta Neuropathol 2020: https://doi.org/10.1007/s00401-020-02137-7