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Transcriptomic analysis of frontotemporal lobar degeneration with TDP-43 pathology reveals cellular alterations across multiple brain regions

Abstract

Frontotemporal lobar degeneration (FTLD) is a group of heterogeneous neurodegenerative disorders affecting the frontal and temporal lobes of the brain. Nuclear loss and cytoplasmic aggregation of the RNA-binding protein TDP-43 represents the major FTLD pathology, known as FTLD-TDP. To date, there is no effective treatment for FTLD-TDP due to an incomplete understanding of the molecular mechanisms underlying disease development. Here we compared postmortem tissue RNA-seq transcriptomes from the frontal cortex, temporal cortex, and cerebellum between 28 controls and 30 FTLD-TDP patients to profile changes in cell-type composition, gene expression and transcript usage. We observed downregulation of neuronal markers in all three regions of the brain, accompanied by upregulation of microglia, astrocytes, and oligodendrocytes, as well as endothelial cells and pericytes, suggesting shifts in both immune activation and within the vasculature. We validate our estimates of neuronal loss using neuropathological atrophy scores and show that neuronal loss in the cortex can be mainly attributed to excitatory neurons, and that increases in microglial and endothelial cell expression are highly correlated with neuronal loss. All our analyses identified a strong involvement of the cerebellum in the neurodegenerative process of FTLD-TDP. Altogether, our data provides a detailed landscape of gene expression alterations to help unravel relevant disease mechanisms in FTLD.

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Acknowledgements

We thank Professor Tamas Revesz, Professor Janice Holton, Professor Francesco Scaravilli, and Professor Margaret Esiri for providing neuropathological reports. We thank all members of the Raj lab for their feedback on the manuscript. JH and TR are funded by grants from the US National Institutes of Health (NIH NIA R56-AG055824 and NIA U01-AG068880). PF is funded by the UK MRCl (MR/M008606/1 and MR/S006508/1), the UK Motor Neurone Disease Association, Rosetrees Trust and the UCLH NIHR Biomedical Research Centre. CB is funded by the Alzheimer’s Research UK (ARUK-RF2019B-005) and the Multiple System Atrophy Trust. TL is supported by an Alzheimer’s Research UK Senior fellowship. This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. Research reported in this paper was supported by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD018522 and S10OD026880. All NYGC ALS Consortium activities are supported by the ALS Association (ALSA, 19-SI-459) and the Tow Foundation. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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JH and TR conceived and designed the project. RH led the main data analysis, under the supervision of JH. CB performed methylation analysis and neuronal estimation. JN provided pathological and clinical information on the samples. TL provided pathological, genetic, clinical information, microglial analysis scores on the samples and performed the atrophy analyses. JH and TR oversaw all aspects of the study, with contributions from TL and PF. The NYGC ALS Consortium and the Target ALS Human Postmortem Tissue Core provided human tissue samples. RH and JH wrote the manuscript with input from all co-authors.

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Correspondence to Jack Humphrey or Towfique Raj.

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All members of the NYGC ALS Consortium are listed in the Supplemental Acknowledgments.

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Hasan, R., Humphrey, J., Bettencourt, C. et al. Transcriptomic analysis of frontotemporal lobar degeneration with TDP-43 pathology reveals cellular alterations across multiple brain regions. Acta Neuropathol 143, 383–401 (2022). https://doi.org/10.1007/s00401-021-02399-9

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  • DOI: https://doi.org/10.1007/s00401-021-02399-9

Keywords

  • FTLD
  • FTD
  • RNA-seq
  • TDP-43
  • FTLD-TDP
  • Dementia
  • Gene expression
  • Transcriptomics