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Exploring Alzheimer’s disease using single-cell/nucleus RNA sequencing data

Scientists have developed a network-based methodology that leverages single-cell/nucleus RNA sequencing data to uncover novel therapeutic targets for Alzheimer’s disease.

The number of Alzheimer’s disease (AD) cases is predicted to double by 2050, affecting over 90 million people worldwide. Although the underlying pathophysiology of AD is still poorly understood, recent studies have implicated neuroinflammation in its onset and progression. However, the broad anti-inflammatory therapies that are currently being used to treat AD are not clinically efficacious. Therefore, there is a need for a better understanding of the behaviour of immune cells in AD to identify novel drug targets.

Single-cell/nucleus RNA sequencing have been used to reveal the roles that microglia and astrocytes play in AD. In fact, there is a growing body of evidence to suggest that microglia and astrocytes are hugely sensitive to their environment, and as a result, are affected by the dysregulation of multiple biochemical pathways in AD pathogenesis. Therefore, identification of the underlying mechanisms linking disease-associated microglia and astrocytes with AD could lead to the development of novel drug targets.

Studying diseased-associated microglia and astrocytes

Recently, a team of researchers developed a network-based methodology that leveraged single-cell/nucleus RNA sequencing data from a number of sources, including AD patient brains, human protein-protein interactions and large-scale longitudinal patient data. Their aim was to identify the molecular networks between disease-associated microglia and astrocytes in order to uncover novel therapeutic targets for AD. Their results were published in Genome Research.

The key findings were as follows:

  • Both common and unique gene network regulators between disease-associated microglia (i.e., PAK1MAPK14, and CSF1R) and disease-associated astrocytes (i.e., NFKB1FOS, and JUN) are significantly enriched by neuro-inflammatory pathways and well-known genetic variants (i.e., BIN1).
  • Shared immune pathways between disease-associated microglia and astrocytes were identified, including Th17 cell differentiation and chemokine signalling.
  • Integrative metabolite-enzyme network analyses suggested that fatty acids and amino acids may trigger molecular alterations in DAM and DAA.
  • Combined network-based prediction and retrospective case-control observations with 7.2 million individuals identified that usage of fluticasone (an approved glucocorticoid receptor agonist) was significantly associated with a reduced incidence of AD.
  • Propensity score–stratified cohort studies revealed that usage of mometasone (a stronger glucocorticoid receptor agonist) was significantly associated with a decreased risk of AD compared to fluticasone after adjusting for age, gender, and disease comorbidities. 

Single-cell/nucleus RNA sequencing informed discoveries

Overall, this study has presented a novel network-based methodology that incorporated large-scale single-cell/nucleus RNA sequencing data to explore the molecular drivers of AD. The scientists showed that molecular networks derived from disease-associated microglia and astrocytes were significantly enriched for well-known immune and AD-related pathobiological pathways.

The identification of these networks offers potential targets for informed drug discovery and repurposing in the future. For example, this research has revealed that fluticasone and mometasone could be potential treatments for AD. Therefore, this suggests that, if broadly applied, utilising large-scale single-cell/nucleus omics data could significantly accelerate innovation in AD drug discovery.

Image credit: New Scientist