The Future Potential of Biosensors to Investigate the Gut-Brain Axis

Microbiota dysbiosis impact on the immune system dysregulation in Huntington's disease (HD)

Huntington's disease (HD) is a neurodegenerative disorder characterized by motor, cognitive, and psychiatric impairments caused by Huntingtin (HTT) gene mutations, resulting in the mutant huntingtin (mHTT) protein. Both innate and adaptive immunities play crucial roles in the pathogenesis of HD. In this chapter, we explore the vital role of the gut microbiota in HD, emphasizing its impact on the immune response and brain health via the gut-brain axis. Dysbiosis influences immune responses and HD pathogenesis through microbial metabolites such as short-chain fatty acids (SCFAs) and pathogen-associated molecular patterns (PAMPs). We discuss advanced mathematical models, telemedicine, and biosensors for tracking HD progression and detecting gut dysbiosis. Nutritional interventions to restore microbiota balance and using artificial intelligence and machine learning to predict disease prognosis and personalized treatments have been highlighted. Based on their unique immune profiles and gut microbiota, personalized medicine has been proposed as a promising strategy for effective HD treatment.

Distinguishing bipolar depression, bipolar mania, and major depressive disorder by gut microbial characteristics

BACKGROUND

Gut microbial disturbance has been widely confirmed in mood disorders. However, little is known about whether gut microbial characteristics can distinguish major depressive disorder (MDD), bipolar depression (BP-D), and bipolar mania (BP-M).

METHODS

This was a prospective case-control study. The composition of gut microbiota was profiled using 16S ribosomal RNA (rRNA) gene sequencing of fecal samples and compared between healthy controls (HC; n = 46), MDD (n = 51), BP-D (n = 44), and patients with BP-M (n = 45).

RESULTS

Gut microbial compositions were remarkably changed in the patients with MDD, BP-D, and BP-M. Compared to HC, distinct gut microbiome signatures were found in MDD, BP-D, and BP-M, and some gut microbial changes were overlapping between the three mood disorders. Furthermore, we identified a signature of 7 operational taxonomic units (OUT; Prevotellaceae-related OUT22, Prevotellaceae-related OUT31, Prevotellaceae-related OTU770, Ruminococcaceae-related OUT70, Bacteroidaceae-related OTU1536, Propionibacteriaceae-related OTU97, Acidaminococcaceae-related OTU34) that can distinguish patients with MDD from those with BP-D, BP-M, or HC, with area under the curve (AUC) values ranging from 0.910 to 0.996.

CONCLUSION

Our results provide the clinical rationale for the discriminative diagnosis of MDD, BP-D, and BP-M by characteristic gut microbial features.