Journal of psychosomatic research · 2022
Gut microbiome and daytime function in Chinese patients with major depressive disorder.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Zhang Qi, Yun Yajun, An Huimei, Zhao Wenxuan, Ma Ting, Wang Zhiren, Yang Fude
Аннотация
BACKGROUND: Major depressive disorder (MDD) is underscored by daytime dysfunction-associated features, including mood disturbances, impaired cognition, fatigue, and daytime sleepiness. Importantly, the gut-brain axis may represent a potential mechanistic link between MDD and daytime dysfunction. Therefore, this study aimed to explore the gut microbiome composition and daytime dysfunction in Chinese patients with MDD.
METHODS: We enrolled 36 patients with MDD and 45 healthy controls (HCs) matched by age, sex, and body mass index (BMI). Daytime function including emotion, fatigue, and sleepiness were assessed using the Epworth Sleepiness Scale (ESS), Fatigue Severity Scale (FSS), Hamilton Anxiety Scale (HAMA), and Hamilton Depression Scale (HAMD). 16S rRNA sequencing was employed to characterize the gut microbiota in stool samples.
RESULTS: The operational taxonomic units (OTUs) OTU255, OUT363 were positively correlated with HAMD and HAMA. OTU244, OTU542 and OTU221 were positively correlated with ESS, HAMD and HAMA. OTU725 and OTU80 were positively correlated with FSS, ESS, HAMD and HAMA, while OTU423 and OTU502 were negatively correlated with all above. Flavonifractor positively correlated with fatigue in patients with MDD and all individuals simultaneously. The correlation between gut microbiome and daytime function was different in MDD and HCs.
CONCLUSIONS: We identified several OTUs associated with the severity of fatigue, depression, daytime sleepiness and anxiety in all individuals. Our results revealed the differences in microbiome found between patients with MDD and HCs. These findings provide insights into the potential microbiota changes that occur in MDD, and will enable the development of specific therapeutic strategies for targeting the various symptoms of depression.
METHODS: We enrolled 36 patients with MDD and 45 healthy controls (HCs) matched by age, sex, and body mass index (BMI). Daytime function including emotion, fatigue, and sleepiness were assessed using the Epworth Sleepiness Scale (ESS), Fatigue Severity Scale (FSS), Hamilton Anxiety Scale (HAMA), and Hamilton Depression Scale (HAMD). 16S rRNA sequencing was employed to characterize the gut microbiota in stool samples.
RESULTS: The operational taxonomic units (OTUs) OTU255, OUT363 were positively correlated with HAMD and HAMA. OTU244, OTU542 and OTU221 were positively correlated with ESS, HAMD and HAMA. OTU725 and OTU80 were positively correlated with FSS, ESS, HAMD and HAMA, while OTU423 and OTU502 were negatively correlated with all above. Flavonifractor positively correlated with fatigue in patients with MDD and all individuals simultaneously. The correlation between gut microbiome and daytime function was different in MDD and HCs.
CONCLUSIONS: We identified several OTUs associated with the severity of fatigue, depression, daytime sleepiness and anxiety in all individuals. Our results revealed the differences in microbiome found between patients with MDD and HCs. These findings provide insights into the potential microbiota changes that occur in MDD, and will enable the development of specific therapeutic strategies for targeting the various symptoms of depression.