Permissive microbiome characterizes human subjects with a neurovascular disease cavernous angioma.
Sean P PolsterAnukriti SharmaCeylan TanesAlan T TangPatricia MerickoYing CaoJulián Carrión-PenagosRomuald GirardJanne KoskimäkiDongdong ZhangAgnieszka StadnikSharbel G RomanosSeán B LyneRobert ShenkarKimberly L YanCornelia LeeAmy AkersLeslie MorrisonMyranda RobinsonAtif ZafarKyle BittingerHelen KimJack A GilbertMark L KahnLe ShenIssam A AwadPublished in: Nature communications (2020)
Cavernous angiomas (CA) are common vascular anomalies causing brain hemorrhage. Based on mouse studies, roles of gram-negative bacteria and altered intestinal homeostasis have been implicated in CA pathogenesis, and pilot study had suggested potential microbiome differences between non-CA and CA individuals based on 16S rRNA gene sequencing. We here assess microbiome differences in a larger cohort of human subjects with and without CA, and among subjects with different clinical features, and conduct more definitive microbial analyses using metagenomic shotgun sequencing. Relative abundance of distinct bacterial species in CA patients is shown, consistent with postulated permissive microbiome driving CA lesion genesis via lipopolysaccharide signaling, in humans as in mice. Other microbiome differences are related to CA clinical behavior. Weighted combinations of microbiome signatures and plasma inflammatory biomarkers enhance associations with disease severity and hemorrhage. This is the first demonstration of a sensitive and specific diagnostic microbiome in a human neurovascular disease.
Keyphrases
- endothelial cells
- protein kinase
- end stage renal disease
- type diabetes
- chronic kidney disease
- inflammatory response
- gene expression
- newly diagnosed
- squamous cell carcinoma
- magnetic resonance imaging
- induced pluripotent stem cells
- oxidative stress
- microbial community
- computed tomography
- pluripotent stem cells
- peritoneal dialysis
- metabolic syndrome
- adipose tissue
- radiation therapy
- risk assessment
- white matter
- insulin resistance
- network analysis
- antibiotic resistance genes
- rectal cancer
- human health