Depression phenotype identified by using single nucleotide exact amplicon sequence variants of the human gut microbiome

• Published in: Molecular psychiatry Vol. 26; no. 8; pp. 4277 - 4287
• Main Authors: Stevens, Bruce R., Roesch, Luiz, Thiago, Priscila, Russell, Jordan T., Pepine, Carl J., Holbert, Richard C., Raizada, Mohan K., Triplett, Eric W.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.08.2021; Nature Publishing Group
• Subjects: 38/22; 692/53/2421; 692/53/2423; 692/699/476/1414; Behavioral Sciences; Biological Psychology; Depression - genetics; Depression, Mental; Development and progression; Diagnosis; Digestive organs; Digestive system; Dysbacteriosis; Fatty acids; Gastrointestinal Microbiome - genetics; Genetic aspects; Genotype & phenotype; Gut microbiota; Health aspects; High-Throughput Nucleotide Sequencing; Humans; Inflammasomes; Intestinal microflora; Learning algorithms; Machine Learning; Medicine; Medicine & Public Health; Mental depression; Metabolic pathways; Metabolism; Microbiomes; Microbiota; Microbiota (Symbiotic organisms); Monoamines; Neurosciences; Nucleotides; Pharmacotherapy; Phenotype; Phenotypes; Physiological aspects; Psychiatry; RNA, Ribosomal, 16S - genetics; γ-Aminobutyric acid; United States
• ISSN: 1359-4184; 1476-5578; 1476-5578
• DOI: 10.1038/s41380-020-0652-5

Single nucleotide exact amplicon sequence variants (ASV) of the human gut microbiome were used to evaluate if individuals with a depression phenotype (DEPR) could be identified from healthy reference subjects (NODEP). Microbial DNA in stool samples obtained from 40 subjects were characterized using high throughput microbiome sequence data processed via DADA2 error correction combined with PIME machine-learning de-noising and taxa binning/parsing of prevalent ASVs at the single nucleotide level of resolution. Application of ALDEx2 differential abundance analysis with assessed effect sizes and stringent PICRUSt2 predicted metabolic pathways. This multivariate machine-learning approach significantly differentiated DEPR ( n  = 20) vs. NODEP ( n  = 20) (PERMANOVA P  < 0.001) based on microbiome taxa clustering and neurocircuit-relevant metabolic pathway network analysis for GABA, butyrate, glutamate, monoamines, monosaturated fatty acids, and inflammasome components. Gut microbiome dysbiosis using ASV prevalence data may offer the diagnostic potential of using human metaorganism biomarkers to identify individuals with a depression phenotype.