TY - JOUR
T1 - Exploring the Relevance between Gut Microbiota-Metabolites Profile and Chronic Kidney Disease with Distinct Pathogenic Factor
AU - Chen, Tso-Hsiao
AU - Cheng, Chung-Yi
AU - Huang, Chun-Kai
AU - Ho, Yi-Hsien
AU - Lin, Jung-Chun
PY - 2023
Y1 - 2023
N2 - Gut dysbiosis-altered metabolite association exhibits specific and convincing utility to differentiate CKD associated with distinct pathogenic factor. These results present the validity of pathogenesis-associated markers across healthy participants and high-risk population toward the early screening, prevention, diagnosis, or personalized treatment of CKD. The intimate correlation of chronic kidney disease (CKD) with structural alteration in gut microbiota or metabolite profile has been documented in a growing body of studies. Nevertheless, a paucity of demonstrated knowledge regarding the impact and underlying mechanism of gut microbiota or metabolite on occurrence or progression of CKD is unclarified thus far. In this study, a liquid chromatography coupled-mass spectrometry and long-read sequencing were applied to identify gut metabolites and microbiome with statistically-discriminative abundance in diabetic CKD patients (n = 39), hypertensive CKD patients (n = 26), or CKD patients without comorbidity (n = 40) compared to those of healthy participants (n = 60). The association between CKD-related species and metabolite was evaluated by using zero-inflated negative binomial (ZINB) regression. The predictive utility of identified operational taxonomic units (OTUs), metabolite, or species-metabolite association toward the diagnosis of incident chronic kidney disease with distinct pathogenic factor was assessed using the random forest regression model and the receiver operating characteristic (ROC) curve. The results of statistical analyses indicated alterations in the relative abundances of 26 OTUs and 41 metabolites that were specifically relevant to each CKD-patient group. The random forest regression model with only species, metabolites, or its association differentially distinguished the hypertensive, diabetic CKD patients, or enrolled CKD patients without comorbidity from the healthy participants. IMPORTANCE Gut dysbiosis-altered metabolite association exhibits specific and convincing utility to differentiate CKD associated with distinct pathogenic factor. These results present the validity of pathogenesis-associated markers across healthy participants and high-risk population toward the early screening, prevention, diagnosis, or personalized treatment of CKD.
AB - Gut dysbiosis-altered metabolite association exhibits specific and convincing utility to differentiate CKD associated with distinct pathogenic factor. These results present the validity of pathogenesis-associated markers across healthy participants and high-risk population toward the early screening, prevention, diagnosis, or personalized treatment of CKD. The intimate correlation of chronic kidney disease (CKD) with structural alteration in gut microbiota or metabolite profile has been documented in a growing body of studies. Nevertheless, a paucity of demonstrated knowledge regarding the impact and underlying mechanism of gut microbiota or metabolite on occurrence or progression of CKD is unclarified thus far. In this study, a liquid chromatography coupled-mass spectrometry and long-read sequencing were applied to identify gut metabolites and microbiome with statistically-discriminative abundance in diabetic CKD patients (n = 39), hypertensive CKD patients (n = 26), or CKD patients without comorbidity (n = 40) compared to those of healthy participants (n = 60). The association between CKD-related species and metabolite was evaluated by using zero-inflated negative binomial (ZINB) regression. The predictive utility of identified operational taxonomic units (OTUs), metabolite, or species-metabolite association toward the diagnosis of incident chronic kidney disease with distinct pathogenic factor was assessed using the random forest regression model and the receiver operating characteristic (ROC) curve. The results of statistical analyses indicated alterations in the relative abundances of 26 OTUs and 41 metabolites that were specifically relevant to each CKD-patient group. The random forest regression model with only species, metabolites, or its association differentially distinguished the hypertensive, diabetic CKD patients, or enrolled CKD patients without comorbidity from the healthy participants. IMPORTANCE Gut dysbiosis-altered metabolite association exhibits specific and convincing utility to differentiate CKD associated with distinct pathogenic factor. These results present the validity of pathogenesis-associated markers across healthy participants and high-risk population toward the early screening, prevention, diagnosis, or personalized treatment of CKD.
U2 - 10.1128/spectrum.02805-22
DO - 10.1128/spectrum.02805-22
M3 - 文章
SN - 2165-0497
VL - 11
SP - e02805-22
JO - Microbiology spectrum
JF - Microbiology spectrum
IS - 1
ER -