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| Status |
Public on Jan 10, 2025 |
| Title |
Eggerthella lenta Down Regulated Flavone and Flaconol Biosynthesis Promoted Kawasaki Disease |
| Organism |
human feces metagenome |
| Experiment type |
Other
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| Summary |
Kawasaki Disease (KD) is a multisystemic vasculitis of unknown etiology in children. The incidence of KD varies by geographic area and correlates with differences in gut microbiota patterns, with the highest incidence in Asian. This study aimed to investigate alterations in fecal microbiota and assess their relationship with systemic inflammation in KD patients. A total of 59 patients and 55 matched controls were included. Fecal samples were collected at the onset of KD. The V3/V4 regions of 16S rDNA were sequenced using the MiSeq platform. PICRUSt 2 was used to analyze the potential functional pathways involved in gut dysbiosis. Alpha (p<0.042) and beta (p<0.001) diversity in KD were significantly decreased when compared to the control group. After multivariate regression, among the seven critical microbes, increased Bacteroides ovtaus (p=0.016) and decreased Eggerthella lenta (p=0.014) could also predict KD risk using receiver operating characteristic curve (ROC) analysis (Eggerthella lenta: area under the ROC curve, AUC=0.841, odds ratio=23.956; Bacteroides ovatus: AUC=0.816, odds ratio=31.365). Notably, Bacteroides ovatus was positively correlated with blood segment cells (p=0.006), but negatively correlated with blood lymphocytes (p=0.013). After multivariate regression, flavone and flavonol biosynthesis decreased in children with KD (p<0.001). Our results indicated that both Bacteroides ovatus and Eggerthella lenta may deregulate flavone and flavonol biosynthesis, consequently modulating immune cells and potentially triggering KD. This study suggests that alterations in the gut microbiota are closely associated with immune responses and provides a new perspective on the etiology, pathogenesis, and treatment of KD.
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| Overall design |
A total of 59 patients and 55 matched controls were included. Fecal samples were collected at the onset of KD. The V3/V4 regions of 16S rDNA were sequenced using the MiSeq platform. PICRUSt 2 was used to analyze the potential functional pathways involved in gut dysbiosis.
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| Contributor(s) |
Yeh Y, Chen K, Huang C, Kuo H |
| Citation missing |
Has this study been published? Please login to update or notify GEO. |
| |
| Submission date |
Jan 06, 2025 |
| Last update date |
Jan 10, 2025 |
| Contact name |
Kuang-Den Chen |
| E-mail(s) |
dennis8857@gmail.com
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| Organization name |
Kaohsiung Chang Gung Memorial Hospital
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| Department |
Translational Research Center in Biomedical Sicences
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| Lab |
Liver transplantation lab
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| Street address |
123, Ta-Pei Rd., Niao-Sung Dist.
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| City |
Kaohsiung |
| ZIP/Postal code |
83342 |
| Country |
Taiwan |
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| Platforms (1) |
| GPL29470 |
Illumina MiSeq (human feces metagenome) |
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| Samples (114)
|
| GSM8713008 |
NC, C13 |
| GSM8713009 |
NC, C16 |
| GSM8713010 |
NC, C18 |
| GSM8713011 |
NC, C20 |
| GSM8713012 |
NC, C21 |
| GSM8713013 |
NC, C22 |
| GSM8713014 |
NC, C27 |
| GSM8713015 |
NC, C2 |
| GSM8713016 |
NC, C30 |
| GSM8713017 |
NC, C31 |
| GSM8713018 |
NC, C32 |
| GSM8713019 |
NC, C5 |
| GSM8713020 |
NC, C6 |
| GSM8713021 |
NC, C7 |
| GSM8713022 |
NC, S11 |
| GSM8713023 |
NC, S14 |
| GSM8713024 |
NC, S18 |
| GSM8713025 |
NC, S19 |
| GSM8713026 |
NC, S1 |
| GSM8713027 |
NC, S3 |
| GSM8713028 |
NC, S4 |
| GSM8713029 |
NC, S50 |
| GSM8713030 |
NC, S5 |
| GSM8713031 |
NC, S6 |
| GSM8713032 |
NC, S7 |
| GSM8713033 |
NC, S7-1 |
| GSM8713034 |
NC, S8 |
| GSM8713035 |
NC, S9 |
| GSM8713036 |
NC, SC29 |
| GSM8713037 |
NC, SC31 |
| GSM8713038 |
NC, SC34 |
| GSM8713039 |
NC, SC35 |
| GSM8713040 |
NC, SC39 |
| GSM8713041 |
NC, SC43 |
| GSM8713042 |
NC, SC45 |
| GSM8713043 |
NC, SC46 |
| GSM8713044 |
NC, SC48 |
| GSM8713045 |
NC, SC49 |
| GSM8713046 |
NC, SC50 |
| GSM8713047 |
NC, SC51 |
| GSM8713048 |
NC, SC52 |
| GSM8713049 |
NC, SC53 |
| GSM8713050 |
NC, SC54 |
| GSM8713051 |
NC, SC55 |
| GSM8713052 |
NC, SC56 |
| GSM8713053 |
NC, SC57 |
| GSM8713054 |
NC, SC58 |
| GSM8713055 |
NC, SC59 |
| GSM8713056 |
NC, SC60 |
| GSM8713057 |
NC, SC61 |
| GSM8713058 |
NC, SC62 |
| GSM8713059 |
NC, SC63 |
| GSM8713060 |
KD, KD10 |
| GSM8713061 |
KD, KD11 |
| GSM8713062 |
KD, KD12 |
| GSM8713063 |
KD, KD13 |
| GSM8713064 |
KD, KD14 |
| GSM8713065 |
KD, KD15 |
| GSM8713066 |
KD, KD16 |
| GSM8713067 |
KD, KD17 |
| GSM8713068 |
KD, KD18 |
| GSM8713069 |
KD, KD19 |
| GSM8713070 |
KD, KD1 |
| GSM8713071 |
KD, KD20 |
| GSM8713072 |
KD, KD2 |
| GSM8713073 |
KD, KD3 |
| GSM8713074 |
KD, KD41 |
| GSM8713075 |
KD, KD42 |
| GSM8713076 |
KD, KD43 |
| GSM8713077 |
KD, KD44 |
| GSM8713078 |
KD, KD49 |
| GSM8713079 |
KD, KD4 |
| GSM8713080 |
KD, KD50 |
| GSM8713081 |
KD, KD51 |
| GSM8713082 |
KD, KD52 |
| GSM8713083 |
KD, KD53 |
| GSM8713084 |
KD, KD54 |
| GSM8713085 |
KD, KD55 |
| GSM8713086 |
KD, KD56 |
| GSM8713087 |
KD, KD57 |
| GSM8713088 |
KD, KD58 |
| GSM8713089 |
KD, KD59 |
| GSM8713090 |
KD, KD5 |
| GSM8713091 |
KD, KD60 |
| GSM8713092 |
KD, KD6 |
| GSM8713093 |
KD, KD73 |
| GSM8713094 |
KD, KD74 |
| GSM8713095 |
KD, KD75 |
| GSM8713096 |
KD, KD76 |
| GSM8713097 |
KD, KD77 |
| GSM8713098 |
KD, KD78 |
| GSM8713099 |
KD, KD79 |
| GSM8713100 |
KD, KD80 |
| GSM8713101 |
KD, KD81 |
| GSM8713102 |
KD, KD82 |
| GSM8713103 |
KD, KD83 |
| GSM8713104 |
KD, KD84 |
| GSM8713105 |
KD, KD85 |
| GSM8713106 |
KD, KD86 |
| GSM8713107 |
KD, KD87 |
| GSM8713108 |
KD, KD8 |
| GSM8713109 |
KD, 1164-1 |
| GSM8713110 |
KD, 1170-1 |
| GSM8713111 |
KD, 1180-1 |
| GSM8713112 |
KD, 1190-1 |
| GSM8713113 |
KD, 1196-1 |
| GSM8713114 |
KD, 1199-1 |
| GSM8713115 |
KD, 1200-1 |
| GSM8713116 |
KD, 1209-1 |
| GSM8713117 |
KD, 1211-1 |
| GSM8713118 |
KD, 1218-1 |
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| Relations |
| BioProject |
PRJNA1207020 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE285935_20241231-Processed-with_taxonomy_table.xlsx |
4.0 Mb |
(ftp)(http) |
XLSX |
SRA Run Selector |
| Raw data are available in SRA |
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