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Biomarkers for end-stage renal disease and application thereof

A technology for end-stage renal disease and microorganisms, which can be used in the determination/examination of microorganisms, biochemical equipment and methods, etc., and can solve problems such as end-stage renal disease that needs to be improved.

Pending Publication Date: 2020-03-13
深圳谱元科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the microbial sources of ESRD-associated metabolites such as uremic toxins and the mechanisms underlying gut microbiota-mediated changes in the ESRD metabolome are understudied, which could yield therapeutic insights
Current research on end-stage renal disease (ESRD) leaves room for improvement

Method used

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  • Biomarkers for end-stage renal disease and application thereof
  • Biomarkers for end-stage renal disease and application thereof
  • Biomarkers for end-stage renal disease and application thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0043] Example 1: Sample Collection

[0044] 223 hemodialysis patients (21-72 years old) were recruited from four hemodialysis centers in Beijing, China. All participants were diagnosed with end-stage renal disease (ESRD) according to Improving Kidney Outcomes Global Organization (KDIGO) clinical practice guidelines and on stable hemodialysis (1-3 times per week). Among the 223 patients with ESRD, 77 cases (34.5%) of glomerulonephritis, 73 cases (32.7%) of end-stage renal disease, 32 cases (14.3%) of hypertensive nephrosclerosis, 6 cases (2.7%) of polycystic kidney disease, interim There were 12 cases (5.4%) of qualitative nephritis, 5 cases (2.2%) of kidney transplantation failure, and 19 cases (8.5%) of unexplained renal failure.

[0045] The control group (26-71 years old, 18.5<BMI<29.9kg / m2) included 69 healthy volunteers who went to Beijing Aerospace Center Hospital for physical examination every year. Exclusion criteria for the control group included hypertension, end-...

Embodiment 2

[0046] Example 2: DNA extraction and sequencing

[0047] 2.1 Collection and storage of fecal samples

[0048] Collect fresh stool at home or in the hospital. All participants were asked to defecate on a special collection paper (developed by Aiken Chemical Co., Ltd., Japan) and separate the feces in sterile test tubes. Put the fresh feces in the test tube into the ice pack, and send it to the laboratory within 2 hours after putting in the ice pack. Soak a stool sample in sterile DNA protection solution (pH 5.2, 0.01mol / L EDTA, 0.025mol / L Na 3 C 6 H 5 O 7 and 5.3mol / L Na 2 SO 4 ) tubes at 4°C until DNA extraction and metagenomic analysis. Other stool samples were immediately frozen and stored at −80°C until use.

[0049] 2.2 DNA extraction

[0050] Total DNA was extracted from approximately 180-200 mg of feces using standard methods. Fresh genomic DNA samples were mechanically fragmented to ~400 bp with Bio.orPico (Dia.de, Belgium). DNA fragments were selected using...

Embodiment 3

[0053] Example 3: Identification of biomarkers

[0054] 3.1 Basic processing of sequencing data

[0055] Under the sequencing platform, the basic processing of WMS data is performed based on the default parameters of the system. Low-quality reads were defined as containing: 1) reads with an estimated error rate >1% for more than 30% of bases; or 2) ambiguous "N" >15 bp. These reads are deleted in pairs. Human genomic DNA reads were identified by SOAP2 and removed if they shared >95% of their sequence with the human genome reference sequence (hg19).

[0056] 3.2 Update gene catalog

[0057] A new gene catalog was established based on the WMS data of all samples. High-quality WMS data were assembled and gene prediction was performed using IDBA-UD (version 1.1.2). If any two genes from different samples have a similarity of 95% or more in 90% of the regions, the shorter gene will be listed as a redundant gene. After removing all redundant genes, we obtained a non-redundant ...

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Abstract

The invention brings forward biomarkers for end-stage renal disease and an application thereof. The biomarkers for end-stage renal disease are Akkermansia muciniphila, Alistipes finegoldii, Alistipesshahii, Bacteroides fibrobacter, Bacteroides fragilis, Bifidobacterium dentium, Clostridium difficile, Clostridium saccharolyticum, Desulfovibrio Vulgaris, Eggerthella lenta, Enterococcus faecalis, Enterococcus faecium, Flavonifractor plautii, Fusobacterium nucleatum, butyric acid-producing enterobacteriaceae, Lactobacillus amylovorus, Lactobacillus casei, Lactobacillus fermentum, Lactobacillus plantarum, Streptococcus infantarius, Streptococcus thermophilus, butyrate-producing bacteria, Eubacterium rectal and Faecalibacterium prausnitzi. Whether a subject suffers from or is susceptible to end-stage renal disease can be effectively determined by determining these microbial markers in the intestinal flora of the subject.

Description

technical field [0001] The invention relates to the field of biomedicine, and specifically relates to end-stage renal disease biomarkers and applications thereof. Background technique [0002] End-stage renal disease (ESRD), a late consequence of chronic kidney disease (CKD), is one of the leading causes of morbidity and mortality worldwide. Currently, the cost of ESRD treatment is staggering, exceeding $50 billion per year in the United States alone. The progression of CKD and its complications are closely related to the accumulation of toxic metabolites in circulation. A large fraction of these toxins are produced by gut microbes and are often not effectively removed by dialysis. In humans, clear associations between microbial composition, metabolic dysregulation, and chronic kidney disease have yet to be established. The markedly altered gut microbiome structure in CKD patients and the disrupted metabolic composition of blood and feces in patients with hemolytic ESRD s...

Claims

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Application Information

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IPC IPC(8): C12Q1/6883C12Q1/689
CPCC12Q1/6883C12Q1/689C12Q2600/106C12Q2600/136
Inventor 覃俊杰李胜辉李少川梁芳
Owner 深圳谱元科技有限公司
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