Evidence map›Paper›PMID 23170922›Full record

ArticleProteome science2012

An individual urinary proteome analysis in normal human beings to define the minimal sample number to represent the normal urinary proteome.

Xuejiao Liu, Chen Shao, Lilong Wei, Jindan Duan, Shuzhen Wu, Xuewang Li, Mingxi Li, Wei Sun

Abstract read
In one paragraph

Article in Proteome science, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. HBFP: a new repository for human body fluid proteome.Database : the journal of biological databases and curation · 2021
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Identification of a Three-Biomarker Panel in Urine for Early Detection of Pancreatic Adenocarcinoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2015
    Article
  12. Article
  13. Article
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xuejiao Liu *Department of Nephrology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifuyan, Wangfujing Street, Beijing, China.
Chen Shao *Department of Physiology and Pathophysiology, National Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences/School of Basic Medicine Peking Union Medical College, 5 Dong Dan San Tiao, Beijing, China.
Lilong WeiClinical laboratory, China-Japan Friendship Hospital, 2 Yinghua Dongjie, Hepingli, Beijing, China.
Jindan DuanCore facility of instrument, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences/School of Basic Medicine Peking Union Medical College, 5 Dong Dan San Tiao, Beijing, China.
Shuzhen WuCore facility of instrument, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences/School of Basic Medicine Peking Union Medical College, 5 Dong Dan San Tiao, Beijing, China.
Xuewang LiDepartment of Nephrology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifuyan, Wangfujing Street, Beijing, China.
Mingxi LiDepartment of Nephrology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifuyan, Wangfujing Street, Beijing, China.
Wei SunCore facility of instrument, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences/School of Basic Medicine Peking Union Medical College, 5 Dong Dan San Tiao, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

unlabelled

backgroundThe urinary proteome has been widely used for biomarker discovery. A urinary proteome database from normal humans can provide a background for discovery proteomics and candidate proteins/peptides for targeted proteomics. Therefore, it is necessary to define the minimum number of individuals required for sampling to represent the normal urinary proteome.

methodsIn this study, inter-individual and inter-gender variations of urinary proteome were taken into consideration to achieve a representative database. An individual analysis was performed on overnight urine samples from 20 normal volunteers (10 males and 10 females) by 1DLC/MS/MS. To obtain a representative result of each sample, a replicate 1DLCMS/MS analysis was performed. The minimal sample number was estimated by statistical analysis.

resultsFor qualitative analysis, less than 5% of new proteins/peptides were identified in a male/female normal group by adding a new sample when the sample number exceeded nine. In addition, in a normal group, the percentage of newly identified proteins/peptides was less than 5% upon adding a new sample when the sample number reached 10. Furthermore, a statistical analysis indicated that urinary proteomes from normal males and females showed different patterns. For quantitative analysis, the variation of protein abundance was defined by spectrum count and western blotting methods. And then the minimal sample number for quantitative proteomic analysis was identified.

conclusionsFor qualitative analysis, when considering the inter-individual and inter-gender variations, the minimum sample number is 10 and requires a balanced number of males and females in order to obtain a representative normal human urinary proteome. For quantitative analysis, the minimal sample number is much greater than that for qualitative analysis and depends on the experimental methods used for quantification.

Identifiers

PMID23170922
PMCPMC3544588

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.