Evidence map›Paper›PMID 36303234›Full record

ArticleJournal of ovarian research2022

Alterations of bacteriome, mycobiome and metabolome characteristics in PCOS patients with normal/overweight individuals.

Guoshu Yin, Fu Chen, Guishan Chen, Xiaoping Yang, Qingxia Huang, Lan Chen, Minjie Chen, Weichun Zhang, Miaoqiong Ou, Man Cao and 6 more

Open access · goldAbstract read
In one paragraph

Article in Journal of ovarian research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 3 pooled it
2.3field-weighted citation impact, top 10% of its field
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

19 citing papers in PubMed, 3 syntheses or guidelines pooled it, 27 citations in OpenAlex.

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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

16 authors at 4 institutions in 1 country.

Guoshu Yin *Department of Endocrinology, the First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China. yinguoshu@126.com.
Fu Chen *Department of Clinical Nutrition, the First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Guishan ChenDepartment of Endocrinology, the First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Xiaoping YangDepartment of Endocrinology, the First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Qingxia HuangDepartment of Endocrinology, the First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Lan ChenDepartment of Endocrinology, the First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Minjie ChenDepartment of Endocrinology, Chaoyang Dafeng Hospital, Shantou, 515154, China.
Weichun ZhangDepartment of Endocrinology, the First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Miaoqiong OuDepartment of Clinical Nutrition, the First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Man CaoDepartment of Mathematics and Numerical Simulation and High-Performance Computing Laboratory, School of Sciences, Nanchang University, Nanchang, 330031, China.
Hong LinDepartment of Reproductive Center, the First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Man ChenDepartment of Reproductive Center, the First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Hongzhi XuInstitute for Microbial Ecology, School of Medicine, Xiamen University, Xiamen, 361005, China.
Jianlin RenInstitute for Microbial Ecology, School of Medicine, Xiamen University, Xiamen, 361005, China. renjianl@xmu.edu.cn.
Yongsong ChenDepartment of Endocrinology, the First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China. yongsongchen@126.com.
Zhangran ChenInstitute for Microbial Ecology, School of Medicine, Xiamen University, Xiamen, 361005, China. zhangran22105@163.com.
Shantou University · CNFirst Affiliated Hospital of Shantou University Medical College · CNXiamen University · CNNanchang University · CN

Funding

Guangdong Provincial Science and Technology Special Fund 210715106900958Medical Scientific Research Foundation of Guangdong Province of China A2020390National Natural Science Foundation of China 81200619National Natural Science Foundation of China 81900541
6 · The paper itself

Abstract

To characterize the gut bacteriome, mycobiome and serum metabolome profiles in polycystic ovary syndrome (PCOS) patients with normal/overweight individuals and evaluate a potential microbiota-related diagnostic method development for PCOS, 16S rRNA and ITS2 gene sequencing using 88 fecal samples and 87 metabolome analysis from serum samples are conducted and PCOS classifiers based on multiomics markers are constructed. There are significant bacterial, fungal community and metabolite differences among PCOS patients and healthy volunteers with normal/overweight individuals. Healthy individuals with overweight/obesity display less abnormal metabolism than PCOS patients and uniquely higher abundance of the fungal genus Mortierella. Nine bacterial genera, 4 predicted pathways, 11 fungal genera and top 30 metabolites are screened out which distinguish PCOS from healthy controls, with AUCs of 0.84, 0.64, 0.85 and 1, respectively. The metabolite-derived model is more accurate than the microbe-based model in discriminating normal BMI PCOS (PCOS-LB) from normal BMI healthy (Healthy-LB), PCOS-HB from Healthy-HB. Featured bacteria, fungi, predicted pathways and serum metabolites display higher associations with free androgen index (FAI) in the cooccurrence network. In conclusion, our data reveal that hyperandrogenemia plays a central role in the dysbiosis of intestinal microecology and the change in metabolic status in patients with PCOS and that its effect exceeds the role of BMI. Healthy women with high BMI showed unique microbiota and metabolic features.The priority of predictive models in discriminating PCOS from healthy status in this study were serum metabolites, fungal taxa and bacterial taxa.

Indexed as

MycobiomePolycystic Ovary SyndromeBacteriaFemaleHumansMetabolomeOverweightRNA, Ribosomal, 16SRNA, Ribosomal, 16SDiagnostic modelMetabolomeMycobiomeObesityPCOS

Identifiers

PMID36303234
PMCPMC9613448
OpenAlexW4307434416

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.