Evidence map›Paper›PMID 32309442›Full record

ArticleBioMed research international2020

Genetic Variations in miR-30 Family Member Regulatory Regions Are Associated with Breast Cancer Risk in a Chinese Population.

Jing Zhou, Lijuan Wang, Sijun Liu, Wen Zhou, Yue Jiang, Jiangbo Du, Juncheng Dai, Guangfu Jin, Hongxia Ma, Zhibin Hu and 2 more

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 64% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Review
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

12 authors at 2 institutions in 1 country.

Jing ZhouDepartment of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.ORCID https://orcid.org/0000-0001-7250-0520
Lijuan WangDepartment of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Sijun LiuDepartment of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, Nanjing, China.
Wen ZhouDepartment of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Yue JiangDepartment of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Jiangbo DuDepartment of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Juncheng DaiDepartment of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.ORCID https://orcid.org/0000-0002-3909-5671
Guangfu JinDepartment of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Hongxia MaDepartment of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Zhibin HuDepartment of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.ORCID https://orcid.org/0000-0002-8277-5234
Jiaping ChenDepartment of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.ORCID https://orcid.org/0000-0002-1687-8112
Hongbing ShenDepartment of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.ORCID https://orcid.org/0000-0002-2581-5906
Nanjing Medical University · CNNorthern Jiangsu People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) of the miR-30 family are closely linked with tumor metastasis and play key roles in the complex malignant phenotypes of cancers by targeting many tumor-related genes. Deregulated expression of miR-30 family members has been commonly observed in breast cancer. However, associations between the genetic variants in the regulatory region of miR-30 family and the risk of breast cancer are still limited, especially in the Chinese Han population. In the present study, we conducted a case-control analysis wherein 1064 breast cancer patients and 1073 healthy controls underwent genotyping of 10 SNPs in the regulatory region of miR-30 family members. Multivariate logistic regression analyses illustrated that the rs763354 variant in the miR-30a regulatory region was linked with a significant decrease in breast cancer risk in an additive model (adjusted OR = 0.86, 95% CI: 0.75-0.98,

Indexed as

AdultAsian PeopleBreastBreast NeoplasmsCase-Control StudiesFemaleGene Expression Regulation, NeoplasticHumansMicroRNAsMiddle AgedPolymorphism, Single NucleotideRegulatory Sequences, Nucleic AcidRisk FactorsYoung AdultMicroRNAsMIRN30b microRNA, human

Identifiers

PMID32309442
PMCPMC7140140
OpenAlexW3013566830

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.