Evidence map›Paper›PMID 40089739›Full record

ArticleBMC medical ethics2025

A scoping review of human genetic resources management policies and databases in high- and middle-low-income countries.

Hongwei Liu, Yin Liu, Yanyan Zhao, Yingqi Ma, Qiong Chen, Huifang Xu, Xiaoyang Wang, Xiaoli Guo, Hong Wang, Zelong Chen and 2 more

Abstract readScoping Review
In one paragraph

Article in BMC medical ethics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Hongwei LiuThe Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Yin LiuThe Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Yanyan ZhaoThe Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Yingqi MaThe Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Qiong ChenThe Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Huifang XuThe Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Xiaoyang WangThe Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Xiaoli GuoThe Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Hong WangThe Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Zelong ChenThe Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Shaokai ZhangThe Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China. shaokaizhang@zzu.edu.cn.
Binbin HanThe Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China. zlyyhanbinbin2859@zzu.edu.cn.

Funding

Henan Province key research and development project 231111312200
6 · The paper itself

Abstract

backgroundThis review examines global human genetic resources management, focusing on genetic data policies and repositories in high- and middle-low-income countries.

methodsA comprehensive search strategy was employed across multiple databases, including official government websites and Google, to gather relevant literature on human genetic resources management policies and genetic resource databases. Documents were screened for relevance, focusing on high-income countries (United States, United Kingdom, Japan) and middle-low-income countries (China, India, Kenya). Data were extracted, coded, and analyzed to identify common themes and differences in genetic resource management practices.

resultsHigh-income countries benefit from robust legal frameworks and advanced technological infrastructures. The United States enforces the Health Insurance Portability and Accountability Act and the Genetic Information Nondiscrimination Act to protect privacy and facilitate data sharing, while Japan relies on the Act on the Protection of Personal Information and ethical guidelines. Additionally, high-income countries host a variety of genetic databases and biobanks that support scientific research. In contrast, middle-low-income countries like China, India, and Kenya are still developing their frameworks. China has regulations such as the Biosecurity Law and the Regulations on the Management of Human Genetic Resources, but still requires more unified standards. India's policies focus on genetic research and data protection through the Biological Diversity Act, while Kenya seeks to improve data management through the 2019 Data Protection Act.

conclusionSignificant disparities exist in human genetic resources management between high-income and middle-low-income countries. High-income countries have robust systems balancing privacy protection with research facilitation, supported by comprehensive and large-scale databases for scientific research. Middle-low-income countries need to enhance legal frameworks and build population-specific databases. Promoting equitable data sharing and adopting best practices from high-income countries are essential for advancing global scientific discovery and ensuring fair management of genetic resources.

Indexed as

Databases, GeneticDeveloped CountriesDeveloping CountriesGenetic PrivacyChinaHealth Insurance Portability and Accountability ActHumansIndiaInformation DisseminationJapanKenyaUnited KingdomUnited StatesDatabasesData sharing policiesHuman genetic resources

Identifiers

PMID40089739
PMCPMC11909912

What OpenQuestion holds

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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.