Evidence map›Paper›PMID 35673428›Full record

ReviewJournal of diabetes and metabolic disorders2022

Meta-analysis of HNF1A-MODY3 variants among human population.

Rachna Behl, Nishtha Malhotra, Vinay Joshi, Shruti Poojary, Sanniya Middha, Shalini Gupta, Arinola B Olaonipekun, Ikechukwu Okoye, Bhushan Wagh, Dibyendu Biswas and 8 more

Abstract readReview
In one paragraph

Review in Journal of diabetes and metabolic disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Genetic Structure of Hereditary Forms of Diabetes Mellitus in Russia.International journal of molecular sciences · 2025
    Article
  5. Article
  6. Article
  7. 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

18 authors.

Rachna BehlDepartment of Biochemistry, Panjab University, Chandigarh, India.
Nishtha MalhotraNew Delhi, India.
Vinay JoshiBirla Institute of Technology, Rishikesh, India.
Shruti PoojaryMumbai, India.
Sanniya MiddhaDepartment of Biochemistry, Panjab University, Chandigarh, India.
Shalini GuptaGuru Nanak Khalsa College of Arts, Science and Commerce, Mumbai, India.
Arinola B OlaonipekunDepartment of Consumer and Food Sciences, The University of Pretoria, Pretoria, South Africa.
Ikechukwu OkoyeDepartment of Mathematical Sciences, Federal University Lokoja, Lokoja, Kogi State Nigeria.
Bhushan WaghMGM Institute Of Bioscience & Technology, Aurangabad, India.
Dibyendu BiswasJIS Institute of Advanced Studies and Research, Kolkata, India.
Chukwuemelie AginahDepartment of Physiology, Chukwuemeka Odumegwu Ojukwu University, Uli, Nigeria.
Bhavya SainiNew Delhi, India.
Chinaza NwanyaDepartment of Biochemistry, University of Lagos, Lagos, Nigeria.
Sopuluchukwu UgwuUniversity of Nigeria, Nsukka, Nigeria.
Modupe M AnthonyDepartment of Biochemistry, Federal University of Technology, Akure, Ondo State Nigeria.
Xuanyu S FangBoston, USA.
Ogunfile FolusoDepartment of Biochemistry and Molecular Biology, Obafemi Awolowo University, Ile-Ife, Osun State Nigeria.
Abdulrahman Tudu IbrahimFaculty of Chemistry, Warsaw University of Technology, 00-664 Warsaw, Poland.ORCID 0000-0003-2604-7467

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Previously, numerous case-control studies have highlighted variants responsible for Maturity onset diabetes of young (MODY). However, these studies have been conducted among diverse populations and hence yielded contradictory results. We, therefore, performed a meta-analysis to precisely find the association of SNPs with the disease for the HNF1A gene. Objective: Meta-analysis of clinically defined studies deciphering mutations in the HNF1A gene responsible for the development of MODY3 was conducted among various populations to determine associations using statistical approaches. Methods: The curation of 505 research articles published between the years 2000-2021 was carried out. Visualization of data-related protocols and statistical-analysis were conducted, which led to the identification of highly prevalent mutations among different populations (majorly Europe). Further comparison between the frequencies of the control (healthy population) and test (diseased population) dataset generated through curation was performed. Results: We identified nine MODY3 mutations (rs587776825, rs1169288, rs1800574, rs2464196, rs137853244, rs137853238, rs587780357, rs137853240 and rs137853243) at the genome-wide significance level ( Conclusion: This meta-analysis found significant associations of mutations in HNF1A with MODY3, consistent with previous studies. Our findings should help elucidate the mutations in a compiled form responsible for causing MODY3. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-022-00975-8.

Indexed as

HNF1AMeta-analysisMODY3Single nucleotide polymorphisms

Identifiers

PMID35673428
PMCPMC9167412

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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.