Evidence map›Paper›PMID 24476040›Full record

ArticleBMC genetics2014

Evaluation of a target region capture sequencing platform using monogenic diabetes as a study-model.

Rui Gao, Yanxia Liu, Anette Prior Gjesing, Mette Hollensted, Xianzi Wan, Shuwen He, Oluf Pedersen, Xin Yi, Jun Wang, Torben Hansen

Abstract readEvaluation Study
In one paragraph

Article in BMC genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
–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

32 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Review
  5. Article
  6. Identification of pathogenicMolecular genetics and metabolism reports · 2023
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  10. Recognition of maturity-onset diabetes of the young in China.Journal of diabetes investigation · 2021
    Article
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  17. Maturity-Onset Diabetes of the Young Identified Among Algerian Probands with Early-Onset Diabetes.Diabetes, metabolic syndrome and obesity : targets and therapy · 2020
    Article
  18. Article
  19. Article
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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

10 authors.

Rui Gao
Yanxia Liu
Anette Prior Gjesing
Mette Hollensted
Xianzi Wan
Shuwen He
Oluf Pedersen
Xin YiBGI-Shenzhen, Shenzhen, China. yix@genomics.cn.
Jun Wang
Torben Hansen

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMonogenic diabetes is a genetic disease often caused by mutations in genes involved in beta-cell function. Correct sub-categorization of the disease is a prerequisite for appropriate treatment and genetic counseling. Target-region capture sequencing is a combination of genomic region enrichment and next generation sequencing which might be used as an efficient way to diagnose various genetic disorders. We aimed to develop a target-region capture sequencing platform to screen 117 selected candidate genes involved in metabolism for mutations and to evaluate its performance using monogenic diabetes as a study-model.

resultsThe performance of the assay was evaluated in 70 patients carrying known disease causing mutations previously identified in HNF4A, GCK, HNF1A, HNF1B, INS, or KCNJ11. Target regions with a less than 20-fold sequencing depth were either introns or UTRs. When only considering translated regions, the coverage was 100% with a 50-fold minimum depth. Among the 70 analyzed samples, 63 small size single nucleotide polymorphisms and indels as well as 7 large deletions and duplications were identified as being the pathogenic variants. The mutations identified by the present technique were identical with those previously identified through Sanger sequencing and Multiplex Ligation-dependent Probe Amplification.

conclusionsWe hereby demonstrated that the established platform as an accurate and high-throughput gene testing method which might be useful in the clinical diagnosis of monogenic diabetes.

Indexed as

Diabetes Mellitus, Type 2DNA Mutational AnalysisGene DuplicationHumansINDEL MutationPolymorphism, Single NucleotideSequence Deletion

Identifiers

PMID24476040
PMCPMC3943834

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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.