Evidence map›Paper›PMID 35047120›Full record

ArticleWorld journal of diabetes2021

Molecular diagnosis of Kallmann syndrome with diabetes by whole exome sequencing and bioinformatic approaches.

Shuang-Shuang Sun, Rui-Xue Wang

Open access · diamondAbstract read
In one paragraph

Article in World journal of diabetes, 2021. 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
0.4field-weighted citation impact, top 32% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. A Novel HemizygousCase reports in endocrinology · 2026
    Article
  2. Article
  3. Article
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

2 authors at 1 institution in 1 country.

Shuang-Shuang SunClinical Lab, Shanxi Provincial People's Hospital, Taiyuan 030012, Shanxi Province, China.
Rui-Xue WangClinical Lab, Shanxi Provincial People's Hospital, Taiyuan 030012, Shanxi Province, China. sss651897@163.com.
Shanxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKallmann syndrome (KS) is a hypogonadotropic hypogonadism accompanied by anosmia or hyposmia. It is associated with the low secretion of gonadotropins which can lead to other abnormal endocrine metabolism disorders such as diabetes. Through genetic and molecular biological methods, more than 10 KS pathogenic genes have been found.

aimTo identify the existing mutation sites of KS with diabetes and reveal the relationship between genotype and phenotype.

methodsWe studied KS pathogenesis through high-throughput exome sequencing on four diabetes' patients with KS for screening the potential pathogenic sites and exploring the genotype-phenotype correlation. Clinical data and peripheral blood samples were collected from the patients. White blood cells were separated and genomic DNA was extracted. High-throughput sequencing of all exons in the candidate pathogenic genes of probands was performed, and the results obtained were analyzed.

resultsSequencing revealed mutations in the KLB p.T313M, ANOS1 p.C172F, and IGSF10 gene (p.Lys1819Arg and p.Arg1035Thr) at different sites, which may have been associated with disease onset.

conclusionThe diagnosis of KS is challenging, especially in early puberty, and the clinical manifestations reflect physical delays in development and puberty. Timely diagnosis and treatment can induce puberty, thereby improving sexual, bone, metabolic and mental health.

Indexed as

ANOS1Bioinformatics analysisDiabetesIGSF10Kallmann syndromeKLBWhole-exome sequencing

Identifiers

PMID35047120
PMCPMC8696644
OpenAlexW4200304953

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.