Evidence map›Paper›PMID 35946057›Full record

ArticleMolecular genetics & genomic medicine2022

Distribution and transmission of copy number variations of uncertain significance in 105 trios.

Qiang Wen, Xiu Wang, Hao Zhang, Xiaoyan Liu, Zhihong Xu

Open access · goldAbstract read
In one paragraph

Article in Molecular genetics & genomic medicine, 2022. 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
0.8field-weighted citation impact, top 26% 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, 3 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Qiang WenDepartment of Reproductive Genetics, Deyang People's Hospital, Deyang, China.ORCID 0000-0002-3822-2034
Xiu WangDepartment of Reproductive Genetics, Deyang People's Hospital, Deyang, China.
Hao ZhangDepartment of Reproductive Genetics, Deyang People's Hospital, Deyang, China.
Xiaoyan LiuDepartment of Reproductive Genetics, Deyang People's Hospital, Deyang, China.
Zhihong XuDepartment of Reproductive Genetics, Deyang People's Hospital, Deyang, China.
Deyang Stomatological Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe distribution and genetic characteristics of copy number variations (CNVs) remain unclear. Here, we investigated the distribution and transmission of CNVs of uncertain significance in fetuses.

methodsLow-coverage massively parallels CNV sequencing of 105 families (parents and their fetuses) was performed to identify fetal CNVs of uncertain significance.

resultsIn the 105 fetuses, 176 CNVs of uncertain significance were detected, and the average number of CNVs carried by fetuses was 1.68 ± 0.80. Among the CNVs carried by the fetuses, 79.8% were inherited (~90.0% of the fetuses) and 20.2% were new mutations (~30.0% of the fetuses). We found that 58.9% CNVs were of maternal origin and 41.1% were of paternal origin. Among the CNV subtypes, de novo CNV distribution was significantly different from inherited CNV distribution. There was no difference in the distribution of maternal and paternal CNV subtypes in the fetuses. The proportion of microdeletions (36.7%) and microduplications (63.3%) was similar in the fetuses and parents. Furthermore, we found that when parents carried more CNVs of uncertain significance, the chance of passing them on to their offspring decreased.

conclusionThis study deepens our understanding of the genetic mechanisms associated with CNV transmission to assist clinicians in prenatal counseling.

Indexed as

DNA Copy Number VariationsFetusFemaleHumansPregnancyCNVs of uncertain significancecopy number variationdistributionheredityprenatal counseling

Identifiers

PMID35946057
PMCPMC9482387
OpenAlexW4292661146

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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.