Evidence map›Paper›PMID 34498116›Full record

ArticleHuman genetics2022

Revealing modifier variations characterizations for elucidating the genetic basis of human phenotypic variations.

Hong Sun, Xiaoping Lan, Liangxiao Ma, Junmei Zhou

Erratum issuedAbstract read
PubMed Publisher
In one paragraph

Article in Human genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. A novel mutation in theFrontiers in genetics · 2022
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Hong SunShanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, 200062, China. shpolor@163.com.
Xiaoping LanShanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, 200062, China.
Liangxiao MaCAS Key Laboratory of Computational Biology, Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200232, China.
Junmei ZhouShanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, 200062, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epistatic interactions complicate the identification of variants involved in phenotypic effect. In-depth knowledge in modifiers and in pathogenic variants would benefit the mechanistic studies on the genetic basis of complex traits. We systematically compared the modifier variants which have evidence of modifier effect with the pathogenic variants from multiple angles. Our study found that genomic loci of modifier variations differ from pathogenic loci in many aspects, such as population genetics statistics, epigenetic features, evolutionary characteristics and functional properties of the variations. Genes containing modifier variation(s) exhibit higher probability of being haploinsufficient and higher probability of recessive disease causation, and they are relatively more important in network communication. Furthermore, we reinforced that co-expression analysis is an effective methodology to predict functional associations between modifier genes and their potential target genes. In many aspects, we detected statistically significant differences between modifier variants/genes and pathogenic variants/genes, and investigated relationships between modifiers and their potential targets. Our results offer some actionable insights that may provide appropriate guidelines to clinical genetics and researchers to elucidate the molecular mechanism underlying the human phenotypic variation.

Indexed as

Biological Variation, PopulationGenes, ModifierHumans

Identifiers

What OpenQuestion holds

Textmetadata
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.