Evidence map›Paper›PMID 25023003›Full record

ArticleGenetics research2014

Novel candidate genes putatively involved in stress fracture predisposition detected by whole-exome sequencing.

Eitan Friedman, Daniel S Moran, Danny Ben-Avraham, Ran Yanovich, Gil Atzmon

Abstract read
In one paragraph

Article in Genetics research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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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

11 citing papers in PubMed.

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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.

Eitan FriedmanSusanne Levy Gertner Oncogenetics Unit,The Danek Gertner Institute of Human Genetics,Chaim Sheba Medical Center, 52621 Tel-Hashomer,Israel.
Daniel S MoranAriel University,Ariel, Samaria,Israel.
Danny Ben-AvrahamDepartments of Medicine and Genetics,Albert Einstein College of Medicine,Bronx, NY 10463,USA.
Ran YanovichHeller Institute,Sheba Medical Center, 52621 Tel-Hashomer,Israel.
Gil AtzmonDepartments of Medicine and Genetics,Albert Einstein College of Medicine,Bronx, NY 10463,USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While genetic factors in all likelihood contribute to stress fracture (SF) pathogenesis, a few studies focusing on candidate genes have previously been reported. The objective of this study is to gain better understanding on the genetic basis of SF in a gene-naive manner. Exome sequence capture followed by massive parallel sequencing of two pooled DNA samples from Israeli combat soldiers was employed: cases with high grade SF and ethnically matched healthy controls. The resulting sequence variants were individually verified using the Sequenom™ platform and the contribution of the genetic alterations was validated in a second cohort of cases and controls. In the discovery set that included DNA pool of cases (n = 34) and controls (n = 60), a total of 1174 variants with >600 reads/variant/DNA pool were identified, and 146 (in 127 genes) of these exhibited statistically significant (P < 0·05) different rates between SF cases and controls after multiple comparisons correction. Subsequent validation of these 146 sequence variants individually in a total of 136 SF cases and 127 controls using the Sequenom™ platform validated 20/146 variants. Of these, three missense mutations (rs7426114, rs4073918, rs3752135 in the NEB, SLC6A18 and SIGLEC12 genes, respectively) and three synonymous mutations (rs2071856, rs2515941, rs716745 in the ELFN2, GRK4, LRRC55 genes) displayed significant different rates in SF cases compared with controls. Exome sequencing seemingly unravelled novel candidate genes as involved in SF pathogenesis and predisposition.

Indexed as

Genetic Predisposition to DiseaseHigh-Throughput Nucleotide SequencingAdolescentAdultBiomarkersCase-Control StudiesExomeFractures, StressHumansMaleMutationSignal TransductionYoung AdultBiomarkers

Identifiers

PMID25023003
PMCPMC7045058

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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.