Evidence map›Paper›PMID 29233175›Full record

ArticleBMC research notes2017

Exome sequencing of multiple-sclerosis patients and their unaffected first-degree relatives.

Sheila Garcia-Rosa, Maria Galli de Amorim, Renan Valieris, Vanessa Daccach Marques, Julio Cesar Cetrulo Lorenzi, Vania Balardin Toller, Guilherme Sciascia do Olival, Wilson Araújo da Silva Júnior, Israel Tojal da Silva, Amilton Antunes Barreira and 2 more

Abstract read
In one paragraph

Article in BMC research notes, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Frontiers in genetics · 2019
    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

12 authors.

Sheila Garcia-RosaLab. of Medical Genomics, International Research Center, A.C.Camargo Cancer Center, Rua Taguá 440, 1st Floor, São Paulo, SP, 01508-010, Brazil.
Maria Galli de AmorimLab. of Medical Genomics, International Research Center, A.C.Camargo Cancer Center, Rua Taguá 440, 1st Floor, São Paulo, SP, 01508-010, Brazil.
Renan ValierisLaboratory of Computational Biology and Bioinformatics, International Research Center, A.C.Camargo Cancer Center, Rua Taguá 440, 1st Floor, São Paulo, SP, 01508-010, Brazil.
Vanessa Daccach MarquesDepartment of Neurosciences, Clinical Neuroimmunology Division, Medical School and Hospital das Clínicas of Ribeirão Preto, University of São Paulo (USP), Avenida Bandeirantes, 3900, Ribeirão Preto, SP, 14049-900, Brazil.
Julio Cesar Cetrulo LorenziCenter for Medical Genomics, HCFMRP/USP, Avenida Bandeirantes, 3900, Ribeirão Preto, SP, 14049-900, Brazil.
Vania Balardin TollerNeurosciences Research Group, Faculdade de Ciências Médicas da Santa Casa de São Paulo, Rua Doutor Cesário Motta Júnior, 61 - Vila Buarque, São Paulo, SP, 01221-020, Brazil.
Guilherme Sciascia do OlivalNeurosciences Research Group, Faculdade de Ciências Médicas da Santa Casa de São Paulo, Rua Doutor Cesário Motta Júnior, 61 - Vila Buarque, São Paulo, SP, 01221-020, Brazil.
Wilson Araújo da Silva JúniorCenter for Medical Genomics, HCFMRP/USP, Avenida Bandeirantes, 3900, Ribeirão Preto, SP, 14049-900, Brazil.
Israel Tojal da SilvaLaboratory of Computational Biology and Bioinformatics, International Research Center, A.C.Camargo Cancer Center, Rua Taguá 440, 1st Floor, São Paulo, SP, 01508-010, Brazil.
Amilton Antunes BarreiraDepartment of Neurosciences, Clinical Neuroimmunology Division, Medical School and Hospital das Clínicas of Ribeirão Preto, University of São Paulo (USP), Avenida Bandeirantes, 3900, Ribeirão Preto, SP, 14049-900, Brazil.
Diana Noronha NunesLab. of Medical Genomics, International Research Center, A.C.Camargo Cancer Center, Rua Taguá 440, 1st Floor, São Paulo, SP, 01508-010, Brazil.
Emmanuel Dias-NetoLab. of Medical Genomics, International Research Center, A.C.Camargo Cancer Center, Rua Taguá 440, 1st Floor, São Paulo, SP, 01508-010, Brazil. emmanuel@cipe.accamargo.org.br.ORCID http://orcid.org/0000-0001-5670-8559

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 480138/2013-3Fundação de Amparo à Pesquisa do Estado de São Paulo 2013/24293-7
6 · The paper itself

Abstract

objectivesThe understanding of complex multifactorial diseases requires the availability of a variety of data for a large-number of affected individuals. In this data note here we provide whole exome sequencing data from a set of non-familiar multiple-sclerosis (MS) patients as well as their unaffected first-degree relatives. This data might help the identification of genomic alterations, including single nucleotide polymorphisms, de novo variations and structural genomic variations, such as copy-number alterations that may impact this disease. DATA DESCRIPTION: This dataset comprises the full exome of 28 Brazilian subjects grouped in eight distinct families, consisting of four complete trios (mother-patient-father) plus another four complete trios with one added unaffected sibling. In total, we present the full exome data of eight patients diagnosed with recurrent remittent multiple sclerosis. Diagnoses were made by experienced neurologists and all enrolled patients had at least 5 years of follow up and specific MS treatment. Exomes were sequenced from leukocyte-derived DNA, after the capture of exons using biotinylated probes, in the Ion Proton platform. For each exome we generated an average of 66.1 million good quality mapped reads with an average length of ~ 160nt. On average, for 90% of the exome a vertical coverage above 20× was reached.

Indexed as

FamilyDatabases, GeneticExomeExome SequencingHumansMultiple Sclerosis‘de novo’InheritanceMultiple sclerosisRemittent-recurrentWhole exome sequencing

Identifiers

PMID29233175
PMCPMC5727932

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Registered trials

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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.