Evidence map›Paper›PMID 34054914›Full record

ArticleFrontiers in genetics2021

Genetic Landscape of Rare Autoinflammatory Disease Variants in Qatar and Middle Eastern Populations Through the Integration of Whole-Genome and Exome Datasets.

Parul Sharma, Abhinav Jain, Vinod Scaria

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2021. 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
0.2field-weighted citation impact, top 48% 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

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
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  3. Journal of medicine and life · 2024
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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

3 authors at 2 institutions in 1 country.

Parul SharmaCenter for Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
Abhinav JainCSIR-Institute of Genomics and Integrative Biology, New Delhi, India.
Vinod ScariaCenter for Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
Institute of Genomics and Integrative Biology · INIndraprastha Institute of Information Technology Delhi · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rare monogenic autoinflammatory diseases are a group of recurrent inflammatory genetic disorders caused due to genetic variants in over 37 genes. While a number of these disorders have been identified and reported in Middle Eastern populations, the carrier frequency of these genetic variants in the Middle Eastern population is not known. The availability of whole-genome and exome datasets of over 1,000 individuals from Qatar persuaded us to explore the genetic epidemiology of rare autoinflammatory genetic variants. We have systematically analyzed genetic variants in genome-scale datasets from Qatar with a compendium of variants associated with autoinflammatory diseases. The variants were systematically reclassified according to the American College of Medical Genetics and Genomics guidelines for interpretation of variant pathogenicity. Our analysis identified seven pathogenic and likely pathogenic variants with significant differences in their allele frequencies compared to the global population. The cumulative carrier frequency of these variants was found to be 2.58%. Furthermore, our analysis revealed that five genes, implicated in rare autoinflammatory diseases, were under natural selection. To the best of our knowledge, this is the first and most comprehensive study on the population-scale analysis and genetic epidemiology of genetic variants that cause rare autoinflammatory disease in Middle Eastern populations.

Indexed as

autoinflammatory diseaseepidemiologygenomeMiddle EastQatar

Identifiers

PMID34054914
PMCPMC8155677
OpenAlexW3162789978

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.