Evidence map›Paper›PMID 35932045›Full record

ArticleHuman genomics2022

1029 genomes of self-declared healthy individuals from India reveal prevalent and clinically relevant cardiac ion channelopathy variants.

Anjali Bajaj, Vigneshwar Senthivel, Rahul Bhoyar, Abhinav Jain, Mohamed Imran, Mercy Rophina, Mohit Kumar Divakar, Bani Jolly, Ankit Verma, Anushree Mishra and 8 more

Open access · goldAbstract read
In one paragraph

Article in Human genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

18 authors at 3 institutions in 1 country.

Anjali BajajCSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110025, India.
Vigneshwar SenthivelCSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110025, India.
Rahul BhoyarCSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110025, India.
Abhinav JainCSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110025, India.
Mohamed ImranCSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110025, India.
Mercy RophinaCSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110025, India.
Mohit Kumar DivakarCSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110025, India.
Bani JollyCSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110025, India.
Ankit VermaCSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110025, India.
Anushree MishraCSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110025, India.
Disha SharmaCSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110025, India.
Siddharthan DeeptiDepartment of Cardiology, All India Institute of Medical Sciences (AIIMS), New Delhi, 110029, India.
Gautam SharmaDepartment of Cardiology, All India Institute of Medical Sciences (AIIMS), New Delhi, 110029, India.
Raghav BansalDepartment of Cardiology, All India Institute of Medical Sciences (AIIMS), New Delhi, 110029, India.
Rakesh YadavDepartment of Cardiology, All India Institute of Medical Sciences (AIIMS), New Delhi, 110029, India.
Vinod ScariaCSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110025, India. vinods@igib.in.
Nitish NaikDepartment of Cardiology, All India Institute of Medical Sciences (AIIMS), New Delhi, 110029, India.
Sridhar SivasubbuCSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110025, India. sridhar@igib.in.
Institute of Genomics and Integrative Biology · INAcademy of Scientific and Innovative Research · INAll India Institute of Medical Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe prevalence and genetic spectrum of cardiac channelopathies exhibit population-specific differences. We aimed to understand the spectrum of cardiac channelopathy-associated variations in India, which is characterised by a genetically diverse population and is largely understudied in the context of these disorders.

resultsWe utilised the IndiGenomes dataset comprising 1029 whole genomes from self-declared healthy individuals as a template to filter variants in 36 genes known to cause cardiac channelopathies. Our analysis revealed 186,782 variants, of which we filtered 470 variants that were identified as possibly pathogenic (440 nonsynonymous, 30 high-confidence predicted loss of function ). About 26% (124 out of 470) of these variants were unique to the Indian population as they were not reported in the global population datasets and published literature. Classification of 470 variants by ACMG/AMP guidelines unveiled 13 pathogenic/likely pathogenic (P/LP) variants mapping to 19 out of the 1029 individuals. Further query of 53 probands in an independent cohort of cardiac channelopathy, using exome sequencing, revealed the presence of 3 out of the 13 P/LP variants. The identification of p.G179Sfs*62, p.R823W and c.420 + 2 T > C variants in KCNQ1, KCNH2 and CASQ2 genes, respectively, validate the significance of the P/LP variants in the context of clinical applicability as well as for large-scale population analysis.

conclusionA compendium of ACMG/AMP classified cardiac channelopathy variants in 1029 self-declared healthy Indian population was created. A conservative genotypic prevalence was estimated to be 0.9-1.8% which poses a huge public health burden for a country with large population size like India. In the majority of cases, these disorders are manageable and the risk of sudden cardiac death can be alleviated by appropriate lifestyle modifications as well as treatment regimens/clinical interventions. Clinical utility of the obtained variants was demonstrated using a cardiac channelopathy patient cohort. Our study emphasises the need for large-scale population screening to identify at-risk individuals and take preventive measures. However, we suggest cautious clinical interpretation to be exercised by taking other cardiac channelopathy risk factors into account.

Indexed as

ChannelopathiesDeath, Sudden, CardiacExome SequencingHumansIndiaACMG/AMPCardiac channelopathiesGenome sequencingIndian populationIndiGenPopulation screeningPrevalence

Identifiers

PMID35932045
PMCPMC9354277
OpenAlexW4289884190

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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.