Evidence map›Paper›PMID 40024972›Full record

ArticleCancer causes & control : CCC2025

Understanding the genetic epidemiology of hereditary breast cancer in India using whole genome data from 1029 healthy individuals.

Aastha Vatsyayan, Prerika Mathur, Rahul C Bhoyar, Mohamed Imran, Vigneshwar Senthivel, Mohit Kumar Divakar, Anushree Mishra, Bani Jolly, Sridhar Sivasubbu, Vinod Scaria

Abstract read
PubMed Publisher
In one paragraph

Article in Cancer causes & control : CCC, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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. Review
  2. Article
  3. Review
  4. Article
  5. 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

10 authors.

Aastha VatsyayanCSIR Institute of Genomics and Integrative Biology (CSIR-IGIB) Mathura Road, Delhi, 110025, India.ORCID http://orcid.org/0000-0002-4093-011X
Prerika MathurDepartment of Biological Sciences, Birla Institute of Technology and Science, Pilani Campus, Pilani, Rajasthan, India.
Rahul C BhoyarCSIR Institute of Genomics and Integrative Biology (CSIR-IGIB) Mathura Road, Delhi, 110025, India.
Mohamed ImranCSIR Institute of Genomics and Integrative Biology (CSIR-IGIB) Mathura Road, Delhi, 110025, India.
Vigneshwar SenthivelCSIR Institute of Genomics and Integrative Biology (CSIR-IGIB) Mathura Road, Delhi, 110025, India.
Mohit Kumar DivakarCSIR Institute of Genomics and Integrative Biology (CSIR-IGIB) Mathura Road, Delhi, 110025, India.
Anushree MishraCSIR Institute of Genomics and Integrative Biology (CSIR-IGIB) Mathura Road, Delhi, 110025, India.
Bani JollyCSIR Institute of Genomics and Integrative Biology (CSIR-IGIB) Mathura Road, Delhi, 110025, India.
Sridhar SivasubbuCSIR Institute of Genomics and Integrative Biology (CSIR-IGIB) Mathura Road, Delhi, 110025, India.
Vinod ScariaCSIR Institute of Genomics and Integrative Biology (CSIR-IGIB) Mathura Road, Delhi, 110025, India. vinods@igib.in.ORCID http://orcid.org/0000-0001-7644-7181

Funding

Council of Scientific and Industrial Research, India CNP-0007
6 · The paper itself

Abstract

Breast cancer is the most highly reported cancer in India. Genetic testing could help tackle the increasing cancer burden by enabling carriers obtain early diagnosis through increased surveillance, and help guide treatment. However, accurate interpretation of variant pathogenicity must be established in a population-specific manner to ensure effective use of genetic testing. Here we query IndiGen data obtained from sequencing 1029 Indian individuals, and perform variant classification of all reported BRCA variants using gold-standard ACMG & AMP guidelines to establish disease epidemiology. To address the high number of VUS variants thus obtained, we further utilize the brca-NOVUS ML tool to obtain pathogenicity predictions in a manner close to ACMG guidelines at scale. Through the manual application of ACMG & AMP guidelines, we determined the genetic prevalence to be the following: 1 in 342 carriers of BRCA1, and 1 in 256 carriers of BRCA2 pathogenic/likely pathogenic variants bear a significant lifetime risk of developing breast / ovarian cancer in India. The high population prevalence and unique variant landscape emphasizes a need for population-scale studies of causative variants to enable effective screening. We advise cautious clinical interpretation, given incomplete penetrance and other complex factors that result in cancer disease. To the best of our knowledge, this is the first and most comprehensive population-scale genetic epidemiological study of BRCA-linked breast cancer variants reported from India.

Indexed as

Breast NeoplasmsGenetic Predisposition to DiseaseAdultBRCA1 ProteinBRCA2 ProteinFemaleGenetic TestingHumansIndiaMiddle AgedWhole Genome SequencingBRCA1 ProteinBRCA1 protein, humanBRCA2 ProteinBRCA2 protein, humanBreast cancerDiagnosisGenetic epidemiologyHereditary cancerMLPopulation genomics

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.