Evidence map›Paper›PMID 31771638›Full record

ArticleGenome medicine2019

Low coverage whole genome sequencing enables accurate assessment of common variants and calculation of genome-wide polygenic scores.

Julian R Homburger, Cynthia L Neben, Gilad Mishne, Alicia Y Zhou, Sekar Kathiresan, Amit V Khera

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 1 pooled it
12.2field-weighted citation impact, top 1% 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

64 citing papers in PubMed, 1 synthesis or guideline pooled it, 128 citations in OpenAlex.

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  12. Low-coverage whole-genome sequencing facilitates accurate and cost-effective haplotype reconstruction in complex mouse crosses.Mammalian genome : official journal of the International Mammalian Genome Society · 2025
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4 more citing papers are in PubMed but not listed here.

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

6 authors at 3 institutions in 1 country.

Julian R HomburgerColor Genomics, 831 Mitten Road, Suite 100, Burlingame, CA, 94010, USA.
Cynthia L NebenColor Genomics, 831 Mitten Road, Suite 100, Burlingame, CA, 94010, USA.
Gilad MishneColor Genomics, 831 Mitten Road, Suite 100, Burlingame, CA, 94010, USA.
Alicia Y ZhouColor Genomics, 831 Mitten Road, Suite 100, Burlingame, CA, 94010, USA.
Sekar KathiresanVerve Therapeutics, Cambridge, MA, USA.
Amit V KheraCenter for Genomic Medicine and Cardiology Division, Department of Medicine, Massachusetts General Hospital, Simches Research Building | CPZN 6.256, Boston, MA, 02114, USA. avkhera@mgh.harvard.edu.ORCID 0000-0001-6535-5839
Color (United States) · USBroad Institute · USVerve Therapeutics (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInherited susceptibility to common, complex diseases may be caused by rare, pathogenic variants ("monogenic") or by the cumulative effect of numerous common variants ("polygenic"). Comprehensive genome interpretation should enable assessment for both monogenic and polygenic components of inherited risk. The traditional approach requires two distinct genetic testing technologies-high coverage sequencing of known genes to detect monogenic variants and a genome-wide genotyping array followed by imputation to calculate genome-wide polygenic scores (GPSs). We assessed the feasibility and accuracy of using low coverage whole genome sequencing (lcWGS) as an alternative to genotyping arrays to calculate GPSs.

methodsFirst, we performed downsampling and imputation of WGS data from ten individuals to assess concordance with known genotypes. Second, we assessed the correlation between GPSs for 3 common diseases-coronary artery disease (CAD), breast cancer (BC), and atrial fibrillation (AF)-calculated using lcWGS and genotyping array in 184 samples. Third, we assessed concordance of lcWGS-based genotype calls and GPS calculation in 120 individuals with known genotypes, selected to reflect diverse ancestral backgrounds. Fourth, we assessed the relationship between GPSs calculated using lcWGS and disease phenotypes in a cohort of 11,502 individuals of European ancestry.

resultsWe found imputation accuracy r

conclusionslcWGS is an alternative technology to genotyping arrays for common genetic variant assessment and GPS calculation. lcWGS provides comparable imputation accuracy while also overcoming the ascertainment bias inherent to variant selection in genotyping array design.

Indexed as

Genetic VariationGenome, HumanGenome-Wide Association StudyGenomicsGenetic Predisposition to DiseaseGenetics, PopulationGenotypeHumansReproducibility of ResultsWhole Genome SequencingAtrial fibrillationBreast cancerCoronary artery diseaseGenome-wide polygenic scoreLow coverage whole genome sequencing

Identifiers

PMID31771638
PMCPMC6880438
OpenAlexW2991501877

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.