Evidence map›Paper›PMID 34385667›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2021

Positive predictive value highlights four novel candidates for actionable genetic screening from analysis of 220,000 clinicogenomic records.

Kelly M Schiabor Barrett, Alexandre Bolze, Yunyun Ni, Simon White, Magnus Isaksson, Lavania Sharma, Elissa Levin, William Lee, Joseph J Grzymski, James T Lu and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.8field-weighted citation impact, top 6% 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

7 citing papers in PubMed, 25 citations in OpenAlex.

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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

12 authors at 2 institutions in 1 country.

Kelly M Schiabor BarrettHelix, San Mateo, CA, USA.
Alexandre BolzeHelix, San Mateo, CA, USA.
Yunyun NiHelix, San Mateo, CA, USA.
Simon WhiteHelix, San Mateo, CA, USA.
Magnus IsakssonHelix, San Mateo, CA, USA.
Lavania SharmaHelix, San Mateo, CA, USA.
Elissa LevinHelix, San Mateo, CA, USA.
William LeeHelix, San Mateo, CA, USA.
Joseph J GrzymskiRenown Institute for Health Innovation, Reno, NV, USA.
James T LuHelix, San Mateo, CA, USA.
Nicole L Washington *Helix, San Mateo, CA, USA.
Elizabeth T Cirulli *Helix, San Mateo, CA, USA. liz.cirulli@helix.com.ORCID 0000-0001-7808-2809
Helix (United States) · USRenown Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo identify conditions that are candidates for population genetic screening based on population prevalence, penetrance of rare variants, and actionability.

methodsWe analyzed exome and medical record data from >220,000 participants across two large population health cohorts with different demographics. We performed a gene-based collapsing analysis of rare variants to identify genes significantly associated with disease status.

resultsWe identify 74 statistically significant gene-disease associations across 27 genes. Seven of these conditions have a positive predictive value (PPV) of at least 30% in both cohorts. Three are already used in population screening programs (BRCA1, BRCA2, LDLR), and we also identify four new candidates for population screening: GCK with diabetes mellitus, HBB with β-thalassemia minor and intermedia, PKD1 with cystic kidney disease, and MIP with cataracts. Importantly, the associations are actionable in that early genetic screening of each of these conditions is expected to improve outcomes.

conclusionWe identify seven genetic conditions where rare variation appears appropriate to assess in population screening, four of which are not yet used in screening programs. The addition of GCK, HBB, PKD1, and MIP rare variants into genetic screening programs would reach an additional 0.21% of participants with actionable disease risk, depending on the population.

Indexed as

Genes, BRCA2Genetic TestingExomeExome SequencingGenetic Predisposition to DiseaseHumansPredictive Value of Tests

Identifiers

PMID34385667
PMCPMC8629756
OpenAlexW3192326429

What OpenQuestion holds

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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.