Evidence map›Paper›PMID 41527333›Full record

ArticleClinical and translational science2026

Pharmacotherapy Risks in Rare Genetic Diseases: Cross-Referencing ACMG Secondary Findings v3.2 List With Clinical Databases.

Josiah D Allen, Benjamin Q Duong, Jordan Vogt, Pamela Arn

Abstract read
In one paragraph

Article in Clinical and translational science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Josiah D AllenDepartment of Precision Medicine and Genomic Health, St. Elizabeth Healthcare, Edgewood, Kentucky, USA.ORCID 0000-0002-2708-2566
Benjamin Q DuongPrecision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA.ORCID 0000-0002-1814-5078
Jordan VogtDepartment of Precision Medicine and Genomic Health, St. Elizabeth Healthcare, Edgewood, Kentucky, USA.
Pamela ArnPrecision Medicine Program, Nemours Children's Health, Jacksonville, Florida, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical genomics and pharmacogenomics have largely remained separate fields, though some genetic variants have overlapping disease risk and drug implications. However, the extent of this overlap is not well studied. To explore this gap, we cross-referenced genes from the American College of Medical Genetics Secondary Findings v3.2 list with genomic databases and drug labeling to identify gene-phenotype pairs with overlapping clinical genomics and pharmacogenomic implications. We searched GeneReviews and PharmGKB (now called ClinPGx) for each gene-phenotype pair and reviewed the FDALabel database contraindications or warnings. Targeted therapies for specific germline/somatic variants were excluded. PGx-trained pharmacists and a genetic counselor classified gene-phenotype pairs into three levels: Level 1 (Food and Drug Administration's or guideline-driven recommendations), Level 2 (potential pharmacotherapy implication), and Level 3 (no/weak interactions). Among 97 gene-phenotype pairs reviewed, 22 (23%) were Level 1, 31 (32%) were Level 2, and 44 (45%) were Level 3. Pharmacotherapy implications included risks inferred by disease pathology (e.g., anticoagulants and hereditary hemorrhagic telangiectasia) and less obvious associations (e.g., Marfan syndrome and fluoroquinolones). Unrecognized medication implications may pose patient safety risks. Greater research, information consolidation and dissemination, and multidisciplinary collaboration among clinical genomics specialists, pharmacogenomic specialists, and other practitioners are essential as genetic testing becomes routine in clinical care.

Indexed as

Genetic Diseases, InbornPharmacogeneticsRare DiseasesDatabases, GeneticDrug LabelingGenetic TestingHumansPhenotypeRisk AssessmentUnited Statesclinical genomicscontraindicationsmultidisciplinary carepharmacogenomicspharmacyrare diseasesecondary findings

Identifiers

PMID41527333
PMCPMC12796505

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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.