Evidence map›Paper›PMID 38815586›Full record

ArticleAmerican journal of human genetics2024

Regional-specific calibration enables application of computational evidence for clinical classification of 5' cis-regulatory variants in Mendelian disease.

Rehan M Villani, Maddison E McKenzie, Aimee L Davidson, Amanda B Spurdle

Abstract read
In one paragraph

Article in American journal of human genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. AJournal of human immunity · 2026
    Article
  4. 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

4 authors.

Rehan M VillaniPopulation Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
Maddison E McKenziePopulation Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
Aimee L DavidsonPopulation Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
Amanda B SpurdlePopulation Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia; University of Queensland, Brisbane, Queensland, Australia. Electronic address: amanda.spurdle@qimrberghofer.edu.au.

Funding

Upgrading rigor and efficiency of germline cancer gene variant classification for the 2020sR01CA264971 · NCI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Sean Vahram Tavtigian · 2022 to 2026
$2.9M
NCI NIH HHS R01 CA264971
6 · The paper itself

Abstract

To date, clinical genetic testing for Mendelian disease variants has focused heavily on exonic coding and intronic gene regions. This multi-step study was undertaken to provide an evidence base for selecting and applying computational approaches for use in clinical classification of 5' cis-regulatory region variants. Curated datasets of clinically reported disease-causing 5' cis-regulatory region variants and variants from matched genomic regions in population controls were used to calibrate six bioinformatic tools as predictors of variant pathogenicity. Likelihood ratio estimates were aligned to code weights following ClinGen recommendations for application of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) classification scheme. Considering code assignment across all reference dataset variants, performance was best for CADD (81.2%) and REMM (81.5%). Optimized thresholds provided moderate evidence toward pathogenicity (CADD, REMM) and moderate (CADD) or supporting (REMM) evidence against pathogenicity. Both sensitivity and specificity of prediction were improved when further categorizing variants based on location in an EPDnew-defined promoter region. Combining predictions (CADD, REMM, and location in a promoter region) increased specificity at the expense of sensitivity. Importantly, the optimal CADD thresholds for assigning ACMG/AMP codes PP3 (≥10) and BP4 (≤8) were vastly different from recommendations for protein-coding variants (PP3 ≥25.3; BP4 ≤22.7); CADD <22.7 would incorrectly assign BP4 for >90% of reported disease-causing cis-regulatory region variants. Our results demonstrate the need to consider a tiered approach and tailored score thresholds to optimize bioinformatic impact prediction for clinical classification of 5' cis-regulatory region variants.

Indexed as

Computational BiologyGenetic Diseases, InbornRegulatory Sequences, Nucleic AcidCalibrationGenetic TestingGenetic VariationHumansACMG/AMPcis-regulatorygeneticsgenomegenomic variantmutationnon-codingpromotersequence analysisvariant classification

Identifiers

PMID38815586
PMCPMC11267523

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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.