Evidence map›Paper›PMID 33798442›Full record

ReviewAmerican journal of human genetics2021

Opportunities and challenges for the computational interpretation of rare variation in clinically important genes.

Gregory McInnes, Andrew G Sharo, Megan L Koleske, Julia E H Brown, Matthew Norstad, Aashish N Adhikari, Sheng Wang, Steven E Brenner, Jodi Halpern, Barbara A Koenig and 4 more

Open access · bronzeAbstract readReview
In one paragraph

Review in American journal of human genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
13.7field-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

50 citing papers in PubMed, 91 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Functional Validation of a Novel Deep IntronicThe application of clinical genetics · 2026
    Article
  6. Article
  7. Review
  8. Article
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  11. Review
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  13. Review
  14. Article
  15. Review
  16. Assessment of the evidence yield for the calibrated PP3/BP4 computational recommendations.Genetics in medicine : official journal of the American College of Medical Genetics · 2024
    Article
  17. Review
  18. Article
  19. Review
  20. 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

14 authors at 6 institutions in 1 country.

Gregory McInnesBiomedical Informatics Training Program, Stanford University, Stanford, CA 94305, USA.
Andrew G SharoBiophysics Graduate Group, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA 94720, USA.
Megan L KoleskeDepartment of Bioengineering and Therapeutics, University of California, San Francisco, San Francisco, CA 94143, USA.
Julia E H BrownProgram in Bioethics, University of California, San Francisco, San Francisco, CA 94143, USA; Institute for Health & Aging, University of California, San Francisco, San Francisco, CA 94143, USA.
Matthew NorstadProgram in Bioethics, University of California, San Francisco, San Francisco, CA 94143, USA; Institute for Health & Aging, University of California, San Francisco, San Francisco, CA 94143, USA.
Aashish N AdhikariInstitute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Illumina, Inc., Foster City, CA 94404, USA.
Sheng WangPaul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA 98195, USA.
Steven E BrennerBiophysics Graduate Group, University of California, Berkeley, Berkeley, CA 94720, USA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA 94720, USA.
Jodi HalpernUCSF-UCB Joint Medical Program, School of Public Health, University of California, Berkeley, Berkeley, CA 94720, USA.
Barbara A KoenigProgram in Bioethics, University of California, San Francisco, San Francisco, CA 94143, USA; Institute for Health & Aging, University of California, San Francisco, San Francisco, CA 94143, USA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Social & Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Humanities & Social Sciences, University of California, San Francisco, San Francisco, CA 94143, USA.
David C MagnusStanford Center for Biomedical Ethics, Stanford University School of Medicine, Stanford, CA 94305, USA.
Renata C GallagherInstitute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Pediatrics, University of California, San Francisco, San Francisco, CA 94143, USA.
Kathleen M GiacominiDepartment of Bioengineering and Therapeutics, University of California, San Francisco, San Francisco, CA 94143, USA.
Russ B AltmanDepartments of Bioengineering & Genetics, Stanford University, Stanford, CA 94305, USA. Electronic address: rbaltman@stanford.edu.
University of California, San Francisco · USStanford University · USUniversity of California, Berkeley · USIllumina (United States) · USInstitute on Aging · USUniversity of Washington · US

Funding

Stanford Center for Clinical & Translational Education and Research (Spectrum)UL1TR003142 · NCATS · STANFORD UNIVERSITY · PI O'HARA, RUTH M · 2019 to 2023
$45.0M
ZIDOVUDINE &LAMIVUDINE &NEVIRAPINE COMBINATION THERAPY IN HIV 1 INFM01RR001271 · NCRR · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KESSLER, DAVID A · 1985 to 2006
$22.7M
Research BaseP30DK063720 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GERMAN, MICHAEL S · 2003 to 2019
$21.8M
UCSF Nutrition Obesity Research CenterP30DK098722 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHRISTIAN VAISSE · 2015 to 2026
$14.6M
PharmGKB: pharmacogenomics discovery and implementationU24HG010615 · NHGRI · STANFORD UNIVERSITY · PI TERI Ellen KLEIN, Michelle Whirl-Carrillo · 2020 to 2026
$9.5M
MOLECULAR BIOPHYSICS TRAINING GRANTT32GM008295 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI HURLEY, JAMES H, WEMMER, DAVID E · 1989 to 2022
$8.1M
Sequencing of Newborn Blood Spot DNA to Improve and Expand Newborn ScreeningU19HD077627 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KOENIG, BARBARA A., KWOK, PUI-YAN · 2013 to 2018
$6.6M
Undergraduate Summer Research Experiences Support for Combining systems biology and structural biology to find new therapeuticsR01GM102365 · NIGMS · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO · 2012 to 2021
$3.0M
Biomedical Data Science Graduate Training at StanfordT32LM012409 · NLM · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2016 to 2020
$1.5M
NCATS NIH HHS UL1 TR003142NCRR NIH HHS M01 RR001271NHGRI NIH HHS U24 HG010615NICHD NIH HHS U19 HD077627NIDDK NIH HHS P30 DK063720NIDDK NIH HHS P30 DK098722NIGMS NIH HHS R01 GM102365NIGMS NIH HHS T32 GM008295NLM NIH HHS T32 LM012409
6 · The paper itself

Abstract

Genome sequencing is enabling precision medicine-tailoring treatment to the unique constellation of variants in an individual's genome. The impact of recurrent pathogenic variants is often understood, however there is a long tail of rare genetic variants that are uncharacterized. The problem of uncharacterized rare variation is especially acute when it occurs in genes of known clinical importance with functionally consequential variants and associated mechanisms. Variants of uncertain significance (VUSs) in these genes are discovered at a rate that outpaces current ability to classify them with databases of previous cases, experimental evaluation, and computational predictors. Clinicians are thus left without guidance about the significance of variants that may have actionable consequences. Computational prediction of the impact of rare genetic variation is increasingly becoming an important capability. In this paper, we review the technical and ethical challenges of interpreting the function of rare variants in two settings: inborn errors of metabolism in newborns and pharmacogenomics. We propose a framework for a genomic learning healthcare system with an initial focus on early-onset treatable disease in newborns and actionable pharmacogenomics. We argue that (1) a genomic learning healthcare system must allow for continuous collection and assessment of rare variants, (2) emerging machine learning methods will enable algorithms to predict the clinical impact of rare variants on protein function, and (3) ethical considerations must inform the construction and deployment of all rare-variation triage strategies, particularly with respect to health disparities arising from unbalanced ancestry representation.

Indexed as

Genetics, MedicalGenomicsMachine LearningPharmacogeneticsPrecision MedicineGenetic VariationGenome, HumanHumansInfant, NewbornMetabolism, Inborn Errors

Identifiers

PMID33798442
PMCPMC8059338
OpenAlexW3147241712

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.