Evidence map›Paper›PMID 31234920›Full record

ReviewOrphanet journal of rare diseases2019

Genome sequencing and implications for rare disorders.

Jennifer E Posey

Abstract readReview
In one paragraph

Review in Orphanet journal of rare diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 1 pooled it
–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

61 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Genome Sequencing Uncovers Additional Findings in Phelan-McDermid Syndrome.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2025
    Article
  9. Article
  10. Benchmark of computational methods to detect digenism in sequencing data.European journal of human genetics : EJHG · 2025
    Review
  11. Review
  12. Article
  13. Article
  14. Automated Shared Phenotype Discovery in Undiagnosed Cohorts for Rare Disease Research.Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications · 2024
    Article
  15. Article
  16. Review
  17. Review
  18. Article
  19. Article
  20. Article

1 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

1 author.

Jennifer E PoseyDepartment of Molecular & Human Genetics, Baylor College of Medicine, One Baylor Plaza, T603, Houston, TX, 77030, USA. jp042803@bcm.edu.ORCID 0000-0003-4814-6765

Funding

Individual genomic analyses to discover the molecular basis and mechanisms contributing to adult-onset diseaseK08HG008986 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI POSEY, JENNIFER ELLEN · 2017 to 2021
$831k
NHGRI NIH HHS K08 HG008986
6 · The paper itself

Abstract

The practice of genomic medicine stands to revolutionize our approach to medical care, and to realize this goal will require discovery of the relationship between rare variation at each of the ~ 20,000 protein-coding genes and their consequent impact on individual health and expression of Mendelian disease. The step-wise evolution of broad-based, genome-wide cytogenetic and molecular genomic testing approaches (karyotyping, chromosomal microarray [CMA], exome sequencing [ES]) has driven much of the rare disease discovery to this point, with genome sequencing representing the newest member of this team. Each step has brought increased sensitivity to interrogate individual genomic variation in an unbiased method that does not require clinical prediction of the locus or loci involved. Notably, each step has also brought unique limitations in variant detection, for example, the low sensitivity of ES for detection of triploidy, and of CMA for detection of copy neutral structural variants. The utility of genome sequencing (GS) as a clinical molecular diagnostic test, and the increased sensitivity afforded by addition of long-read sequencing or other -omics technologies such as RNAseq or metabolomics, are not yet fully explored, though recent work supports improved sensitivity of variant detection, at least in a subset of cases. The utility of GS will also rely upon further elucidation of the complexities of genetic and allelic heterogeneity, multilocus rare variation, and the impact of rare and common variation at a locus, as well as advances in functional annotation of identified variants. Much discovery remains to be done before the potential utility of GS is fully appreciated.

Indexed as

ExomeGenetic Predisposition to DiseaseGenetic TestingGenomicsHumansRare DiseasesDiagnostic utilityExome sequencingGenome sequencingMendelian conditionsMolecular diagnosesRare diseaseUndiagnosed diseases

Identifiers

PMID31234920
PMCPMC6591893

What OpenQuestion holds

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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.