Evidence map›Paper›PMID 31603214›Full record

ReviewBrain : a journal of neurology2019

Informing disease modelling with brain-relevant functional genomic annotations.

Regina H Reynolds, John Hardy, Mina Ryten, Sarah A Gagliano Taliun

Abstract readReview
In one paragraph

Review in Brain : a journal of neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. An Update on the Genetics of IgA Nephropathy.Journal of clinical medicine · 2023
    Review
  2. Article
  3. Article
  4. Article
  5. 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.

Regina H ReynoldsDepartment of Neurodegenerative Disease, University College London (UCL) Institute of Neurology, London, UK.
John HardyDepartment of Neurodegenerative Disease, University College London (UCL) Institute of Neurology, London, UK.
Mina RytenDepartment of Neurodegenerative Disease, University College London (UCL) Institute of Neurology, London, UK.
Sarah A Gagliano TaliunCenter for Statistical Genetics and Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Funding

Medical Research Council G0701075Medical Research Council G0901254Medical Research Council MR/K01417X/1Medical Research Council MR/L501542/1Medical Research Council MR/N008324/1Medical Research Council MR/N026004/1Parkinson's UK G-0907
6 · The paper itself

Abstract

The past decade has seen a surge in the number of disease/trait-associated variants, largely because of the union of studies to share genetic data and the availability of electronic health records from large cohorts for research use. Variant discovery for neurological and neuropsychiatric genome-wide association studies, including schizophrenia, Parkinson's disease and Alzheimer's disease, has greatly benefitted; however, the translation of these genetic association results to interpretable biological mechanisms and models is lagging. Interpreting disease-associated variants requires knowledge of gene regulatory mechanisms and computational tools that permit integration of this knowledge with genome-wide association study results. Here, we summarize key conceptual advances in the generation of brain-relevant functional genomic annotations and amongst tools that allow integration of these annotations with association summary statistics, which together provide a new and exciting opportunity to identify disease-relevant genes, pathways and cell types in silico. We discuss the opportunities and challenges associated with these developments and conclude with our perspective on future advances in annotation generation, tool development and the union of the two.

Indexed as

Genetic Predisposition to DiseaseGenome-Wide Association StudyPhenotypePolymorphism, Single NucleotideBrain DiseasesComputer SimulationGenomicsHumanscellular resolutionfunctional genomic annotationsgenome-wide associationneurodegenerative disordersneuropsychiatric disorders

Identifiers

PMID31603214
PMCPMC6885670

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Registered trials

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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.