Evidence map›Paper›PMID 35317627›Full record

ArticleBiology letters2022

Modelling the genetic aetiology of complex disease: human-mouse conservation of noncoding features and disease-associated loci.

George Powell, Helen Long, Louisa Zolkiewski, Rebecca Dumbell, Ann-Marie Mallon, Cecilia M Lindgren, Michelle M Simon

Abstract read
In one paragraph

Article in Biology letters, 2022. 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. Review
  2. Review
  3. The genetics of adipose tissue metabolism.Royal Society open science · 2024
    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

7 authors.

George PowellBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.ORCID 0000-0002-8378-0043
Helen LongBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.
Louisa ZolkiewskiMRC Harwell Institute, Mammalian Genetics Unit, Oxfordshire OX11 0RD, UK.ORCID 0000-0002-9205-3358
Rebecca DumbellNottingham Trent University, Clifton Lane, Nottingham NG11 8NS, UK.ORCID 0000-0002-8805-3777
Ann-Marie MallonMRC Harwell Institute, Mammalian Genetics Unit, Oxfordshire OX11 0RD, UK.
Cecilia M LindgrenBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.
Michelle M SimonMRC Harwell Institute, Mammalian Genetics Unit, Oxfordshire OX11 0RD, UK.

Funding

Medical Research Council MC_U142661184Medical Research Council MC_U142684171
6 · The paper itself

Abstract

Understanding the genetic aetiology of loci associated with a disease is crucial for developing preventative measures and effective treatments. Mouse models are used extensively to understand human pathobiology and mechanistic functions of disease-associated loci. However, the utility of mouse models is limited in part by evolutionary divergence in transcription regulation for pathways of interest. Here, we summarize the alignment of genomic (exonic and multi-cell regulatory) annotations alongside Mendelian and complex disease-associated variant sites between humans and mice. Our results highlight the importance of understanding evolutionary divergence in transcription regulation when interpreting functional studies using mice as models for human disease variants.

Indexed as

Gene Expression RegulationGenomeAnimalsHumansMicealignmentannotationcomplex diseaseconservationMendelian diseaseorthologue

Identifiers

PMID35317627
PMCPMC8941414

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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.