Evidence map›Paper›PMID 27287392›Full record

ArticleJournal of medical genetics2016

Phenome-wide association study maps new diseases to the human major histocompatibility complex region.

Jixia Liu, Zhan Ye, John G Mayer, Brian A Hoch, Clayton Green, Loren Rolak, Christopher Cold, Seik-Soon Khor, Xiuwen Zheng, Taku Miyagawa and 3 more

Abstract read
In one paragraph

Article in Journal of medical genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Lichen Planus: What is New in Diagnosis and Treatment?American journal of clinical dermatology · 2024
    Review
  8. Article
  9. Article
  10. Comprehensive Insight into Lichen Planus Immunopathogenesis.International journal of molecular sciences · 2023
    Review
  11. Article
  12. Article
  13. Lichen Planus.Frontiers in medicine · 2021
    Review
  14. Article
  15. Article
  16. Review
  17. PheProb: probabilistic phenotyping using diagnosis codes to improve power for genetic association studies.Journal of the American Medical Informatics Association : JAMIA · 2018
    Article
  18. Article
  19. Observational
  20. Review
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

13 authors.

Jixia LiuCenter for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA.
Zhan YeBiomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA.
John G MayerBiomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA.
Brian A HochBiomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA.
Clayton GreenDepartment of Dermatology, Marshfield Clinic, Marshfield, Wisconsin, USA.
Loren RolakDepartment of Neurology, Marshfield Clinic, Marshfield, Wisconsin, USA.
Christopher ColdDepartment of Pathology, Marshfield Clinic, Marshfield, Wisconsin, USA.
Seik-Soon KhorDepartment of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Xiuwen ZhengDepartment of Biostatistics, University of Washington, Seattle, Washington, USA.
Taku MiyagawaDepartment of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan Sleep Disorders Project, Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan.
Katsushi TokunagaDepartment of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Murray H BrilliantCenter for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA.
Scott J HebbringCenter for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA.

Funding

Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
IRIS: Incorporating Research Into SightU01HG006389 · NHGRI · ESSENTIA INSTITUTE OF RURAL HEALTH · PI MCCARTY, CATHERINE ANNE · 2011 to 2014
$4.1M
PheWAS of Loss-of-Function VariantsR01GM114128 · NIGMS · MARSHFIELD CLINIC RESEARCH FOUNDATION · PI HEBBRING, SCOTT JOSEPH · 2015 to 2019
$1.7M
Development and Application of Phenome-wide Scan of Heritability (PheSH)K22LM011938 · NLM · MARSHFIELD CLINIC RESEARCH FOUNDATION · PI HEBBRING, SCOTT JOSEPH · 2014 to 2016
$405k
NCATS NIH HHS UL1 TR000427NHGRI NIH HHS U01 HG006389NIGMS NIH HHS R01 GM114128NLM NIH HHS K22 LM011938
6 · The paper itself

Abstract

backgroundOver 160 disease phenotypes have been mapped to the major histocompatibility complex (MHC) region on chromosome 6 by genome-wide association study (GWAS), suggesting that the MHC region as a whole may be involved in the aetiology of many phenotypes, including unstudied diseases. The phenome-wide association study (PheWAS), a powerful and complementary approach to GWAS, has demonstrated its ability to discover and rediscover genetic associations. The objective of this study is to comprehensively investigate the MHC region by PheWAS to identify new phenotypes mapped to this genetically important region.

methodsIn the current study, we systematically explored the MHC region using PheWAS to associate 2692 MHC-linked variants (minor allele frequency ≥0.01) with 6221 phenotypes in a cohort of 7481 subjects from the Marshfield Clinic Personalized Medicine Research Project.

resultsFindings showed that expected associations previously identified by GWAS could be identified by PheWAS (eg, psoriasis, ankylosing spondylitis, type I diabetes and coeliac disease) with some having strong cross-phenotype associations potentially driven by pleiotropic effects. Importantly, novel associations with eight diseases not previously assessed by GWAS (eg, lichen planus) were also identified and replicated in an independent population. Many of these associated diseases appear to be immune-related disorders. Further assessment of these diseases in 16 484 Marshfield Clinic twins suggests that some of these diseases, including lichen planus, may have genetic aetiologies.

conclusionsThese results demonstrate that the PheWAS approach is a powerful and novel method to discover SNP-disease associations, and is ideal when characterising cross-phenotype associations, and further emphasise the importance of the MHC region in human health and disease.

Indexed as

Chromosomes, Human, Pair 6Major Histocompatibility ComplexPolymorphism, GeneticAdultAgedFemaleGenetic Association StudiesHumansImmune System DiseasesInflammationLichen PlanusMaleMiddle AgedPhenotypeWhite PeopleGenome-Wide Association Study (GWAS)HLAmajor histocompatibility complex (MHC)phenome-wide association study (PheWAS)Precision Medicine

Identifiers

PMID27287392
PMCPMC5035188

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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.