Evidence map›Paper›PMID 30737014›Full record

ReviewBiological psychiatry2019

Predicting Polygenic Risk of Psychiatric Disorders.

Alicia R Martin, Mark J Daly, Elise B Robinson, Steven E Hyman, Benjamin M Neale

Abstract readReview
In one paragraph

Review in Biological psychiatry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 127 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
127citing papers in PubMed, 5 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

127 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Trial
  7. Article
  8. Article
  9. Article
  10. Observational
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article

67 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

5 authors.

Alicia R MartinAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts. Electronic address: armartin@broadinstitute.org.
Mark J DalyAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts.
Elise B RobinsonAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.
Steven E HymanStanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts.
Benjamin M NealeAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts.

Funding

Generalizing polygenic risk prediction methods across populations for insights into psychiatric diseaseK99MH117229 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI MARTIN, ALICIA · 2018 to 2019
$262k
NIMH NIH HHS K99 MH117229
6 · The paper itself

Abstract

Genetics provides two major opportunities for understanding human disease-as a transformative line of etiological inquiry and as a biomarker for heritable diseases. In psychiatry, biomarkers are very much needed for both research and treatment, given the heterogenous populations identified by current phenomenologically based diagnostic systems. To date, however, useful and valid biomarkers have been scant owing to the inaccessibility and complexity of human brain tissue and consequent lack of insight into disease mechanisms. Genetic biomarkers are therefore especially promising for psychiatric disorders. Genome-wide association studies of common diseases have matured over the last decade, generating the knowledge base for increasingly informative individual-level genetic risk prediction. In this review, we discuss fundamental concepts involved in computing genetic risk with current methods, strengths and weaknesses of various approaches, assessments of utility, and applications to various psychiatric disorders and related traits. Although genetic risk prediction has become increasingly straightforward to apply and common in published studies, there are important pitfalls to avoid. At present, the clinical utility of genetic risk prediction is still low; however, there is significant promise for future clinical applications as the ancestral diversity and sample sizes of genome-wide association studies increase. We discuss emerging data and methods aimed at improving the value of genetic risk prediction for disentangling disease mechanisms and stratifying subjects for epidemiological and clinical studies. For all applications, it is absolutely critical that polygenic risk prediction is applied with appropriate methodology and control for confounding to avoid repeating some mistakes of the candidate gene era.

Indexed as

Genetic Predisposition to DiseaseGenetic TestingGenome-Wide Association StudyHumansMental DisordersMultifactorial InheritancePredictive Value of TestsRisk AssessmentComplex traitsHeritabilityLiability threshold modelPolygenic risk scoresPopulation geneticsPrecision medicinePsychiatric disordersPsychiatric geneticsStatistical genetics

Identifiers

PMID30737014
PMCPMC6599546

What OpenQuestion holds

Textmetadata
LicenceTDM
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.