Evidence map›Paper›PMID 33686288›Full record

ArticleNature genetics2021

Identifying loci with different allele frequencies among cases of eight psychiatric disorders using CC-GWAS.

Wouter J Peyrot, Alkes L Price

Open access · bronzeAbstract read
In one paragraph

Article in Nature genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed, 7 pooled it
14.7field-weighted citation impact, top 1% of its field
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

76 citing papers in PubMed, 7 syntheses or guidelines pooled it, 115 citations in OpenAlex.

  1. A genome-wide association meta-analysis of all-cause and vascular dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
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  13. Polygenic scores in psychiatric research and clinical practice.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026
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  18. Symptom-specific genetics reveal heterogeneity within major depressive disorder.medRxiv : the preprint server for health sciences · 2026
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16 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 2 countries.

Wouter J PeyrotDepartment of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA. wpeyrot@hsph.harvard.edu.ORCID http://orcid.org/0000-0001-7954-8383
Alkes L PriceDepartment of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA. aprice@hsph.harvard.edu.ORCID http://orcid.org/0000-0002-2971-7975
Broad Institute · US

Funding

Epidemiologic StudiesU19CA148065 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI AHSAN, HABIBUL, BRUGGE, JOAN SIEFERT · 2010 to 2014
$10.6M
Statistical methods for studies of rare variantsR01MH101244 · NIMH · HARVARD MEDICAL SCHOOL · PI Benjamin Michael Neale, ALKES L PRICE · 2013 to 2026
$9.4M
Statistical methods to localize disease heritability and identify biological mechanismsR37MH107649 · NIMH · BROAD INSTITUTE, INC. · PI Benjamin Michael Neale · 2019 to 2026
$7.0M
Methods for Genome-wide Association Studies in Admixed PopulationsR01HG006399 · NHGRI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI PRICE, ALKES L · 2011 to 2024
$6.3M
Theory and methods for mediation and interactionR01CA222147 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI TCHETGEN TCHETGEN, ERIC JOEL, VANDERWEELE, TYLER · 2018 to 2022
$2.1M
Cancer Research UK C1287/A10118Cancer Research UK C1287/A10710Cancer Research UK C1287/A16563CIHRNCI NIH HHS R01 CA222147NCI NIH HHS U19 CA148065NHGRI NIH HHS R01 HG006399NIMH NIH HHS R01 MH101244NIMH NIH HHS R37 MH107649
6 · The paper itself

Abstract

Psychiatric disorders are highly genetically correlated, but little research has been conducted on the genetic differences between disorders. We developed a new method (case-case genome-wide association study; CC-GWAS) to test for differences in allele frequency between cases of two disorders using summary statistics from the respective case-control GWAS, transcending current methods that require individual-level data. Simulations and analytical computations confirm that CC-GWAS is well powered with effective control of type I error. We applied CC-GWAS to publicly available summary statistics for schizophrenia, bipolar disorder, major depressive disorder and five other psychiatric disorders. CC-GWAS identified 196 independent case-case loci, including 72 CC-GWAS-specific loci that were not significant at the genome-wide level in the input case-control summary statistics; two of the CC-GWAS-specific loci implicate the genes KLF6 and KLF16 (from the Krüppel-like family of transcription factors), which have been linked to neurite outgrowth and axon regeneration. CC-GWAS loci replicated convincingly in applications to datasets with independent replication data.

Indexed as

Gene FrequencyGenetic LociAllelesAxonsBipolar DisorderCase-Control StudiesDatasets as TopicGene ExpressionGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansKruppel-Like Factor 6Kruppel-Like Transcription FactorsMajor Depressive DisorderNeuronal OutgrowthPolymorphism, Single NucleotideKLF16 protein, humanKLF6 protein, humanKruppel-Like Factor 6Kruppel-Like Transcription Factors

Identifiers

PMID33686288
PMCPMC8038973
OpenAlexW3134771351

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.