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

Autor: Wouter J. Peyrot, Alkes L. Price
Přispěvatelé: Complex Trait Genetics, Psychiatry, APH - Mental Health
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Bipolar Disorder
Schizophrenia/genetics
Datasets as Topic
Gene Expression
Genome-wide association study
0302 clinical medicine
Gene Frequency
Polymorphism (computer science)
Kruppel-Like Factor 6/genetics
0303 health sciences
Bipolar Disorder/genetics
Major/genetics
Single Nucleotide
3. Good health
Anorexia nervosa (differential diagnoses)
Schizophrenia
Major depressive disorder
Neuronal Outgrowth/genetics
Depressive Disorder
Major/genetics
medicine.medical_specialty
Neuronal Outgrowth
Kruppel-Like Transcription Factors
Axons/metabolism
Biology
Polymorphism
Single Nucleotide
03 medical and health sciences
Genetics
medicine
Kruppel-Like Factor 6
Humans
Genetic Predisposition to Disease
Bipolar disorder
Allele
Polymorphism
Psychiatry
Allele frequency
Kruppel-Like Transcription Factors/genetics
Alleles
030304 developmental biology
Depressive Disorder
Major
Depressive Disorder
Case-control study
medicine.disease
Axons
Genetic distance
Genetic Loci
Case-Control Studies
Autism
030217 neurology & neurosurgery
Genome-Wide Association Study
Zdroj: Peyrot, W J & Price, A L 2021, ' Identifying loci with different allele frequencies among cases of eight psychiatric disorders using CC-GWAS ', Nature Genetics, vol. 53, no. 4, pp. 445-454 . https://doi.org/10.1038/s41588-021-00787-1
Nature genetics, 53(4), 445-454. Nature Publishing Group
Peyrot, W J & Price, A L 2021, ' Identifying loci with different allele frequencies among cases of eight psychiatric disorders using CC-GWAS ', Nature genetics, vol. 53, no. 4, pp. 445-454 . https://doi.org/10.1038/s41588-021-00787-1
Nature Genetics, 53(4), 445-454. Nature Publishing Group
ISSN: 1061-4036
DOI: 10.1101/2020.03.04.977389
Popis: Psychiatric disorders are highly genetically correlated, and many studies have focused on their shared genetic components. However, little research has been conducted on the genetic differences between psychiatric disorders, because case-case comparisons of allele frequencies among cases currently require individual-level data from cases of both disorders. We developed a new method (CC-GWAS) to test for differences in allele frequency among cases of two different disorders using summary statistics from the respective case-control GWAS; CC-GWAS relies on analytical assessments of the genetic distance between cases and controls of each disorder. Simulations and analytical computations confirm that CC-GWAS is well-powered and attains effective control of type I error. In particular, CC-GWAS identifies and discards false positive associations that can arise due to differential tagging of a shared causal SNP (with the same allele frequency in cases of both disorders), e.g. due to subtle differences in ancestry between the input case-control studies. We applied CC-GWAS to publicly available summary statistics for schizophrenia, bipolar disorder and major depressive disorder, and identified 116 independent genome-wide significant loci distinguishing these three disorders, including 21 CC-GWAS-specific loci that were not genome-wide significant in the input case-control summary statistics. Two of the CC-GWAS-specific loci implicate the genes KLF6 and KLF16 from the Kruppel-like family of transcription factors; these genes have been linked to neurite outgrowth and axon regeneration. We performed a broader set of case-case comparisons by additionally analyzing ADHD, anorexia nervosa, autism, obsessive-compulsive disorder and Tourette’s Syndrome, yielding a total of 196 independent loci distinguishing eight psychiatric disorders, including 72 CC-GWAS-specific loci. We confirmed that loci identified by CC-GWAS replicated convincingly in applications to data sets for which independent replication data were available. In conclusion, CC-GWAS robustly identifies loci with different allele frequencies among cases of different disorders using results from the respective case-control GWAS, providing new insights into the genetic differences between eight psychiatric disorders.
Databáze: OpenAIRE
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