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Cross-Trait Meta-Analysis Explores Potential Pleiotropy Across Psychiatric Conditions

NEW YORK – An international team led by investigators in the Netherlands has profiled pleiotropic genetic contributors to a dozen psychiatric conditions, documenting overlap between pairs of conditions and an outsized effect for schizophrenia-associated genes and variants.

While the analysis pointed to "substantial pleiotropic overlap" between pairs of conditions, associations found across nine of the 12 conditions were largely limited to evolutionarily conserved portions of the genome, co-senior and corresponding author Sophie van der Sluis, a child and adolescent psychology and psychiatry researcher at VU University Medical Centre, and her colleagues wrote.

As they reported in Nature Genetics on Monday, the researchers turned to cross-trait meta-analyses to assess the SNPs, genes, pathways, cell, and tissue types shared by 12 psychiatric conditions ranging from attention-deficit/hyperactivity disorder (ADHD), anxiety disorder, or depression to schizophrenia or post-traumatic stress disorder, using summary statistics from prior genome-wide association studies on individual traits.

The association studies considered included as many as 386,533 participants, in the case of insomnia, and as few as 9,725 individuals (obsessive-compulsive disorder), the team explained. The group's heritability linkage disequilibrium score regression analyses centered on SNPs found across the GWAS that passed quality control steps.

"Overall, the power of the 12 psychiatric disorder GWAS, as well as the strength of their genetic signal, varied considerably, which may affect subsequent detection of genetic overlap," the authors cautioned.

After uncovering genetic similarities across the conditions with genomic structural equation modeling and the help of the University of Queensland/QIMR Berghofer Medical Research Institute's Complex Trait Genetics Virtual Lab platform, the team performed a sample size weighted cross-trait GWAS meta-analysis using mvGWAMA (multivariate GWAS meta-analysis software).

From there, the investigators turned to a functional mapping and annotation approach known as FUMA to find 75 new and known risk loci from a set of almost 4,700 genome-wide significant SNPs unearthed in the cross-trait analysis. They also considered associations at the gene level, while incorporating regulatory insights from expression quantitative trait locus and chromatin interaction maps to flag nearly 350 psychiatric disorder-linked genes.

More than three-dozen genes and some 17 genomic risk loci appeared to coincide with more than one of the psychiatric conditions considered, they reported, while non-overlapping associations were found for four biological pathways, dozens of neuronal cell types, and 11 tissue types. Apparent overlap dipped further in analyses that included more than two conditions, though evolutionarily conserved regions stood out as potential cross-condition contributors.

"Although no loci or SNPs, and only two genes, were associated with more than two psychiatric disorders, we did observe extensive overlap among multiple psychiatric disorders for three functional genomic categories, suggesting enrichment of psychiatric disorders' genetic signal in evolutionarily conserved regions, and widespread sub-significant gene-overlap enrichment for most of the included psychiatric disorders," the authors reported.

The team noted that more than half of the genes found stemmed from schizophrenia-related associations, while the SNPs, loci, and genes implicated in the conditions dropped substantially when schizophrenia was not included in the association analyses.

"The current study highlights multiple pressing challenges that affect the potential success of cross-trait genetic research," the authors concluded, highlighting sample size, diagnostic, and other differences across conditions. "Resolving such challenges is necessary to advance our understanding of biological mechanisms underlying comorbid disorders."