npj Genomic MedicineGeneticsPeer-reviewed journal article
Both rare and common genetic variants contribute to autism in the Faroe Islands
Claire S. LeblondiD, Freddy CliquetiD, Coralie Carton-Buonafine, Guillaume HuguetiD, Alexandre MathieuiD, Thomas KergroheniD, Julien BurattiiD, Nathalie Lemière, Laurence CuissetiD, Thierry BienvenuiD, Anne BolandiD, Jean‐François DeleuzeiD, Tórmóður Stórá, Rannvá Biskupstø, Jónrit HallingiD, Guðrið AndorsdóttiriD, Eva BillstedtiD, Christopher GillbergiD, Thomas BourgeroniD
Abstract
The number of genes associated with autism is increasing, but few studies have been performed on epidemiological cohorts and in isolated populations. Here, we investigated 357 individuals from the Faroe Islands including 36 individuals with autism, 136 of their relatives and 185 non-autism controls. Data from SNP array and whole exome sequencing revealed that individuals with autism compared to controls had a higher burden of copy-number variants (p < 0.05), higher inbreeding status (p < 0.005) and higher load of homozygous deleterious variants (p < 0.01). Our analysis supports the role of several genes/loci associated with autism (e.g. NRXN1, ADNP, 22q11 deletion) and identified new truncating (e.g. GRIK2, ROBO1, NINL and IMMP2L) or recessive deleterious variants (e.g. KIRELL3 and CNTNAP2) affecting autism-risk genes. It also revealed three genes involved in synaptic plasticity, RIMS4, KALRN and PLA2G4A, carrying de novo deleterious variants in individuals with autism without intellectual disability. In summary, our analysis provides a better understanding of the genetic architecture of autism in isolated populations by highlighting the role of both common and rare gene variants and pointing at new autism-risk genes. It also indicates that more knowledge about how multiple genetic hits affect neuronal function will be necessary to fully understand the genetic architecture of autism.
- organism: human
- assay: whole-exome sequencing
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- Citations
- 84
- FWCI
- 6.84
- Field percentile
- top 2%
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