Lars Bolund

Identifying Rare Variation in Cases of Schizophrenia in the Isolated Population of the Faroe Islands using Whole-genome Sequencing

Research output: Contribution to conferencePosterResearch

  • Thomas Damm Als
  • Francesco Lescai, Denmark
  • Hans Dahl, Amplexa Genetics A/s, Odense, Denmark
  • Ditte Demontis
  • August Wang, Capitol Region of Denmark, Denmark
  • Gudrid Andorsdottir, Genetic Biobank of the Faroes, Denmark
  • Marjun Biskopstø, Genetic Biobank of the Faroes, Faroe Islands
  • Oddbjørg Johansen, Genetic Biobank of the Faroes, Faroe Islands
  • Jakob Grove
  • Mette Nyegaard, Denmark
  • Lars Bolund
  • Ole Mors
  • Wang Jun, BGI-Shenzhen, Denmark
  • Anders Børglum
The allelic architecture of schizophrenia (SZ) is likely to be underlined by a combination of multiple common and rare variants. Genome-wide association studies (GWAS) and large-scale consortia meta-analysis of GWAS have successfully been applied in the search for common variants affecting the risk of developing SZ. However, these studies are designed to examining only “the common variant” proportion of the genomic landscape of SZ.
Due to increased genetic drift during founding and potential bottlenecks, followed by population expansion, isolated populations may be particularly useful in identifying rare disease variants, that may appear at higher frequencies and/or within a more clearly distinct haplotype structure compared to outbred populations. Small isolated populations also typically show reduced phenotypic, genetic and environmental heterogeneity, thus making them advantageous in studies aiming to map risk variants involved in complex traits.
We aim at utilizing samples of cases and controls of the isolated population of the Faroe Islands to conduct whole-genome-sequence analysis in order to identify rare genetic variants associated with schizophrenia.

We will search for rare genetic variants influencing susceptibility to schizophrenia using whole genome sequencing of Faroese case-control samples.
We will conduct association testing based on IBD information (IBD association testing) by analysing genome-wide association of shared IBD segments identified by the method implemented in GERMLINE and clustered using the DASH algorithm. Genomic regions with evidence for shared ancestral polymorphisms and/or genetic linkage co-segregation will thus be prioritized. We hypothesize greater degree of IBD sharing of rare haplotypes in cases compared to controls for regions harbouring disease susceptibility variants.
Concurrently we will test for association of single variants within IBD regions in combination with gene-based tests. We will take into account the genetic structure of the Faroese population thereby minimizing spurious association caused by population substructure.

Per sample mean depth is nowhere less than 4.3x and is on average 6.7x. More than 10 million Single Nucleotide Variants (SNVs) were identified based multi-sample calling of the aligned sequences.

Identified risk alleles may, however, either appear to be private to the isolated population and not observed elsewhere or extremely rare in other populations. Findings using isolated populations may therefore not necessarily generalise to other populations, thus making replication difficult, but findings may still contribute to a general understanding of disease aetiology. We expect to identify novel and/or rare variants associated with schizophrenia susceptibility, that my be relevant for the general understanding of the aetiology of schizophrenia and of direct importance on the Faroe Islands and neighbouring populations with shared ancestry.

Funding: This study was funded by the Lundbeck Foundation, Denmark. Disclaimer: The Lundbeck Foundation had no involvement in any aspect of the study.
Original languageDanish
Publication year17 Oct 2015
Publication statusPublished - 17 Oct 2015
EventXXIII World Congress of Psychiatric Genetics - Fairmont Royal York, Toronto, Canada
Duration: 16 Oct 201520 Oct 2015


ConferenceXXIII World Congress of Psychiatric Genetics
LocationFairmont Royal York

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ID: 95702639