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BMC Med Genet. 2010 Sep 21;11:134. doi: 10.1186/1471-2350-11-134.

Population-based study of genetic variation in individuals with autism spectrum disorders from Croatia.

Author information

  • 1Department of Pathology, Laboratory Medicine, Biomedical Graduate Studies, University of Pennsylvania, Philadelphia 19104, USA. lswang@mail.med.upenn.edu

Abstract

BACKGROUND:

Genome-wide studies on autism spectrum disorders (ASDs) have mostly focused on large-scale population samples, but examination of rare variations in isolated populations may provide additional insights into the disease pathogenesis.

METHODS:

As a first step in the genetic analysis of ASD in Croatia, we characterized genetic variation in a sample of 103 subjects with ASD and 203 control individuals, who were genotyped using the Illumina HumanHap550 BeadChip. We analyzed the genetic diversity of the Croatian population and its relationship to other populations, the degree of relatedness via Runs of Homozygosity (ROHs), and the distribution of large (>500 Kb) copy number variations.

RESULTS:

Combining the Croatian cohort with several previously published populations in the FastME analysis (an alternative to Neighbor Joining) revealed that Croatian subjects cluster, as expected, with Southern Europeans; in addition, individuals from the same geographic region within Europe cluster together. Whereas Croatian subjects could be separated from a sample of healthy control subjects of European origin from North America, Croatian ASD cases and controls are well mixed. A comparison of runs of homozygosity indicated that the number and the median length of regions of homozygosity are higher for ASD subjects than for controls (p = 6 × 10(-3)). Furthermore, analysis of copy number variants found a higher frequency of large chromosomal rearrangements (>2 Mb) in ASD cases (5/103) than in ethnically matched control subjects (1/197, p = 0.019).

CONCLUSIONS:

Our findings illustrate the remarkable utility of high-density genotype data for subjects from a limited geographic area in dissecting genetic heterogeneity with respect to population and disease related variation.

PMID:
20858243
[PubMed - indexed for MEDLINE]
PMCID:
PMC2954843
Free PMC Article

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