Evidence map›Paper›PMID 20858243›Full record

ArticleBMC medical genetics2010

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

Li-San Wang, Dubravka Hranilovic, Kai Wang, Ingrid E Lindquist, Lindsay Yurcaba, Zorana-Bujas Petkovic, Nicole Gidaya, Branimir Jernej, Hakon Hakonarson, Maja Bucan

Open access · goldAbstract read
In one paragraph

Article in BMC medical genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 2 countries.

Li-San WangDepartment of Pathology, Laboratory Medicine, Biomedical Graduate Studies, University of Pennsylvania, Philadelphia 19104, USA. lswang@mail.med.upenn.edu
Dubravka Hranilovic
Kai Wang
Ingrid E Lindquist
Lindsay Yurcaba
Zorana-Bujas Petkovic
Nicole Gidaya
Branimir Jernej
Hakon Hakonarson
Maja Bucan
University of Pennsylvania · USChildren's Hospital of Philadelphia · USRudjer Boskovic Institute · HRUniversity of Zagreb · HR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenome-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.

methodsAs 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.

resultsCombining 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).

conclusionsOur 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.

Indexed as

Genetics, PopulationGenetic VariationAdultAge FactorsChildChild Development Disorders, PervasiveCluster AnalysisCroatiaFemaleGenome, HumanGenotypeHumansMaleOligonucleotide Array Sequence Analysis

Identifiers

PMID20858243
PMCPMC2954843
OpenAlexW2100795902

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.