Analysis of High-Resolution HapMap of DTNBP1 (Dysbindin) Suggests No Consistency between Reported Common Variant Associations and Schizophrenia
Analysis of High-Resolution HapMap of DTNBP1 (Dysbindin) Suggests No Consistency between Reported Common Variant Associations and Schizophrenia is a research paper published in The American Journal of Human Genetics (2006). On theSindex it has a DataRank of 0.655. It has been cited 78 times.
Abstract
DTNBP1 was first identified as a putative schizophrenia-susceptibility gene in Irish pedigrees, with a report of association to common genetic variation. Several replication studies have reported confirmation of an association to DTNBP1 in independent European samples; however, reported risk alleles and haplotypes appear to differ between studies, and comparison among studies has been confounded because different marker sets were employed by each group. To facilitate evaluation of existing evidence of association and further work, we supplemented the extensive genotype data, available through the International HapMap Project (HapMap), about DTNBP1 by specifically typing all associated single-nucleotide polymorphisms reported in each of the studies of the Centre d'Etude du Polymorphisme Humain (CEPH)-derived HapMap sample (CEU). Using this high-density reference map, we compared the putative disease-associated haplotype from each study and found that the association studies are inconsistent with regard to the identity of the disease-associated haplotype at DTNBP1. Specifically, all five "replication" studies define a positively associated haplotype that is different from the association originally reported. We further demonstrate that, in all six studies, the European-derived populations studied have haplotype patterns and frequencies that are consistent with HapMap CEU samples (and each other). Thus, it is unlikely that population differences are creating the inconsistency of the association studies. Evidence of association is, at present, equivocal and unsatisfactory. The new dense map of the region may be valuable in more-comprehensive follow-up studies.
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DataRank Breakdown
Base Score Contribution
0.655
From this paper's citation signal
Citation Network Contribution
0
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- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
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- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.