ArticleThe American journal of psychiatry2014
Revisiting schizophrenia linkage data in the NIMH Repository: reanalysis of regularized data across multiple studies.
Article in The American journal of psychiatry, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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.
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Who cites it
4 citing papers in PubMed.
- Genetics of schizophrenia (Review).Experimental and therapeutic medicine · 2020Review
- [Search for risk genes in schizophrenia].Der Nervenarzt · 2017Review
- The impact of clinical heterogeneity in schizophrenia on genomic analyses.Schizophrenia research · 2015Article
- The value of regenotyping older linkage data sets with denser marker panels.Human heredity · 2014Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
objectiveThe Combined Analysis of Psychiatric Studies (CAPS) project conducted extensive review and regularization across studies of all schizophrenia linkage data available as of 2011 from the National Institute of Mental Health-funded Center for Collaborative Genomic Studies on Mental Disorders, also known as the Human Genetics Initiative (HGI). The authors reanalyzed the data using statistical methods tailored to accumulation of evidence across multiple, potentially highly heterogeneous, sets of data.
methodData were subdivided based on contributing study, major population group, and presence or absence within families of schizophrenia with a substantial affective component. The posterior probability of linkage (PPL) statistical framework was used to sequentially update linkage evidence across these data subsets (omnibus results).
resultsWhile some loci previously implicated using the HGI data were also identified in the present omnibus analysis (2q36.1, 15q23), others were not. Several loci were found that had not previously been reported in the HGI samples but are supported by independent linkage or association studies (3q28, 12q23.1, 11p11.2, Xq26.1). Not surprisingly, differences were seen across population groups. Of particular interest are signals on 11p15.3, 11p11.2, and Xq26.1, for which data from families with a substantial affective component support linkage while data from the remaining families provide evidence against linkage. All three of these loci overlap with loci reported in independent studies of bipolar disorder or mixed bipolar-schizophrenia samples.
conclusionsPublic data repositories provide the opportunity to leverage large multisite data sets for studying complex disorders. Analysis with a statistical method specifically designed for such data enables us to extract new information from an existing data resource.
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