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Tiina Paunio

Researcher at University of Helsinki

Publications -  289
Citations -  29057

Tiina Paunio is an academic researcher from University of Helsinki. The author has contributed to research in topics: Population & Bipolar disorder. The author has an hindex of 59, co-authored 263 publications receiving 24006 citations. Previous affiliations of Tiina Paunio include Centre national de la recherche scientifique & National Institute for Health and Welfare.

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Biological insights from 108 schizophrenia-associated genetic loci

Stephan Ripke, +354 more
- 24 Jul 2014 - 
TL;DR: Associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses.
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Large recurrent microdeletions associated with schizophrenia

Hreinn Stefansson, +81 more
- 11 Sep 2008 - 
TL;DR: In a genome-wide search for CNVs associating with schizophrenia, a population-based sample was used to identify de novo CNVs by analysing 9,878 transmissions from parents to offspring and three deletions significantly associate with schizophrenia and related psychoses in the combined sample.
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Common variants conferring risk of schizophrenia

Hreinn Stefansson, +94 more
- 06 Aug 2009 - 
TL;DR: Findings implicating the MHC region are consistent with an immune component to schizophrenia risk, whereas the association with NRGN and TCF4 points to perturbation of pathways involved in brain development, memory and cognition.
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Genome Scan Meta-Analysis of Schizophrenia and Bipolar Disorder, Part II: Schizophrenia

Cathryn M. Lewis, +54 more
TL;DR: The GSMA produced significant genomewide evidence for linkage on chromosome 2q and suggests that some or all of these regions contain loci that increase susceptibility to schizophrenia in diverse populations.
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Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Bjarni J. Vilhjálmsson, +394 more
TL;DR: LDpred is introduced, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel, and outperforms the approach of pruning followed by thresholding, particularly at large sample sizes.