Literature DB >> 25496659

The impact of clinical heterogeneity in schizophrenia on genomic analyses.

Sherri G Liang1, Tiffany A Greenwood2.   

Abstract

Though clinically useful, the diagnostic systems currently employed are not well equipped to capture the substantial clinical heterogeneity observed for most psychiatric disorders, as exemplified by the complex psychotic disorder(s) that Bleuler aptly labeled the "Group of Schizophrenias". The clinical heterogeneity associated with schizophrenia has likely frustrated decades of attempts to illuminate the underlying genetic architecture, although recent genome-wide association studies have begun to provide valuable insight into the role of common genetic risk variants. Here we demonstrate the importance of using diagnostic information to identify a core form of the disorder and to eliminate potential comorbidities in genetic studies. We also demonstrate why applying a diagnostic screening procedure to the control dataset to remove individuals with potentially related disorders is critical. Additionally, subjects may participate in multiple studies at different institutions or may have genotype data released by more than one research group. It is thus good practice to verify that no identical subjects exist within or between samples prior to conducting any type of genetic analysis to avoid potential confounding of results. While the availability of genomic data for large collections of subjects has facilitated many investigations that would otherwise not have been possible, we clearly show why one must use caution when acquiring data from publicly available sources. Although the broad vs. narrow debate in terms of phenotype definition in genetic analyses will remain, it is likely that both approaches will yield different results and that both will have utility in resolving the genetic architecture of schizophrenia.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Diagnostics; Genome-wide association; Heterogeneity; Schizophrenia

Mesh:

Year:  2014        PMID: 25496659      PMCID: PMC4308487          DOI: 10.1016/j.schres.2014.11.019

Source DB:  PubMed          Journal:  Schizophr Res        ISSN: 0920-9964            Impact factor:   4.939


  56 in total

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Journal:  Nat Genet       Date:  2008-09       Impact factor: 38.330

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Stephen W Scherer; Nicholas J Schork; Thomas G Schulze; Johannes Schumacher; Markus Schwarz; Edward Scolnick; Laura J Scott; Jianxin Shi; Paul D Shilling; Stanley I Shyn; Jeremy M Silverman; Susan L Slager; Susan L Smalley; Johannes H Smit; Erin N Smith; Edmund J S Sonuga-Barke; David St Clair; Matthew State; Michael Steffens; Hans-Christoph Steinhausen; John S Strauss; Jana Strohmaier; T Scott Stroup; James S Sutcliffe; Peter Szatmari; Szabocls Szelinger; Srinivasa Thirumalai; Robert C Thompson; Alexandre A Todorov; Federica Tozzi; Jens Treutlein; Manfred Uhr; Edwin J C G van den Oord; Gerard Van Grootheest; Jim Van Os; Astrid M Vicente; Veronica J Vieland; John B Vincent; Peter M Visscher; Christopher A Walsh; Thomas H Wassink; Stanley J Watson; Myrna M Weissman; Thomas Werge; Thomas F Wienker; Ellen M Wijsman; Gonneke Willemsen; Nigel Williams; A Jeremy Willsey; Stephanie H Witt; Wei Xu; Allan H Young; Timothy W Yu; Stanley Zammit; Peter P Zandi; Peng Zhang; Frans G Zitman; Sebastian Zöllner; 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Authors:  Mirko Manchia; Jeffrey Cullis; Gustavo Turecki; Guy A Rouleau; Rudolf Uher; Martin Alda
Journal:  PLoS One       Date:  2013-10-11       Impact factor: 3.240

10.  Biological insights from 108 schizophrenia-associated genetic loci.

Authors: 
Journal:  Nature       Date:  2014-07-22       Impact factor: 49.962

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  7 in total

1.  Alteration of gray matter microstructure in schizophrenia.

Authors:  Johanna Seitz; Yogesh Rathi; Amanda Lyall; Ofer Pasternak; Elisabetta C Del Re; Margaret Niznikiewicz; Paul Nestor; Larry J Seidman; Tracey L Petryshen; Raquelle I Mesholam-Gately; Joanne Wojcik; Robert W McCarley; Martha E Shenton; Inga K Koerte; Marek Kubicki
Journal:  Brain Imaging Behav       Date:  2018-02       Impact factor: 3.978

2.  Single-nucleus RNA sequencing of midbrain blood-brain barrier cells in schizophrenia reveals subtle transcriptional changes with overall preservation of cellular proportions and phenotypes.

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3.  NRN1 Gene as a Potential Marker of Early-Onset Schizophrenia: Evidence from Genetic and Neuroimaging Approaches.

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Journal:  Int J Mol Sci       Date:  2022-07-05       Impact factor: 6.208

Review 4.  Genetic assessment of additional endophenotypes from the Consortium on the Genetics of Schizophrenia Family Study.

Authors:  Tiffany A Greenwood; Laura C Lazzeroni; Monica E Calkins; Robert Freedman; Michael F Green; Raquel E Gur; Ruben C Gur; Gregory A Light; Keith H Nuechterlein; Ann Olincy; Allen D Radant; Larry J Seidman; Larry J Siever; Jeremy M Silverman; William S Stone; Catherine A Sugar; Neal R Swerdlow; Debby W Tsuang; Ming T Tsuang; Bruce I Turetsky; David L Braff
Journal:  Schizophr Res       Date:  2015-11-18       Impact factor: 4.939

5.  HSPB1 Gene Variants and Schizophrenia: A Case-Control Study in a Polish Population.

Authors:  Malgorzata Kowalczyk; Krzysztof Kucia; Aleksander Owczarek; Renata Suchanek-Raif; Monika Paul-Samojedny; Piotr Choreza; Jan Kowalski
Journal:  Dis Markers       Date:  2022-03-15       Impact factor: 3.434

6.  Proteomic Analysis of Plasma Markers in Patients Maintained on Antipsychotics: Comparison to Patients Off Antipsychotics and Normal Controls.

Authors:  Rudolf Engelke; Sami Ouanes; Suhaila Ghuloum; Rifka Chamali; Nancy Kiwan; Hina Sarwath; Frank Schmidt; Karsten Suhre; Hassen Al-Amin
Journal:  Front Psychiatry       Date:  2022-04-25       Impact factor: 4.157

7.  Immune-Related Genomic Schizophrenic Subtyping Identified in DLPFC Transcriptome.

Authors:  Eva Childers; Elijah F W Bowen; C Harker Rhodes; Richard Granger
Journal:  Genes (Basel)       Date:  2022-07-04       Impact factor: 4.141

  7 in total

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