Evidence map›Paper›PMID 26555806›Full record

ReviewCurrent opinion in neurobiology2016

New statistical approaches exploit the polygenic architecture of schizophrenia--implications for the underlying neurobiology.

Andrew J Schork, Yunpeng Wang, Wesley K Thompson, Anders M Dale, Ole A Andreassen

Abstract readReview
In one paragraph

Review in Current opinion in neurobiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 1 pooled it
6.9field-weighted citation impact, top 3% 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

43 citing papers in PubMed, 1 synthesis or guideline pooled it, 68 citations in OpenAlex.

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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

5 authors at 2 institutions in 2 countries.

Andrew J SchorkMultimodal Imaging Laboratory, UC San Diego, La Jolla, CA, USA; Center for Human Development, UC San Diego, La Jolla, CA, USA; Kavli Institute for Brain and Mind, UC San Diego, La Jolla, CA, USA; Department of Cognitive Science, UC San Diego, La Jolla, CA, USA.
Yunpeng WangMultimodal Imaging Laboratory, UC San Diego, La Jolla, CA, USA; NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Neuroscience, UC San Diego, La Jolla, CA, USA.
Wesley K ThompsonMultimodal Imaging Laboratory, UC San Diego, La Jolla, CA, USA; Department of Psychiatry, UC San Diego, La Jolla, CA, USA.
Anders M DaleMultimodal Imaging Laboratory, UC San Diego, La Jolla, CA, USA; Department of Neuroscience, UC San Diego, La Jolla, CA, USA; Department of Psychiatry, UC San Diego, La Jolla, CA, USA; Department of Radiology, UC San Diego, La Jolla, CA, USA. Electronic address: andersmdale@gmail.com.
Ole A AndreassenNORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. Electronic address: o.a.andreassen@medisin.uio.no.
UC San Diego Health System · USOslo University Hospital · NO

Funding

Creating a Pediatric Imaging-Genomics Data ResourceRC2DA029475 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CHANG, LINDA, DALE, ANDERS M · 2009 to 2011
$9.1M
Mapping Individual Cognitive Differences to Neural Variance and School ReadinessR01HD061414 · NICHD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JERNIGAN, TERRY L. · 2010 to 2014
$3.3M
Traning Clinical Scientists in Radiological ImagingT32EB005970 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Eric Y Chang, Rebecca Ann Rakow-Penner · 2007 to 2026
$3.2M
Polygenicity, Pleiotrophy and Power: Novel Statistical Methods for Gene DiscoveryR01GM104400 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI THOMPSON, WESLEY KURT · 2014 to 2017
$1.6M
NIBIB NIH HHS T32 EB005970NICHD NIH HHS R01 HD061414NICHD NIH HHS R01HD061414NIDA NIH HHS RC2 DA029475NIDA NIH HHS RC2DA029475NIGMS NIH HHS 1R01GM104400-01ANIGMS NIH HHS R01 GM104400
6 · The paper itself

Abstract

Schizophrenia is a complex disorder with high heritability. Recent findings from several large genetic studies suggest a large number of risk variants are involved (i.e. schizophrenia is a polygenic disorder) and analytic approaches could be tailored for this scenario. Novel statistical approaches for analyzing GWAS data have recently been developed to be more sensitive to polygenic traits. These approaches have provided intriguing new insights into neurobiological pathways and support for the involvement of regulatory mechanisms, neurotransmission (glutamate, dopamine, GABA), and immune and neurodevelopmental pathways. Integrating the emerging statistical genetics evidence with sound neurobiological experiments will be a crucial, and challenging, next step in deciphering the specific disease mechanisms of schizophrenia.

Indexed as

Statistics as TopicGene Regulatory NetworksGenome-Wide Association StudyHumansLinkage DisequilibriumMultifactorial InheritanceSchizophrenia

Identifiers

PMID26555806
PMCPMC5380793
OpenAlexW2113194812

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.