| Title |
Genetics of Schizophrenia: Ready to Translate?
|
|---|---|
| Published in |
Current Psychiatry Reports, July 2017
|
| DOI | 10.1007/s11920-017-0807-5 |
| Pubmed ID | |
| Authors |
Claire Foley, Aiden Corvin, Shigeki Nakagome |
| Abstract |
This is an era where we have significantly advanced the understanding of the genetic architecture of schizophrenia. In this review, we consider how this knowledge may translate into advances that will improve patient care. Large-scale genome-wide association studies (GWAS) have identified more than a hundred loci each making a small contribution to illness risk. Meta-analysis of copy number variants (CNVs) in the Psychiatric Genomics Consortium (PGC) dataset has confirmed that some variants have a moderate or large impact on risk, although these are rare in the population. Genome sequencing advances allow a much more comprehensive evaluation of genomic variation. We describe the key findings from whole exome studies to date. These studies are happening against a backdrop of growing understanding of the regulation and expression of genes and better functional tools to investigate molecular mechanisms in model systems. We provide an overview of how recent approaches in schizophrenia genetics are converging and consider how they could impact on diagnostics, the development of personalized medicine, and drug discovery. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 188 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 188 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 40 | 21% |
| Student > Ph. D. Student | 28 | 15% |
| Student > Master | 19 | 10% |
| Researcher | 9 | 5% |
| Student > Doctoral Student | 8 | 4% |
| Other | 21 | 11% |
| Unknown | 63 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 34 | 18% |
| Medicine and Dentistry | 28 | 15% |
| Neuroscience | 24 | 13% |
| Psychology | 8 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 3% |
| Other | 17 | 9% |
| Unknown | 71 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 May 2019.
All research outputs
#13,513,523
of 23,964,824 outputs
Outputs from Current Psychiatry Reports
#797
of 1,227 outputs
Outputs of similar age
#149,951
of 319,348 outputs
Outputs of similar age from Current Psychiatry Reports
#19
of 33 outputs
Altmetric has tracked 23,964,824 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,227 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.5. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
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We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.