TY - JOUR
T1 - Genetics of schizophrenia and bipolar disorder
T2 - Potential clinical applications
AU - Gupta, Rishab
AU - Bigdeli, Tim B.
AU - Buckley, Peter F.
AU - Fanous, Ayman H.
N1 - Publisher Copyright:
© SLACK Incorporated.
PY - 2021
Y1 - 2021
N2 - Schizophrenia and bipolar disorder were the first psychiatric illnesses to demonstrate familial aggregation in systematic studies. Twin studies demonstrate high (up to 80%) heritability. Several decades of research using linkage, candidate gene, genome-wide association studies (GWASs), and next-generation sequencing studies ensued in the effort to identify etiologically relevant genetic variants. Over the last decade, GWASs using consortium-based datasets of tens of thousands of participants led to the confirmation of polygenic architectures in both illnesses, which overlapped with each other, as well as the identification of hundreds of mostly non-coding variants. Large, recurrent copy number variants (CNVs) and a higher CNV burden have been robustly identified in schizophrenia, but not bipolar disorder. Polygenic risk scores have emerged as promising signatures of underlying illness risk, which might be useful in predicting treatment response and other outcome phenotypes. Pharmacogenetic studies show promise to identify variants that predict drug response and adverse effects. However, they are currently underpowered because of the expense of conducting trials with sample sizes adequate to detect genetic variants of small effect. Large-scale precision medicine efforts such as All of Us and the Million Veteran Program are in process and might yet yield such information.
AB - Schizophrenia and bipolar disorder were the first psychiatric illnesses to demonstrate familial aggregation in systematic studies. Twin studies demonstrate high (up to 80%) heritability. Several decades of research using linkage, candidate gene, genome-wide association studies (GWASs), and next-generation sequencing studies ensued in the effort to identify etiologically relevant genetic variants. Over the last decade, GWASs using consortium-based datasets of tens of thousands of participants led to the confirmation of polygenic architectures in both illnesses, which overlapped with each other, as well as the identification of hundreds of mostly non-coding variants. Large, recurrent copy number variants (CNVs) and a higher CNV burden have been robustly identified in schizophrenia, but not bipolar disorder. Polygenic risk scores have emerged as promising signatures of underlying illness risk, which might be useful in predicting treatment response and other outcome phenotypes. Pharmacogenetic studies show promise to identify variants that predict drug response and adverse effects. However, they are currently underpowered because of the expense of conducting trials with sample sizes adequate to detect genetic variants of small effect. Large-scale precision medicine efforts such as All of Us and the Million Veteran Program are in process and might yet yield such information.
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U2 - 10.3928/00485713-20210310-01
DO - 10.3928/00485713-20210310-01
M3 - Article
AN - SCOPUS:85105132935
SN - 0048-5713
VL - 51
SP - 158
EP - 164
JO - Psychiatric Annals
JF - Psychiatric Annals
IS - 4
ER -