Translating genome-wide association findings into new therapeutics for psychiatry.
paper
Cited
Public
- Authors
- Breen, Gerome; Li, Qingqin; Roth, Bryan L; O'Donnell, Patricio; Didriksen, Michael; Dolmetsch, Ricardo; O'Reilly, Paul F; Gaspar, HΓ©lΓ©na A; Manji, Husseini; Huebel, Christopher; Kelsoe, John R; Malhotra, Dheeraj; Bertolino, Alessandro; Posthuma, Danielle; Sklar, Pamela; Kapur, Shitij; Sullivan, Patrick F; Collier, David A; Edenberg, Howard J
- Year
- 2016
- Journal
- Nature neuroscience
- PMID
- 27786187
- DOI
- 10.1038/nn.4411
- PMCID
- PMC5676453
Genome-wide association studies (GWAS) in psychiatry, once they reach sufficient sample size and power, have been enormously successful. The Psychiatric Genomics Consortium (PGC) aims for mega-analyses with sample sizes that will grow to >1 million individuals in the next 5 years. This should lead to hundreds of new findings for common genetic variants across nine psychiatric disorders studied by the PGC. The new targets discovered by GWAS have the potential to restart largely stalled psychiatric drug development pipelines, and the translation of GWAS findings into the clinic is a key aim of the recently funded phase 3 of the PGC. This is not without considerable technical challenges. These approaches complement the other main aim of GWAS studies, risk prediction approaches for improving detection, differential diagnosis, and clinical trial design. This paper outlines the motivations, technical and analytical issues, and the plans for translating PGC phase 3 findings into new therapeutics.
PGC GWAS Drug Target Analysis Strategy: utilising diverse information sources for drug target discovery.
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| Name | Type |
|---|---|
| ADHD | phenotype |
| Alzheimer's disease | phenotype |
| anorexia nervosa | phenotype |
| anti-diabetes drugs local | drug |
| Aripiprazole lauroxil local | drug |
| autism | phenotype |
| bipolar disorder | phenotype |
| brain circuits | anatomy |
| Brainseq25 local | cohort |
| BrainSeq25 local | cohort |
| Brexpiprazole local | drug |
| C4 local | gene |
| cardiovascular disease risk local | phenotype |
| Cariprazine local | drug |
| clinical trials | cohort |
| CommonMind Consortium | cohort |
| common variants | cohort |
| complex disorders | phenotype |
| compounds | drug |
| copy number variation | variant |
| de-novo damaging mutations local | variant |
| disorder | phenotype |
| dopamine receptors | drug |
| eQTLGen Consortium | cohort |
| First episode psychosis local | phenotype |
| genes | gene |
| genetic risk | cohort |
| genetic variants | cohort |
| GWAS | cohort |
| HMGCR | gene |
| humans | cohort |
| hypercholesterolemia local | phenotype |
| intellectual disability | phenotype |
| intermediate phenotypes | phenotype |
| Large, deeply phenotyped longitudinal samples local | cohort |
| LDL cholesterol | phenotype |
| LDL cholesterol metabolism local | phenotype |
| lipid levels | phenotype |
| LPA local | gene |
| major depressive disorder | phenotype |
| mQTL | variant |
| mutations | variant |
| neuronal networks local | anatomy |
| novel therapeutics local | drug |
| PCSK9 | gene |
| pervasive developmental delay local | phenotype |
| PGC | cohort |
| PGC3 disorders local | phenotype |
| plasma lipoprotein(a) levels local | phenotype |
| polygenic risk score | cohort |
| postmortem brain | anatomy |
| pQTL | variant |
| PsychENCODE | cohort |
| psychiatric disorders | phenotype |
| Psychiatric Genomics Consortium | cohort |
| rare variant | cohort |
| risk allele | cohort |
| rodents | cohort |
| schizophrenia | phenotype |
| Serotonin receptors local | drug |
| SLC30A8 | gene |
| SNP | cohort |
| type 2 diabetes | phenotype |
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