ReviewNature neuroscience2016
Translating genome-wide association findings into new therapeutics for psychiatry.
Review in Nature neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 5 of them syntheses that pooled 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.
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.
Who cites it
73 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder.Nature genetics · 2024Pooled it
- Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression.Biological psychiatry · 2020Pooled it
- RICOPILI: Rapid Imputation for COnsortias PIpeLIne.Bioinformatics (Oxford, England) · 2020Pooled it
- Biological annotation of genetic loci associated with intelligence in a meta-analysis of 87,740 individuals.Molecular psychiatry · 2019Pooled it
- Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression.Nature genetics · 2018Pooled it
- Polygenic risk scores and plasma proteomics identify cancer-related proteins and trans-regulated protein networks.Cell genomics · 2026Article
- Leveraging and partitioning polygenic risk scores to identify cancer-related proteins.medRxiv : the preprint server for health sciences · 2025Article
- Validated metabolomic biomarkers in psychiatric disorders: a narrative review.Molecular medicine (Cambridge, Mass.) · 2025Review
- Genomic strategies for drug repurposing.Journal of the Egyptian National Cancer Institute · 2024Review
- How Real-World Data Can Facilitate the Development of Precision Medicine Treatment in Psychiatry.Biological psychiatry · 2024Review
- Progress and Implications from Genetic Studies of Bipolar Disorder.Neuroscience bulletin · 2024Review
- The effects of methylphenidate and atomoxetine on Drosophila brain at single-cell resolution and potential drug repurposing for ADHD treatment.Molecular psychiatry · 2024Article
- Multi-omics cannot replace sample size in genome-wide association studies.Genes, brain, and behavior · 2023Article
- multi-GPA-Tree: Statistical approach for pleiotropy informed and functional annotation tree guided prioritization of GWAS results.PLoS computational biology · 2023Article
- Examining the shared etiology of psychopathology with genome-wide association studies.Physiological reviews · 2023Review
- Regulation of Human Endogenous Metabolites by Drug Transporters and Drug Metabolizing Enzymes: An Analysis of Targeted SNP-Metabolite Associations.Metabolites · 2023Article
- Exploring Genetic and Neural Risk of Specific Reading Disability within a Nuclear Twin Family Case Study: A Translational Clinical Application.Journal of personalized medicine · 2023Article
- Ethnic, gender and other sociodemographic biases in genome-wide association studies for the most burdensome non-communicable diseases: 2005-2022.Human molecular genetics · 2023Article
- CACNA1C (CaNeuropharmacology · 2022Review
- Charting the Landscape of Genetic Overlap Between Mental Disorders and Related Traits Beyond Genetic Correlation.The American journal of psychiatry · 2022Article
13 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
Abstract
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.
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Registered trials
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.