ReviewSchizophrenia research2018
Genetic analysis of deep phenotyping projects in common disorders.
Review in Schizophrenia research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed.
- Genetic Polymorphisms and Diversity in Nonalcoholic Fatty Liver Disease (NAFLD): A Mini Review.Biomedicines · 2022Review
- Affective response to physical activity as a deep phenotype in a non-randomized pilot study.Scientific reports · 2022Article
- Genome-wide association study accounting for anticholinergic burden to examine cognitive dysfunction in psychotic disorders.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2021Article
- Emerging machine learning approaches to phenotyping cellular motility and morphodynamics.Physical biology · 2021Review
- Neuroplasticity, Neurotransmission and Brain-Related Genes in Major Depression and Bipolar Disorder: Focus on Treatment Outcomes in an Asiatic Sample.Advances in therapy · 2018Article
- Cardiovascular Precision Medicine in the Genomics Era.JACC. Basic to translational science · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Several studies of complex psychotic disorders with large numbers of neurobiological phenotypes are currently under way, in living patients and controls, and on assemblies of brain specimens. Genetic analyses of such data typically present challenges, because of the choice of underlying hypotheses on genetic architecture of the studied disorders and phenotypes, large numbers of phenotypes, the appropriate multiple testing corrections, limited numbers of subjects, imputations required on missing phenotypes and genotypes, and the cross-disciplinary nature of the phenotype measures. Advances in genotype and phenotype imputation, and in genome-wide association (GWAS) methods, are useful in dealing with these challenges. As compared with the more traditional single-trait analyses, deep phenotyping with simultaneous genome-wide analyses serves as a discovery tool for previously unsuspected relationships of phenotypic traits with each other, and with specific molecular involvements.
Indexed as
Identifiers
What OpenQuestion holds
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.