ReviewCells2020
Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric Disorders.
Review in Cells, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 19 citations in OpenAlex.
- Psychiatric Genomics 2025: State of the Art and the Path Forward.The Psychiatric clinics of North America · 2025Review
- Endophenotype 2.0: updated definitions and criteria for endophenotypes of psychiatric disorders, incorporating new technologies and findings.Translational psychiatry · 2024Review
- Integration of xeno-free single-cell cloning in CRISPR-mediated DNA editing of human iPSCs improves homogeneity and methodological efficiency of cellular disease modeling.Stem cell reports · 2023Article
- Mutations in human DNA methyltransferase DNMT1 induce specific genome-wide epigenomic and transcriptomic changes in neurodevelopment.Human molecular genetics · 2023Article
- Review
- Article
- In Vitro Recapitulation of Neuropsychiatric Disorders with Pluripotent Stem Cells-Derived Brain Organoids.International journal of environmental research and public health · 2021Review
- Treatment patterns and appropriateness of antipsychotic prescriptions in patients with schizophrenia.Scientific reports · 2021Observational
- Single-Cell Transcriptomics Supports a Role ofInternational journal of molecular sciences · 2021Review
- Chromatin Remodeler CHD8 in Autism and Brain Development.Journal of clinical medicine · 2021Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome-wide association studies (GWAS) have identified an increasing number of genetic variants that significantly associate with psychiatric disorders. Despite this wealth of information, our knowledge of which variants causally contribute to disease, how they interact, and even more so of the functions they regulate, is still poor. The availability of embryonic stem cells (ESCs) and the advent of patient-specific induced pluripotent stem cells (iPSCs) has opened new opportunities to investigate genetic risk variants in living disease-relevant cells. Here, we analyze how this progress has contributed to the analysis of causal relationships between genetic risk variants and neuronal phenotypes, especially in schizophrenia (SCZ) and bipolar disorder (BD). Studies on rare, highly penetrant risk variants have originally led the field, until more recently when the development of (epi-) genetic editing techniques spurred studies on cause-effect relationships between common low risk variants and their associated neuronal phenotypes. This reorientation not only offers new insights, but also raises issues on interpretability. Concluding, we consider potential caveats and upcoming developments in the field of ESC/iPSC-based modeling of causality in psychiatric disorders.
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.