ArticleFrontiers in psychiatry2022
Expansion of Schizophrenia Gene Network Knowledge Using Machine Learning Selected Signals From Dorsolateral Prefrontal Cortex and Amygdala RNA-seq Data.
Article in Frontiers in psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 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
11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.
- Genetic Influences on the Developing Young Brain and Risk for Neuropsychiatric Disorders.Biological psychiatry · 2023Pooled it
- A Systematic Review of the Human Accelerated Regions in Schizophrenia and Related Disorders: Where the Evolutionary and Neurodevelopmental Hypotheses Converge.International journal of molecular sciences · 2023Pooled it
- Examining the gene network and prognostic biomarkers in the onset of colorectal cancer in stool samples using machine learning.Discover oncology · 2026Article
- In vivo mapping of protein-protein interactions of schizophrenia risk factors generates an interconnected disease network.Schizophrenia (Heidelberg, Germany) · 2026Article
- Whole transcriptome sequencing to uncover CircRNA expression patterns linked to schizophrenia pathogenesis.European journal of medical research · 2025Article
- Perturbations in the neuroactive ligand-receptor interaction and renin angiotensin system pathways are associated with cancer-related cognitive impairment.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025Article
- Exploring the Intersection of Schizophrenia, Machine Learning, and Genomics: Scoping Review.JMIR bioinformatics and biotechnology · 2024Article
- Nicotine Exposure in a Phencyclidine-Induced Mice Model of Schizophrenia: Sex-Selective Medial Prefrontal Cortex Protein Markers of the Combined Insults in Adolescent Mice.International journal of molecular sciences · 2023Article
- Development and validation of asthma risk prediction models using co-expression gene modules and machine learning methods.Scientific reports · 2023Article
- Study on the treatment of postmenopausal osteoporosis with quercetin in Liuwei Dihuang Pill based on network pharmacology.Journal of orthopaedic surgery and research · 2023Article
- The gene expression patterns as surrogate indices of pH in the brain.Frontiers in psychiatry · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is widely accepted, given the complex nature of schizophrenia (SCZ) gene networks, that a few or a small number of genes are unlikely to represent the underlying functional pathways responsible for SCZ pathogenesis. Several studies from large cohorts have been performed to search for key SCZ network genes using different analytical approaches, such as differential expression tests, genome-wide association study (GWAS), copy number variations, and differential methylations, or from the analysis of mutations residing in the coding regions of the genome. However, only a small portion (<10%) of candidate genes identified in these studies were considered SCZ disease-associated genes in SCZ pathways. RNA sequencing (RNA-seq) has been a powerful method to detect functional signals. In this study, we used RNA-seq data from the dorsolateral prefrontal cortex (DLPFC) from 254 individuals and RNA-seq data from the amygdala region from 46 individuals. Analysis was performed using machine learning methods, including random forest and factor analysis, to prioritize the numbers of genes from previous SCZ studies. For genes most differentially expressed between SCZ and healthy controls, 18 were added to known SCZ-associated pathways. These include three genes (
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.