ReviewGenes2023
The Genetic Side of the Mood: A Scientometric Review of the Genetic Basis of Mood Disorders.
Review in Genes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Effect of Benzodiazepines and Z-Drug Medications During Antenatal and Postnatal Depression and Anxiety: A Systematic Review and Meta-Analysis.Combinatorial chemistry & high throughput screening · 2025Pooled it
- Culture and the assumptions about appearance and reality: a scientometric look at a century of research.Frontiers in psychology · 2023Pooled it
- Circulating long noncoding RNA: New frontiers in biomarker research for mood disorders.Genomic psychiatry : advancing science from genes to society · 2025Article
- Deciphering the epigenetic role of long non-coding RNAs in mood disorders: Focus on human brain studies.Clinical and translational medicine · 2025Review
- Correlation of theFrontiers in pharmacology · 2024Article
- Sleep Profiles in Eating Disorders: A Scientometric Study on 50 Years of Clinical Research.Healthcare (Basel, Switzerland) · 2023Review
- Mental Health in the Post-Lockdown Scenario: A Scientometric Investigation of the Main Thematic Trends of Research.International journal of environmental research and public health · 2023Review
- Review
- A Scientometric Review of Infant Cry and Caregiver Responsiveness: Literature Trends and Research Gaps over 60 Years of Developmental Study.Children (Basel, Switzerland) · 2023Review
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mood disorders are highly heritable psychiatric disorders. Over the years, many genetic polymorphisms have been identified to pose a higher risk for the development of mood disorders. To overview the literature on the genetics of mood disorders, a scientometric analysis was performed on a sample of 5342 documents downloaded from Scopus. The most active countries and the most impactful documents in the field were identified. Furthermore, a total of 13 main thematic clusters emerged in the literature. From the qualitative inspection of clusters, it emerged that the research interest moved from a monogenic to a polygenic risk framework. Researchers have moved from the study of single genes in the early 1990s to conducting genome-wide association studies around 2015. In this way, genetic overlaps between mood disorders and other psychiatric conditions emerged too. Furthermore, around the 2010s, the interaction between genes and environmental factors emerged as pivotal in understanding the risk for mood disorders. The inspection of thematic clusters provides a valuable insight into the past and recent trends of research in the genetics of mood disorders and sheds light onto future lines of research.
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.