Trial reportTranslational psychiatry2017
A latent genetic subtype of major depression identified by whole-exome genotyping data in a Mexican-American cohort.
Trial report in Translational psychiatry, 2017. 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
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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.
- Genetic variation associated with depression in Latin American populations: a systematic review of single-nucleotide variants.Frontiers in psychiatry · 2026Pooled it
- Data-driven biological subtypes of depression: systematic review of biological approaches to depression subtyping.Molecular psychiatry · 2019Pooled it
- Classification of major depressive disorder using vertex-wise brain sulcal depth, curvature, and thickness with a deep and a shallow learning model.Molecular psychiatry · 2026Article
- Integrating brain imaging features and genomic profiles for the subtyping of major depression.Psychological medicine · 2025Article
- Dissecting biological heterogeneity in major depressive disorder based on neuroimaging subtypes with multi-omics data.Translational psychiatry · 2025Article
- The Molecular Genetics of Dissociative Symptomatology: A Transdiagnostic Literature Review.Genes · 2022Review
- Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2021Article
- Machine learning analysis of exome trios to contrast the genomic architecture of autism and schizophrenia.BMC psychiatry · 2020Article
- Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns.NeuroImage. Clinical · 2020Article
- White Matter Abnormalities in Major Depression Biotypes Identified by Diffusion Tensor Imaging.Neuroscience bulletin · 2019Article
- Machine Learning based Psychology: Advocating for A Data-Driven Approach.International journal of psychological researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Identifying data-driven subtypes of major depressive disorder (MDD) is an important topic of psychiatric research. Currently, MDD subtypes are based on clinically defined depression symptom patterns. Although a few data-driven attempts have been made to identify more homogenous subgroups within MDD, other studies have not focused on using human genetic data for MDD subtyping. Here we used a computational strategy to identify MDD subtypes based on single-nucleotide polymorphism genotyping data from MDD cases and controls using Hamming distance and cluster analysis. We examined a cohort of Mexican-American participants from Los Angeles, including MDD patients (n=203) and healthy controls (n=196). The results in cluster trees indicate that a significant latent subtype exists in the Mexican-American MDD group. The individuals in this hidden subtype have increased common genetic substrates related to major depression and they also have more anxiety and less middle insomnia, depersonalization and derealisation, and paranoid symptoms. Advances in this line of research to validate this strategy in other patient groups of different ethnicities will have the potential to eventually be translated to clinical practice, with the tantalising possibility that in the future it may be possible to refine MDD diagnosis based on genetic data.
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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.