SynthesisProgress in neuro-psychopharmacology & biological psychiatry2018
Imaging genetics paradigms in depression research: Systematic review and meta-analysis.
Synthesis in Progress in neuro-psychopharmacology & biological psychiatry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 22 citations in OpenAlex.
- Brain-derived neurotrophic factor (BDNF) epigenomic modifications and brain-related phenotypes in humans: A systematic review.Neuroscience and biobehavioral reviews · 2023Pooled it
- Application of a diathesis-stress model to the interplay of cortical structural development and emerging depression in youth.Clinical psychology review · 2020Pooled it
- Neurobiological mechanisms and brain network dysfunction in major depressive disorder: an integrative review.Frontiers in integrative neuroscience · 2026Review
- Gray and white matter differences in the medial temporal lobe in late-life depression: a multimodal PET-MRI investigation.Psychological medicine · 2025Article
- Genetic polymorphisms iniScience · 2022Article
- Machine Learning and Deep Learning for the Pharmacogenomics of Antidepressant Treatments.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2021Review
- Left Cerebral Cortex Complexity in Patients with Major Depression Disorder: A Small-Sample Pilot Study.Psychiatry and clinical psychopharmacology · 2021Article
- Predicting Depression in Community Dwellers Using a Machine Learning Algorithm.Diagnostics (Basel, Switzerland) · 2021Article
- Deep Learning with Neuroimaging and Genomics in Alzheimer's Disease.International journal of molecular sciences · 2021Review
- Comparison of Regression and Machine Learning Methods in Depression Forecasting Among Home-Based Elderly Chinese: A Community Based Study.Frontiers in psychiatry · 2021Article
- Dopamine Multilocus Genetic Profile, Spontaneous Activity of Left Superior Temporal Gyrus, and Early Therapeutic Effect in Major Depressive Disorder.Frontiers in psychiatry · 2020Article
- Neuroscience-Informed Treatments.Focus (American Psychiatric Publishing) · 2019Article
- Association between genetic variants and depression in a Romanian cohort.Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologieArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 10 institutions in 8 countries.
Funding
Abstract
Imaging genetics studies involving participants with major depressive disorder (MDD) have expanded. Nevertheless, findings have been inconsistent. Thus, we conducted a systematic review and meta-analysis of imaging genetics studies that enrolled MDD participants across major databases through June 30th, 2017. Sixty-five studies met eligibility criteria (N = 4034 MDD participants and 3293 controls), and there was substantial between-study variability in the methodological quality of included studies. However, few replicated findings emerged from this literature with only 22 studies providing data for meta-analyses (882 participants with MDD and 616 controls). Total hippocampal volumes did not significantly vary in MDD participants or controls carrying either the BDNF Val66Met 'Met' (386 participants with MDD and 376 controls) or the 5-HTTLPR short 'S' (310 participants with MDD and 230 controls) risk alleles compared to non-carriers. Heterogeneity across studies was explored through meta-regression and subgroup analyses. Gender distribution, the use of medications, segmentation methods used to measure the hippocampus, and age emerged as potential sources of heterogeneity across studies that assessed the association of 5-HTTLPR short 'S' alleles and hippocampal volumes. Our data also suggest that the methodological quality of included studies, publication year, and the inclusion of brain volume as a covariate contributed to the heterogeneity of studies that assessed the association of the BDNF Val66Met 'Met' risk allele and hippocampal volumes. In exploratory voxel-wise meta-analyses, MDD participants carrying the 5-HTTLPR short 'S' allele had white matter microstructural abnormalities predominantly in the corpus callosum, while carriers of the BDNF Val66Met 'Met' allele had larger gray matter volumes and hyperactivation of the right middle frontal gyrus compared to non-carriers. In conclusion, few replicated findings emerged from imaging genetics studies that included participants with MDD. Nevertheless, we explored and identified specific sources of heterogeneity across studies, which could provide insights to enhance the reproducibility of this emerging field.
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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.