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Record W4403636309 · doi:10.1186/s12888-024-06195-z

Genetic polymorphism involved in major depressive disorder: a systemic review and meta-analysis

2024· review· en· W4403636309 on OpenAlexaboutno aff
Areeya Suktas, Tipaya Ekalaksananan, Sirinart Aromseree, Sureewan Bumrungthai, Nopparat Songserm, Chamsai Pientong

Bibliographic record

VenueBMC Psychiatry · 2024
Typereview
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsnot available
FundersKhon Kaen University
KeywordsMeta-analysisMajor depressive disorderPolymorphism (computer science)PsychiatryMedicinePsychologyGeneticsGenotypeBiologyGeneInternal medicineCognition

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVE: Genetic polymorphism studies in families and twins indicated the heritability of depression. However, the association between genes with genetic polymorphism and depression provides various findings and remains unclear. Therefore, we conducted a systematic review and meta-analysis to determine the genes with their polymorphism associated with the symptomatic depression known as major depressive disorder (MDD). MATERIALS AND METHODS: PubMed and Scopus were searched for relevant studies published before May 22, 2023 (1968-2023), and 62 were selected for this review. The study's bias risk was investigated using the Newcastle-Ottawa scale. Gene functional enrichment analysis was investigated for molecular function (MF) and biological process (BP) and pathways. A meta-analysis of the studied genes that were replicative in the same single nucleotide polymorphism was conducted using a random-effect model. RESULTS: The 49 genes involved in MDD were studied and engaged in several pathways, such as tryptophan metabolism or dopaminergic and serotonergic synapses. Based on gene overlapping in MF and BP, 13 genes with polymorphisms were identified as related to MDD. Most of them were only studied once. Solute carrier family 6 member 4 (SLC6A4) overlapping between MF and BP and brain-derived neurotrophic factor (BDNF) as unique to BP were replicative studied and used in the meta-analysis. The polymorphism of SLC6A4 SS and LS genotypes increased the occurrence of MDD development but not significantly [odd ratio (OR) = 1.39; 95% confidence interval (CI) = 0.87-2.22; P = 0.16 and OR = 1.13; 95% CI = 0.84-1.53; P = 0.42, respectively]. A similar result was observed for BDNF rs6265 GG (OR = 1.26; 95% CI = 0.78-2.06; P = 0.35) and BDNF rs6265 AA genotypes (OR = 1.12; 95% CI = 0.77-1.64; P = 0.56). These studies indicated low bias and significant heterogeneity. CONCLUSION: At least 13 studied genes with polymorphisms were involved in MDD development according to MF and BP, but not significantly. These results suggest that MDD development risk factors might require genetic and other factors for interaction and induction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.025
Bibliometrics0.0080.011
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.085
GPT teacher head0.345
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2024
Admission routes1
Has abstractyes

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