ArticleMedicine2020
BDNF polymorphisms across the spectrum of psychiatric morbidity: A protocol for a systematic review and meta-analysis.
Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis 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
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Long Non-coding RNA LINC01119 Promotes Neuropathic Pain by Stabilizing BDNF Transcript.Frontiers in molecular neuroscience · 2021Article
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
No grant is acknowledged in the PubMed record.
Abstract
backgroundNowadays, psychiatric morbidities are more and more common, which imposes huge social and economic burden on all countries across the world. Mental illnesses are found to be related to genetics. Over the past few years, a large number of risk genes and loci related to psychiatric morbidities have been reported. The brain-derived neurotrophic factor (BDNF) is one of the main candidates in neuropsychiatric genetics. However, different studies have shown inconsistencies regarding effect modification of BDNF polymorphisms on psychiatric morbidities. Therefore, in the present study, we aim to qualitatively and quantitatively summarize the relationship between BDNF single nucleotide polymorphisms (SNPs) and various psychiatric morbidities through a meta-analysis.
methodsPubMed, Web of Science and Embase will be searched using a specified search strategy to identify relevant studies up to April 2020. The meta-analysis will be performed on (1) allele model, (2) dominant model, (3) recessive model, (4) homozygote, and (5) heterozygote model. Sensitivity analyses will be conducted to explore the impact of individual studies on the overall result by evaluating the odd ratios (ORs) with their corresponding 95% confidence intervals (CIs) before and after removing each of the studies from our meta-analysis. Chi-square test will be used to determine whether the observed allele or genotype frequencies in the controls are consistent with HWE. The statistical heterogeneity will be verified by I statistics. The fixed effects model is needed to estimate the ORs and 95% CIs when there was no heterogeneity between results of included studies (I < 50%); instead, the random effects model should be used when results of included studies showed significant heterogeneity (I > 50%). Publication bias will be evaluated with the use of Begg test and Egger test (P < .05 is considered statistically significant). DISCUSSION: With this protocol, a methodology is established that explores the effect modification of BDNF polymorphisms on the association with psychiatric morbidities. Findings from this meta-analysis can provide significant insight into the etiology of psychiatric morbidities. REGISTRATION: Open Science Framework (OSF) Preregistration. September 15, 2020. OSF.IO/QS7XT.
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.