Evidence map›Paper›PMID 31787753›Full record

SynthesisThe pharmacogenomics journal2020

Meta-analytic method reveal a significant association of theBDNF Val66Met variant with smoking persistence based on a large samples.

Hailong Zhao, Shuicai Xiong, Zhiwei Li, Xuebiao Wu, Lijuan Li

Abstract readMeta-Analysis
In one paragraph

Synthesis in The pharmacogenomics journal, 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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Hailong ZhaoDepartment of Pathophysiology, Zunyi Medical University, Zunyi, 563000, China.
Shuicai XiongPeople's hospital of Jinxian County, Nanchang, 331700, China.
Zhiwei LiPeople's hospital of Jinxian County, Nanchang, 331700, China.
Xuebiao WuDepartment of Pathophysiology, Zunyi Medical University, Zunyi, 563000, China. Wuxuebiao@yahoo.com.
Lijuan LiDepartment of Pathophysiology, Zunyi Medical University, Zunyi, 563000, China. LiLijuan@zmc.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although numerous genetic studies have reported the link between Val66Met in BDNF gene with smoking, the findings remain controversial, mainly due to small-to-moderate sample sizes. The main aim of current investigation is to explore whether the variant of Val66Met has any genetic functions in the progress of smoking persistence. The Val-based dominant genetic model considering Val/* (namely, Val/Val + Val/Met) and Met/Met as two genotypes with comparison of the frequency of each genotype in current smokers and never smokers. There were seven genetic association articles including eight independent datasets with 10,160 participants were chosen in current meta-analytic investigation. In light of the potent effects of ethnicity on homogeneity across studies, we carried out separated meta-analyses according to the ancestry origin by using the wide-used tool of Comprehensive Meta-analysis software (V 2.0). Our meta-analyses results indicated that the Val66Met polymorphism was significantly linked with smoking persistence based on either all the chosen samples (N = 10,160; Random and fixed models: pooled OR = 1.23; 95% CI = 1.03-1.46; P value = 0.012) or Asian samples (N = 2,095; Fixed model: pooled OR = 1.25; 95% CI = 1.01-1.54; P value = 0.044; Random model: pooled OR = 1.25; 95% CI = 1.001-1.56; P value = 0.049). No significant clue of bias in publications or heterogeneity across studies was detected. Thus, we conclude that the Val66Met (rs6265) variant conveys genetic susceptibility to maintaining smoking, and smokers who carry Val/* genotypes have a higher possibility of maintaining smoking than those having Met/Met genotype.

Indexed as

Brain-Derived Neurotrophic FactorCase-Control StudiesDatabases, FactualGenetic VariationHumansMethioninePolymorphism, Single NucleotideSmokingValineBDNF protein, humanBrain-Derived Neurotrophic FactorMethionineValine

Identifiers

PMID31787753
PMCPMC7253357

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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.