Evidence map›Paper›PMID 32001736›Full record

ArticleScientific reports2020

Association of relative brain age with tobacco smoking, alcohol consumption, and genetic variants.

Kaida Ning, Lu Zhao, Will Matloff, Fengzhu Sun, Arthur W Toga

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
75citing papers in PubMed, 2 pooled it
20.9field-weighted citation impact, top 1% of its field
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

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.

3 · Its place in the literature

Who cites it

75 citing papers in PubMed, 2 syntheses or guidelines pooled it, 158 citations in OpenAlex.

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15 more citing papers are in PubMed but not listed here.

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 at 1 institution in 1 country.

Kaida NingUSC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, California, 90033, USA.
Lu ZhaoUSC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, California, 90033, USA.
Will MatloffUSC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, California, 90033, USA.
Fengzhu SunMolecular and Computational Biology Program, University of Southern California, Los Angeles, CA, 90089, USA.
Arthur W TogaUSC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, California, 90033, USA. Toga@loni.usc.edu.
University of Southern California · US

Funding

TR&D3: Intrinsic Surface MappingP41EB015922 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI VAN HORN, JOHN DARRELL · 2012 to 2022
$14.1M
TrainingU54EB020406 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TOGA, ARTHUR W · 2014 to 2018
$12.5M
Genetic Influences on Human Neuroanatomical ShapesR01MH094343 · NIMH · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TOGA, ARTHUR W · 2012 to 2016
$2.4M
Medical Research Council MC_PC_12028Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NIBIB NIH HHS P41 EB015922NIBIB NIH HHS U54 EB020406NIMH NIH HHS R01 MH094343
6 · The paper itself

Abstract

Brain age is a metric that quantifies the degree of aging of a brain based on whole-brain anatomical characteristics. While associations between individual human brain regions and environmental or genetic factors have been investigated, how brain age is associated with those factors remains unclear. We investigated these associations using UK Biobank data. We first trained a statistical model for obtaining relative brain age (RBA), a metric describing a subject's brain age relative to peers, based on whole-brain anatomical measurements, from training set subjects (n = 5,193). We then applied this model to evaluation set subjects (n = 12,115) and tested the association of RBA with tobacco smoking, alcohol consumption, and genetic variants. We found that daily or almost daily consumption of tobacco and alcohol were both significantly associated with increased RBA (P < 0.001). We also found SNPs significantly associated with RBA (p-value < 5E-8). The SNP most significantly associated with RBA is located in MAPT gene. Our results suggest that both environmental and genetic factors are associated with structural brain aging.

Indexed as

AgedAged, 80 and overAgingAlcohol DrinkingBiological Specimen BanksBrainCognitionFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNeuroimagingPolymorphism, Single NucleotideSmokingtau ProteinsMAPT protein, humantau Proteins

Identifiers

PMID32001736
PMCPMC6992742
OpenAlexW3003241500

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.