Evidence map›Paper›PMID 31280115›Full record

ArticleNeurobiology of aging2019

Identification of age- and gender-associated long noncoding RNAs in the human brain with Alzheimer's disease.

Mei Cao, Huaqing Li, Jian Zhao, Juan Cui, Guoku Hu

Open access · greenAbstract read
In one paragraph

Article in Neurobiology of aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 2 pooled it
3.4field-weighted citation impact, top 6% 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

50 citing papers in PubMed, 2 syntheses or guidelines pooled it, 79 citations in OpenAlex.

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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 at 4 institutions in 3 countries.

Mei CaoCore Laboratory, School of Medicine, Sichuan Provincial People's Hospital Affiliated to University of Electronic Science and Technology of China, Chengdu, People's Republic of China.
Huaqing LiDepartment of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA.
Jian ZhaoKey Laboratory of Biological Resource and Ecological Environment of Chinese Education Ministry, College of Life Sciences, Sichuan University, Chengdu, People's Republic of China. Electronic address: zj804@163.com.
Juan CuiDepartment of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA. Electronic address: jcui@unl.edu.
Guoku HuDepartment of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center, Omaha, NE, USA. Electronic address: guoku.hu@unmc.edu.
University of Nebraska–Lincoln · USNebraska Medical Center · USSichuan University · CNUniversity of Electronic Science and Technology of China · CN

Funding

Therapeutics Core (Page 286)P30MH062261 · NIMH · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI BUCH, SHILPA J., FOX, HOWARD S · 2000 to 2021
$37.7M
The role of stress in the fetal origin of obesity and metabolic dysfunctionP20GM104320 · NIGMS · UNIVERSITY OF NEBRASKA LINCOLN · PI ZEMPLENI, JANOS · 2014 to 2024
$24.9M
HIV-1 mediated synaptodendritic injury and microglial activation: Role of extracellular vesicle miRNAsR01MH112848 · NIMH · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI BUCH, SHILPA J., HU, GUOKU · 2017 to 2021
$2.1M
HIV Tat & cocaine-mediated alterations in microglial migration & activation involve epigenetic reulation of miRNAsR01DA043138 · NIDA · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI BUCH, SHILPA J., GUO, MINGLEI · 2016 to 2020
$1.9M
Intranasal delivery of exosomes loaded with miRs -223 and -124 as a therapeutic strategy for HAND in cocaine usersR21DA046831 · NIDA · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI CHIVERO, ERNEST, GURUMURTHY, CHANNABASAVAIAH · 2018 to 2019
$419k
Exosome-mediated anti-microRNA delivery into the CNS: A Novel Threpautic for HAND in opiate usersR21DA042704 · NIDA · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI GUO, MINGLEI, HU, GUOKU · 2017 to 2018
$414k
NIDA NIH HHS R01 DA043138NIDA NIH HHS R21 DA042704NIDA NIH HHS R21 DA046831NIGMS NIH HHS P20 GM104320NIMH NIH HHS P30 MH062261NIMH NIH HHS R01 MH112848
6 · The paper itself

Abstract

Alzheimer's disease (AD) is an age- and gender-associated brain disorder. Long noncoding RNAs (lncRNAs) have emerged as key regulators of brain development, homeostasis, and pathologies. Here, we used gene array data sets and bioinformatics analysis to identify differentially expressed age- and gender-associated lncRNAs in human AD brains. We found that the expressions of 16 age-associated and 13 gender-associated lncRNAs were dysregulated in AD brains. Notably, the expressions of age-associated lncRNAs-SNHG19 and LINC00672-were significantly correlated with Braak stage of AD, positively and negatively, respectively, whereas the expressions of gender-associated lncRNAs-RNF144A-AS1, LY86-AS1, and LINC00639-were negatively correlated with Braak stage of AD. Functional analysis suggests that the pathways involved in neurodegenerative diseases, synaptic vesicle cycle, and endocytosis were overly represented within age- and gender-associated lncRNA-correlating genes. The identification of age- and gender-associated lncRNAs and their differential expressions in the human AD brain provide potential targets for further experimental validation and mechanistic investigation, which could, in turn, pave the way for developing age- and gender-specific prevention and adjunctive therapeutic options for patients with AD.

Indexed as

Sex CharacteristicsAdultAgedAged, 80 and overAgingAlzheimer DiseaseBrainFemaleGene ExpressionHumansMaleMiddle AgedRNA, Long NoncodingYoung AdultRNA, Long NoncodingAgingAlzheimer's diseaseBrainGender differencesLong noncoding RNA

Identifiers

PMID31280115
PMCPMC6732230
OpenAlexW2954494252

What OpenQuestion holds

Textmetadata
LicenceTDM
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.