Differential long noncoding RNA profiling of BMI in twins

Weilong Li; Jan Baumbach; Martin J. Larsen; Afsaneh Mohammadnejad; Jesper Lund; Kaare Christensen; Lene Christiansen; Qihua Tan

doi:10.2217/epi-2020-0033

Differential long noncoding RNA profiling of BMI in twins

Weilong Li, Jan Baumbach, Martin J. Larsen, Afsaneh Mohammadnejad, Jesper Lund, Kaare Christensen, Lene Christiansen, Qihua Tan

Chair of Experimental Bioinformatics

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

Aim: Many efforts have been deployed to identify genetic variants associated with BMI. Alternatively, we explore epigenetic contribution to BMI variation by focusing on long noncoding RNAs (lncRNAs) which represents a key layer of epigenetic control. Materials & methods: We analyzed lncRNA expression in whole blood of 229 monozygotic twin pairs in association with BMI using generalized estimating equations. Results & conclusion: Six lncRNA probes were identified as significant (false discovery rate <0.05), with BMI showing causal effects on the expression of the significant lncRNAs. Functional annotation of differential profiles identified Gene ontology biological processes including kidney development, regulations of lipid biosynthetic process, circadian rhythm, notch signaling, etc. Whole blood lncRNAs are significantly expressed in response to BMI variation.

Original language	English
Pages (from-to)	1531-1541
Number of pages	11
Journal	Epigenomics
Volume	12
Issue number	17
DOIs	https://doi.org/10.2217/epi-2020-0033
State	Published - Sep 2020

Keywords

BMI
causal inference
lncRNA
twin study

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.2217/epi-2020-0033

Cite this

@article{c2aee0553a6e4bfbaebf6666109cf4d9,

title = "Differential long noncoding RNA profiling of BMI in twins",

abstract = "Aim: Many efforts have been deployed to identify genetic variants associated with BMI. Alternatively, we explore epigenetic contribution to BMI variation by focusing on long noncoding RNAs (lncRNAs) which represents a key layer of epigenetic control. Materials & methods: We analyzed lncRNA expression in whole blood of 229 monozygotic twin pairs in association with BMI using generalized estimating equations. Results & conclusion: Six lncRNA probes were identified as significant (false discovery rate <0.05), with BMI showing causal effects on the expression of the significant lncRNAs. Functional annotation of differential profiles identified Gene ontology biological processes including kidney development, regulations of lipid biosynthetic process, circadian rhythm, notch signaling, etc. Whole blood lncRNAs are significantly expressed in response to BMI variation.",

keywords = "BMI, causal inference, lncRNA, twin study",

author = "Weilong Li and Jan Baumbach and Larsen, {Martin J.} and Afsaneh Mohammadnejad and Jesper Lund and Kaare Christensen and Lene Christiansen and Qihua Tan",

note = "Publisher Copyright: {\textcopyright} 2020 Qihua Tan.",

year = "2020",

month = sep,

doi = "10.2217/epi-2020-0033",

language = "English",

volume = "12",

pages = "1531--1541",

journal = "Epigenomics",

issn = "1750-1911",

publisher = "Taylor and Francis Ltd.",

number = "17",

}

TY - JOUR

T1 - Differential long noncoding RNA profiling of BMI in twins

AU - Li, Weilong

AU - Baumbach, Jan

AU - Larsen, Martin J.

AU - Mohammadnejad, Afsaneh

AU - Lund, Jesper

AU - Christensen, Kaare

AU - Christiansen, Lene

AU - Tan, Qihua

PY - 2020/9

Y1 - 2020/9

N2 - Aim: Many efforts have been deployed to identify genetic variants associated with BMI. Alternatively, we explore epigenetic contribution to BMI variation by focusing on long noncoding RNAs (lncRNAs) which represents a key layer of epigenetic control. Materials & methods: We analyzed lncRNA expression in whole blood of 229 monozygotic twin pairs in association with BMI using generalized estimating equations. Results & conclusion: Six lncRNA probes were identified as significant (false discovery rate <0.05), with BMI showing causal effects on the expression of the significant lncRNAs. Functional annotation of differential profiles identified Gene ontology biological processes including kidney development, regulations of lipid biosynthetic process, circadian rhythm, notch signaling, etc. Whole blood lncRNAs are significantly expressed in response to BMI variation.

AB - Aim: Many efforts have been deployed to identify genetic variants associated with BMI. Alternatively, we explore epigenetic contribution to BMI variation by focusing on long noncoding RNAs (lncRNAs) which represents a key layer of epigenetic control. Materials & methods: We analyzed lncRNA expression in whole blood of 229 monozygotic twin pairs in association with BMI using generalized estimating equations. Results & conclusion: Six lncRNA probes were identified as significant (false discovery rate <0.05), with BMI showing causal effects on the expression of the significant lncRNAs. Functional annotation of differential profiles identified Gene ontology biological processes including kidney development, regulations of lipid biosynthetic process, circadian rhythm, notch signaling, etc. Whole blood lncRNAs are significantly expressed in response to BMI variation.

KW - BMI

KW - causal inference

KW - lncRNA

KW - twin study

UR - http://www.scopus.com/inward/record.url?scp=85092120536&partnerID=8YFLogxK

U2 - 10.2217/epi-2020-0033

DO - 10.2217/epi-2020-0033

M3 - Article

C2 - 32901529

AN - SCOPUS:85092120536

SN - 1750-1911

VL - 12

SP - 1531

EP - 1541

JO - Epigenomics

JF - Epigenomics

IS - 17

ER -

Differential long noncoding RNA profiling of BMI in twins

Abstract

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this