Cargando…

Complex trait methylation scores in the prediction of major depressive disorder

BACKGROUND: DNA methylation (DNAm) is associated with time-varying environmental factors that contribute to major depressive disorder (MDD) risk. We sought to test whether DNAm signatures of lifestyle and biochemical factors were associated with MDD to reveal dynamic biomarkers of MDD risk that may...

Descripción completa

Detalles Bibliográficos
Autores principales: Barbu, Miruna C., Amador, Carmen, Kwong, Alex S.F., Shen, Xueyi, Adams, Mark J., Howard, David M., Walker, Rosie M., Morris, Stewart W., Min, Josine L., Liu, Chunyu, van Dongen, Jenny, Ghanbari, Mohsen, Relton, Caroline, Porteous, David J., Campbell, Archie, Evans, Kathryn L., Whalley, Heather C., McIntosh, Andrew M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9062752/
https://www.ncbi.nlm.nih.gov/pubmed/35490552
http://dx.doi.org/10.1016/j.ebiom.2022.104000
_version_ 1784699018503258112
author Barbu, Miruna C.
Amador, Carmen
Kwong, Alex S.F.
Shen, Xueyi
Adams, Mark J.
Howard, David M.
Walker, Rosie M.
Morris, Stewart W.
Min, Josine L.
Liu, Chunyu
van Dongen, Jenny
Ghanbari, Mohsen
Relton, Caroline
Porteous, David J.
Campbell, Archie
Evans, Kathryn L.
Whalley, Heather C.
McIntosh, Andrew M.
author_facet Barbu, Miruna C.
Amador, Carmen
Kwong, Alex S.F.
Shen, Xueyi
Adams, Mark J.
Howard, David M.
Walker, Rosie M.
Morris, Stewart W.
Min, Josine L.
Liu, Chunyu
van Dongen, Jenny
Ghanbari, Mohsen
Relton, Caroline
Porteous, David J.
Campbell, Archie
Evans, Kathryn L.
Whalley, Heather C.
McIntosh, Andrew M.
author_sort Barbu, Miruna C.
collection PubMed
description BACKGROUND: DNA methylation (DNAm) is associated with time-varying environmental factors that contribute to major depressive disorder (MDD) risk. We sought to test whether DNAm signatures of lifestyle and biochemical factors were associated with MDD to reveal dynamic biomarkers of MDD risk that may be amenable to lifestyle interventions. METHODS: Here, we calculated methylation scores (MS) at multiple p-value thresholds for lifestyle (BMI, smoking, alcohol consumption, and educational attainment) and biochemical (high-density lipoprotein (HDL) and total cholesterol) factors in Generation Scotland (GS) (N=9,502) and in a replication cohort (ALSPAC(adults), N=565), using CpG sites reported in previous well-powered methylome-wide association studies. We also compared their predictive accuracy for MDD to a MDD MS in an independent GS sub-sample (N=4,432). FINDINGS: Each trait MS was significantly associated with its corresponding phenotype in GS (β(range)=0.089–1.457) and in ALSPAC (β(range)=0.078–2.533). Each MS was also significantly associated with MDD before and after adjustment for its corresponding phenotype in GS (β(range)=0.053–0.145). After accounting for relevant lifestyle factors, MS for educational attainment (β=0.094) and alcohol consumption (MS(p-value)<0.01–0.5; β(range)=-0.069–0.083) remained significantly associated with MDD in GS. Smoking (AUC=0.569) and educational attainment (AUC=0.585) MSs could discriminate MDD from controls better than the MDD MS (AUC=0.553) in the independent GS sub-sample. Analyses implicating MDD did not replicate across ALSPAC, although the direction of effect was consistent for all traits when adjusting for the MS corresponding phenotypes. INTERPRETATION: We showed that lifestyle and biochemical MS were associated with MDD before and after adjustment for their corresponding phenotypes (p(nominal)<0.05), but not when smoking, alcohol consumption, and BMI were also included as covariates. MDD results did not replicate in the smaller, female-only independent ALSPAC cohort (N(ALSPAC)=565; N(GS)=9,502), potentially due to demographic differences or low statistical power, but effect sizes were consistent with the direction reported in GS. DNAm scores for modifiable MDD risk factors may contribute to disease vulnerability and, in some cases, explain additional variance to their observed phenotypes. FUNDING: Wellcome Trust.
format Online
Article
Text
id pubmed-9062752
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-90627522022-05-04 Complex trait methylation scores in the prediction of major depressive disorder Barbu, Miruna C. Amador, Carmen Kwong, Alex S.F. Shen, Xueyi Adams, Mark J. Howard, David M. Walker, Rosie M. Morris, Stewart W. Min, Josine L. Liu, Chunyu van Dongen, Jenny Ghanbari, Mohsen Relton, Caroline Porteous, David J. Campbell, Archie Evans, Kathryn L. Whalley, Heather C. McIntosh, Andrew M. EBioMedicine Articles BACKGROUND: DNA methylation (DNAm) is associated with time-varying environmental factors that contribute to major depressive disorder (MDD) risk. We sought to test whether DNAm signatures of lifestyle and biochemical factors were associated with MDD to reveal dynamic biomarkers of MDD risk that may be amenable to lifestyle interventions. METHODS: Here, we calculated methylation scores (MS) at multiple p-value thresholds for lifestyle (BMI, smoking, alcohol consumption, and educational attainment) and biochemical (high-density lipoprotein (HDL) and total cholesterol) factors in Generation Scotland (GS) (N=9,502) and in a replication cohort (ALSPAC(adults), N=565), using CpG sites reported in previous well-powered methylome-wide association studies. We also compared their predictive accuracy for MDD to a MDD MS in an independent GS sub-sample (N=4,432). FINDINGS: Each trait MS was significantly associated with its corresponding phenotype in GS (β(range)=0.089–1.457) and in ALSPAC (β(range)=0.078–2.533). Each MS was also significantly associated with MDD before and after adjustment for its corresponding phenotype in GS (β(range)=0.053–0.145). After accounting for relevant lifestyle factors, MS for educational attainment (β=0.094) and alcohol consumption (MS(p-value)<0.01–0.5; β(range)=-0.069–0.083) remained significantly associated with MDD in GS. Smoking (AUC=0.569) and educational attainment (AUC=0.585) MSs could discriminate MDD from controls better than the MDD MS (AUC=0.553) in the independent GS sub-sample. Analyses implicating MDD did not replicate across ALSPAC, although the direction of effect was consistent for all traits when adjusting for the MS corresponding phenotypes. INTERPRETATION: We showed that lifestyle and biochemical MS were associated with MDD before and after adjustment for their corresponding phenotypes (p(nominal)<0.05), but not when smoking, alcohol consumption, and BMI were also included as covariates. MDD results did not replicate in the smaller, female-only independent ALSPAC cohort (N(ALSPAC)=565; N(GS)=9,502), potentially due to demographic differences or low statistical power, but effect sizes were consistent with the direction reported in GS. DNAm scores for modifiable MDD risk factors may contribute to disease vulnerability and, in some cases, explain additional variance to their observed phenotypes. FUNDING: Wellcome Trust. Elsevier 2022-04-29 /pmc/articles/PMC9062752/ /pubmed/35490552 http://dx.doi.org/10.1016/j.ebiom.2022.104000 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Articles
Barbu, Miruna C.
Amador, Carmen
Kwong, Alex S.F.
Shen, Xueyi
Adams, Mark J.
Howard, David M.
Walker, Rosie M.
Morris, Stewart W.
Min, Josine L.
Liu, Chunyu
van Dongen, Jenny
Ghanbari, Mohsen
Relton, Caroline
Porteous, David J.
Campbell, Archie
Evans, Kathryn L.
Whalley, Heather C.
McIntosh, Andrew M.
Complex trait methylation scores in the prediction of major depressive disorder
title Complex trait methylation scores in the prediction of major depressive disorder
title_full Complex trait methylation scores in the prediction of major depressive disorder
title_fullStr Complex trait methylation scores in the prediction of major depressive disorder
title_full_unstemmed Complex trait methylation scores in the prediction of major depressive disorder
title_short Complex trait methylation scores in the prediction of major depressive disorder
title_sort complex trait methylation scores in the prediction of major depressive disorder
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9062752/
https://www.ncbi.nlm.nih.gov/pubmed/35490552
http://dx.doi.org/10.1016/j.ebiom.2022.104000
work_keys_str_mv AT barbumirunac complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT amadorcarmen complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT kwongalexsf complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT shenxueyi complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT adamsmarkj complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT howarddavidm complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT walkerrosiem complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT morrisstewartw complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT minjosinel complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT liuchunyu complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT vandongenjenny complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT ghanbarimohsen complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT reltoncaroline complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT porteousdavidj complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT campbellarchie complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT evanskathrynl complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT whalleyheatherc complextraitmethylationscoresinthepredictionofmajordepressivedisorder
AT mcintoshandrewm complextraitmethylationscoresinthepredictionofmajordepressivedisorder