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Meta-Analysis
. 2023 Mar;33(3):301-311.
doi: 10.1089/thy.2022.0373. Epub 2023 Mar 1.

Epigenome-Wide Association Study Reveals CpG Sites Associated with Thyroid Function and Regulatory Effects on KLF9

Antoine Weihs  1 , Layal Chaker  2   3 , Tiphaine C Martin  4   5 , Kim V E Braun  6 , Purdey J Campbell  7 , Simon R Cox  8 , Myriam Fornage  9   10 , Christian Gieger  11   12   13 , Hans J Grabe  1   14 , Harald Grallert  11   12 , Sarah E Harris  8 , Brigitte Kühnel  11   12 , Riccardo E Marioni  15 , Nicholas G Martin  16 , Daniel L McCartney  15 , Allan F McRae  17 , Christa Meisinger  18 , Joyce B J van Meurs  19   20 , Jana Nano  12   21 , Matthias Nauck  22   23 , Annette Peters  11   12   13   21 , Holger Prokisch  24   25 , Michael Roden  26   27   28 , Elizabeth Selvin  29   30 , Marian Beekman  31 , Diana van Heemst  32 , Eline P Slagboom  31 , Brenton R Swenson  33 , Adrienne Tin  29   34 , Pei-Chien Tsai  5   35   36 , Andre Uitterlinden  19 , W Edward Visser  2 , Henry Völzke  23   37 , Melanie Waldenberger  11   12   13 , John P Walsh  7   38 , Anna Köttgen  29   39 , Scott G Wilson  5   7   40 , Robin P Peeters  2 , Jordana T Bell  5 , Marco Medici  2 , Alexander Teumer  1   23   37   41
Affiliations
Meta-Analysis

Epigenome-Wide Association Study Reveals CpG Sites Associated with Thyroid Function and Regulatory Effects on KLF9

Antoine Weihs et al. Thyroid. 2023 Mar.

Abstract

Background: Thyroid hormones play a key role in differentiation and metabolism and are known regulators of gene expression through both genomic and epigenetic processes including DNA methylation. The aim of this study was to examine associations between thyroid hormones and DNA methylation. Methods: We carried out a fixed-effect meta-analysis of epigenome-wide association study (EWAS) of blood DNA methylation sites from 8 cohorts from the ThyroidOmics Consortium, incorporating up to 7073 participants of both European and African ancestry, implementing a discovery and replication stage. Statistical analyses were conducted using normalized beta CpG values as dependent and log-transformed thyrotropin (TSH), free thyroxine, and free triiodothyronine levels, respectively, as independent variable in a linear model. The replicated findings were correlated with gene expression levels in whole blood and tested for causal influence of TSH and free thyroxine by two-sample Mendelian randomization (MR). Results: Epigenome-wide significant associations (p-value <1.1E-7) of three CpGs for free thyroxine, five for free triiodothyronine, and two for TSH concentrations were discovered and replicated (combined p-values = 1.5E-9 to 4.3E-28). The associations included CpG sites annotated to KLF9 (cg00049440) and DOT1L (cg04173586) that overlap with all three traits, consistent with hypothalamic-pituitary-thyroid axis physiology. Significant associations were also found for CpGs in FKBP5 for free thyroxine, and at CSNK1D/LINCO1970 and LRRC8D for free triiodothyronine. MR analyses supported a causal effect of thyroid status on DNA methylation of KLF9. DNA methylation of cg00049440 in KLF9 was inversely correlated with KLF9 gene expression in blood. The CpG at CSNK1D/LINC01970 overlapped with thyroid hormone receptor alpha binding peaks in liver cells. The total additive heritability of the methylation levels of the six significant CpG sites was between 25% and 57%. Significant methylation QTLs were identified for CpGs at KLF9, FKBP5, LRRC8D, and CSNK1D/LINC01970. Conclusions: We report novel associations between TSH, thyroid hormones, and blood-based DNA methylation. This study advances our understanding of thyroid hormone action particularly related to KLF9 and serves as a proof-of-concept that integrations of EWAS with other -omics data can provide a valuable tool for unraveling thyroid hormone signaling in humans by complementing and feeding classical in vitro and animal studies.

Keywords: DNA methylation; KLF9; Mendelian randomization; gene expression; thyroid function.

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Conflict of interest statement

H.J.G. has received travel grants and speakers honoraria from Fresenius Medical Care, Neuraxpharm, Servier, and Janssen Cilag as well as research funding from Fresenius Medical Care not related to this work. R.E.M. has received speaker fees from Illumina and is an advisor to the Epigenetic Clock Development Foundation. All other authors declare no conflicts of interest.

Figures

FIG. 1.
FIG. 1.
Flowchart of the analyses performed in the current study. Image created with BioRender.com
FIG. 2.
FIG. 2.
Chicago plot showing the results of the TSH discovery analysis. Red labels show the significant sites (p-value <1.1E-07) of the discovery analysis, while green labels show results of the combined analysis. The black line shows the epigenome-wide significance cutoff (1.1E-07). Points plotted in the upper panel show a positive correlation with TSH, while those plotted below have a negative association. TSH, thyrotropin.
FIG. 3.
FIG. 3.
Chicago plot showing the results of the fT4 discovery analysis. Red labels show the significant sites (p-value <1.1E-07) of the discovery analysis, while green labels show results of the combined analysis. The black line shows the epigenome-wide significance cutoff (1.1E-07). Points plotted in the upper panel show a positive correlation with fT4, while those plotted below have a negative association. fT4, free thyroxine.
FIG. 4.
FIG. 4.
Chicago plot showing the results of the fT3 discovery analysis. Red labels show the significant sites (p-value <1.1E-07) of the discovery analysis, while green labels show results of the combined analysis. The black line shows the epigenome-wide significance cutoff (1.1E-07). Points plotted in the upper panel show a positive correlation with fT3, while those plotted below have a negative association. fT3, free triiodothyronine.
FIG. 5.
FIG. 5.
Overview of the study analyses and findings. Known mechanisms and associations are colored in black, and new findings revealed by this study are marked in blue color. Image created with BioRender.com
See this image and copyright information in PMC

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