Epigenome‐wide association study of sarcopenia: findings from the Hertfordshire Sarcopenia Study (HSS)

Introduction

Sarcopenia, defined as the loss of muscle mass, strength, and function with advancing age, is associated with a number of adverse physical and metabolic changes that contribute to morbidity, impaired quality of life, increased health care costs, and mortality. Although several operational definitions of sarcopenia are used worldwide,1, 2 there is general consensus that defining sarcopenia relies on low muscle function (either weak muscle strength or impaired physical performance, i.e. slower gait speed) in combination with low whole-body or appendicular lean mass.1, 3-5 Prevalence estimates have been reported to be between 1–29% amongst community-dwelling older adults, 14–33% for those in long-term care, and 10% for those in acute hospital.3, 6

A decline in muscle mass, strength, and function is a fundamental consequence of ageing; however, there is significant variability between individuals in the rate of loss in old age. Some of the variability can be explained by fixed genetic factors,7, 8 but much of the remaining variation is unexplained. There is growing evidence that suggests epigenetic processes play a prominent role in the development of many complex diseases.9 Processes such as DNA methylation induce heritable changes in gene expression without a change in nucleotide sequence.10 As inter-individual DNA methylation is specified by the interaction of both genotypic and environmental influences,11 changes in DNA methylation within skeletal muscle may provide novel insights into the variability in muscle ageing, as well as provide powerful biomarkers when compared with either genotype or lifestyle factors alone. To date, a number of human studies have compared DNA methylation in muscle tissue from young versus old individuals12-16 and reported differential methylation of genes involved in axon guidance,12, 13 cytoskeletal function,13, 16 cell adhesion,12, 13 muscle contraction,15 calcium signalling,15 and mTOR signalling.12 DNA methylation in muscle tissue in individuals with sarcopenia compared with healthy aged-matched controls has not previously been reported. A comparison of the muscle transcriptome in 119 older men with sarcopenia versus age-matched controls from Singapore, Hertfordshire UK, and Jamaica demonstrated that the major transcriptional signature of sarcopenia was mitochondrial bioenergetic dysfunction in skeletal muscle, with down-regulation of oxidative phosphorylation genes.17 However, whether these transcriptional changes are mediated through changes in DNA methylation is not known. Here, we sought to identify DNA methylation changes in muscle associated with sarcopenia, and its components, namely, grip strength, appendicular lean mass index (ALMi), and gait speed.

Methods Study design

All participants were recruited from the Hertfordshire Cohort Study (HCS),18 a retrospective cohort study based in the UK designed to investigate life course influences on muscle function in community-dwelling older people. DNA was analysed from 40 male participants from the first phase of the study, the Hertfordshire Sarcopenia Study (HSS),19, 20 and from the male participants of the second extension phase of the study (n = 43), herein termed HSSe.21 The 40 males from the HSS and the 43 males from the HSSe were the only samples with sufficient DNA for both genome-wide methylation analysis and pyrosequencing. All participants gave written informed consent, and the study was approved by the Hertfordshire Research Ethics Committee (07/Q0204/68). Sarcopenia was defined according to the European Working Group on Sarcopenia in Older People (EWGSOP)3 criteria, with the following thresholds: ALMi (ALM/height2) ≤ 7.23 kg/m2 for men and ≤5.67 kg/m2 for women; grip strength < 30 kg for men and <20 kg for women; and walking speed ≤ 0.8 m/s. Participants were classed as healthy controls (normal ALMi, gait speed, and grip strength) or as having sarcopenia (low ALMi and low gait speed and/or low grip strength).

Procedures

Body composition (appendicular lean mass) was assessed by dual-energy X-ray absorptiometry (DXA) (Hologic Discovery, software version 12.5). Isometric grip strength (kilograms) was measured three times in each hand using a Jamar handheld hydraulic dynamometer (Promedics, UK), and the highest value of six measures used.22 Customary walking speed was measured over a 3 m course. Percutaneous muscle biopsies of the vastus lateralis were conducted after an overnight fast under local anaesthetic using a Weil–Blakesley conchotome.23

Infinium Human MethylationEPIC BeadChip array

Genomic DNA was extracted from muscle from HSS participants using the QIAamp DNA mini kit (Qiagen) and from HSSe participants using the high salt method.24 A total of 750 ng of genomic DNA was treated with sodium bisulfite using Zymo EZ DNA Methylation-Gold kit (ZymoResearch, USA) and hybridized to the Infinium Human MethylationEPIC BeadChip array (Illumina, Inc., USA) at the Centre for Molecular Medicine and Therapeutics (http://www.cmmt.ubc.ca).

Infinium Human MethylationEPIC BeadChip array data processing

EPIC array data were processed using the Bioconductor package minfi25 in R (version 3.4.2). See details described in Supporting Information, Data S1. After pre-processing and QC, 77 samples for the muscle tissue analysis remained, and 10 for the myoblast analysis.

Infinium Human MethylationEPIC BeadChip array data analysis

Robust regression models were run using limma (v3.38.3).26 Models were adjusted for age, and surrogate variables, to account differences in cellular heterogeneity. The analysis was controlled for multiple testing with the Benjamini–Hochberg adjustment for false discovery rate (FDR), using an FDR < 0.05. See full details in Data S1.

Gene ontology, histone, and transcription factor enrichment analysis

Protein–protein interaction (PPI) networks were carried out using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and visualized in Cytoscape. Large networks were segmented using the MCODE algorithm,27 and gene ontology (GO) enrichment determined using BiNGO.28 Enrichment of differentially methylated CpGs (dmCpGs) amongst regions of histone modifications and transcription factor binding sites was assessed using the ChIP-seq peak data from ENCODE in male human skeletal muscle tissue (https://www.encodeproject.org).

Muscle epigenetic age estimator

Epigenetic age acceleration was calculated as the residuals of regressing the epigenetic age estimated by the muscle epigenetic age estimator (MEAT)14 over chronological age.

RNA sequencing and analysis

RNA was extracted from frozen muscle tissue using the mirVana™ miRNA Isolation Kit (Ambion, Life Technologies), and RNA sequencing carried out as described in Migliavacca et al.17

Pyrosequencing methylation analysis

Quantitative DNA methylation analysis was carried out by pyrosequencing, described in Data S1. Primer sequences are shown in Supporting Information, Table S1.

Isolation of myoblast cells from muscle biopsies

Details of myoblast isolation and culture are described in Data S1. Briefly, biopsies were minced (three with sarcopenia and three healthy aged-matched controls), digested in 0.5 mg/mL collagenase (Sigma), before pre-plating to remove fibroblasts, and sorting using CD56 MicroBeads (Miltenyi Biotech).29 Isolation of myogenic cells was confirmed by immunocytochemistry, which showed ≥96% of cells as CD56 positive after sorting. Cells were grown in either proliferation medium [Dulbecco's modified Eagle's medium (DMEM) containing 20% foetal bovine serum (FBS), 10% horse serum (HS), 1% chick embryo extract, and 1% penicillin/streptomycin (P/S)] or differentiation media (DMEM containing 2% HS and 1% P/S). Human primary myoblasts were treated with GSK343 (MedChemExpress), an inhibitor of EZH2,30 at 20 nM, 200 nM, and 2 μM after the initiation of differentiation over a 10 day period.

Immunocytochemistry

Cells were stained for myosin heavy chain (MYHC), PAX7, and 4′,6-diamidino-2-phenylindole (DAPI) (1 μg/mL). See details in Data S1. To calculate the fusion index, the number of nuclei within myotubes (containing 2+ nuclei) was counted and the ratio of this number to the total number of nuclei was determined.

Metabolic flux assay

Mitochondrial bioenergetics were measured using the Agilent Seahorse XF96 Mito Stress Test (details in Data S1). After measurement, cells were lysed and a protein assay was carried out for normalization. Each data point represents the mean ± standard deviation of six replicates for each condition.

Statistical analysis

All statistical analyses were carried out in R (version 3.4.2). Demographic characteristics were compared between controls and those with sarcopenia using the Mann–Whitney U tests. The hypergeometric distribution probability test was used to test the significance of the overlap between dmCpGs associated with different measures of muscle mass/function. Fisher's exact test was used to test the enrichment of dmCpGs amongst the different histone modifications, chromatin enhancer states, and genomic regions relative to CpG islands. Linear models were fitted to the pyrosequencing data including age as a covariate. Correlation analysis of the methylation and gene expression data was carried out using Spearman's correlation. Statistical analysis of the GSK343-treated cell cultures was carried out using the Wilcoxon signed-rank test for the immunocytochemistry and paired t-test for the metabolic flux assays, with data from sarcopenia and control myoblasts analysed as one group to maximize statistical power.

Results Participant characteristics

Of the 83 men who had muscle tissue available, 77 samples passed downstream quality control and were included in further analysis. Participant characteristics are given in Table 1. Men who had sarcopenia (n = 11) were older (P = 0.019) and had a lower body mass index (P < 0.001) compared with those who did not have sarcopenia. As expected, men with sarcopenia also had lower measures of muscle mass [total lean mass, appendicular lean mass (ALM), and ALMi; all P < 0.001] and reduced muscle function [gait speed (P < 0.001)] and grip strength (P = 0.001) compared with those who did not have sarcopenia.

Table 1. Participant characteristics Control (n = 41) Sarcopenia (n = 11) Total (n = 77a) Age (years) 74.49 ± 3.25 77.12 ± 3.74 75.66 ± 3.55 *P = 1.90 × 10−2 Height (cm) 172.32 ± 5.77 171.68 ± 9.81 172.22 ± 6.12 P = 9.22 × 10−1 Weight (kg) 83.45 ± 12.81 76.06 ± 12.14 79.10 ± 12.32 ***P = 1.00 × 10−3 BMI (kg/m 2) 28.04 ± 3.66 25.74 ± 2.86 26.10 ± 3.47 ****P = 1.28 × 10−4 Total lean mass (kg) 55.33 ± 6.94 47.82 ± 5.45 51.58 ± 7.29 ****P = 2.96 × 10−7 ALM (kg) 24.42 ± 2.98 20.03 ± 2.68 22.35 ± 3.46 ****P = 4.06 × 10−10 Fat mass (kg) 24.15 ± 8.02 24.61 ± 9.05 23.77 ± 7.81 P = 5.64 × 10−1 Grip strength (kg) 38.05 ± 6.86 29.00 ± 8.72 36.19 ± 7.15 ***P = 1.00 × 10−3 Gait speed (m/s) 1.08 ± 018 0.82 ± 0.26 1.05 ± 021 ****P = 3.61 × 10−4 ALMi (kg/m2) 8.21 ± 0.76 6.77 ± 0.36 7.53 ± 0.98 ****P = 5.92 × 10−15 ALM, appendicular lean mass; ALMi, appendicular lean mass index; BMI, body mass index. a Twenty participants were not classed as healthy controls or as having sarcopenia using the European Working Group on Sarcopenia in Older People definition; however, they were included in the continuous analyses of ALMi, grip strength, and gait speed. * P-value ≤ 0.05. ** P-value ≤ 0.01. *** P-value ≤ 0.001. **** P-value ≤ 0.0001. Identification of differentially methylated CpGs in muscle biopsies associated with sarcopenia

There were significant (FDR, P < 0.05) associations between DNA methylation and sarcopenia, with 176 CpGs significantly associated with sarcopenia (Tables 2 and S2). The top two dmCpGs were located in an intergenic region on chromosome 1 (cg17974166, FDR = 2.67 × 10−10, and cg01647314, FDR = 1.06 × 10−7) (Figure 1A + 1B); 53.4% of the dmCpGs showed hypermethylation in those with sarcopenia (Figure 1C), with a significant over-representation of dmCpGs in the OpenSea (P = 0.0188) and CpG island (P = 1.28 × 10−5) regions (Figure 1D).

Table 2. Top 25 sarcopenia-associated differentially methylated CpGs Probe logFC Average methylation FDR Gene cg17974166 0.1244 0.1246 2.67 × 10−10 cg01647314 0.0831 0.1640 1.06 × 10−7 cg10941472 0.0823 0.1102 1.49 × 10−6 cg20843809 −0.1151 0.8705 4.22 × 10−6 cg07236061 −0.1987 0.8646 2.28 × 10−4 LINC01331 cg22843429 −0.0497 0.8661 2.28 × 10−4 EMG1 cg03622584 0.0528 0.6245 3.03 × 10−4 LOC101927934 cg00384701 0.0430 0.3116 3.28 × 10−4 cg10977501 −0.0346 0.9088 3.81 × 10−4 MYOM2 cg27191906 0.0676 0.6362 4.51 × 10−4 OR2J2 cg00172812 0.1024 0.2311 4.51 × 10−4 cg00102685 −0.0368 0.9359 5.33 × 10−4 cg08344114 −0.0378 0.5612 7.77 × 10−4 cg27473406 −0.0416 0.3952 7.77 × 10−4 cg26945376 0.0331 0.1893 7.77 × 10−4 CLIP1 cg10956589 0.0330 0.4653 8.66 × 10−4 cg03532253 −0.0296 0.8865 9.09 × 10−4 SUOX cg25441771 0.0316 0.0468 2.20 × 10−3 MCCC1 cg16307778 −0.0501 0.8696 2.75 × 10−3 cg15744876 −0.0428 0.5705 3.17 × 10−3 cg04344695 0.0434 0.4816 3.66 × 10−3 CA12 cg27253454 −0.0323 0.7946 3.66 × 10−3 USP43 cg14659184 −0.0499 0.8841 4.01 × 10−3 LINC00925 cg20266770 0.0451 0.2541 4.45 × 10−3 cg25963061 0.0336 0.7137 4.59 × 10−3 UBQLNL FC, fold change; FDR, false discovery rate. image

(A) Volcano plot of the differential methylation analysis with respect to sarcopenia, with the significant probes (FDR < 0.05) highlighted in red and probes with an FDR < 0.25 highlighted in green. The top 10 dmCpGs have been annotated. (B) Manhattan plot for the differential methylation analysis with respect to sarcopenia. All significant sarcopenia-associated dmCpGs are shown as bold red points, with the top 10 dmCpGs annotated. Black line: Bonferroni threshold (P-value = 1.33 × 10−7); red line: FDR threshold (P-value = 2.34 × 10−5). (C) Pie chart showing the proportions of dmCpGs showing increased or decreased methylation associated with sarcopenia. (D) Pie chart showing the proportions of the locations of the sarcopenia-associated dmCpGs. (E) Venn diagram indicating the overlap in the number of CpGs (FDR < 0.2) associated with sarcopenia and the multiple measures of muscle mass.

To understand the contribution of muscle mass, strength, and function to the methylation signature associated with sarcopenia, we analysed DNA methylation with respect to ALMi, grip strength, and gait speed as continuous variables. ALMi was associated with 71 dmCpGs; grip strength with 49 dmCpGs; and gait speed with 23 dmCpGs (Tables S3–S5). The top dmCpG associated with ALMi was cg22350027, located in the body of the phospholipase C-like protein 2 (PLCL2) gene (FDR = 9.68 × 10−6), while the top dmCpGs associated with grip strength and gait speed were located in the intergenic region of chromosome 17 (FDR = 0.0003) and chromosome 1 (FDR = 0.0017), respectively. There was significant overlap between the dmCpGs associated with sarcopenia and ALMi (P = 3.40 × 10−35), sarcopenia and gait speed (P = 4.78 × 10−3), and sarcopenia and grip strength (P = 7.55 × 10−6) (Table S6, Figure 1E). However, there was no overlap between the dmCpGs associated with ALMi, grip strength, or gait speed.

Sarcopenia is not associated with accelerated epigenetic age

To determine whether the methylation changes associated with sarcopenia represented accelerated muscle ageing, epigenetic age acceleration was calculated.14 Epigenetic age as determined by MEAT was strongly correlated with chronological age (Supporting Information, Figure S2; Pearson's r = 0.421, P = 0.0001). However, there were no significant associations of accelerated epigenetic ageing with sarcopenia status, ALMi, gait speed, or grip strength (Table S7).

Sarcopenia and the individual measures of muscle mass, strength, and function are associated with multiple differentially methylated regions

Regional analysis identified differentially methylated regions (DMRs) associated with sarcopenia, ALMI, grip strength, and gait speed (Tables S8–S11). Sarcopenia was associated with 141 DMRs (Stouffer < 0.05), with the top DMR located within the promoter region of the Methylcrotonyl-CoA Carboxylase 1 (MCCC1) gene, consisting of 13 CpGs (Stouffer = 3.62 × 10−12). ALMi was associated with 135 DMRs, with the top DMR located within the zinc finger protein 57 (ZFP57) gene. Grip strength was associated with 28 DMRs, with the top DMR located within the claudin 10 (CLDN10) gene (Stouffer = 8.29 × 10−4). Gait speed was associated with 24 DMRs, with the top DMR located in an intergenic region on chromosome 1 (Stouffer = 7.53 × 10−4). There were three DMRs associated with both sarcopenia and ALMi, but no DMRs that overlapped between sarcopenia and grip strength, or sarcopenia and gait speed.

Correlation between DNA methylation and gene expression in skeletal muscle tissue

Of the 77 samples analysed by EPIC DNA methylation arrays, 34 muscle samples had previously been analysed using total RNAseq.17 Therefore, to explore the correlation between DNA methylation and gene expression, we examined the sarcopenia-associated dmCpGs with an FDR < 0.2 annotated to a gene (n = 470), with the RNAseq data, removing transcripts with low expression across all samples. This resulted in 298 transcript–CpG pairs. Correlation analysis of the transcript–CpG pairs revealed 29 with a significant correlation between methylation and expression at an FDR < 0.2 (Table 3). There were multiple dmCpGs within MCCC1, which were associated with transcript levels: three CpGs in the body of the MCCC1 gene (cg08395365, cg22211233, and cg00161968) and one within 200 bp of the MCCC1 TSS (cg00890010) were negatively associated with MCCC1 expression, while cg23476885, located in the body of the MCCC1 gene, was positively associated with MCCC1 expression.

Table 3. Correlation between DNA methylation and RNA expression (false discovery rate < 0.2) Probe Spearman's ρ P-value FDR Gene CpG position dmCpGs cg20108671 −0.6327 8.57E-05 0.0260 SCAPER 5′UTR cg03854273 −0.5939 2.80E-04 0.0339 LPCAT3 Body cg13403462 −0.5875 3.36E-04 0.0339 NECAB3 TSS200 cg24859375 −0.5438 1.06E-03 0.0786 LPCAT3 1st exon cg04180086 0.5355 1.30E-03 0.0786 IRX4 Body cg01554606 −0.5150 2.09E-03 0.0981 MYLK Body cg08395365 −0.5001 2.92E-03 0.0981 MCCC1 Body cg07655627 −0.4967 3.14E-03 0.0981 NUDT12 Body cg09166085 −0.4937 3.36E-03 0.0981 NUDT12 3′UTR cg02976617 −0.4934 3.38E-03 0.0981 NUDT12 Body cg22211233 −0.4909 3.56E-03 0.0981 MCCC1 Body cg23423191 −0.4860 3.95E-03 0.0997 STK10 5′UTR cg00617927 0.4756 4.90E-03 0.1073 COL27A1 TSS1500 cg03073264 −0.4750 4.96E-03 0.1073 NUDT12 Body cg08767025 0.4652 6.03E-03 0.1219 SOX5 TSS200 cg22350027 0.4597 6.72E-03 0.1273 PLCL2 Body cg16938504 −0.4564 7.18E-03 0.1279

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