Cannabis significantly alters DNA methylation of the human ovarian follicle in a concentration-dependent manner

Abstract

Cannabis is increasingly consumed by women of childbearing age, and the reproductive and epigenetic effects are unknown. The purpose of this study was to evaluate the potential epigenetic implications of cannabis use on the female ovarian follicle. Whole-genome methylation was assessed in granulosa cells from 14 matched case-control patients. Exposure status was determined by liquid chromatography-mass spectrometry (LC-MS/MS) measurements of five cannabis-derived phytocannabinoids in follicular fluid. DNA methylation was measured using the Illumina TruSeq Methyl Capture EPIC kit. Differential methylation, pathway analysis and correlation analysis were performed. We identified 3679 differentially methylated sites, with two-thirds affecting coding genes. A hotspot region on chromosome 9 was associated with two genomic features, a zinc-finger protein (ZFP37) and a long non-coding RNA (FAM225B). There were 2214 differentially methylated genomic features, 19 of which have been previously implicated in cannabis-related epigenetic modifications in other organ systems. Pathway analysis revealed enrichment in G protein-coupled receptor signaling, cellular transport, immune response and proliferation. Applying strict criteria, we identified 71 differentially methylated regions, none of which were previously annotated in this context. Finally, correlation analysis revealed 16 unique genomic features affected by cannabis use in a concentration-dependent manner. Of these, the histone methyltransferases SMYD3 and ZFP37 were hypomethylated, possibly implicating histone modifications as well. Herein, we provide the first DNA methylation profile of human granulosa cells exposed to cannabis. With cannabis increasingly legalized worldwide, further investigation into the heritability and functional consequences of these effects is critical for clinical consultation and for legalization guidelines.

Keywords: DNA methylation; cannabis; epigenetics; granulosa cells; marijuana; Δ9-THC.

Figure 1.

Localization and genomic feature annotation associated with differentially methylated sites (DMS) in case versus control groups. (A) Of the 3679 DMS, 497 were associated with CpG islands (CpGi) (13.5%), 339 were associated with CpG shores (CpGs) (9.2%) and 2843 were not associated with either CpGi or CpGs and deemed CpGother (CpGo) (77.3%). (B) Of the 2214 unique genomic features that the DMS mapped to, 251 were associated with CpGi (10.6%), 210 were associated with CpGs (8.9%) and 1900 were not associated with either and deemed CpGo (80.5%). (C) Stratification of unique genomic feature biotypes of DMS within ±5 kb of the transcription start site. (D) Proportions of DMS in hypo-, hyper-methylated and all DMS associated with specific genic annotation using the ‘annotatr’ package.

Figure 2.

Manhattan plots of the genome-wide differentially methylated sites (DMS) found in the case versus control group. All sites on these plots are significant. Significance is defined as percent methylation difference >25% and an adjusted P-value (q-value) <0.01. The y-axis represents the −log₁₀(adjusted P). (A) Manhattan plot of all autosomes and the X chromosome. (B) Manhattan plot of only chromosome 9, depicting the ‘hotspot’ region on the distal q arm. (C) Manhattan plot of only the chromosome 9 ‘hotspot’ region ranging from chr9:113059999-113089725.

Figure 3.

Gene set enrichment analysis of differentially methylated sites (DMS). Gene set enrichment analysis (GSEA) was conducted using g:Profiler-g:GOSt and interrogating KEGG, Reactome and Wikipathways databases. Genesets were considered significant if they had an adjusted P-value (q-value) <0.05 and five or more genes in the gene set. g:SCS multiple testing correction method was used to determine significance. (A) GSEA of all hypomethylated DMS. (B) GSEA of all hypermethylated DMS. A full list of gene sets can be found in Supplementary Tables SII and SIII, respectively.

Figure 4.

Correlation analysis of differentially methylated regions (DMR) and cannabis usage. Correlations between follicular fluid Δ9-THC concentration in the cannabis group and granulosa cell DNA methylation levels for DMS identified as differentially methylated, analyzed by Pearson correlation. To control for multiple comparisons, P values from 0.04 to 0.055 were considered a trend, and values below P = 0.04 were considered significant. All DMS displaying a concentration-dependent effect can be found in Table IV.

Figure 5.

Volcano plot of targeted RNASeq of cases versus controls. Target RNAseq was conducted on 24 samples (14 cases and 10 controls) using a custom designed ampliseq target panel. Differential expression was conducted using DESeq2. Genes were considered differentially expressed with a fold change (FC) 2 < FC < −2.