Epigenetic insights into neuropsychiatric and cognitive symptoms in Parkinson’s disease: A DNA co-methylation network analysis

Parkinson’s disease is a highly heterogeneous disorder, encompassing a complex spectrum of clinical presentation including motor, sleep, cognitive and neuropsychiatric symptoms. We aimed to investigate genome-wide DNA methylation networks in post-mortem Parkinson’s disease brain samples and test for region-specific association with common neuropsychiatric and cognitive symptoms. Of traits tested, we identify a co-methylation module in the substantia nigra with significant correlation to depressive symptoms and with ontological enrichment for terms relevant to neuronal and synaptic processes. Notably, expression of the genes annotated to the methylation loci present within this module are found to be significantly enriched in neuronal subtypes within the substantia nigra. These findings highlight the potential involvement of neuronal-specific changes within the substantia nigra with regard to depressive symptoms in Parkinson’s disease.


Introduction
Parkinson's disease (PD) is the second most common neurodegenerative disease and is the fastest growing in prevalence of all neurological disorders, estimated to affect 6.1 million individuals worldwide based on a 2016 census 1 .Clinically, PD is defined by its cardinal motor symptoms (resting tremor, bradykinesia, rigidity and postural instability) 2 , but highly prevalent features of the disease encompass a range of cognitive and neuropsychiatric symptoms 3 .Common symptoms, reported in a high proportion of patients, include depression 4 , anxiety 5 , psychosis (most prominently hallucinations and delusions) 6 , apathy 7 , cognitive impairment and dementia 8 .The cumulative effect of these secondary symptoms greatly increases disease burden for patients and complicates treatment 9,10 .As examples, psychosis is an associated factor to increased nursing home placement 11 , mortality and caregiver burden in PD 12 .Dopaminergic therapies, highly prescribed for motor symptom treatment, reportedly increase individual risk for the emergence of psychosis symptoms 13 .The development of these secondary symptoms is not always timed after the diagnosis of the primary motor disorder, for example, depression is a common manifestation in premorbid PD and has been associated as a risk factor for motor symptom development [14][15][16] .
Furthermore, the therapies that exist for these non-motor symptoms are currently minimally effective, despite the considerable disease burden they represent.
Although the occurrence of neuropsychiatric and cognitive symptoms in PD is much more common than in age-matched populations 9,10 , individual to individual level susceptibility to these secondary features is highly variable 17,18 .Genetic liability has been implicated, for example a recent genome-wide association study (GWAS) of cognitive progression in PD highlighted the contribution of risk genes such as GBA with worsening cognitive decline over time 19 and meta analyses of the gene have shown an association to the emergence of psychosis and depression symptoms 20 .However, given the high levels of heterogeneity within the condition, PD secondary symptoms likely share a complex underlying etiology, owing to additional factors aside from genetics.One potential contributing factor is epigenetic changes, which play an intermediary role between genetic and environmental risk, and regulate gene expression 21 .DNA methylation, which refers to the reversible addition of methyl groups to cytosines typically in a CpG dinucleotide, is the most studied epigenetic mechanism in neurological disorders 22 .Indeed, several studies have shown robust alterations in DNA methylation in a number of genes in different neurodegenerative diseases, in both the brain and blood, including Alzheimer's disease (AD) [23][24][25] , PD [26][27][28] and Dementia with Lewy bodies (DLB) 29 .Interestingly, associations have also been reported for secondary symptoms of these neurodegenerative disease, for example with psychosis symptoms in AD 30 or cognition in PD 27 .However the analysis of DNA methylation signatures in relation to PD secondary symptoms is understudied and has predominantly been undertaken in peripheral tissues such as blood 31 .
In the current study we investigated the relationship between DNA methylation patterns and the occurrence of key secondary symptoms in PD (dementia, hallucinations, depression, anxiety, aggression, sleep disorder), using weighted gene correlation network analysis (WGCNA) in multiple disease-relevant brain regions.Subsequently, gene ontology and cell type enrichment analysis were performed on the genes comprising the significant modules to identify dysfunctional pathways and the cell types likely driving this.
We highlight a core finding of a co-methylation module specific to the substantia nigra, significantly correlated to depressive symptom presentation and significantly enriched for neuronally relevant synaptic terms.Assessing the expression of genes annotated to this module found enriched expression in specific neuronal sub-populations within the substantia nigra, indicative of neuronal changes within this region that may play a role in the development of depressive symptoms within PD.

Results
A cohort to assess DNA methylation signatures of PD neuropsychiatric and cognitive symptoms Our study comprised a cohort of 97 idiopathic Parkinson's Disease (PD) patients with post-mortem DNA methylomic profiling conducted on the Illumina Infinium 450K array (Figure 1A).Three brain regions were assessed: the substantia nigra (SN, n = 88), caudate nucleus (CN, n = 82) and prefrontal cortex (FC, n = 88), with the majority of cases having all brain regions represented in this dataset (Figure 1A,C).PD patients had a mean age of 78.25 years at death (SD = 6.17) with the average patient having had PD symptoms for over ten years (mean = 12.63, SD = 8.28).Pathologically, these patients predominantly showed late stage PD-associated Lewy body (LB) pathology 12 (LB Braak stage mean = 5.54, SD = 0.81) with relatively mild AD-associated neurofibrillary tangle (NFT) pathology 32,33 (NFT Braak stage mean = 1.91,SD = 0.72) (Figure 1B).
The primary hypothesis of this study posits that the prevailing neuropsychiatric and cognitive manifestations observed in PD exhibit a distinctive epigenetic profile in the brain, distinguishing individuals presenting with these symptoms from those who do not.To test this hypothesis, we annotated binary symptom prevalence from antemortem clinical records for six phenotypes: dementia, hallucinations, depression, anxiety, aggression, and sleep disorder (Methods, Figure 1C).The majority of these sub-symptoms showed overlap in their presentation and demographic differences (Supplementary Figure 1, Supplementary Table 1) as could be expected with cumulative disease burden 34 .To identify DNA methylation signatures associated with the phenotypes of interest, we investigated co-methylation changes by implementing weighted gene correlation network analysis (WGCNA).This was also useful as a strategy to reduce the number of features and increase statistical power, given our modest sample size for conducting epigenome-wide association studies (EWAS), particularly when examining binary variables related to phenotypes of interest.

DNA co-methylation networks show brain region specific correlation to depressive and aggression symptoms
To identify co-methylated modules within each brain region, we followed a standardized WGCNA protocol (Methods), and tested their association with sub-trait presentation, after regressing out key covariates (age, sex, technical batch, proportions of neurons, post-mortem interval (PMI)).The number of detected modules differed across each brain region, with 27 modules identified in the SN (Supplementary Figure 2), eight in the FC (Supplementary Figure 3) and 18 in the CN (Supplementary Figure 4).The correlation of these modules to trait presentation also differed across brain regions.Stronger module-trait correlations were observed in the SN and CN, with two modules passing the Bonferroni significance threshold for the number of tests within each trait association (Figure 2, SN: P < 0.0019, CN: P < 0.0028), with no significant correlations in the FC (Figure 2).The significant SN module correlated with depressive symptoms in PD (Spearman's Coefficient = 0.33, P = 0.0016) and was comprised of 1,375 distinct methylated loci, whilst the significant CN module that was significantly correlated to aggression presentation (Spearman's Coefficient = 0.35, P = 0.0015) was comprised of 475 distinct methylated loci.
When assessing module membership of these two significant modules, a weak but significant correlation was observed between P-value significance of depressive symptom association and module membership for methylated loci within the SN depression associated module (Pearson's Coefficient = 0.12, p-value = 1.24 x 10 -5 , Supplementary Figure 5A).By contrast the CN aggression associated module does not show any indication of correlation between module membership and probe significance from the aggression symptom association (Pearson's Coefficient = 0.07, p-value = 0.13, Supplementary Figure 5B).Although no further modules passed our threshold for multiple testing correction, several other modules in these regions did show nominal significance in their correlation with trait presentation (Figure 2, Supplementary Figure 2, Supplementary Figure 4).Of particular note, a set of four modules in the CN all showed correlation with anxiety symptoms.However, we have focused our downstream analyses on the Bonferroni-significant module identified in the SN (with respect to depression) and the CN (associated with aggression), henceforth referred to as the DepressionSN module and the AggressionCN module, respectively.
To test whether the association of the DepressionSN module was affected by onset of depression before motor symptoms we subset the depression group based on annotation of depressive symptoms before PD diagnosis (Premorbid depression, n = 9) versus those without annotation preceding PD diagnosis (Depression, n = 23) and compared both groups to the group without depression annotation (No Depression, n = 54).Both premorbid depression and depression groups showed increased eigengene values compared to the non-depressed group (Supplementary Figure 6).A pairwise comparison of the three groups with a Wilcoxon rank sum test, with BH correction found a significant difference between the non-depressed and depressed group (q-value = 0.02) whilst no significant difference was observed between any of the other groupwise comparisons with the premorbid or non-depressed group.

Genes annotated from depression-associated DNA co-methylation in PD show ontological enrichment for synaptic processes
Next, to gain insight into potential underlying molecular functions captured by these trait-associated modules, we performed Gene Ontology (GO) analysis in the missMethyl package, a method which tests for enrichment for gene symbols annotated to each methylated loci whilst correcting for coverage bias of the 450K array 35 .The DepressionSN module showed nominal enrichment (P value <0.01) for 28 terms; within the top 10 most enriched terms (Figure 3, Supplementary Table 2), several were related to synaptic function, including synapse, maintenance of synapse structure and presynaptic active zone.Two additional terms were related to corticotropin releasing hormone.In addition, we also observed terms of extrinsic component of membrane, cellular component maintenance and sodium channel regulator activity.KEGG pathway enrichment identified 10 pathways with nominal enrichment (P value < 0.05), the topmost containing multiple pathways relevant to signalling (mTOR, Insulin, Phospholipase D, Apelin and Adrenergic) and longevity regulation (Supplementary Table 3).
The AggressionCN module showed nominal enrichment (P value <0.01) for 49 terms, the top 10 most enriched (Figure 3, Supplementary Table 4), being related to electron transport chain, cytosol, spinal cord signalling, protein transport, transcription repression, ATP metabolism, ion binding, calcium ion transport and 14-3-3 protein binding.KEGG pathway enrichment identified 36 pathways with nominal enrichment (P value < 0.05) and included pathways relevant to carbon metabolism, diabetes and notch signalling (Supplementary Table 5).

Genes annotated to the depression-associated DNA co-methylation module show significantly enriched expression in neuronal subtypes of the substantia nigra
As a number of terms in the gene ontology analysis of the DepressionSN module indicated neuronal involvement, we next sought to elucidate the cell-specific expression of genes annotated to the DNA methylation loci in the DepressionSN module, using a reference set of human single nucleus RNAseq data 36 generated in the SN and using Expression Weighted Cell Enrichment analysis (EWCE) to test for enrichment.Of the 617 genes overlapping between the DepressionSN module methylation dataset and the reference snRNAseq data, we observed significant enrichment of expression in neurons only (Figure 4, Supplementary Table 6).Of a total of 68 defined cell subtypes annotated in the original study by Kamath and colleagues, 15 showed a significant expression enrichment for DepressionSN annotated genes (BH corrected q value < 0.05), corresponding to seven excitatory neuronal populations, four inhibitory neuronal populations and four dopaminergic neuronal populations.Of these populations, the two with the highest standard deviation shift from the mean expression were both excitatory: POSTN and OPRD1 (7.44 and 6.35 standard deviations from the mean, respectively).This provides evidence that the network of genes present within the DepressionSN module has functional relevance in disease as it is likely driven by SN neuronal cell types.Benjamini-Hochberg (BH)-corrected significant enrichments (q < 0.05) are annotated with asterisks.Standard deviations from the mean value is displayed along the Y-axis.Standard deviation from the mean indicates the number of standard deviations from the mean level of expression of genes in the DepressionSN module, relative to the bootstrapped mean for that cell type.

Discussion
In this report we have investigated multiple common secondary symptom traits in PD across three diseaserelevant brain regions and explored the contribution of DNA methylation (summarized into inter-correlated DNA methylation networks) with trait presentation.We report region-specific associations between DNA methylation networks and trait presentation, specifically in association with depression in the SN and aggression in the CN.Subsequent downstream analyses indicated that genes related to the depression-associated SN co-methylation network (DepressionSN module) are enriched for ontological terms corresponding to synaptic processes, with significant overrepresentation of genes that are expressed in neuronal cells in the SN inferred from a separate snRNAseq dataset.
Depression in PD has a prevalence of roughly 40-46% 37 and is a common premorbid symptom, being a risk factor for both PD development 14 and worse symptom progression over time 38 .The pathophysiology underlying depressive symptoms in PD however remains poorly understood, with multiple potential threads of evidence for its etiology and relation to PD pathological development.Our results relating to SN neuronal changes lend support to dopaminergic theories of PD depression onset.Previous studies have shown that depressed PD patients present with greater neuronal loss 39 and gliosis 40 in the SN than non-depressed patients.Furthermore, alpha-synuclein pathology in the SN has been reported to be significantly higher in the SN of depressed cases versus non-depressed 39 .This regional neurodegeneration and consequent disruption of dopaminergic neurotransmission may be a contributing factor to the epigenetic alterations we observe in our results.However, the epigenetic network identified appears to be most enriched for expression in non-dopaminergic excitatory and inhibitory neurons, contradicting the evidence that this effect is purely a result of dopaminergic neurodegeneration.Further research is needed to fully elucidate the contribution of these SN neuronal cell types in the context of PD depression.
A potential avenue for further research could be in animal models of PD neurodegeneration, specifically in the context of PD depression.A number of rodent studies utilizing neurotoxic compounds such as 1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine (MPTP), which cause selective dopaminergic neuron degeneration, report depression-like behaviours, even manifesting before the onset of motor impairments 41 .Importantly the onset of this depression-like phenotype is variable 42,43 , potentially allowing for a controlled model for assessment of specific cell type contributions to the variable onset of PD depression, as mediated by midbrain dopaminergic degeneration.Interestingly, in the original publication of the single nucleus RNA reference data used in our study, Kamath et al 36 reported consistencies in dopaminergic subtypes between rodents and primate cell types, but reported one cell subtype characterized by expression of CALB1 and GEM ("CALB1_GEM") to be highly specific to primates.We observe this cell subtype as one of the four dopaminergic populations with significant enrichment of PD depression-associated network genes.This may have implications for the translatability of findings between rodent models and human disease in the context of PD depression.
As is a common issue with DNA methylation studies, in particular in bulk tissue, the causality of any changes detected is unclear, in particular in a disease process where cell type proportion changes are implicit.
Although we have controlled for inferred cell type proportions, we cannot exclude the fact that the perturbed DNA methylation network we observe in the SN may be a downstream consequence of broad neurodegeneration in this brain region.Furthermore, it is premature to conclude whether differential DNA methylation of genes present within this particular network lead to altered expression, an assumption reliedupon for the findings of the snRNAseq enrichment analysis.Further work, in appropriate powered cohorts to look at a depression trait within PD and testing gene expression changes in the SN is required to validate this.However, our study represents the first of its type to look at underlying epigenomic changes with multiple symptom changes in PD and provides a basis for replication to confirm our findings.
A caveat to our findings is in the nature of the phenotyping data present and the clinical binary subsetting used in our trait annotations.Although care has been taken to annotate these records ante-mortem, we are limited in our ability to resolve clinical traits and inaccuracy may be present within this labelling criteria.In particular, we do not have capacity to resolve timing of symptoms for certain individuals and are limited to binary presentation over lifetime.This may have had a detrimental impact on identifying significant findings for specific outcomes tested in this study.Ideally, the use of quantitative scoring criteria, for example, the geriatric depression scale, Unified Parkinson's Disease Rating Scale, or neuropsychiatric inventory (lacking in the case notes available for the current cohort) in future studies will allow for standardization of these traits.

Conclusions
To conclude, we find evidence of regional epigenetic changes in relation to the development of secondary symptoms in PD, investigating multiple common secondary symptom traits in PD across three relevant brain regions and exploring the contribution of DNA methylation (summarised into inter correlated networks) with trait presentation.We find brain region-specific correlations between these networks and trait presentation, specifically in association with depression in the SN and highlight relevant ontological terms enriched within this network.Finally, we find that expression of genes within this network are specifically enriched for expression within relevant neuronal subtypes, prioritizing neuronal changes in the SN and cell types with potential contribution to the onset of PD depression.

Figure 1 :
Figure 1: Overview of study design and samples used.A) Sample information and data analysis flowchart as detailed in Methods B) Demographic summaries of PD patients profiled with histograms or bar-charts representing overall numbers for each variable.Length of disease corresponds to time interval between recorded age of PD diagnosis and age at death.C) Summary table of sub-symptoms tested in primary WGCNA association analysis.Symptoms were annotated for binary status in the ante-mortem clinical records.Symptom prevalence per each brain region tested is shown and is annotated as Absent/Present.

Figure 2 :
Figure 2: Co-methylation network association to sub symptom occurrence in PD.Points represent individual module eigengenes for the substantia nigra (n = 27), frontal cortex (n = 8) and caudate nucleus (n = 18), repeatedly tested using correlation analysis in association with traits displayed along the y axis.Points are colored by the trait they are being tested for association with and sized by the absolute correlation coefficient value of the association.For clinical binary traits Spearman's correlation was used, whilst for years of disease Pearson's correlation was used.The -log10(p-value) of the association tests is displayed along the X-axis.The gray dashed line represents P-value = 0.05, whilst the Black dashed line represents the Bonferroni correction threshold for each brain region, controlling for the number of tests within each trait association, equivalent to 0.05 divided by the number of module eigengenes per region (SN: P < 0.0019, CN: P < 0.0028, FC P < 0.006).

Figure 3 :
Figure 3: Gene Ontology Enrichment plots.The top 10 most significant terms for gene ontology (GO) enrichment analyses in A) the SN Depression associated module and B) the CN Aggression associated module.The term titles are displayed along the Y-axes, with -log10(P) for enrichment significance shown along the X-axis.Points are sized by the proportion of the overall ontology gene numbers represented in that specific module.

Figure 4 :
Figure 4: Expression Weighted Cell Enrichment analysis of DepressionSN module genes within the snRNAseq dataset from Kamath et al 36 .Sub-cell type annotations along the X-axis are grouped by their broader cell class.