Patients with late-onset Alzheimer's disease (LOAD) frequently manifest comorbid neuropsychiatric symptoms with depression and anxiety being most frequent, and individuals with major depressive disorder (MDD) have an increased prevalence of LOAD. This suggests shared etiologies and intersecting pathways between LOAD and MDD. We performed pleiotropy analyses using LOAD and MDD GWAS data sets from the International Genomics of Alzheimer's Project (IGAP) and the Psychiatric Genomics Consortium (PGC), respectively. We found a moderate enrichment for SNPs associated with LOAD across increasingly stringent levels of significance with the MDD GWAS association (LOAD| MDD), of maximum four and eightfolds, including and excluding the APOE-region, respectively. Association analysis excluding the APOE-region identified numerous SNPs corresponding to 40 genes, 9 of which are known LOAD-risk loci primarily in chromosome 11 regions that contain the SPI1 gene and MS4A genes cluster, and others were novel pleiotropic risk-loci for LOAD conditional with MDD. The most significant associated SNPs on chromosome 11 overlapped with eQTLs found in whole-blood and monocytes, suggesting functional roles in gene regulation. The reverse conditional association analysis (MDD|LOAD) showed a moderate level,~sevenfold, of polygenic overlap, however, no SNP showed significant association. Pathway analyses replicated previously reported LOAD biological pathways related to immune response and regulation of endocytosis. In conclusion, we provide insights into the overlapping genetic signatures underpinning the common phenotypic manifestations and inter-relationship between LOAD and MDD. This knowledge is crucial to the development of actionable targets for novel therapies to treat depression preceding dementia, in an effort to delay or ultimately prevent the onset of LOAD.

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Peroxisome proliferator-activated receptor-γ (PPARγ), is a transcription factor that governs pathways, such as lipid metabolism and immune response, that have been implicated in the etiology of LOAD. Previously, we established HepG2-derived cell-lines with stable knockdown of PPARγ gene, and showed an increase in mRNA levels of genes mapped in the APOE linkage disequilibrium (LD) region on chromosome 19q13.32, with the greatest effect observed for APOE-mRNA. Here, we extended the analysis using our PPARγ knockdown model system and investigated the broader effect on expression changes of genes implicated in LOAD via genome wide association studies (GWAS). We applied the nCounter gene expression assay (NanoString) using a panel of twenty-four LOAD-associated genes inferred by proximity to the top significantly associated SNPs. Two independent PPARγ knockdown cell-lines showed changes in mRNA levels of a total of seven genes compared to a control HepG2 cell-line; six of which, ABCA7, APOE, CASS4, CELF1, PTK2B, and ZCWPW1, were upregulated and one, DSG2, was downregulated upon PPARγ knockdown. Our results propose that PPARγ may act as a master regulator of the transcription of several genes involved in LOAD pathogenesis. Our study provided the premise for further analyses including a larger set of genes positioned within a wider range of linkage disequilibrium (LD) regions tagged by all LOAD significantly associated SNPs.

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Parkinson’s disease (PD) and dementia with Lewy body (DLB) are the most common synucleinopathies. SNCA gene is a major genetic risk factor for these diseases group, and dysregulation of its expression has been implicated in the genetic etiologies of several synucleinopathies. DNA methylation at CpG island (CGI) within SNCA intron 1 has been suggested as a regulatory mechanism of SNCA expression, and changes in methylation levels at this region were associated with PD and DLB. However, the role of DNA methylation in the regulation of SNCA expression in a cell-type specific manner and its contribution to the pathogenesis of PD and DLB remain poorly understood, and the data are conflicting. Here, we employed a bisulfite pyrosequencing technique to profile the DNA methylation across SNCA intron 1 CGI in PD and DLB compared to age- and sex-matched normal control subjects. We analyzed homogenates of bulk post-mortem frozen frontal cortex samples and a subset of neuronal and glia nuclei sorted by the fluorescence-activated nuclei sorting (FANS) method. Bulk brain tissues showed no significant difference in the overall DNA methylation across SNCA intron 1 CGI region between the neuropathological groups. Sorted neuronal nuclei from PD frontal cortex showed significant lower levels of DNA methylation at this region compared to normal controls, but no differences between DLB and control, while sorted glia nuclei exhibited trends of decreased overall DNA methylation in DLB only. In conclusion, our data suggested disease-dependent cell-type specific differential DNA methylation within SNCA intron 1 CGI. These changes may affect SNCA dysregulation that presumably mediates disease-specific risk. Our results can be translated into the development of the SNCA intron 1 CGI region as an attractive therapeutics target for gene therapy in patients who suffer from synucleinopathies due to SNCA dysregulation.

Dysregulation of alpha-synuclein expression has been implicated in the pathogenesis of synucleinopathies, in particular Parkinson’s Disease (PD) and Dementia with Lewy bodies (DLB). Previous studies have shown that the alternatively spliced isoforms of the SNCA gene are differentially expressed in different parts of the brain for PD and DLB patients. Similarly, SNCA isoforms with skipped exons can have a functional impact on the protein domains. The large intronic region of the SNCA gene was also shown to harbor structural variants that affect transcriptional levels. Here, we apply the first study of using long read sequencing with targeted capture of both the gDNA and cDNA of the SNCA gene in brain tissues of PD, DLB, and control samples using the PacBio Sequel system. The targeted full-length cDNA (Iso-Seq) data confirmed complex usage of known alternative start sites and variable 3′ UTR lengths, as well as novel 5′ starts and 3′ ends not previously described. The targeted gDNA data allowed phasing of up to 81% of the ~114 kb SNCA region, with the longest phased block exceeding 54 kb. We demonstrate that long gDNA and cDNA reads have the potential to reveal long-range information not previously accessible using traditional sequencing methods. This approach has a potential impact in studying disease risk genes such as SNCA, providing new insights into the genetic etiologies, including perturbations to the landscape the gene transcripts, of human complex diseases such as synucleinopathies.