Vikas Bansal

Background: Parkinson’s disease (PD) and schizophrenia (SZ), while clinically distinct, exhibit overlapping symptoms and neurobiological features. Emerging genetic evidence suggests a shared heritable component between the two disorders. In this study, we aim to identify novel genetic loci common to both PD and SZ and to further investigate the convergent molecular mechanisms that may underlie their shared pathophysiology. Methods: We analyzed large-scale genome-wide association studies (GWAS) on SZ (55,193 cases and 74,132 controls) and PD (56,306 cases and 1,417,791 controls) using a proxy-phenotype method combined with a Bayesian statistical approach to evaluate overlap in common genetic variants and enhance statistical power for genetic discovery. To elucidate the biological mechanisms underlying newly identified shared genetic loci associated with PD and SZ, we leveraged single-cell RNA sequencing (scRNA-seq) data from induced pluripotent stem cell (iPSC)-derived dopaminergic neurons generated by the FOUNDIN-PD consortium (416,216 high-quality single-cells from PD patients). We performed differential gene expression analysis, and gene ontology (GO) enrichment analysis to systematically investigate the functional relevance of one shared loci in a disease-relevant cellular context. The polygenic risk score (PRS) model was constructed by stratifying overlapping SNPs based on effect directions to predict PD clinical outcomes in the Tuebingen Parkinson cohort (TUEPAC). MAGMA gene-set enrichment analysis was used to identify the cell types enriched for each SNP set. Results: We identified five SNPs with concordant effect directions and nine SNPs with discordant effect directions shared between PD and SZ. Of these fourteen SNPs, eleven were in linkage disequilibrium with previously reported PD GWAS hits. In addition, we identified three novel shared SNPs (rs2240921, rs11649804, and rs9607782) associated with both PD and SZ. Notably, a missense variant in RAI1 (rs11649804) emerged as a shared genetic signal between the two disorders. Differential expression analysis and gene ontology (GO) enrichment analysis implicated RAI1 in mitochondrial dysfunction-related biological processes, highlighting its potential role in PD pathogenesis. In addition, PD_discordant PRS was associated with non-motor symptoms and uniquely associated with genes expressed in brain vascular cell types. Conclusion: In summary, our study provides novel insights into the shared genetic architecture of PD and SZ, highlighting previously unrecognized loci with potential cross-disorder relevance. Functional characterization of RAI1 loci suggests that mitochondrial dysfunction may represent convergent biological mechanisms underlying both neurodegenerative and psychiatric pathologies. Moreover, variants with opposing cross-disorders effects may capture biological pathways specifically contributing to non-motor heterogeneity. These findings advance our understanding of the molecular interplay between PD and SZ and open new avenues for the identification of shared therapeutic targets.

Several prior studies have proposed the involvement of various brain regions and cell types in Parkinson’s disease (PD) pathology. Here, we performed snRNA-seq on the prefrontal cortex and anterior cingulate regions from a small cohort of post-mortem control and PD brain tissue. We found a significant association of oligodendrocytes (ODCs) and oligodendrocyte precursor cells (OPCs) with PD-linked risk loci and report several dysregulated genes and pathways, including regulation of tau-protein kinase activity, regulation of inclusion body assembly and protein processing involved in protein targeting to mitochondria. In an independent PD cohort with clinical measures (681 cases and 549 controls), polygenic risk scores derived from the dysregulated genes significantly predicted Montreal Cognitive Assessment (MoCA)-, and Beck Depression Inventory-II (BDI-II)-scores but not motor impairment (UPDRS-III). We extended our analysis of clinical outcome prediction by incorporating differentially expressed genes from three separate datasets that were previously published by different laboratories. In the first dataset from the anterior cingulate cortex, we identified an association between ODCs and BDI-II. In the second dataset obtained from the substantia nigra (SN), OPCs displayed an association with UPDRS-III. In the third dataset from the SN region, a distinct subtype of OPCs, labeled OPC_ADM, exhibited an association with UPDRS-III. Intriguingly, the OPC_ADM cluster also demonstrated a significant increase in PD samples. These results suggest that by expanding our focus to glial cells, we can uncover region-specific molecular pathways associated with PD symptoms.

Despite extensive research, the contribution of the LRRK2 p.G2019S mutation to Parkinson’s disease (PD) remains unclear. Recent findings indicate oligodendrocytes (ODCs) and their progenitors are vulnerable in PD pathogenesis. Notably, oligodendrocyte precursor cells (OPCs) exhibit high endogenous expression of LRRK2 . We induced PD patient-iPSCs with the LRRK2 p.G2019S mutation into oligodendroglial lineages and performed single-cell RNA sequencing. Cell type composition analysis revealed an increase in OPCs, proliferating OPCs and ciliated ependymal cells in LRRK2 lines, all of which are characterized by LRRK2 expression. Differential expression analysis revealed transcriptomic changes in several pathways, including down-regulation of genes related to myelin assembly in ODCs, semaphorin-plexin pathway in OPCs, and cilium movement in proliferating OPCs. Cell-cell communication analysis identified significant alterations in several signaling pathways including a deactivation of PSAP signaling and an activation of MIF signaling in LRRK2 lines. Additionally, we observed an overall increase in SEMA6 signaling communication in LRRK2 cell lines; however, OPCs derived from these LRRK2 lines specifically lost SEMA6 signaling due to a down-regulation of SEMA6A and PLXNA2 . Pseudotemporal trajectory analysis revealed that SHH had significantly altered expression along the pseudotime, accompanied by higher expression levels in LRRK2 lines. We propose that dysfunctional semaphorin-plexin signaling, along with cilia movement and SHH signaling, might represent early events in PD pathology.

Accumulating evidence suggests that endogenous retroviruses (ERVs) play an important role in the host response to infection and the development of disease. By analyzing ChIP-sequencing data sets, we show that SARS-CoV-2 infection induces H3K27 acetylation of several loci within the LTR69 subfamily of ERVs. Using functional assays, we identified one SARS-CoV-2-activated LTR69 locus, termed Dup69, which exhibits regulatory activity and is responsive to the transcription factors IRF3 and p65/RELA. LTR69_Dup69 is located about 500 bp upstream of a long non-coding RNA gene (ENSG00000289418) and within the PTPRN2 gene encoding a diabetes-associated autoantigen. Both ENSG00000289418 and PTPRN2 showed a significant increase in expression upon SARS-CoV-2 infection. Thus, our study sheds light on the interplay of exogenous with endogenous viruses and helps to understand how ERVs regulate gene expression during infection.

Several prior studies have proposed the involvement of various brain regions and cell types in Parkinson’s disease (PD) pathology. Here, we performed snRNA-seq on the prefrontal cortex and anterior cingulate regions from post-mortem control and PD brain tissue. We found a significant association of oligodendrocytes (ODCs) and oligodendrocyte precursor cells (OPCs) with PD-linked risk loci and report several dysregulated genes and pathways, including regulation of tau-protein kinase activity, regulation of inclusion body assembly and protein processing involved in protein targeting to mitochondria. In an independent PD cohort with clinical measures (681 cases and 549 controls), polygenic risk scores derived from the dysregulated genes significantly predicted Montreal Cognitive Assessment (MoCA)-, and Beck Depression Inventory-II (BDI-II)-scores but not motor impairment (UPDRS-III). We extended our analysis of clinical outcome prediction by incorporating three separate datasets that were previously published by different laboratories. In the first dataset from the anterior cingulate cortex, we identified a correlation between ODCs and BDI-II. In the second dataset obtained from the substantia nigra (SN), OPCs displayed notable predictive ability for UPDRS-III. In the third dataset from the SN region, a distinct subtype of OPCs, labeled OPC_ADM, exhibited predictive ability for UPDRS-III. Intriguingly, the OPC_ADM cluster also demonstrated a significant increase in PD samples. These results suggest that by expanding our focus to glial cells, we can uncover region-specific molecular pathways associated with PD symptoms.

Accumulating evidence suggests that endogenous retroviruses (ERVs) play an important role in the host response to infection and the development of disease. By combining RNA- and ChIP-sequencing analyses with RT-qPCR, we show that SARS-CoV-2 infection induces the LTR69 subfamily of ERVs, both in vitro and in vivo . Using functional assays, we identified one SARS-CoV-2-activated LTR69 locus, termed Dup69, which exhibits enhancer activity and is responsive to the transcription factors IRF3 and p65/RelA. LTR69-Dup69 is located about 500 bp upstream of a long non-coding RNA gene (ENSG00000289418) and within the PTPRN2 gene encoding a diabetes-associated autoantigen. Both ENSG00000289418 and PTPRN2 showed a significant increase in expression upon SARS-CoV-2 infection. Thus, our study sheds light on the interplay of exogenous with endogenous viruses and helps to understand how ERVs regulate gene expression during infection.

A role of CD4 ⁺ T cells during the progression from nonalcoholic fatty liver disease (NAFLD) to nonalcoholic steatohepatitis (NASH) has been suggested, but which polarization state of these cells characterizes this progression and the development of fibrosis remain unclear. In addition, a gut-liver axis has been suggested to play a role in NASH, but the role of CD4 ⁺ T cells in this axis has just begun to be investigated. Combining single-cell RNA sequencing and multiple-parameter flow cytometry, we provide the first cell atlas to our knowledge focused on liver-infiltrating CD4 ⁺ T cells in patients with NAFLD and NASH, showing that NASH is characterized by a population of multicytokine-producing CD4 ⁺ T cells. Among these cells, only those with a Th17 polarization state were enriched in patients with advanced fibrosis. In parallel, we observed that Bacteroides appeared to be enriched in the intestine of NASH patients and to correlate with the frequency of multicytokine-producing CD4 ⁺ T cells. In short, we deliver a CD4 ⁺ T cell atlas of NAFLD and NASH, providing the rationale to target CD4 ⁺ T cells with a Th17 polarization state to block fibrosis development. Finally, our data offer an early indication to test whether multicytokine-producing CD4 ⁺ T cells are part of the gut-liver axis characterizing NASH.

Aggregates of medin amyloid (a fragment of the protein MFG-E8, also known as lactadherin) are found in the vasculature of almost all humans over 50 years of age^1,2, making it the most common amyloid currently known. We recently reported that medin also aggregates in blood vessels of ageing wild-type mice, causing cerebrovascular dysfunction³. Here we demonstrate in amyloid-β precursor protein (APP) transgenic mice and in patients with Alzheimer’s disease that medin co-localizes with vascular amyloid-β deposits, and that in mice, medin deficiency reduces vascular amyloid-β deposition by half. Moreover, in both the mouse and human brain, MFG-E8 is highly enriched in the vasculature and both MFG-E8 and medin levels increase with the severity of vascular amyloid-β burden. Additionally, analysing data from 566 individuals in the ROSMAP cohort, we find that patients with Alzheimer’s disease have higherMFGE8expression levels, which are attributable to vascular cells and are associated with increased measures of cognitive decline, independent of plaque and tau pathology. Mechanistically, we demonstrate that medin interacts directly with amyloid-β to promote its aggregation, as medin forms heterologous fibrils with amyloid-β, affects amyloid-β fibril structure, and cross-seeds amyloid-β aggregation both in vitro and in vivo. Thus, medin could be a therapeutic target for prevention of vascular damage and cognitive decline resulting from amyloid-β deposition in the blood vessels of the brain.

The transcriptional activity of Transposable Elements (TEs) has been involved in numerous pathological processes, including neurodegenerative diseases such as amyotrophic lateral sclerosis and frontotemporal lobar degeneration. The TE expression analysis from short-read sequencing technologies is, however, challenging due to the multitude of similar sequences derived from singular TEs subfamilies and the exaptation of TEs within longer coding or non-coding RNAs. Specialised tools have been developed to quantify the expression of TEs that either relies on probabilistic re-distribution of multimapper count fractions or allow for discarding multimappers altogether. Until now, the benchmarking across those tools was largely limited to aggregated expression estimates over whole TEs subfamilies. Here, we compared the performance of recently published tools (SQuIRE, TElocal, SalmonTE) with simplistic quantification strategies (featureCounts in unique, fraction and random modes) at the individual loci level. Using simulated datasets, we examined the false discovery rate and the primary driver of those false positive hits in the optimal quantification strategy. Our findings suggest a high false discovery number that exceeds the total number of correctly recovered active loci for all the quantification strategies, including the best performing tool TElocal. As a remedy, filtering based on the minimum number of read counts or baseMean expression improves the F1 score and decreases the number of false positives. Finally, we demonstrate that additional profiling of Transcription Start Site mapping statistics (using a k-means clustering approach) significantly improves the performance of TElocal while reporting a reliable set of detected and differentially expressed TEs in human simulated RNA-seq data.