Biology subjects

Budde, J. P.

Publications and source records attributed to Budde, J. P..

5 recordsLinked to original sources

bioRxiv2026

Parietal Cortex Transcriptomics Refines Parkinson Disease GWAS Nomination and Highlights STAT3 as a Putative Upstream Glial Regulator

Parkinson disease (PD) affects more than 1.1 million individuals in the United States and around 12 million worldwide. Although Genome Wide Association Studies (GWAS) have substantially advanced our understanding of PD genetic architecture, the regulatory mechanisms linking PD risk loci to disease-relevant gene expression remain incompletely characterized, limiting our ability to infer disease mechanisms from genetic associations. Here, we integrated disease-state parietal cortex transcriptomics with the International Parkinsons Disease Genomics Consortium (iPDGC) locus prioritization to refine PD gene nomination and identify biologically plausible candidates missed by GWAS-only approaches. Using bulk RNA-seq from 99 neuropathologically confirmed PD cases and 30 neuropathologically confirmed controls, we prioritized candidate genes across 78 loci and classified them according to concordance between genetic evidence and differential expression in diseased cortices. This integrative approach recovered candidate genes not captured by external GWAS-based prioritization methods and highlighted synaptic, lysosomal, and proteostasis pathways as major components of PD risk biology. Network and transcription factor analyses further suggested coordinated regulation of these genes, with STAT3 emerging as a putative upstream glial regulator. Together, these findings suggest that integrating disease-state transcriptomics with genetic prioritization can refine PD risk-gene nomination and uncover regulatory programs that may be missed by GWAS alone.

neuroscience↗

bioRxiv2019

Overlapping Genetic Architecture between Parkinson Disease and Melanoma

Epidemiologic studies have reported inconsistent results regarding an association between Parkinson disease (PD) and cutaneous melanoma (melanoma). Identifying shared genetic architecture between these diseases can support epidemiologic findings and identify common risk genes and biological pathways. Here we apply polygenic, linkage disequilibrium-informed methods to the largest available case-control, genome-wide association study summary statistic data for melanoma and PD. We identify positive and significant genetic correlation (correlation: 0.17, 95% CI 0.10 to 0.24; P = 4.09 x 10-06) between melanoma and PD. We further demonstrate melanoma and PD-inferred gene expression to overlap across tissues (correlation: 0.14, 95% CI 0.06 to 0.22; P = 7.87 x 10-04), and highlight seven genes including PIEZO1, TRAPPC2L, and SOX6 as potential mediators of the genetic correlation between melanoma and PD. These findings demonstrate specific, shared genetic architecture between PD and melanoma that manifests at the level of gene expression.

genetics↗

bioRxiv2019

Single- nuclei RNA sequencing from human brain to study for Mendelian and sporadic AD

Alzheimer Disease (AD) is the most common form of dementia. This neurodegenerative disorder is associated with neuronal death and gliosis heavily impacting the cerebral cortex. AD has a substantial but heterogeneous genetic component, presenting both Mendelian and complex genetic architectures. Using bulk RNA-seq from parietal lobes and deconvolution methods, we previously reported that brains exhibiting different AD genetic architecture exhibit different cellular proportions. Here, we sought to directly investigate AD brain changes in cell proportion and gene expression using single cell resolution. To do so, we generated unsorted single-nuclei RNA-sequencing data from brain tissue. We leveraged tissue donated from a carrier of a Mendelian genetic mutation and two family members who suffer from AD, but do not have the same mutation. We evaluated alternative alignment approaches to maximize the titer of reads, genes and cells with high quality. In addition, we employed distinct clustering strategies to determine the best approach to identify cell clusters that reveal neuronal and glial cell types and avoid artifacts such as sample and batch effects. We propose an approach to cluster cells that reduces biases and enable further analyses. We identified distinct types of neurons, both excitatory and inhibitory, and glial cells, including astrocytes, oligodendrocytes, and microglia among others. In particular, we identified a reduced proportion of excitatory neurons in the Mendelian mutation carrier, but a similar distribution of inhibitory neurons. Furthermore, we investigated whether single-nuclei RNA-seq from human brains recapitulate the expression profile of Disease Associated Microglia (DAM) discovered in mouse models. We also determined that when analyzing human single-nuclei data it is critical to control for biases introduced by donor specific expression profiles. In conclusion, we propose a collection of best practices to generate a highly-detailed molecular cell atlas of highly informative frozen tissue stored in brain banks. Importantly, we have developed a new web application to make this unique single-nuclei molecular atlas publicly available.

genomics↗

bioRxiv2019

The TMEM106B rs1990621 protective variant is also associated with increased neuronal proportion

BackgroundIn previous studies, we observed decreased neuronal and increased astrocyte proportions in AD cases in parietal brain cortex by using a deconvolution method for bulk RNA-seq. These findings suggested that genetic risk factors associated with AD etiology have a specific effect in the cellular composition of AD brains. The goal of this study is to investigate if there are genetic determinants for brain cell compositions.\n\nMethodsUsing cell type composition inferred from transcriptome as a disease status proxy, we performed cell type association analysis to identify novel loci related to cellular population changes in disease cohort. We imputed and merged genotyping data from seven studies in total of 1,669 samples and derived major CNS cell type proportions from cortical RNAseq data. We also inferred RNA transcript integrity number (TIN) to account for RNA quality variances. The model we performed in the analysis was: normalized neuronal proportion [~] SNP + Age + Gender + PC1 + PC2 + median TIN.\n\nResultsA variant rs1990621 located in the TMEM106B gene region was significantly associated with neuronal proportion (p=6.40x10-07) and replicated in an independent dataset. The association became more significant as we combined both discovery and replication datasets in multi-tissue meta-analysis (p=9.42x10-09) and joint analysis (p=7.66x10-10). This variant is in high LD with rs1990622 (r2 = 0.98) which was previously identified as a protective variant in FTD cohorts. Further analyses indicated that this variant is associated with increased neuronal proportion in participants with neurodegenerative disorders, not only in AD cohort but also in cognitive normal elderly cohort. However, this effect was not observed in a younger schizophrenia cohort with a mean age of death < 65. The second most significant loci for neuron proportion was APOE, which suggested that using neuronal proportion as an informative endophenotype could help identify loci associated with neurodegeneration.\n\nConclusionThis result suggested a common pathway involving TMEM106B shared by aging groups in the present or absence of neurodegenerative pathology may contribute to cognitive preservation and neuronal protection.

neuroscience↗

bioRxiv2017

Precision genome-editing with CRISPR/Cas9 in human induced pluripotent stem cells

Genome engineering in human induced pluripotent stem cells (iPSCs) represent an opportunity to examine the contribution of pathogenic and disease modifying alleles to molecular and cellular phenotypes. However, the practical application of genome-editing approaches in human iPSCs has been challenging. We have developed a precise and efficient genome-editing platform that relies on allele-specific guideRNAs (gRNAs) paired with a robust method for culturing and screening the modified iPSC clones. By applying an allele-specific gRNA design strategy, we have demonstrated greatly improved editing efficiency without the introduction of additional modifications of unknown consequence in the genome. Using this approach, we have modified nine independent iPSC lines at five loci associated with neurodegeneration. This genome-editing platform allows for efficient and precise production of isogenic cell lines for disease modeling. Because the impact of CRISPR/Cas9 on off-target sites remains poorly understood, we went on to perform thorough off-target profiling by comparing the mutational burden in edited iPSC lines using whole genome sequencing. The bioinformatically predicted off-target sites were unmodified in all edited iPSC lines. We also found that the numbers of de novo genetic variants detected in the edited and unedited iPSC lines were similar. Thus, our CRISPR/Cas9 strategy does not specifically increase the mutational burden. Furthermore, our analyses of the de novo genetic variants that occur during iPSC culture and genome-editing indicate an enrichment of de novo variants at sites identified in dbSNP. Taken together, we propose that this enrichment represents regions of the genome more susceptible to mutation. Herein, we present an efficient and precise method for allele-specific genome-editing in iPSC and an analyses pipeline to distinguish off-target events from de novo mutations occurring with culture.

genetics↗