A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex.

The molecular organization of the human neocortex historically has been studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally defined spatial domains that move beyond classic cytoarchitecture. We used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex. Integration with paired single-nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we mapped the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains.

hadge: a comprehensive pipeline for donor deconvolution in single-cell studies.

Single-cell multiplexing techniques (cell hashing and genetic multiplexing) combine multiple samples, optimizing sample processing and reducing costs. Cell hashing conjugates antibody-tags or chemical-oligonucleotides to cell membranes, while genetic multiplexing allows to mix genetically diverse samples and relies on aggregation of RNA reads at known genomic coordinates. We develop hadge (hashing deconvolution combined with genotype information), a Nextflow pipeline that combines 12 methods to perform both hashing- and genotype-based deconvolution. We propose a joint deconvolution strategy combining best-performing methods and demonstrate how this approach leads to the recovery of previously discarded cells in a nuclei hashing of fresh-frozen brain tissue.

RAB32 Ser71Arg in autosomal dominant Parkinson's disease: linkage, association, and functional analyses.

BACKGROUND: Parkinson's disease is a progressive neurodegenerative disorder with multifactorial causes, among which genetic risk factors play a part. The RAB GTPases are regulators and substrates of LRRK2, and variants in the LRRK2 gene are important risk factors for Parkinson's disease. We aimed to explore genetic variability in RAB GTPases within cases of familial Parkinson's disease. METHODS: We did whole-exome sequencing in probands from families in Canada and Tunisia with Parkinson's disease without a genetic cause, who were recruited from the Centre for Applied Neurogenetics (Vancouver, BC, Canada), an international consortium that includes people with Parkinson's disease from 36 sites in 24 countries. 61 RAB GTPases were genetically screened, and candidate variants were genotyped in relatives of the probands to assess disease segregation by linkage analysis. Genotyping was also done to assess variant frequencies in individuals with idiopathic Parkinson's disease and controls, matched for age and sex, who were also from the Centre for Applied Neurogenetics but unrelated to the probands or each other. All participants were aged 18 years or older. The sequencing and genotyping findings were validated by case-control association analyses using bioinformatic data obtained from publicly available clinicogenomic databases (AMP-PD, GP2, and 100 000 Genomes Project) and a private German clinical diagnostic database (University of Tübingen). Clinical and pathological findings were summarised and haplotypes were determined. In-vitro studies were done to investigate protein interactions and enzyme activities. FINDINGS: Between June 1, 2010, and May 31, 2017, 130 probands from Canada and Tunisia (47 [36%] female and 83 [64%] male; mean age 72·7 years [SD 11·7; range 38-96]; 109 White European ancestry, 18 north African, two east Asian, and one Hispanic] underwent whole-exome sequencing. 15 variants in RAB GTPase genes were identified, of which the RAB32 variant c.213C>G (Ser71Arg) cosegregated with autosomal dominant Parkinson's disease in three families (nine affected individuals; non-parametric linkage Z score=1·95; p=0·03). 2604 unrelated individuals with Parkinson's disease and 344 matched controls were additionally genotyped, and five more people originating from five countries (Canada, Italy, Poland, Turkey, and Tunisia) were identified with the RAB32 variant. From the database searches, in which 6043 individuals with Parkinson's disease and 62 549 controls were included, another eight individuals were identified with the RAB32 variant from four countries (Canada, Germany, UK, and USA). Overall, the association of RAB32 c.213C>G (Ser71Arg) with Parkinson's disease was significant (odds ratio [OR] 13·17, 95% CI 2·15-87·23; p=0·0055; I2=99·96%). In the people who had the variant, Parkinson's disease presented at age 54·6 years (SD 12·75, range 31-81, n=16), and two-thirds had a family history of parkinsonism. RAB32 Ser71Arg heterozygotes shared a common haplotype, although penetrance was incomplete. Findings in one individual at autopsy showed sparse neurofibrillary tangle pathology in the midbrain and thalamus, without Lewy body pathology. In functional studies, RAB32 Arg71 activated LRRK2 kinase to a level greater than RAB32 Ser71. INTERPRETATION: RAB32 Ser71Arg is a novel genetic risk factor for Parkinson's disease, with reduced penetrance. The variant was found in individuals with Parkinson's disease from multiple ethnic groups, with the same haplotype. In-vitro assays show that RAB32 Arg71 activates LRRK2 kinase, which indicates that genetically distinct causes of familial parkinsonism share the same mechanism. The discovery of RAB32 Ser71Arg also suggests several genetically inherited causes of Parkinson's disease originated to control intracellular immunity. This shared aetiology should be considered in future translational research, while the global epidemiology of RAB32 Ser71Arg needs to be assessed to inform genetic counselling. FUNDING: National Institutes of Health, the Canada Excellence Research Chairs program, Aligning Science Across Parkinson's, the Michael J Fox Foundation for Parkinson's Research, and the UK Medical Research Council.

A pathogenic variant in RAB32 causes autosomal dominant Parkinson's disease and activates LRRK2 kinase.

Background: Parkinson's disease (PD) is a progressive neurodegenerative disorder. Mendelian forms have revealed multiple genes, with a notable emphasis on membrane trafficking; RAB GTPases play an important role in PD as a subset are both regulators and substrates of LRRK2 protein kinase. To explore the role of RAB GTPases in PD, we undertook a comprehensive examination of their genetic variability in familial PD. Methods: Affected probands from 130 multi-incident PD families underwent whole-exome sequencing and genotyping, Potential pathogenic variants in 61 RAB GTPases were genotyped in relatives to assess disease segregation. These variants were also genotyped in a larger case-control series, totaling 3,078 individuals (2,734 with PD). The single most significant finding was subsequently validated within genetic data (6,043 with PD). Clinical and pathologic findings were summarized for gene-identified patients, and haplotypes were constructed. In parallel, wild-type and mutant RAB GTPase structural variation, protein interactions, and resultant enzyme activities were assessed. Findings: We found RAB32 c.213C>G (Ser71Arg) to co-segregate with autosomal dominant parkinsonism in three multi-incident families. RAB32 Ser71Arg was also significantly associated with PD in case-control samples: genotyping and database searches identified thirteen more patients with the same variant that was absent in unaffected controls. Notably, RAB32 Ser71Arg heterozygotes share a common haplotype. At autopsy, one patient had sparse neurofibrillary tangle pathology in the midbrain and thalamus, without Lewy body pathology. In transfected cells the RAB32 Arg71 was twice as potent as Ser71 wild type to activate LRRK2 kinase. Interpretation: Our study provides unequivocal evidence to implicate RAB32 Ser71Arg in PD. Functional analysis demonstrates LRRK2 kinase activation. We provide a mechanistic explanation to expand and unify the etiopathogenesis of monogenic PD. Funding: National Institutes of Health, the Canada Excellence Research Chairs program, Aligning Science Across Parkinson's, the Michael J. Fox Foundation for Parkinson's Research, and the UK Medical Research Council.

escheR: unified multi-dimensional visualizations with Gestalt principles.

Summary: The creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve the design and interpretability of multi-dimensional data in 2D data visualizations, layering aesthetics to display multiple variables. The proposed visualization can be applied to spatially-resolved transcriptomics data, but also broadly to data visualized in 2D space, such as embedding visualizations. We provide an open source R package escheR, which is built off of the state-of-the-art ggplot2 visualization framework and can be seamlessly integrated into genomics toolboxes and workflows. Availability and implementation: The open source R package escheR is freely available on Bioconductor (https://bioconductor.org/packages/escheR).

aws-s3-integrity-check: an open-source bash tool to verify the integrity of a dataset stored on Amazon S3.

Amazon Simple Storage Service (Amazon S3) is a widely used platform for storing large biomedical datasets. Unintended data alterations can occur during data writing and transmission, altering the original content and generating unexpected results. However, no open-source and easy-to-use tool exists to verify end-to-end data integrity. Here, we present aws-s3-integrity-check, a user-friendly, lightweight, and reliable bash tool to verify the integrity of a dataset stored in an Amazon S3 bucket. Using this tool, we only needed ∼114 min to verify the integrity of 1,045 records ranging between 5 bytes and 10 gigabytes and occupying ∼935 gigabytes of the Amazon S3 cloud. Our aws-s3-integrity-check tool also provides file-by-file on-screen and log-file-based information about the status of each integrity check. To our knowledge, this tool is the only open-source one that allows verifying the integrity of a dataset uploaded to the Amazon S3 Storage quickly, reliably, and efficiently. The tool is freely available for download and use at https://github.com/SoniaRuiz/aws-s3-integrity-check and https://hub.docker.com/r/soniaruiz/aws-s3-integrity-check.

Age-related telomere attrition in the human putamen.

Age is a major risk factor for neurodegenerative diseases. Shortening of leucocyte telomeres with advancing age, arguably a measure of "biological" age, is a known phenomenon and epidemiologically correlated with age-related disease. The main mechanism of telomere shortening is cell division, rendering telomere length in post-mitotic cells presumably stable. Longitudinal measurement of human brain telomere length is not feasible, and cross-sectional cortical brain samples so far indicated no attrition with age. Hence, age-related changes in telomere length in the brain and the association between telomere length and neurodegenerative diseases remain unknown. Here, we demonstrate that mean telomere length in the putamen, a part of the basal ganglia, physiologically shortens with age, like leukocyte telomeres. This was achieved by using matched brain and leukocyte-rich spleen samples from 98 post-mortem healthy human donors. Using spleen telomeres as a reference, we further found that mean telomere length was brain region-specific, as telomeres in the putamen were significantly shorter than in the cerebellum. Expression analyses of genes involved in telomere length regulation and oxidative phosphorylation revealed that both region- and age-dependent expression pattern corresponded with region-dependent telomere length dynamics. Collectively, our results indicate that mean telomere length in the human putamen physiologically shortens with advancing age and that both local and temporal gene expression dynamics correlate with this, pointing at a potential mechanism for the selective, age-related vulnerability of the nigro-striatal network.

escheR: Unified multi-dimensional visualizations with Gestalt principles.

The creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve the design and interpretability of multi-dimensional data in 2D data visualizations, layering aesthetics to display multiple variables. The proposed visualization can be applied to spatially-resolved transcriptomics data, but also broadly to data visualized in 2D space, such as embedding visualizations. We provide an open source R package escheR, which is built off of the state-of-the-art ggplot2 visualization framework and can be seamlessly integrated into genomics toolboxes and workflows.

Integrated single cell and unsupervised spatial transcriptomic analysis defines molecular anatomy of the human dorsolateral prefrontal cortex.

Generation of a molecular neuroanatomical map of the human prefrontal cortex reveals novel spatial domains and cell-cell interactions relevant for psychiatric disease. The molecular organization of the human neocortex has been historically studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally-defined spatial domains that move beyond classic cytoarchitecture. Here we used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex (DLPFC). Integration with paired single nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we map the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains. Finally, we provide resources for the scientific community to explore these integrated spatial and single cell datasets at research.libd.org/spatialDLPFC/.

Photizo: an open-source library for cross-sample analysis of FTIR spectroscopy data.

MOTIVATION: With continually improved instrumentation, Fourier transform infrared (FTIR) microspectroscopy can now be used to capture thousands of high-resolution spectra for chemical characterization of a sample. The spatially resolved nature of this method lends itself well to histological profiling of complex biological specimens. However, current software can make joint analysis of multiple samples challenging and, for large datasets, computationally infeasible. RESULTS: To overcome these limitations, we have developed Photizo-an open-source Python library enabling high-throughput spectral data pre-processing, visualization and downstream analysis, including principal component analysis, clustering, macromolecular quantification and mapping. Photizo can be used for analysis of data without a spatial component, as well as spatially resolved data, obtained e.g. by scanning mode IR microspectroscopy and IR imaging by focal plane array detector. AVAILABILITY AND IMPLEMENTATION: The code underlying this article is available at https://github.com/DendrouLab/Photizo with access to example data available at https://zenodo.org/record/6417982#.Yk2O9TfMI6A.

No strong HLA association with MOG antibody disease in the UK population.

Improvements in assays for detecting serum antibodies against myelin oligodendrocyte glycoprotein (MOG) have led to the appreciation of MOG-antibody-associated disease (MOGAD) as a novel disorder. However, much remains unknown about its etiology. We performed human leukocyte antigen (HLA) analysis in 82 MOGAD patients of European ancestry in the UK population. No HLA class II associations were observed, thus questioning the mechanism of anti-MOG antibody generation. A weak protective association of HLA-C*03:04 was observed (OR = 0.26, 95% CI = 0.10-0.71, pc  = 0.013), suggesting a need for continued efforts to better understand MOGAD genetics and pathophysiology.