Biology subjects

Cookson, M. R.

Publications and source records attributed to Cookson, M. R..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Haplotype-Resolved DNA Methylation at the APOE Locus identifies Allele-Specific Epigenetic Signatures Relevant to Alzheimer's Disease Risk

The APOE gene encodes a key lipid transport protein and plays a central role in Alzheimers disease (AD) pathogenesis. Three common APOE alleles, {varepsilon}2 (rs7412(C>T), {varepsilon}3 (reference), and {varepsilon}4 (rs429358(T>C)), arise from two coding variants in exon 4 and confer distinct AD risk profiles, with {varepsilon}4 increasing risk and {varepsilon}2 providing protection. The {varepsilon}3-linked APOE variant rs769455[T] has also been associated with elevated AD risk in individuals of African ancestry carrying both rs769455[T] and {varepsilon}4 alleles. These single nucleotide variants (SNVs) reside in a cytosine-phosphate-guanine (CpG) island, which is a region with a higher frequency of CpG sites compared to the rest of the genome. CpG sites are subject to 5-methylcytosine (5mC) methylation by DNA methyltransferases which add a methyl group to the fifth carbon on the cytosine residue of a CpG site. The presence of SNVs can disrupt this process, making these regions prime targets for differential methylation; however, allele-specific methylation patterns in APOE remain poorly resolved due to technical limitations of conventional bisulfite and methylation array based methods, including degraded DNA quality, sparse CpG coverage, and lack of haplotype phasing. Here, we leverage high-accuracy long-read sequencing data to generate haplotype-resolved methylation profiles of the APOE locus in 332 postmortem brain samples from two ancestrally different cohorts. This includes 201 individuals of European ancestry from the North American Brain Expression Consortium (NABEC), comprising 402 haplotypes (48 {varepsilon}2 and 58 {varepsilon}4 alleles), and 131 individuals of African and African admixed ancestry from the Human Brain Core Collection (HBCC), comprising 262 haplotypes (25 {varepsilon}2, 64 {varepsilon}4, and 7 rs769455 alleles). A linear regression analysis identified 18 novel differentially methylated CpG sites (DMCs) associated with APOE {varepsilon}2, {varepsilon}4, and rs769455 within a gene cluster spanning TOMM40, APOE, APOC1, and APOC4-APOC2. This represents the most comprehensive haplotype-resolved methylation study of APOE in human brain tissue to date. Our results uncover distinct allele-specific methylation signatures and demonstrate the power of long-read sequencing for resolving epigenetic variation relevant to AD risk.

genomics↗

bioRxiv2025

Dissecting the biological impact of GBA1 mutations using multi-omics in an isogenic setting

GBA1 is a risk gene for multiple neurodegenerative diseases, including Lewy Body Dementia and Parkinsons disease, and biallelic pathogenic variants in the gene result in the lysosomal storage disorder Gaucher disease. GBA1 encodes the enzyme glucocerebrosidase (GCase), and alterations in the gene result in reduced enzymatic activity, which affects lysosome function downstream. Induced pluripotent stem cells (iPSCs) are a useful tool for testing the functional consequences of gene variants in an isogenic setting. Additionally, they can be used to perform multiomic studies to explore biological effects independent of disease mechanisms. Using CRISPR-edited isogenic KOLF2.1J iPSC lines containing pathogenic GBA1 variants D409H (p.D448H), D409V (p.D448V) and GBA1 knockout line generated by the iPSC Neurodegenerative Disease Initiative (iNDI), we examined potential molecular mechanisms and downstream consequences of GCase reduction. In this study, we confirm that this isogenic series behaves as expected for loss of function variants, despite the known difficulties with GBA1 editing. We identified that there are limited overlapping results across cell types suggesting potential different downstream effects caused by GBA1 variants. Additionally, we note that RNA-based quantitation may not be the best method to characterize GCase mechanisms, but protein and metabolomic analyses may be used to evaluate differences across genotypes.

genomics↗

bioRxiv2025

Cell-specific RNA isoform remodeling in the aging mouse brain

Aging is associated with increases in risk of multiple chronic diseases and at the cellular level, with disruptions in RNA homeostasis. Single-cell transcriptomic studies have revealed RNA abundance heterogeneity across brain cell types but the more complex changes in RNA processing such as alternative splicing, isoform usage, transcription start and polyadenylation site selection remain uncharacterized. Here, we combine single-cell analysis with long-read nanopore sequencing to capture full-length RNA isoforms and uncover temporal changes in RNA transcription, processing, and alternative splicing in the aging mouse cortex and hippocampus. By profiling transcriptomes from young adult to very old mice, we identify non-linear, cell-type-specific isoform expression changes and isoform usage shifts, primarily driven by transcription start site selection. These aging-associated isoform changes alter the coding potential and poly(A) site position of genes. Our data also reveal a high proportion of senescence in immune cells, far exceeding that of other cell types. We also identify isoform markers that, when applied to a machine learning model, distinguish senescent from normal immune cells. This study provides a full-length RNA isoform-based atlas of the aging mouse brain, offering insights into RNA metabolism remodeling across brain cell types throughout the lifespan.

genomics↗

bioRxiv2025

3D organoids containing endothelial and neural cells generation by serial inductions of differentiation on human iPSC-derived embryoid bodies

3D brain organoids have been widely used as a tool to study human brain development and disorders. Although endothelial cells play important roles in the brain development and pathogenesis in neurological disorders, most 3D brain organoids lack inherent endothelial cells and need either the addition of endothelial cells or to be transplanted to animals to reconstitute such vascular structures, likely missing the developmental interactions of endothelial cells and other cells in the human brain. In order to reconstitute a 3D organoid mimicking the in vivo neural and endothelial cells development, we cultured iPSC-derived embryoid bodies in sequentially applied endothelial and neuronal induction media along with Matrigel embedding. The resulting 3D organoid consists of both neural cells and endothelial cells with vascular like structures, as determined by immunostaining. With scRNA-Seq analysis, the brain organoid was confirmed to contain neural cell types similar with human brains, including a variety of excitatory and inhibitory neurons and glia. Furthermore, when compared with traditional cerebral organoids without endothelial cells using RNA-Seq analysis, the endothelial containing neural organoids (EC-neural organoids) showed difference in gene profiles and favored angiogenesis and vasculogenesis. Of the differentially expressed genes, KRBA2 expression was found higher in neural cells and its inhibition by siRNA treatment resulted in decreased transcriptions of a variety of genes such as neuronal differentiation specific genes but not in genes specific to pluripotent stem cells such as OCT4. The EC-neural organoids also express receptors to SARS-CoV-2 similar to human brains. This 3D model provides a useful tool to study the interactions of endothelial cells and neural cells in the brain development and neural infectious disorders where endothelial cells and pericytes play pivotal roles.

neuroscience↗

bioRxiv2025

Large-scale HLA immunopeptidome and interactome profiling in microglia

Microglia are immune cells of the brain and act as major antigen presenting cells. Antigen presentation involves the human leukocyte antigen (HLA) complex, which is implicated in genetic risk of multiple neurodegenerative diseases. How HLA affects the function of microglia in the context of neurodegenerative disease remains unclear. Here, we investigated the HLA epitopes and their protein interactome in human induced pluripotent stem cell (iPSC)-derived microglia-like cells (iMGLs) using systematic mass spectrometry (MS)-based immunopeptidomics, whole-cell proteomics, affinity purification, and prediction algorithms. Our results revealed the presence of almost 7,000 peptides presented by HLA class I and II within microglia. We further showed that the immunopeptidome landscapes of iPSCs, iMGLs and interferon-gamma (IFN{gamma}) stimulated iMGLs are all readily distinguishable. Furthermore, HLA interacts with different groups of proteins in iPSCs compared to iMGLs which involve proteins in immune response. Importantly, we detected 25 HLA epitopes derived from 15 genes associated with Alzheimers and related dementias such as Tau, PLD3 (Alzheimers disease), TDP-43, FUS (Frontotemporal dementia), and PARK7, VPS35 (Lewy Body dementia). We predicted 31 mutant epitopes derived from these ADRD genes that could be presented with strong interaction to HLA molecules. Along with these epitopes, we observed an enrichment of immune-related interaction proteins in microglia treated with IFN{gamma}. These results provide evidence that aggregated and mutated proteins can interact with HLA alleles and be presented on the cell surface by microglia cells. This study sheds light on the antigen presenting and adaptive immunity mechanism within the central nervous system and its possible effects on neurodegenerative diseases.

immunology↗

bioRxiv2025

Temporal dynamics of proteome and phosphorproteome during neuronal differentiation in the reference KOLF2.1J iPSC line

Induced pluripotent stem cell (iPSC)-derived neurons have emerged as a powerful model to investigate both neuronal development and neurodegenerative diseases. Although transcriptomics and imaging have been applied to characterize neuronal development signatures, comprehensive datasets of protein and post-translational modifications (PTMs) are not readily available. Here, we applied quantitative proteomics and phosphoproteomics to profile the differentiation of the KOLF2.1J iPSC line, the first reference line of the iPSC Neurodegenerative Disease Initiative (iNDI) project. We developed an automated workflow enabling high-coverage enrichment of proteins and phosphoproteins. Our results revealed molecular signatures across proteomic and phosphoproteomic landscapes during differentiation of iPSC-derived neurons. Proteomic data highlighted distinct changes in mitochondrial pathways throughout the course of differentiation, while phosphoproteomics revealed specific regulatory dynamics in GTPase signaling pathways and microtubule proteins. Additionally, phosphosite dynamics exhibited discordant trends compared to protein expression, particularly in processes related to axon functions and RNA transport. Furthermore, we mapped the kinase dynamic changes that are critical for neuronal development and maturation. We developed an interactive Web app (https://niacard.shinyapps.io/Phosphoproteome/) to visualize temporal landscape dynamics of protein and phosphosite expression. By establishing baselines of proteomic and phosphoproteomic profiles for neuronal differentiation, this dataset offers a valuable resource for future research into neuronal development and neurodegenerative diseases using this reference iPSC line. HighlightsO_LITemporal dynamics of proteome and phosphoproteome profiles in KOLF2.1J iPSC derived neurons. C_LIO_LIPhosphoproteomics highlights GTPase signaling and microtubule regulation in neuronal differentiation. C_LIO_LIKinome mapping reveals a shift in kinase activity patterns from early to late differentiation. C_LIO_LIShinyapp for visualizing the trajectory of protein and phosphosite expression during neuronal differentiation. C_LI

neuroscience↗

bioRxiv2025

Proteomic Analysis of Endemic Viral Infections in Neuronsoffers Insights into Neurodegenerative Diseases

Endemic viral infections with low pathogenicity are often overlooked due to their mild symptoms, yet they can exert long-term effects on cellular function and contribute to disease pathogenesis. While viral infections have been implicated in neurodegenerative disorders, their impact on the neuronal proteome remains poorly understood. Here, we differentiated human induced pluripotent stem cells (KOLF2.1J) into mature neurons to investigate virus-induced proteomic changes following infection with five neurotropic endemic human viruses: Herpes simplex virus 1 (HSV-1), Human coronavirus 229E (HCoV-229E), Epstein-Barr virus (EBV), Varicella-Zoster virus (VZV), and Influenza A virus (H1N1). Given that these viruses can infect adults and have the potential to cross the placental barrier, their molecular impact on neurons may be relevant across the lifespan. Using mass spectrometry-based proteomics with a customized library for simultaneous detection of human and viral proteins, we confirmed successful infections and identified virus-specific proteomic signatures. Notably, virus-induced protein expression changes converged on key neuronal pathways, including those associated with neurodegeneration. Gene co-expression network analysis identified protein modules correlated with viral proteins. Pathway enrichment analysis of these modules revealed associations with the nervous system, including pathways linked to Alzheimers and Parkinsons disease. Remarkably, several viral-induced proteomic alterations overlapped with changes observed in postmortem Alzheimers patient brains, suggesting a mechanistic connection between viral exposure and neurodegenerative disease progression. These findings provide molecular insights into how common viral infections perturb neuronal homeostasis and may contribute to neurodegenerative pathology, highlighting the need to consider endemic viruses as potential environmental risk factors in neurological disorders.

neuroscience↗

bioRxiv2024

Long-read sequencing of hundreds of diverse brains provides insight into the impact of structural variation on gene expression and DNA methylation

Structural variants (SVs) drive gene expression in the human brain and are causative of many neurological conditions. However, most existing genetic studies have been based on short-read sequencing methods, which capture fewer than half of the SVs present in any one individual. Long-read sequencing (LRS) enhances our ability to detect disease-associated and functionally relevant structural variants; however, its application in large-scale genomic studies has been limited by challenges in sample preparation and high costs. Here, we leverage a new scalable wet-lab protocol and computational pipeline for whole-genome Oxford Nanopore Technologies sequencing and apply it to neurologically normal control samples from the North American Brain Expression Consortium (NABEC) (European ancestry) and Human Brain Collection Core (HBCC) (African or African admixed ancestry) cohorts. Through this work, we present a publicly available long-read resource from 351 human brain samples (median N50: 27 Kbp and at an average depth of ~40x genome coverage). We discover approximately 234,905 SVs and produce locally phased assemblies that cover 95% of all protein-coding genes in GRCh38. To resolve cis-regulatory effects, we develop ASM-LR, a method for allele-specific methylation analysis from long-read data, revealing both strong and subtle regulatory effects, including numerous novel methylation QTLs masked in unphased models. Our results highlight the power of haplotype-resolved methylation to uncover regulatory mechanisms and establish a foundational resource for exploring how genetic variation shapes gene expression and epigenetic architecture across diverse ancestries.

genomics↗

bioRxiv2024

Characterization of DNA methylation in PBMCs and donor-matched iPSCs shows methylation is reset during stem cell reprogramming

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/627515v2_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@18cda69org.highwire.dtl.DTLVardef@574c4corg.highwire.dtl.DTLVardef@1522644org.highwire.dtl.DTLVardef@4e799c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG HighlightsO_LIGeneration of a population-level set of iPSC lines from healthy individuals across the lifespan C_LIO_LIAging-related features were reset based on epigenetic markers of cytosine methylation and telomere length C_LIO_LIBy comparing methQTLs in iPSC vs. their donor PBMCs, we find that detection of methQTLs reflect biological functions of different cell types C_LI DNA methylation is an important epigenetic mechanism that helps define and maintain cellular functions. It is influenced by many factors, including environmental exposures, genotype, cell type, sex, and aging. Since age is the primary risk factor for developing neurodegenerative diseases, it is important to determine if aging-related DNA methylation is retained when cells are reprogrammed to an induced Pluripotent Stem Cell (iPSC) state. Here, we selected peripheral blood mononuclear cells (PBMCs; n = 99) from a cohort of diverse and healthy individuals enrolled in the Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing (GESTALT) study to convert to iPSCs. After reprogramming we evaluated the resulting iPSCs for DNA methylation signatures to determine if they reflect the confounding factors of age and environmental factors. We used genome-wide DNA methylation arrays in both cell types to show that the epigenetic clock is largely reset to an early methylation age after conversion of PBMCs to iPSCs. We further examined the epigenetic age of each cell type using an Epigenome-wide Association Study (EWAS). Finally, we identified a set of methylation Quantitative Trait Loci (methQTL) in each cell type. Our results show that age-related DNA methylation is largely reset in iPSCs, and each cell type has a unique set of methylation sites that are genetically influenced.

molecular biology↗

bioRxiv2024

14-3-3 binding maintains the Parkinson's associated kinase LRRK2 in an inactive state

Leucine-rich repeat kinase 2 (LRRK2) is a central player in cellular signaling and a significant contributor to Parkinsons disease (PD) pathogenesis. 14-3-3 proteins are essential regulators of LRRK2, modulating its activity. Here, we present the cryo- electron microscopy structure of the LRRK2:14-3-32 autoinhibitory complex, showing that a 14-3-3 dimer stabilizes an autoinhibited LRRK2 monomer by binding to key phosphorylation sites and the COR-A and COR-B subdomains within the Roc-COR GTPase domain of LRRK2. This interaction locks LRRK2 in an inactive conformation, restricting LRR domain mobility and preventing dimerization and oligomer formation. Our mutagenesis studies reveal that PD-associated mutations at the COR:14-3-3 interface and within the GTPase domain reduce 14-3-3 binding, diminishing its inhibitory effect on LRRK2. These findings provide a structural basis for understanding how LRRK2 likely remains dormant within cells, illuminate aspects of critical PD biomarkers, and suggest therapeutic strategies to enhance LRRK2-14-3-3 interactions to treat PD and related disorders.

biochemistry↗

bioRxiv2024

Decreased SNCA Expression in Whole-Blood RNA Analysis of Parkinson's Disease Adjusting for Lymphocytes

Blood-based RNA transcriptomics offers a promising avenue for identifying biomarkers of Parkinsons Disease (PD) progression and may provide mechanistic insights into the systemic biological processes underlying its pathogenesis beyond the well-defined neurodegenerative features. Previous studies have indicated an age-dependent increase in neutrophil-enriched gene expression, alongside a reduction in lymphocyte counts, in individuals with PD. These immune cell changes can obscure disease-relevant transcriptomic signals. In this study, we performed differential expression (DE) analysis of whole-blood RNA sequencing data from PD cohorts, incorporating a correction for immune cell-enriched gene expression, particularly neutrophil-related pathways, to improve the resolution of PD-associated molecular changes. Using 1,254 Parkinsons Progression Markers Initiative (PPMI) samples with complete blood count (CBC) data, we developed a predictive model to estimate neutrophil percentages in a 6,987 PPMI and Parkinsons Disease Biomarkers Program (PDBP) samples. We mitigated the confounding effects of immune cell-enriched gene expression by integrating predicted neutrophil percentages as a covariate in DE analysis. This approach revealed a consistent and significant downregulation of SNCA across all PD cohorts, a finding previously obscured by immune cell signatures. Lowered SNCA expression was found in individuals with known predisposition genes (e.g., SNCA, GBA, LRRK2) and in non-genetic PD cohorts lacking known pathogenic mutations, suggesting it may represent a key transcriptomic hallmark of the disease.

bioinformatics↗

bioRxiv2024

Single-cell spatial transcriptomics reveals molecular patterns of selective neuronal vulnerability to α-synuclein pathology in a transgenic mouse model of Lewy body disease

In Parkinsons disease and dementia with Lewy bodies, aggregated and phosphorylated -synuclein pathology appears in select neurons throughout cortical and subcortical regions, but little is currently known about why certain populations are selectively vulnerable. Here, using imaging spatial transcriptomics (IST) coupled with downstream immunofluorescence for -synuclein phosphorylated at Ser129 (pSyn) in the same tissue sections, we identified neuronal subtypes in the cortex and hippocampus of transgenic human -synuclein-overexpressing mice that preferentially developed pSyn pathology. Additionally, we investigated the transcriptional underpinnings of this vulnerability, pointing to expression of Plk2, which phosphorylates -synuclein at Ser129, and human SNCA (hSNCA), as key to pSyn pathology development. Finally, we performed differential expression analysis, revealing gene expression changes broadly downstream of hSNCA overexpression, as well as pSyn-dependent alterations in mitochondrial and endolysosomal genes. Overall, this study yields new insights into the formation of -synuclein pathology and its downstream effects in a synucleinopathy mouse model.

neuroscience↗

bioRxiv2024

Opposing actions of JIP4 and RILPL1 provide antagonistic motor force to dynamically regulate membrane reformation during lysosomal tubulation/sorting driven by LRRK2

Lysosomes are dynamic cellular structures that adaptively remodel their membrane in response to stimuli, including membrane damage. We previously uncovered a process we term LYTL (LYsosomal Tubulation/sorting driven by Leucine-Rich Repeat Kinase 2 [LRRK2]), wherein damaged lysosomes generate tubules sorted into mobile vesicles. LYTL is orchestrated by the Parkinsons disease-associated kinase LRRK2 that recruits the motor adaptor protein and RHD family member JIP4 to lysosomes via phosphorylated RAB proteins. To identify new players involved in LYTL, we performed unbiased proteomics on isolated lysosomes after LRRK2 kinase inhibition. Our results demonstrate that there is recruitment of RILPL1 to ruptured lysosomes via LRRK2 activity to promote phosphorylation of RAB proteins at the lysosomal surface. RILPL1, which is also a member of the RHD family, enhances the clustering of LRRK2-positive lysosomes in the perinuclear area and causes retraction of LYTL tubules, in contrast to JIP4 which promotes LYTL tubule extension. Mechanistically, RILPL1 binds to p150Glued, a dynactin subunit, facilitating the transport of lysosomes and tubules to the minus end of microtubules. Further characterization of the tubulation process revealed that LYTL tubules move along tyrosinated microtubules, with tubulin tyrosination proving essential for tubule elongation. In summary, our findings emphasize the dynamic regulation of LYTL tubules by two distinct RHD proteins and pRAB effectors, serving as opposing motor adaptor proteins: JIP4, promoting tubulation via kinesin, and RILPL1, facilitating tubule retraction through dynein/dynactin. We infer that the two opposing processes generate a metastable lysosomal membrane deformation that facilitates dynamic tubulation events.

cell biology↗

bioRxiv2024

Large structural variants in KOLF2.1J are unlikely to compromise neurological disease modelling

Gracia-Diaz and colleagues analysed high-density DNA microarray and whole genome sequencing (WGS) data from the KOLF2.1J reference human induced pluripotent stem cell (hiPSC) line1, and report the presence of five high-confidence heterozygous copy number variants (CNVs) at least 100kbp in length2. Since three of these CNVs span coding genes, some of which have been associated with neurodevelopmental disease, the authors raise the concern that these CNVs may compromise the utility of KOLF2.1J for neurological disease modelling. We appreciate their thorough analysis and thoughtful interpretation, and agree that potential users of this line should be made aware of all cases where KOLF2.1J differs from the reference genome. However, we believe that the benefits from the widespread use of KOLF2.1J outweigh the potential risks that might arise from the identified CNVs.

cell biology↗

bioRxiv2023

Differential LRRK2 signalling and gene expression in WT-LRRK2 and G2019S-LRRK2 mouse microglia treated with zymosan and MLi2.

IntroductionMutations in the Leucine Rich Repeat Kinase 2 (LRRK2) gene cause autosomal dominant Parkinsons disease (PD) with the most common causative mutation being the LRRK2 p.G2019S within the kinase domain. LRRK2 protein is highly expressed in the human brain and also in the periphery, and high expression of dominant PD genes in immune cells suggest involvement of microglia and macrophages in inflammation related to PD. LRRK2 is known to respond to extracellular signalling including TLR4 resulting in alterations in gene expression, with the response to TLR2 signalling through zymosan being less known. MethodsHere, we investigated the effects of zymosan, a TLR2 agonist and the potent and specific LRRK2 kinase inhibitor MLi-2 on gene expression in microglia from LRRK2-WT and LRRK2 p.G2019S knock-in mice by RNA-Sequencing analysis. ResultsWe observed both overlapping and distinct zymosan and MLi-2 mediated gene expression profiles in microglia. At least two candidate Genome-Wide Association (GWAS) hits for PD, CathepsinB (Ctsb) and Glycoprotein-nmb (Gpnmb), were notably downregulated by zymosan treatment. Genes involved in inflammatory response and nervous system development were up and downregulated respectively with zymosan treatment while MLi-2 treatment particularly exhibited upregulated genes for ion transmembrane transport regulation. Furthermore, we observed the top twenty most significantly differentially expressed genes in LRRK2 p.G2019S microglia show enriched biological processes in iron transport and response to oxidative stress. DiscussionOverall, these results suggest that microglial LRRK2 may contribute to PD pathogenesis through altered inflammatory pathways. Our findings should encourage future investigations of these putative avenues in the context of PD pathogenesis.

neuroscience↗

bioRxiv2023

Divergent patterns of healthy aging across human brain regions at single-cell resolution reveal links to neurodegenerative disease

Given that age is a significant risk factor for multiple neurodegenerative diseases, investigating normal brain aging may help identify molecular events that may contribute to increased disease risk over time. Single-nucleus RNA sequencing (snRNA-seq) enables analysis of gene expression changes within specific cell-types, potentially offering insights into the molecular mechanisms underlying aging. However, most brain snRNA-Seq datasets used age-matched controls from studies focused on pathological processes and have largely been limited to cortical regions. Therefore, there is a need to investigate the non-pathological aging process in brain regions that are vulnerable to age-related diseases. Here, we report a snRNA-seq study of 6 young (20-30 years) and 7 aged (60-85 years) encompassing four different brain regions: the entorhinal cortex, middle temporal gyrus, subventricular zone, and putamen. We captured over 150,000 nuclei that represented 10 broad cell-types. While we did not find statistically significant differences in cell-type proportions with age, region- and cell-type-specific differential expression analyses identified over 8,000 age-associated genes. Notably, within a given cell-type, most of these associations were region-specific. Functional enrichment analyses of the gene sets for each cell-type-region combination revealed diverse biological processes, including multiple hallmarks of aging, such as proteostasis, interactions with cytokines, vesicular trafficking, metabolism, inflammation, and metal ion homeostasis. Overall, our findings suggest that unique cell-types exhibit distinct transcriptional aging profiles both at the cell-type level and across different brain regions.

neuroscience↗

bioRxiv2022

Application of Aligned-UMAP to longitudinal biomedical studies

Longitudinal multi-dimensional biological datasets are ubiquitous and highly abundant. These datasets are essential to understanding disease progression, identifying subtypes, and drug discovery. Discovering meaningful patterns or disease pathophysiologies in these datasets is challenging due to their high dimensionality, making it difficult to visualize hidden patterns. Several methods have been developed for dimensionality reduction, but they are limited to cross-sectional datasets. Recently proposed Aligned-UMAP, an extension of the UMAP algorithm, can visualize high-dimensional longitudinal datasets. In this work, we applied Aligned-UMAP on a broad spectrum of clinical, imaging, proteomics, and single-cell datasets. Aligned-UMAP reveals time-dependent hidden patterns when color-coded with the metadata. We found that the algorithm parameters also play a crucial role and must be tuned carefully to utilize the algorithms potential fully. Altogether, based on its ease of use and our evaluation of its performance on different modalities, we anticipate that Aligned-UMAP will be a valuable tool for the biomedical community. We also believe our benchmarking study becomes more important as more and more high-dimensional longitudinal data in biomedical research becomes available. Highlights- explored the utility of Aligned-UMAP in longitudinal biomedical datasets - offer insights on optimal uses for the technique - provide recommendations for best practices In BriefHigh-dimensional longitudinal data is prevalent yet understudied in biological literature. High-dimensional data analysis starts with projecting the data to low dimensions to visualize and understand the underlying data structure. Though few methods are available for visualizing high dimensional longitudinal data, they are not studied extensively in real-world biological datasets. A recently developed nonlinear dimensionality reduction technique, Aligned-UMAP, analyzes sequential data. Here, we give an overview of applications of Aligned-UMAP on various biomedical datasets. We further provide recommendations for best practices and offer insights on optimal uses for the technique.

bioinformatics↗

bioRxiv2022

Genome-wide analysis of Structural Variants in Parkinson's Disease using Short-Read Sequencing data

Parkinsons disease is a complex neurodegenerative disorder, affecting approximately one million individuals in the USA alone. A significant proportion of risk for Parkinsons disease is driven by genetics. Despite this, the majority of the common genetic variation that contributes to disease risk is unknown, in-part because previous genetic studies have focussed solely on the contribution of single nucleotide variants. Structural variants represent a significant source of genetic variation in the human genome. However, because assay of this variability is challenging, structural variants have not been cataloged on a genome-wide scale, and their contribution to the risk of Parkinsons disease remains unknown. In this study, we 1) leveraged the GATK-SV pipeline to detect and genotype structural variants in 7,772 short-read sequencing data and 2) generated a subset of matched whole-genome Oxford Nanopore Technologies long-read sequencing data from the PPMI cohort to allow for comprehensive structural variant confirmation. We detected, genotyped, and tested 3,154 "high-confidence" common structural variant loci, representing over 412 million nucleotides of non-reference genetic variation. Using the long-read sequencing data, we validated three structural variants that may drive the association signals at known Parkinsons disease risk loci, including a 2kb intronic deletion within the gene LRRN4. Further, we confirm that the majority of structural variants in the human genome cannot be detected using short-read sequencing alone, encompassing on average around 4 million nucleotides of inaccessible sequence per genome. Therefore, although these data provide the most comprehensive survey of the contribution of structural variants to the genetic risk of Parkinsons disease to date, this study highlights the need for large-scale long-read datasets to fully elucidate the role of structural variants in Parkinsons disease.

genetics↗