Biology subjects

Calini, D.

Publications and source records attributed to Calini, D..

6 recordsLinked to original sources

bioRxiv2024

Single-nucleus and spatial transcriptomic profiling of human temporal cortex and white matter reveals novel associations with AD pathology

Alzheimers disease (AD) is a neurodegenerative disorder with complex pathological manifestations and is the leading cause of cognitive decline and dementia in elderly individuals. A major goal in AD research is to identify new therapeutic pathways by studying the molecular and cellular changes in the disease, either downstream or upstream of the pathological hallmarks. In this study, we present a comprehensive investigation of cellular heterogeneity from the temporal cortex region of 40 individuals, comprising healthy donors and individuals with differing tau and amyloid burden. Using single-nucleus transcriptome analysis of 430,271 nuclei from both gray and white matter of these individuals, we identified cell type-specific subclusters in both neuronal and glial cell types with varying degrees of association with AD pathology. In particular, these associations are present in layer specific glutamatergic (excitatory) neuronal types, along with GABAergic (inhibitory) neurons and glial subtypes. These associations were observed in early as well as late pathological progression. We extended this analysis by performing multiplexed in situ hybridization using the CARTANA platform, capturing 155 genes in 13 individuals with varying levels of tau pathology. By modeling the spatial distribution of these genes and their associations with the pathology, we not only replicated key findings from our snRNA data analysis, but also identified a set of cell type-specific genes that show selective enrichment or depletion near pathological inclusions. Together, our findings allow us to prioritize specific cell types and pathways for targeted interventions at various stages of pathological progression in AD.

neuroscience↗

bioRxiv2023

Disease-specific selective vulnerability and neuroimmune pathways in dementia revealed by single cellgenomics

Summary/AbstractThe development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNAseq and ATACseq in Alzheimer disease (AD), Frontotemporal degeneration (FTD), and Progressive Supranuclear Palsy (PSP), analyzing 40 participants, yielding over 1.4M cells from three brain regions ranging in vulnerability and pathological burden. We identify 35 shared disease-associated cell types and 14 that are disease-specific, replicating those previously identified in AD. Disease-specific cell states represent molecular features of disease-specific glial-immune mechanisms and neuronal vulnerability in each disorder, layer 4/5 intra-telencephalic neurons in AD, layer 2/3 intra-telencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We infer intrinsic disease-associated gene regulatory networks, which we empirically validate by chromatin footprinting. We find that causal genetic risk acts in specific neuronal and glial cells that differ across disorders, primarily non-neuronal cells in AD and specific neuronal subtypes in FTD and PSP. These data illustrate the heterogeneous spectrum of glial and neuronal composition and gene expression alterations in different dementias and identify new therapeutic targets by revealing shared and disease-specific cell states.

neuroscience↗

bioRxiv2022

Single nuclei RNAseq stratifies multiple sclerosis patients into three distinct white matter glia responses

The lack of understanding of the cellular and molecular basis of clinical and genetic heterogeneity in progressive multiple sclerosis (MS) has hindered the search for new effective therapies. Here, to address this gap, we analysed 632,000 single nuclei RNAseq profiles of 156 brain tissue samples, comprising white matter (WM) lesions, normal appearing WM, grey matter (GM) lesions and normal appearing GM from 54 MS patients and 26 controls. We observed the expected changes in overall neuronal and glial numbers previously described within the classical lesion subtypes. We found highly cell type-specific gene expression changes in MS tissue, with distinct differences between GM and WM areas, confirming different pathologies. However, surprisingly, we did not observe distinct gene expression signatures for the classical different WM lesion types, rather a continuum of change. This indicates that classical lesion characterization better reflects changes in cell abundance than changes in cell type gene expression, and indicates a global disease effect. Furthermore, the major biological determinants of variability in gene expression in MS WM samples relate to individual patient effects, rather than to lesion types or other metadata. We identify four subgroups of MS patients with distinct WM glial gene expression signatures and patterns of oligodendrocyte stress and/or maturation, suggestive of engagement of different pathological processes, with an additional more variable regenerative astrocyte signature. The discovery of these patterns, which were also found in an independent MS patient cohort, provides a framework to use molecular biomarkers to stratify patients for optimal therapeutic approaches for progressive MS, significantly advances our mechanistic understanding of progressive MS, and highlights the need for precision-medicine approaches to address heterogeneity among MS patients.

neuroscience↗

bioRxiv2021

A structured evaluation of cryopreservation in generating single cell transcriptomes from cerebrospinal fluid

ImportanceA robust cerebrospinal fluid (CSF) cell cryopreservation protocol using high resolution single-cell (sc) transcriptomic data would enable the deployment of this important modality in multi-center translational research studies and clinical trials in which many sites do not have the expertise or resources to produce data from fresh samples. It would also serve to reduce technical variability in larger projects. ObjectiveTo test a reliable cryopreservation protocol adapted for CSF cells, facilitating the characterization of these rare, fragile cells in moderate to large scale studies. DesignDiagnostic lumbar punctures were performed on twenty-one patients at two independent sites. Excess CSF was collected and cells were isolated. Each cell sample was split into two fractions for single cell analysis using one of two possible chemistries: 3 sc-RNA-Sequencing or 5sc-RNA-Sequencing. One cell fraction was processed fresh while the second sample was cryopreserved and profiled at a later time after thawing. SettingThe research protocol was deployed at two academic medical centers taking care of multiple sclerosis and other neurological conditions. Participants21 subjects (age 24 - 72) were recruited from individuals undergoing a diagnostic lumbar puncture for suspected neuroinflammatory disease or another neurologic illness; they donated excess CSF. FindingsOur comparison of fresh and cryopreserved data from the same individuals demonstrates highly efficient recovery of all known CSF cell types. The proportion of all cell types was similar between the fresh and the cryopreserved cells processed, and RNA expression was not significantly different. Results were comparable at both performance sites, and with different single cell sequencing chemistries. Cryopreservation also did not affect recovery of T and B cell clonotype diversity. Conclusion and relevanceOur cryopreservation protocol for CSF-cells provides an important alternative to fresh processing of fragile CSF cells: cryopreservation enables the involvement of sites with limited capacity for experimental manipulation and reduces technical variation by enabling batch processing and pooling of samples. Key pointsO_ST_ABSQuestionC_ST_ABSHow efficient is CSF cryopreservation for single-cell transcriptome analysis and can it be implemented in large multi-center translational and clinical trial settings? FindingsWe compared single-cell transcriptomes of paired fresh and cryopreserved CSF from 21 patients at two independent sites. We validate the efficacy of a simple and cost effective CSF cryopreservation method that preserves the composition and the transcriptomes of CSF cells stored for weeks-months. The protocol is deployed in a large multicenter Phase 4 MS clinical trial. MeaningA validated CSF cryopreservation method that would significantly advance basic science and biomarker research in neurological disorders by implementing single-cell transcriptome analyses in multi-center research and clinical trials.

genetics↗

bioRxiv2020

CellMixS: quantifying and visualizing batch effects in single cell RNA-seq data

A key challenge in single cell RNA-sequencing (scRNA-seq) data analysis are dataset- and batch-specific differences that can obscure the biological signal of interest. While there are various tools and methods to perform data integration and correct for batch effects, their performance can vary between datasets and according to the nature of the bias. Therefore, it is important to understand how batch effects manifest in order to adjust for them in a reliable way. Here, we systematically explore batch effects in a variety of scRNA-seq datasets according to magnitude, cell type specificity and complexity. We developed a cell-specific mixing score (cms) that quantifies how well cells from multiple batches are mixed. By considering distance distributions (in a lower dimensional space), the score is able to detect local batch bias and differentiate between unbalanced batches (i.e., when one cell type is more abundant in a batch) and systematic differences between cells of the same cell type. We implemented cms and related metrics to detect batch effects or measure structure preservation in the CellMixS R/Bioconductor package. We systematically compare different metrics that have been proposed to quantify batch effects or bias in scRNA-seq data using real datasets with known batch effects and synthetic data that mimic various real data scenarios. While these metrics target the same question and are used interchangeably, we find differences in inter- and intra-dataset scalability, sensitivity and in a metrics ability to handle batch effects with differentially abundant cell types. We find that cell-specific metrics outperform cell type-specific and global metrics and recommend them for both method benchmarks and batch exploration.

bioinformatics↗

bioRxiv2019

On the discovery of population-specific state transitions from multi-sample multi-condition single-cell RNA sequencing data

Single-cell RNA sequencing (scRNA-seq) has quickly become an empowering technology to profile the transcriptomes of individual cells on a large scale. Many early analyses of differential expression have aimed at identifying differences between subpopulations, and thus are focused on finding subpopulation markers either in a single sample or across multiple samples. More generally, such methods can compare expression levels in multiple sets of cells, thus leading to cross-condition analyses. However, given the emergence of replicated multi-condition scRNA-seq datasets, an area of increasing focus is making sample-level inferences, termed here as differential state analysis. For example, one could investigate the condition-specific responses of cell subpopulations measured from patients from each condition; however, it is not clear which statistical framework best handles this situation. In this work, we surveyed the methods available to perform cross-condition differential state analyses, including cell-level mixed models and methods based on aggregated "pseudobulk" data. We developed a flexible simulation platform that mimics both single and multi-sample scRNA-seq data and provide robust tools for multi-condition analysis within the muscat R package.

bioinformatics↗