The genetic basis of most traits is highly polygenic and dominated by non-coding alleles. It is widely assumed that such alleles exert small regulatory effects on the expression of cis-linked genes. However, despite the availability of gene expression and epigenomic datasets, few variant-to-gene links have emerged. It is unclear whether these sparse results are due to limitations in available data and methods, or to deficiencies in the underlying assumed model. To better distinguish between these possibilities, we identified 220 gene-trait pairs in which protein-coding variants influence a complex trait or its Mendelian cognate. Despite the presence of expression quantitative trait loci near most GWAS associations, by applying a gene-based approach we found limited evidence that the baseline expression of trait-related genes explains GWAS associations, whether using colocalization methods (8% of genes implicated), transcription-wide association (2% of genes implicated), or a combination of regulatory annotations and distance (4% of genes implicated). These results contradict the hypothesis that most complex trait-associated variants coincide with homeostatic expression QTLs, suggesting that better models are needed. The field must confront this deficit and pursue this 'missing regulation.' 

The missing link between genetic association and regulatory function

The lack of understanding as to the cellular and molecular basis of clinical and genetic heterogeneity in progressive multiple sclerosis (MS) has hindered the search for new effective therapies and biomarkers. Here, to address this gap, we analysed 740,000 single nuclei RNAseq profiles of 165 samples of white matter (WM) lesions, normal appearing WM, grey matter (GM) lesions and normal appearing GM from 55 MS patients and 28 controls. We find that gene expression changes in response to MS are highly cell-type specific in WM and GM lesions but are largely shared within an individual cell-type across lesions, following a continuum rather than discrete lesion-specific molecular programs. The major biological determinants of variability in gene expression in MS samples relate to individual patient effects, rather than to lesion types or other metadata. Using multi-omics factor analysis (MOFA+), we identify three subgroups of MS patients with distinct oligodendrocyte composition and WM glial gene expression signatures, suggestive of engagement of different pathological/regenerative processes. The discovery of these three patterns significantly advances our mechanistic understanding of progressive MS, provides a framework to use molecular biomarkers to stratify patients for best therapeutic approaches for progressive MS, and highlights the need for precision-medicine approaches to address heterogeneity among MS patients.

/pdf/single-nuclei-rnaseq-stratifies-multiple-sclerosis-patients-rla4q6mv.pdf

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

The cerebrospinal fluid (CSF) features a unique immune cell composition and is in constant contact with the brain borders, thus permitting insights into the brain to diagnose and monitor diseases. Recently, the meninges, which are filled with CSF, were identified as a neuroimmunological interface, highlighting the potential of exploring central nervous system (CNS) immunity by studying CNS border compartments. Here, we summarize how single-cell transcriptomics of such border compartments advance our understanding of neurological diseases, the challenges that remain, and what opportunities novel multi-omic methods offer. Single-cell transcriptomics studies have detected cytotoxic CD4+ T cells and clonally expanded T and B cells in the CSF in the autoimmune disease multiple sclerosis; clonally expanded pathogenic CD8+ T cells were found in the CSF and in the brain adjacent to β-amyloid plaques of dementia patients; in patients with brain metastases, CD8+ T cell clonotypes were shared between the brain parenchyma and the CSF and persisted after therapy. We also outline how novel multi-omic approaches permit the simultaneous measurements of gene expression, chromatin accessibility, and protein in the same cells, which remain to be explored in the CSF. This calls for multicenter initiatives to create single-cell atlases, posing challenges in integrating patients and modalities across centers. While high-dimensional analyses of CSF cells are challenging, they hold potential for personalized medicine by better resolving heterogeneous diseases and stratifying patients. 

/pdf/high-dimensional-investigation-of-the-cerebrospinal-fluid-to-2cco75m9.pdf

High-dimensional investigation of the cerebrospinal fluid to explore and monitor CNS immune responses

There is an urgent and unmet need to advance our ability to translate genetic studies of psychiatric disorders into clinically actionable information, which could transform diagnostics and even one day lead to novel (and potentially presymptomatic) therapeutic interventions. Today, although there are hundreds of significant loci associated with psychiatric disorders, resolving the target gene(s) and pathway(s) impacted by each is a major challenge. Integrating human induced pluripotent stem cell-based approaches with CRISPR-mediated genomic engineering strategies makes it possible to study the impact of patient-specific variants within the cell types of the brain. As the scale and scope of functional genomic studies expands, so does our ability to resolve the complex interplay of the many risk variants linked to psychiatric disorders. In this review, the author discusses some of the technological advances that make it possible to ask exciting questions that are fundamental to our understanding of psychiatric disorders. How do distinct risk variants converge and interact with each other (and the environment) across the diverse cell types that comprise the human brain? Can clinical trajectories and/or therapeutic response be predicted from genetic profiles? Just as critically, by spreading the message that genetic risk for psychiatric disorders is biological and fundamentally no different than for other human conditions, we can dispel the stigma associated with mental illness.

Using Stem Cell Models to Explore the Genetics Underlying Psychiatric Disorders: Linking Risk Variants, Genes, and Biology in Brain Disease.

Genetic liability associated with schizophrenia most frequently arises from common genetic variation that confers small individual effects and contributes to phenotypes only when considered in aggregate. These risk variants are typically non-coding and act by genetically regulating the expression of one or more gene targets (eGenes), but the mechanisms by which unlinked eGenes interact to contribute to complex genetic risk remains unclear. Here we apply a pooled CRISPR approach to evaluate in parallel ten schizophrenia eGenes in human glutamatergic neurons. Querying the shared neuronal impacts across eGenes reveals shared downstream transcriptomic impacts (“convergence”) concentrated on pathways of brain development and synaptic signaling. The composition and strength of convergent networks is influenced by both the similarity of eGene functional annotation and the strength of eGene co-expression in human postmortem brain tissue. Convergent networks resolve distinct patterns of eGene up-regulation associated with individual-level risk in the post-mortem dorsolateral prefrontal cortex that are broadly enriched for neuropsychiatric disorder risk genes and may represent molecular subtypes of schizophrenia. Convergent gene targets are druggable as novel points of therapeutic intervention. Overall, convergence suggests a model to explain how non-additive interactions arise between risk genes and may explain cross-disorder pleiotropy of genetic risk for psychiatric disorders.

/pdf/convergent-impact-of-schizophrenia-risk-genes-lfalemji.pdf

Convergent impact of schizophrenia risk genes

Most expression quantitative trait loci (eQTL) studies to date have been performed in heterogeneous brain tissues as opposed to specific cell types. To investigate the genetics of gene expression in adult human cell types from the central nervous system (CNS), we performed an eQTL analysis using single nuclei RNA-seq from 196 individuals in eight CNS cell types. We identified 6108 eGenes, a substantial fraction (43%, 2620 out of 6108) of which show cell-type specific effects, with strongest effects in microglia. Integration of CNS cell-type eQTLs with GWAS revealed novel relationships between expression and disease risk for neuropsychiatric and neurodegenerative diseases. For most GWAS loci, a single gene colocalized in a single cell type providing new clues into disease etiology. Our findings demonstrate substantial contrast in genetic regulation of gene expression among CNS cell types and reveal genetic mechanisms by which disease risk genes influence neurological disorders.

/pdf/cell-type-specific-cis-eqtls-in-eight-brain-cell-types-1rdv2zzgmw.pdf

Cell-type specific cis-eQTLs in eight brain cell-types identifies novel risk genes for human brain disorders

Cerebrospinal fluid (CSF) biomarkers are important for multiple sclerosis (MS) diagnosis. Moreover, absent of autopsy or biopsy tissue, CSF is the most relevant source for studying the immune cells involved in MS pathophysiology. Single-cell RNA sequencing (scRNA-seq) provides new opportunities to advance our understanding of disease-associated changes in CSF immune cells. Here, using scRNA-seq data generated from 58 CSF and 10 PBMC samples, we provide an updated atlas of the immune cells present in human CSF in MS and other neuroinflammatory conditions, including novel lymphoid and myeloid cell clusters. Our atlas can thus serve as a reference for future studies of immune cells in neuroinflammation. Our further characterization of CSF myeloid cells suggests that most CSF microglia-like cells resemble two of the previously-described brain microglia signatures. Additionally, our data from a sex-mismatched bone marrow transplant recipient suggest that CSF microglia-like cells are of peripheral origin. Our comparisons between MS and other neuroinflammatory disorders show a highly-specific increase in plasma cells, along with reductions in the proportion of microglia-like cells in MS CSF. Furthermore, our analyses on MS patients receiving anti-CD20 therapy ocrelizumab suggest that the treatment effects are not limited to B cell depletion, and ocrelizumab appears to reverse some MS-associated T and myeloid changes in CSF. Finally, we utilized our atlas to prioritize (1) CSF cell types expressing genes associated with MS susceptibility, and (2) ligand-receptor gene pairs that are differentially expressed in MS CSF, providing targets for further mechanistic and causal investigations in pathophysiology and treatment of MS.

https://www.biorxiv.org/content/biorxiv/early/2021/11/05/2021.11.01.466797.full.pdf

Julien Bryois

Papers

Cell-type specific cis-eQTLs in eight brain cell-types identifies novel risk genes for human brain disorders

Defining the architecture of cerebrospinal fluid cellular communities in neuroinflammatory diseases