Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input–output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1–5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

Prion protein (PrP) concentration controls the kinetics of prion replication and is a genetically and pharmacologically validated therapeutic target for prion disease. In order to evaluate PrP concentration as a pharmacodynamic biomarker and assess its contribution to known prion disease risk factors, we developed and validated a plate-based immunoassay reactive for PrP across six species of interest and applicable to brain and cerebrospinal fluid (CSF). PrP concentration varies dramatically between different brain regions in mice, cynomolgus macaques, and humans. PrP expression does not appear to contribute to the known risk factors of age, sex, or common PRNP genetic variants. CSF PrP is lowered in the presence of rare pathogenic PRNP variants, with heterozygous carriers of P102L displaying 55% and of D178N just 31% the CSF PrP concentration of mutation-negative controls. In rodents, pharmacologic reduction of brain Prnp RNA is reflected in brain parenchyma PrP, and in turn in CSF PrP, validating CSF as a sampling compartment for the effect of PrP-lowering therapy. Our findings support the use of CSF PrP as a pharmacodynamic biomarker for PrP-lowering drugs, and suggest that relative reduction from individual baseline CSF PrP concentration may be an appropriate marker for target engagement.

We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

BackgroundBlood‐based biomarkers offer the possibility of inexpensive, minimally invasive, and accessible diagnostic tools for Alzheimer’s Disease (AD). In the context of clinical trials, these biomarkers hold promise for subject stratification and monitoring the effects of therapeutic interventions. The day‐to‐day variability of these measures must be robustly characterized to determine which blood‐based biomarkers would be the most sensitive for detecting treatment‐related responses. In this study we evaluate biomarker performance in plasma and identify the most reliable candidates for clinical trials.MethodEDTA plasma samples were collected from healthy controls (n=20, 50% female, mean age 56.03 ± 9.43 years) at baseline, 2 weeks, and 4 weeks. Singleplex ELISA and multiplex MesoScale Discovery (MSD) immunoassays were used to measure over 25 biomarkers that were selected for their relevance to dysregulated processes in AD and previously validated in cerebrospinal fluid (CSF). Technical performance was assessed by calculating intra‐ and inter‐plate coefficients of variation (CVs), analyzing dilution linearity, and evaluating freeze‐thaw stability. Biological intra‐individual variability was examined by calculating a biotemporal CV for each subject across the three timepoints.ResultsMost biomarkers were quantifiable in plasma and exhibited technical performance within our thresholds (intra‐ and inter‐plate CV < 15%). The biomarkers exhibited a range of freeze‐thaw stability, with mean CVs from 5.2% for Adiponectin, a regulator of glucose metabolism, to 30.2% for GRP78, an ER chaperone protein. Plasma levels were relatively stable across time (biotemporal CV < 20%) for several biomarkers, including 24‐OHC, VEGF‐D, Flt‐1, PlGF, sST2, and sTREM2. Several proteins exhibited significant variability over time (biotemporal CV > 20%), such as 8‐OHdG, GRP78, and YKL‐40.ConclusionKey metabolic, vascular, and inflammatory biomarkers were reliably measurable in the plasma of healthy individuals. Several markers exhibited substantial variability over a 2‐4 week time period, which should be taken into consideration when selecting appropriate markers for assessing drug‐target engagement. Designing future clinical trials with multiple baseline visits will allow us to establish biological variability metrics for each individual’s biomarker levels, providing greater confidence in determining treatment effects. Evaluating biomarker stability in other large‐scale subject populations will be necessary to best inform blood‐based biomarker selection for clinical trials.