The Human BioMolecular Atlas Program (HuBMAP) aims to create a multi-scale spatial atlas of the healthy human body at single-cell resolution by applying advanced technologies and disseminating resources to the community. As the HuBMAP moves past its first phase, creating ontologies, protocols and pipelines, this Perspective introduces the production phase: the generation of reference spatial maps of functional tissue units across many organs from diverse populations and the creation of mapping tools and infrastructure to advance biomedical research.HuBMAP was founded with the goal of establishing state-of-the-art frameworks for building spatial multiomic maps of non-diseased human organs at single-cell resolution 1 . During the first phase (2018)(2019)(2020)(2021)(2022), the priorities of the project included the validation and development of assay platforms; workflows for data processing, management, exploration and visualization; and the establishment of protocols, quality control standards and standard operating procedures. Extensive infrastructure was established through a coordinated effort among the various HuB-MAP integration, visualization and engagement teams, tissue-mapping centres, technology and tools development and rapid technology implementation teams and working groups 1 . Single-cell maps, predominantly consisting of two-dimensional (2D) spatial data as well as data from dissociated cells, were generated for several organs. The HuBMAP Data Portal (https://portal.hubmapconsortium.org) was established for open access to experimental tissue data and reference atlas data.The infrastructure was augmented with software tools for tissue data registration, processing, annotation, visualization, cell segmentation and automated annotation of cell types and cellular neighbourhoods from spatial data. Computational methods were developed for integrating multiple data types across scales and interpretation 2 . Standard reference terminology and a common coordinate framework spanning anatomical to biomolecular scales were established to ensure interoperability across organs, research groups and consortia 3 . Guidelines to capture high-quality multiplexed spatial data 4 were established including validated panels of cell-and structure-specific antibodies 5 . The first phase produced a large number of manuscripts (https://commonfund.nih.gov/ publications?pid=43) including spatially resolved single-cell maps [6][7][8][9][10][11] .The production phase of HuBMAP was launched in the autumn of 2022. The focus is on scaling data production spanning diverse biological variables (for example, age and ethnicity) and deployment and enhancement of analytical, visualization and navigational tools to generate high-resolution 3D accessible maps of major functional tissue units from more than 20 organs. This phase involves over 60 institutions and 400 researchers with opportunities for active intra-and inter-consortia collaborations and building a foundational resource for new biological insights and precision medicine. Below, ...

STATEMENT OF TRANSLATIONAL RELEVANCEThe CIMAC-CIDC is a Network of laboratories and a bioinformatics center established to perform biomarker analysis and correlation with clinical outcome data from immunotherapy trials. The specific goal for the Network is to perform comprehensive immune profiling of specimens from trials, using assays that span genomics, transcriptomics, and phenotyping analysis of the tumor, tumor microenvironment, and periphery. Identification of biomarkers to optimize immunotherapies for cancer patients requires analytically-validated and harmonized assays across multiple laboratories allowing cross-site and cross-trial analyses. Therefore, harmonization of assay protocols, a key requirement for reducing data variability and allowing interpretation and integration of assay data across trials and laboratories, plays an important part in the Network's infrastructure. A centralized database for integration of clinical and assay data facilitates the identification of biomarkers to optimize immunotherapy approaches and management of cancer patients.

Purpose: Variants in the gene encoding Programmed Cell Death-1 (PDCD1) have been associated with susceptibility to Systemic Lupus Erythematosus and other autoimmune diseases. Giv-en that clinically distinct autoimmune phenotypes share common genetic susceptibility factors, vari-ants in PDCD-1 were tested for a possible association with Juvenile Idiopathic Arthritis (JIA).Methods: Four Single Nucleotide Polymorphisms (SNPS) in the PDCD1 gene were genotyped and analyzed: rs7421861, rs11568821, rs10204525, and rs7568402 in 834 cases and 855 controls of Northern European ancestry. Each variant was examined for possible associations with JIA and then analyzed for association with JIA categories.Results:PDCD1 variants showed no association with JIA in the cohort overall (rs7421861 p=0.63, rs11568821 p=0.13, rs10204525 p=0.31, and rs7568402 p=0.45). Stratification by JIA categories indicated a significant association between systemic JIA and PDCD1 rs7568402 (OR=0.53, p=0.0027), which remained significant after 10,000 permutations, but was not replicated in an inde-pendent multi-ethnic systemic JIA cohort. A nominal association between enthesitis-related arthritis and rs115668821 was also observed (OR=0.22, p=0.012).Conclusion: Unlike other multiple autoimmune disease associated genetic variants, there was no as-sociation between PDCD1 variants and JIA or JIA categories.

Conflict of interest statement: AHR is a named inventor of a technology titled "Metal labeled Vericells for mass cytometry", and both he and Mount Sinai have received payments associated with licensing of this technology. CW holds equity in BioNTech, Inc. CW is a co-founder and scientific advisory board member of