To understand the health impact of long-duration spaceflight, one identical twin astronaut was monitored before, during, and after a 1-year mission onboard the International Space Station; his twin served as a genetically matched ground control. Longitudinal assessments identified spaceflight-specific changes, including decreased body mass, telomere elongation, genome instability, carotid artery distension and increased intima-media thickness, altered ocular structure, transcriptional and metabolic changes, DNA methylation changes in immune and oxidative stress–related pathways, gastrointestinal microbiota alterations, and some cognitive decline postflight. Although average telomere length, global gene expression, and microbiome changes returned to near preflight levels within 6 months after return to Earth, increased numbers of short telomeres were observed and expression of some genes was still disrupted. These multiomic, molecular, physiological, and behavioral datasets provide a valuable roadmap of the putative health risks for future human spaceflight.

Metabolomics, the large-scale study of the metabolic complement of the cell [1][2][3] , is a mature science that has been practiced for over 20 years 4 . Indeed, it is now a commonly used experimental systems biology tool with demonstrated utility in both fundamental and applied aspects of plant, microbial and mammalian research [5][6][7][8][9][10][11][12][13][14][15] . Among the many thousands of studies published in this area over the last 20 years, notable highlights [5][6][7][8]10,11,16 are briefly described in Supplementary Note 1.Despite the insight afforded by such studies, the nature of metabolites, particularly their diversity (in both chemical structure and dynamic range of abundance 9,12 ), remains a major challenge with regard to the ability to provide adequate coverage of the metabolome that can complement that achieved for the genome, transcriptome and proteome. Despite these comparative limitations, enormous advances have been made with regard to the number of analytes about which accurate quantitative information can be acquired, and a vast number of studies have yielded important biological information and biologically active metabolites across the kingdoms of life 14 . We have previously estimated that upwards of 1 million different metabolites occur across the tree of life, with between 1,000 and 40,000 estimated to occur in a single species 4 .

Type 2 diabetes mellitus (T2D) is a growing health problem, but little is known about its early disease stages, its effects on biological processes or the transition to clinical T2D. To understand the earliest stages of T2D better, we obtained samples from 106 healthy individuals and individuals with prediabetes over approximately four years and performed deep profiling of transcriptomes, metabolomes, cytokines, and proteomes, as well as changes in the microbiome. This rich longitudinal data set revealed many insights: first, healthy profiles are distinct among individuals while displaying diverse patterns of intra- and/or inter-personal variability. Second, extensive host and microbial changes occur during respiratory viral infections and immunization, and immunization triggers potentially protective responses that are distinct from responses to respiratory viral infections. Moreover, during respiratory viral infections, insulin-resistant participants respond differently than insulin-sensitive participants. Third, global co-association analyses among the thousands of profiled molecules reveal specific host–microbe interactions that differ between insulin-resistant and insulin-sensitive individuals. Last, we identified early personal molecular signatures in one individual that preceded the onset of T2D, including the inflammation markers interleukin-1 receptor agonist (IL-1RA) and high-sensitivity C-reactive protein (CRP) paired with xenobiotic-induced immune signalling. Our study reveals insights into pathways and responses that differ between glucose-dysregulated and healthy individuals during health and disease and provides an open-access data resource to enable further research into healthy, prediabetic and T2D states.

Recent advances highlight a pivotal role for cellular metabolism in programming immune responses. Here, we demonstrate that cell-autonomous generation of nicotinamide adenine dinucleotide (NAD+) via the kynurenine pathway (KP) regulates macrophage immune function in aging and inflammation. Isotope tracer studies revealed that macrophage NAD+ derives substantially from KP metabolism of tryptophan. Genetic or pharmacological blockade of de novo NAD+ synthesis depleted NAD+, suppressed mitochondrial NAD+-dependent signaling and respiration, and impaired phagocytosis and resolution of inflammation. Innate immune challenge triggered upstream KP activation but paradoxically suppressed cell-autonomous NAD+ synthesis by limiting the conversion of downstream quinolinate to NAD+, a profile recapitulated in aging macrophages. Increasing de novo NAD+ generation in immune-challenged or aged macrophages restored oxidative phosphorylation and homeostatic immune responses. Thus, KP-derived NAD+ operates as a metabolic switch to specify macrophage effector responses. Breakdown of de novo NAD+ synthesis may underlie declining NAD+ levels and rising innate immune dysfunction in aging and age-associated diseases.

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Precision health relies on the ability to assess disease risk at an individual level, detect early preclinical conditions and initiate preventive strategies. Recent technological advances in omics and wearable monitoring enable deep molecular and physiological profiling and may provide important tools for precision health. We explored the ability of deep longitudinal profiling to make health-related discoveries, identify clinically relevant molecular pathways, and impact behavior in a prospective longitudinal cohort ( n = 109) enriched for risk of type 2 diabetes mellitus (DM). The cohort underwent integrative Personalized Omics Profiling (iPOP) from samples collected quarterly for up to 8 years (median 2.8 years) using clinical measures and emerging technologies including genome, immunome, transcriptome, proteome, metabolome, microbiome, and wearable monitoring. We discovered over 67 clinically actionable health discoveries and identified multiple molecular pathways associated with metabolic, cardiovascular and oncologic pathophysiology. We developed prediction models for insulin resistance using omics measurements illustrating their potential to replace burdensome tests. Finally, study participation lead the majority of participants to implement diet and exercise changes. Altogether, we conclude that deep longitudinal profiling can lead to actionable health discoveries and provide relevant information for precision health.

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous largescale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.Cancer forms and progresses through a series of critical transitions-from pre-malignant to malignant states, from locally contained to metastatic disease, and from treatment-responsive to treatment-resistant tumors (Figure 1). Although specifics differ across tumor types and patients, all transitions involve complex dynamic interactions between diverse pre-malignant, malignant, and non-malignant cells (e.g., stroma cells and immune cells), often organized in specific patterns within the tumor

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