Alina Isakova

Aging affects cellular organelles differently, but whether subcellular aging predicts human disease remains unknown. Here, we integrated organelle-enriched proteins in plasma and cerebrospinal fluid proteomes from 61,931 individuals to model aging of 10 organelles across the human lifespan. Organelle aging was heterogeneous with lysosomes, plasma membranes, and Golgi compartments accelerating rapidly after age 60. Individuals with four or more prematurely aged compartments exhibited up to 22-fold higher kidney disease risk and up to 8-fold higher mortality risk. Major diseases are characterized by distinct organelle aging signatures and disease risk increased with the number of accelerated organelles. APOE-ε4 dosage was associated with lysosomal and mitochondrial aging and reduced PDP1 levels, implicating altered energy metabolism. Decomposition of organelle signature coefficients into biological programs further showed that diseases are associated with distinct subcellular patterns. These findings establish organelle-resolved aging as a measurable dimension of human biology, revealing subcellular mechanisms underlying disease susceptibility and resilience. One sentence summary: Human organelles age at different rates, revealing distinct molecular signatures that predict disease risk, resilience and mortality.

The serotonin system modulates nearly all neural circuits across development and adulthood and is a major pharmacological target for mood and anxiety disorders. Forebrain-projecting serotonin neurons are organized into projection-defined subsystems that align with molecular heterogeneity, but how these subsystems assemble during development remains unclear. We combined whole-brain developmental projection maps with single-cell transcriptomics to define the spatiotemporal and molecular logic of postnatal serotonin innervation. Using a deep-learning pipeline, we generated four-dimensional whole-brain maps of postnatal serotonin axon density and uncovered two coupled modes of regulation: region-specific trajectories of axon growth and refinement, and an early-postnatal, brain-wide synchronization of innervation. To link these dynamics to cell-intrinsic programs, we profiled single-cell transcriptomes of forebrain-projecting serotonin neurons from embryonic through postnatal stages and reconstructed developmental trajectories. We found that serotonin neuron heterogeneity was established embryonically and that the subtype taxonomy was largely conserved between mice and humans. Across serotonin subtypes, we observed a coordinated surge in wiring-molecule expression at mouse postnatal day 4 that aligned with the subsequent global innervation wave. Tracing subtypes defined by developmentally conserved markers at birth revealed complementary projection territories and engagement of distinct postnatal wiring modules that matched region-specific terminal maturation. Together, these results show that brain-wide serotonin innervation is built through embryonic subtype specification and two layers of postnatal control: system-level synchronization and subtype-specific terminal development.

Aging is asynchronous across cells and organs. Here we tested whether plasma proteomics can be used to analyze cell type-specific aging. From analyses of over 7,000 plasma proteins measured in 60,542 individuals, we developed machine learning models to estimate the biological age of over 40 cell types spanning neuronal, immune, glial, endocrine, epithelial and musculoskeletal origins. We observed that 20–25% of individuals exhibited accelerated aging in a single cell type and 1–3% in 10 or more cell types. Cellular aging signatures were associated with disease status and predicted incident disease and mortality over 15 years of follow-up. Individuals with the APOE4 genotype showed older astrocytes but younger macrophages compared to APOE3 carriers, whereas the APOE2 genotype had inverse associations. Moreover, extreme astrocyte aging tripled the risk of incident Alzheimer’s Disease in individuals with two APOE4 alleles, while youthful astrocytes reduced risk. Individuals with extremely aged compared to youthful skeletal myocytes exhibited a 12.7-fold higher risk of developing amyotrophic lateral sclerosis. In individuals who smoked, extreme respiratory epithelial cell aging was associated with a 58% higher lung cancer risk compared to smoking alone. Specific cellular vulnerabilities and cumulative cellular aging burden influenced survival, with youthful immune and neuronal cell types conferring protective effects. Finally, we developed a polycellular aging risk score that stratified mortality risk across cohorts and proteomics platforms. These findings establish a framework for quantifying human physiology at cellular resolution, revealing heterogeneous aging trajectories and their impact on disease susceptibility and resilience.

Collateral arteries are natural bypasses that can reroute blood flow around arterial blockages, limiting tissue injury during stroke and coronary artery disease. Despite their clinical effectiveness, therapeutic strategies to stimulate collateral artery growth remain unavailable due to our limited understanding of their developmental mechanisms. Remarkably, guinea pigs display exceptionally dense collateral artery networks across various organs, resulting in complete resistance to ischemic damage in the brain and heart. In this study, we compared single-cell RNA sequencing (scRNA-seq) from guinea pig and mouse tissues to identify endothelial cell (EC) gene expression patterns associated with extensive collateral artery development. We then developed an in vivo Perturb-seq platform in mice to test whether genes differentially expressed in guinea pigs influence artery EC specification. This pipeline identified artery repressors that were downregulated in guinea pigs and increased pial collateral abundance when inhibited in mice. Downstream analysis suggests that artery repressors, including WNT and hypoxia response genes, function in two capillary EC subsets— Esm1+ pre-artery and Apln+ angiogenic tip cells. Reduced activity of these repressors allows more ECs to acquire arterial identity, potentiating collateral artery formation. Collectively, our study establishes a strategy for discovering the genes underlying species-specific traits, suggests that guinea pigs have collaterals due to decreased activity of artery inhibitor pathways and hypoxia responses, and identifies novel targets for stimulating collateral artery formation ( Graphical abstract ). Abstract Figure:

Current single-cell RNA atlases largely capture polyadenylated transcripts while missing critical regulatory layers from noncoding RNA. To address this, we develop a generalizable framework that adapts total RNA profiling for use in standard droplet-based platforms and captures a broad complement of coding and noncoding RNAs using a unified pipeline. Applying this approach to the developing human brain, we generate a dataset mapping diverse RNA biotypes across all neuronal and non-neuronal lineages, revealing biotype-specific expression programs with cell-type and temporal specificity. Tracking microRNA dynamics in Cajal-Retzius neurons, transient and early-born neurons in the cortex, we show the enrichment and target anticorrelation of MIR137, associated with schizophrenia and intellectual disability, suggesting tight regulatory control. We apply TotalX to human peripheral blood mononuclear cells and identify transcriptional modules combining coding and noncoding RNAs and tRNA dynamics. In addition, we analyze dengue-infected hepatocytes and capture non-adenylated viral transcripts that distinguish infection states. This expanded coverage helps with understanding cellular identity and gene regulation at the atlas scale.

Modern biology increasingly relies on complex, high-dimensional datasets such as single-cell RNA sequencing (scRNA-seq), which present a vast space of potential hypotheses. Systematically exploring this space is often impractical, as scRNA-seq analyses are time-consuming and require substantial computational and domain expertise. To address this challenge, we introduce CellVoyager, an AI agent built on large language models that autonomously generates and implements scRNA-seq analyses within a Jupyter notebook environment. We evaluate CellVoyager on CellBench, a benchmark of 76 published scRNA-seq studies, where it outperforms GPT-4o and o3-mini by up to 23% in predicting which analyses authors ultimately conducted, given only the papers’ background sections. Across three in-depth case studies, CellVoyager generated novel findings in COVID-19, cell–cell communication and aging that experts consistently rated as creative and scientifically sound. These results demonstrate CellVoyager’s potential to accelerate computational biology and uncover missing insights by autonomously analyzing biological data at scale.

Understanding neuronal connectivity at single-cell resolution remains a fundamental challenge in neuroscience, with current methods particularly limited in mapping long-distance circuits and preserving cell type information. Here we present Connectome-seq, a high-throughput method that combines engineered synaptic proteins, RNA barcoding and parallel single-nucleus and single-synaptosome sequencing to map neuronal connectivity at single-synapse resolution. This adeno-associated virus-based approach enables simultaneous capture of both synaptic connections and molecular identities of connected neurons. We validated this approach in the mouse pontocerebellar circuit, identifying both established and potentially uncharacterized synaptic connections. Through integrated analysis of connectivity and gene expression, we identified molecular markers enriched in connected neurons, suggesting potential molecular determinants of circuit-specific connectivity. By enabling systematic mapping of neuronal connectivity across brain regions with single-cell precision and gene expression information, Connectome-seq provides a scalable platform for comprehensive circuit analysis across different experimental conditions and biological states.

Aging is asynchronous across cells and organs, but whether plasma proteins can capture cell type-specific aging and predict disease and mortality remains unknown. We developed machine learning models to estimate the biological age of more than 40 distinct cell types—spanning neuronal, immune, glial, endocrine, epithelial, and musculoskeletal origins—using over 7,000 plasma proteins measured in 60,000 individuals across three cohorts, comprising the largest human plasma proteomics aging study to date. Individuals showed heterogeneous aging profiles, with 20-25% exhibiting accelerated aging in a single cell type and 1-3% across ten or more cell types. APOE genotype showed antagonistic aging effects in different cell types: APOE4 carriers exhibited older astrocytes but younger macrophages, while APOE2 carriers showed the inverse. Cellular aging signatures were uniquely associated with disease status and predicted incident disease and mortality over 15 years of follow-up. Amyotrophic lateral sclerosis (ALS) showed the strongest association with skeletal myocyte aging (hazard ratio = 12.7 for extreme accelerated versus youthful aging). In Alzheimer’s disease (AD), prevalent cases showed accelerated aging across multiple neural and peripheral cell types, with extreme astrocyte aging conferring AD risk comparable to APOE4 carrier status. Moreover, extreme astrocyte aging increased AD risk in APOE4/4 carriers threefold, while youthful astrocytes strikingly reduced risk. Beyond neurodegeneration, respiratory cell aging identified smokers at 58% higher lung cancer risk, and myeloid aging identified normoglycemic individuals at higher diabetes risk. Both specific cellular vulnerabilities and cumulative aging burden influenced survival, wherein youthful immune or neuronal profiles were protective. A polycellular aging risk score provided robust mortality risk stratification across platforms and cohorts. These findings establish a framework for quantifying biological aging at the cellular resolution using plasma proteomics, revealing heterogeneity in aging trajectories and their impact on disease susceptibility and resilience.

Brain barriers, cerebrospinal fluid (CSF) dynamics, and peripheral factors are implicated as significant contributors to Alzheimer's disease (AD). The choroid plexus (ChP) is a blood-brain interface that produces CSF and forms the blood-CSF barrier. However, how ChP pathology develops across the lifespan and contributes to AD has not been systematically characterized. Here, we report a multi-modal ChP atlas integrating single-nucleus transcriptomics from 49 individuals, AI-assisted quantitative histopathology across >500 postmortem samples age 16 to 105, spatial transcriptomics, and functional studies in 5xFAD mice. We identify fibrosis, calcification, and macrophage abnormalities as hallmarks of ChP aging, with AD pathology conferring additional effects, including expansion of a pro-inflammatory fibroblast-macrophage signaling niche. In 5xFAD mice, macrophage dysfunction is associated with impaired epithelial barrier maintenance and repair. Together, these data provide a foundational resource for understanding ChP dysfunction in aging and AD and propose the macrophage-fibroblast-epithelial barrier axis as a driver of ChP pathology.

Non-coding RNAs represent a widespread and diverse layer of post-transcriptional regulation across cell types and states, yet much of their diversity remains uncharted at single-cell resolution. This gap stems from the limitations of widely used single-cell RNA-sequencing protocols, which focus on polyadenylated transcripts and miss many short or non-polyadenylated RNAs. Here, we adapted single-cell RNA-sequencing on the 10x Genomics platform to capture a broad complement of coding and non-coding RNAs—including miRNAs, tRNAs, lncRNAs, histone RNAs, and non-adenylated viral transcripts. This approach enabled the discovery of rich, dynamic non-coding RNA programs across immune cells, virally infected hepatocytes, and the developing human brain. In dengue virus-infected hepatocytes, we detect non-adenylated viral transcripts and distinguish active from transcriptionally quiescent infected states, each with distinct host regulatory signatures. In brain tissue, we identify biotype-specific, cell-type–restricted non-coding RNAs, including miRNAs whose expression anticorrelates with predicted targets, consistent with post-transcriptional regulatory relationships. We show that MIR137, one of the strongest GWAS loci associated with schizophrenia and intellectual disability, is expressed specifically in Cajal-Retzius cells, an early-born but transient population that guides subsequent cortical neuron migration. These findings demonstrate the importance of non-coding RNAs in defining cell identity and state, and show how expanded transcriptome coverage can reveal additional layers of gene control—now accessible through practical and scalable single-cell profiling.