Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
23 authors.
Wei YangDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID 0000-0002-0178-9256
Kelsi L WatkinsCenter for Evolution and Medicine, Arizona State University, Tempe, AZ, USA.ORCID 0000-0001-5330-5025
Alex R DeCasienComputational and Evolutionary Neurogenomics Unit, National Institute on Aging, Bethesda, MD, USA.ORCID 0000-0002-6205-5408
Mary B O'NeillBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-3003-495X
Martin O BohlenDepartment of Biomedical Engineering, Duke University, Durham, NC, USA.ORCID 0000-0001-6522-146X
Diana R O'DayBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.
Madeleine DuranDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID 0000-0003-1648-2369
Chengxiang QiuDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID 0000-0002-6346-8669
Anastasia MeleshkoBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.
Anh VoBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.
Melia MenkeSchool of Life Sciences, Arizona State University, Tempe, AZ, USA.
Diego CalderonDepartment of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.ORCID 0000-0002-6990-9066
Cayo Biobank Research Unit
Jérôme SalletStem Cell and Brain Research Institute, Université Lyon, Lyon, France.ORCID 0000-0002-7878-0209
James P HighamDepartment of Anthropology, New York University, New York, NY, USA.
Melween I MartínezCaribbean Primate Research Center, University of Puerto Rico, San Juan, PR, USA.ORCID 0000-0003-1030-9506
Cole TrapnellDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID 0000-0002-8105-4347
Lea M StaritaDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID 0000-0003-2870-5099
Michael J MontagueDepartment of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0003-0253-4404
Michael L PlattDepartment of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0003-3912-8821
Kenneth L ChiouDepartment of Biology, University of Alabama at Birmingham, AL, USA.ORCID 0000-0001-7247-4107
Jay ShendureDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID 0000-0002-1516-1865
Noah Snyder-MacklerCenter for Evolution and Medicine, Arizona State University, Tempe, AZ, USA.ORCID 0000-0003-3026-6160
Funding
Translational Science InitiativeP40OD012217 · OD · UNIVERSITY OF PUERTO RICO MED SCIENCES · PI CARLOS A SARIOL · 2012 to 2026
$40.4M
GENETIC APPROACHES TO AGING RESEARCHT32AG000057 · NIA · UNIVERSITY OF WASHINGTON · PI RABINOVITCH, PETER S · 1985 to 2019
$14.2M
Mechanisms Regulating Complex Social BehaviorR01MH108627 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI HUETTEL, SCOTT ALLEN, PLATT, MICHAEL L · 2016 to 2025
$7.1M
Neural Circuit Mechanisms Mediating TMS and Oxytocin Effects on Social CognitionR37MH109728 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI PLATT, MICHAEL L · 2016 to 2025
$6.7M
Versatile, exponentially scalable methods for single cell molecular profilingR01HG010632 · NHGRI · UNIVERSITY OF WASHINGTON · PI Jay Ashok Shendure, Bruce Colston Trapnell · 2019 to 2026
$5.9M
Single cell transcriptional and epigenomic atlas of the macaque brain across the lifespanU01MH121260 · NIMH · UNIVERSITY OF WASHINGTON · PI PLATT, MICHAEL L, SHENDURE, JAY ASHOK · 2019 to 2021
$4.8M
Social modifiers of the pace of aging across multiple domains and tissuesR01AG060931 · NIA · UNIVERSITY OF WASHINGTON · PI BRENT, LAUREN JOHANNA NICOLE, HIGHAM, JAMES P · 2019 to 2023
$3.6M
Animal Model of Genetics and Social Behavior in Autism Spectrum DisordersR01MH096875 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI PLATT, MICHAEL L · 2012 to 2016
$3.6M
Impacts of hurricanes and social buffering on biological aging in a free-ranging animal modelR01AG084706 · NIA · NEW YORK UNIVERSITY · PI Lauren Johanna Nicole Brent, James P Higham · 2023 to 2026
$2.5M
Neurogenomics of Vulnerability and Resilience to Mental Health Syndromes in Response to Extreme Life EventsR01MH118203 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI PLATT, MICHAEL L · 2019 to 2023
$1.9M
Effects of a major natural disaster on the pace of aging in a nonhuman primate modelR56AG071023 · NIA · NEW YORK UNIVERSITY · PI BRENT, LAUREN JOHANNA NICOLE, HIGHAM, JAMES P · 2021 to 2021
$839k
Gene regulatory analysis of social integration and resilience during agingR00AG051764 · NIA · UNIVERSITY OF WASHINGTON · PI SNYDER-MACKLER, NOAH · 2017 to 2019
Brain aging is a complex process with profound health and societal consequences. However, the molecular and cellular pathways that govern its temporal progression-along with any cell type-, region-, and sex-specific heterogeneity in such progression-remain poorly defined. Here, we present a transcriptomic atlas of 5.3 million cells from 582 samples spanning 11 brain regions of 55 rhesus macaques (29 female, 26 male), aged 5 months (early life) to 21 years (late adulthood). We annotate 12 major cell classes and 225 subclusters, including region-specific subtypes of excitatory and inhibitory neurons, astrocytes, and ependymal cells. We identify a vulnerable excitatory neuron population in the superficial cortical lamina and a cortical interneuron population that are less abundant later in life, along with subtle, region-specific, age-associated compositional differences in subpopulations of microglia and oligodendrocytes, whose detection required single-cell resolution. Finally, we chart convergent and divergent age-associated molecular signatures across brain regions and cell classes-where some of these signatures are sex-specific and could underlie sex biases in neurological disorders. We find that age-associated transcriptional programs not only overlap substantially with those seen in Alzheimer's disease (AD), but also unfold along distinct temporal trajectories across brain regions, suggesting that aging and AD may share molecular roots that emerge at different life stages and in region-specific, sex-specific windows of vulnerability. This work provides a temporal, regional, and sex-stratified atlas of the aging primate brain, offering insights into cell type-specific vulnerabilities and regional heterogeneity with translational human relevance.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Single-cell, multi-region profiling of the macaque brain across the lifespan. · full record | OpenQuestion