Article in Nature genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
0numbers the graph read from it
0cells of the map it votes in
8citing 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
19 authors.
Tereza ClarenceCenter for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA. clarence.tereza@gmail.com.ORCID http://orcid.org/0000-0002-0099-2797
Panos RoussosCenter for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA. panagiotis.roussos@mssm.edu.ORCID http://orcid.org/0000-0002-4640-6239
Funding
Conduits: Mount Sinai Health System Translational Science HubUL1TR004419 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Rosalind J Wright · 2022 to 2026
$46.4M
Understanding the molecular mechanisms that contribute to neuropsychiatric symptoms in Alzheimer DiseaseR01AG067025 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI FINKBEINER, STEVEN M, HAROUTUNIAN, VAHRAM · 2019 to 2023
$11.8M
Higher Order Chromatin and Genetic Risk for Alzheimer's DiseaseR01AG050986 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI ROUSSOS, PANAGIOTIS · 2015 to 2025
$11.2M
Understanding the protective and neuroinflammatory role of human brain immune cells in Alzheimer DiseaseR01AG065582 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI HAROUTUNIAN, VAHRAM, ROUSSOS, PANAGIOTIS · 2020 to 2024
$9.9M
The adaptive-innate immune interactome across multiple tissues in Alzheimer's diseaseR01AG082185 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI VAHRAM HAROUTUNIAN, Donghoon Lee · 2023 to 2026
$9.0M
The BrainCellQTL consortium: QTL mapping in the human brain at the single cell levelU24AG087563 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Panagiotis Roussos · 2024 to 2026
$7.2M
Molecular Profiling of SchizophreniaR01MH110921 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI CHESS, ANDREW J, ROUSSOS, PANAGIOTIS · 2016 to 2020
$6.9M
The 3D genome in transcriptional regulation across the postnatal life span, with implications for schizophrenia and bipolar disorderU01MH116442 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI AKBARIAN, SCHAHRAM, DRACHEVA, STELLA · 2018 to 2022
$5.9M
A regulome and transcriptome atlas of fetal and adult human neurogenesisRF1MH128970 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI CAI, LONG, HOF, PATRICK R · 2021 to 2021
$5.5M
Multiethnic genomic epigenomic and transcriptomic fine-mapping and functional validation analysis of schizophrenia and bipolar disorder risk lociR01MH125246 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI ROUSSOS, PANAGIOTIS · 2021 to 2025
$5.0M
Risk genetic variants and cis regulation of gene expression in Bipolar DisorderR01MH109677 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI ROUSSOS, PANAGIOTIS · 2016 to 2020
$4.6M
Functional genomic resource and integrative model of dopaminergic circuitry associated with psychiatric diseaseU01DA048279 · NIDA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI AKBARIAN, SCHAHRAM, BRENNAND, KRISTEN JENNIFER · 2019 to 2023
$3.5M
BLRD VA I01 BX002395BLRD VA I01 BX005160BLRD VA I01 BX006642BLRD VA IK6 BX006524NCATS NIH HHS UL1 TR004419NIA NIH HHS R01 AG050986NIA NIH HHS R01 AG065582NIA NIH HHS R01 AG067025NIA NIH HHS R01 AG082185NIA NIH HHS U24 AG087563NIDA NIH HHS U01 DA048279NIH HHS S10 OD026880NIH HHS S10 OD030463NIMH NIH HHS R01 MH109677NIMH NIH HHS R01 MH110921NIMH NIH HHS R01 MH122590NIMH NIH HHS R01 MH125246NIMH NIH HHS RF1 MH128970NIMH NIH HHS RF1 MH133703NIMH NIH HHS U01 MH116442U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) R01-MH109677U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) R01-MH122590U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) R01-MH125246U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) U01-DA048279U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) U01-MH116442U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging) R01-AG050986U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging) R01-AG065582U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging) R01-AG067025U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging) R01-AG082185
6 · The paper itself
Abstract
Human brain development spans from embryogenesis to adulthood, with dynamic gene expression controlled by cell-type-specific cis-regulatory element activity and three-dimensional genome organization. To advance our understanding of postnatal brain development, we simultaneously profiled gene expression and chromatin accessibility in 101,924 single nuclei from four brain regions across ten donors, covering five key postnatal stages from infancy to late adulthood. Using this dataset and chromosome conformation capture data, we constructed enhancer-based gene regulatory networks to identify cell-type-specific regulators of brain development and interpret genome-wide association study loci for ten main brain disorders. Our analysis connected 2,318 cell-specific loci to 1,149 unique genes, representing 41% of loci linked to the investigated traits, and highlighted 55 genes influencing several disease phenotypes. Pseudotime analysis revealed distinct stages of postnatal oligodendrogenesis and their regulatory programs. These findings provide a comprehensive dataset of cell-type-specific gene regulation at critical timepoints in postnatal brain development.
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.
Multiomic single-cell profiling identifies critical regulators of postnatal brain. · full record | OpenQuestion