A Map of Transcriptional Heterogeneity and Regulatory Variation in Human Microglia
Open accessPublished version of a preprint
Abstract
Microglia, the tissue-resident macrophages of the central nervous system (CNS), play critical roles in immune defense, development and homeostasis. However, isolating microglia from humans in large numbers is challenging. Here, we profiled gene expression variation in primary human microglia isolated from 141 patients undergoing neurosurgery. Using single-cell and bulk RNA sequencing, we identify how age, sex and clinical pathology influence microglia gene expression and which genetic variants have microglia-specific functions using expression quantitative trait loci (eQTL) mapping. We follow up one of our findings using a human induced pluripotent stem cell-based macrophage model to fine-map a candidate causal variant for Alzheimer's disease at the BIN1 locus. Our study provides a population-scale transcriptional map of a critically important cell for human CNS development and disease.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Single cell RNA sequencing has identified at least 9 distinct microglial signatures with varying predominance depending on the health status of the neuronal tissue.
“Single cell RNA sequencing has been particularly useful, with at least 9 distinct microglial signatures identified with varying predominance, depending on the health status of the neuronal tissue [73,74].”
From Risk mitigation of immunogenicity: a key to personalized retinal gene therapy (2021) · cites this paper as [74]
Young et al. constructed eQTLs in primary human microglia (n=93) and detected 401 eQTLs, some colocalizing with AD loci including BIN1.
“Recently, Young et al. constructed expression QTLs (eQTLs) in primary human microglia (n = 93 individuals/samples), and detected 401 eQTLs, some of which colocalized with AD loci, including BIN126.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [26]
Sharing between our microglia and previously published microglia was low, with only a few known loci in AD and PD (BIN1, PICALM, CHRNB1).
“The sharing between our microglia and previously published microglia26 was low (Fig. 5b), with only a few known loci in AD and PD (BIN1, PICALM, CHRNB1), presumably due to lower power in the Young et al. data compared to our multi-tissue meta-analysis.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [26]
The low sharing with Young et al. is presumably due to lower power in the Young et al. data compared to our multi-tissue meta-analysis.
“The sharing between our microglia and previously published microglia26 was low (Fig. 5b), with only a few known loci in AD and PD (BIN1, PICALM, CHRNB1), presumably due to lower power in the Young et al. data compared to our multi-tissue meta-analysis.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [26]
Age-related changes were found in genes involved in a wide range of inflammatory responses.
“In addition, we found age-related changes in genes involved in a wide range of inflammatory responses, in line with previous results in aging in microglia16,26,62 and peripheral blood39.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [26]
eQTL sharing was both cell type- and region-dependent, with highest sharing between MiGA and Young et al. microglia (π1 = 0.81-0.86), but lower sharing in SVZ (π1 = 0.51).
“We found that eQTL sharing was both cell type- and region-dependent (Fig. 4d), with the highest sharing between MiGA and the Young et al. microglia (π1 = 0.81–0.86), but with a lower sharing in the SVZ (π1 = 0.51).”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [26]
Disease-associated eQTL results were partly shared between MiGA and the microglia eQTL study by Young et al.
“Disease-associated eQTLs results were partly shared between MiGA and the microglia eQTL study by Young et al26.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [26]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 60 · Cited by 213
Research works printed but not linked: 1
- [23]Jansen I Savage J Watanabe K Bryois J Williams D Genetic meta-analysis identifies 10 novel loci and functional pathways for Alzheimer’s disease risk bioRxiv 2018
- Authors
- Young, A. M. H., Kumasaka, N., Calvert, F., Hammond, T. R., Knights, A., Panousis, N., Park, J. S., Schwartzentruber, J., Liu, J., Kundu, K., Segel, M., Murphy, N. A., McMurran, C. E., Bulstrode, H., Correia, J., Budohoski, K. P., Joannides, A., Guilfoyle, M. R., Trivedi, R., Kirollos, R., Morris, R., Garnett, M. R., Timofeev, I., Jalloh, I., Holland, K., Mannion, R., Mair, R., Watts, C., Price, S. J., Kirkpatrick, P. J., Santarius, T., Mountjoy, E., Ghoussaini, M., Soranzo, N., Bayraktar, O. A., Stevens, B., Hutchinson, P. J., Franklin, R. J. M., & Gaffney, D. J.
- Affiliations
- Wellcome/MRC Cambridge Stem Cell Institute (GB)
- Wellcome Sanger Institute (GB)
- Broad Institute (US)
- European Bioinformatics Institute (GB)
- Biogen (United States) (US)
- University of Cambridge (GB)
- Corresponding author
- Franklin, Robin J. M.
- Gaffney, Daniel J.
- ORCID
- Kumasaka, Natsuhiko
- Hammond, Timothy R.
- Knights, Andrew
- Panousis, Nikolaos
- Park, Jun Sung
- Schwartzentruber, Jeremy
- Kundu, Kousik
- Segel, Michael
- Murphy, Natalia A.
- McMurran, Christopher E.
- Bulstrode, Harry
- Correia, Jason
- Budohoski, Karol P.
- Joannides, Alexis
- Trivedi, Rikin
- Timofeev, Ivan
- Jalloh, Ibrahim
- Mannion, Richard
- Mair, Richard
- Watts, Colin
- Price, Stephen J.
- Santarius, Thomas
- Mountjoy, Edward
- Ghoussaini, Maya
- Soranzo, Nicole
- Bayraktar, Omer A.
- Stevens, Beth
- Hutchinson, Peter J.
- Franklin, Robin J. M.
- Gaffney, Daniel J.
- Venue
- Nature Genetics
- Published
- 2021-06
- Volume
- 53
- Issue
- 6
- Pages
- 861-868
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC7610960
- OpenAlex
- W3164885408
- Cited by
- 213
- References
- 60
- Citations by year
- 2026: 18 · 2025: 40 · 2024: 43 · 2023: 32 · 2022: 51 · 2021: 26 · 2020: 3
- FWCI
- 15.28
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Nature Genetics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Apollo (University of Cambridge) (submittedVersion)
- Apollo
- Funders
- Wellcome Trust (WT206194, RRZD/029, 203151/Z/16/Z)
- Topics
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Keywords
- human microglia, microglial gene expression, transcriptional heterogeneity, expression quantitative trait loci, single-cell transcriptomics, induced pluripotent stem cell-derived macrophages, Alzheimer's disease, BIN1, germline genetic variants, age and sex effects, cortical anatomy, neurosurgical patients, central nervous system
- MeSH terms
- Alzheimer Disease, Gene Expression Regulation, Humans, Models, Genetic, Transcription, Genetic, Sequence Analysis, RNA, Microglia, Quantitative Trait Loci, Single-Cell Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
