The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Polarization of the Effects of Autoimmune and Neurodegenerative Risk Alleles in Leukocytes
Open accessAbstract
Immunogenetic Variation: Many genetic variants have been implicated in disease but their effects in function across tissues and cell-types remain to be resolved. Raj et al. (p. 519 ) present an analysis of expression quantative trait loci (eQTL) measuring messenger RNA levels and examined correlations between genotypes and gene expression in purified monocytes and T cells in healthy individuals of European, African, and Asian descent. Most, but not all, of the eQTLs and their effects on expression were shared between the populations, as well as a substantial proportion between the cell types. Links were found with disease-associated variants and loci that previous genome-wide analyses have implicated in neurodegenerative and autoimmune diseases.
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“These results reinforce the emerging genetic and epigenetic association between AD and a network of microglial expressed genes2,5,17–21”
From A common haplotype lowers PU.1 expression in myeloid cells and delays onset of Alzheimer's disease (2017) · cites this paper as [21]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“An important finding is that the enrichment is observed not only in immune cells that have long been studied in MS, e.g. T cells, but also in B cells whose role has emerged more recently.(25)”
From Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility (2019) · cites this paper as [25]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“MS GWAS loci are also enriched for expression quantitative trait loci (eQTL) in multiple tissues,46, 57 supporting the idea that much risk is due to changes to gene regulation.”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [57]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Genetic studies have highlighted a prominent role for microglia in susceptibility to different neurodegenerative diseases, particularly Alzheimer’s disease (AD)10–12.”
From Single cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer’s disease (2020) · cites this paper as [12]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“However, recent evidence from genome-wide association studies (GWAS) and other follow-up analyses has suggested that a proportion of the genetic risk of neurological and psychiatric diseases acts through myeloid cells22–25.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [22]
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“Together, these results highlight shared genetic regulation between microglia and monocytes, which is only partly captured in whole-tissue brain data22.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [22]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
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“Further, AD-risk alleles are polarized for cis-expression quantitative trait locus (cis-eQTL) effects in monocytes21.”
From A common haplotype lowers PU.1 expression in myeloid cells and delays onset of Alzheimer's disease (2017) · cites this paper as [21]
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“Furthermore, while the adaptive immune system has been proposed to play a predominant role in MS onset,(26) we now demonstrate that many elements of innate immunity, such as natural killer (NK) cells and dendritic cells also display strong enrichment for MS susceptibility genes.”
From Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility (2019) · cites this paper as [26]
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“human genome-wide association studies (GWASs) support a causal role for immune mechanisms (Jansen et al., 2019; Kunkle et al., 2019; Raj et al., 2014).”
From Meta-Analysis of the Alzheimer’s Disease Human Brain Transcriptome and Functional Dissection in Mouse Models (2020) · cites this paper as Raj et al., 2014
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“First, our sample size is still small in comparison to monocyte and brain datasets22,41–43.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [22]
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In the citing paper
“On the other hand, CLECL1 represents a simpler case of a known susceptibility effect that has previously been linked to altered CLECL1 RNA expression in monocytes (26, 32); its enrichment in microglial cells, which share many molecular pathways with other myeloid cells, is more straightforward to understand.”
From Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility (2019) · cites this paper as [26]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“MS4A6A, a gene related to AD risk22,68,69, was one of the genes that showed a region-specific effect of age68,70.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [22]
Experimental — accuracy not yet measuredIn the citing paper
“This idea is supported by studies showing that alleles associated with AD show an effect on gene expression specifically in monocytes.”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [193]
In the citing paper
“AD-associated variants were enriched for colocalization with eQTLs specifically regulating gene expression in monocytes, but not in T-cells, demonstrating AD variants have a cell-type specific effect on gene expression.”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [193]
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Citations
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Systematic Localization of Common Disease-Associated Variation in Regulatory DNA
Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., et al. (2012) · Science · doi:10.1126/science.1222794 · Cited by 3,716
Mechanisms underlying inflammation in neurodegeneration
Glass, C. K., Saijo, K., Winner, B., Marchetto, M. C., & Gage, F. H. (2010) · Cell · doi:10.1016/j.cell.2010.02.016 · Cited by 3,580
LocusZoom: regional visualization of genome-wide association scan results
Pruim, R. J., Welch, R. P., Sanna, S., Teslovich, T. M., Chines, P. S., Gliedt, T. P., Boehnke, M., Abecasis, G. R., & Willer, C. J. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq419 · Cited by 2,707
Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis
Leek, J. T., & Storey, J. D. (2007) · PLoS Genetics · doi:10.1371/journal.pgen.0030161 · Cited by 1,930
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Rashid, R., & Ramirez‐Ortiz, Z. G. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27104552
Adewuyi, E. O., Auta, A., Ossai, C. I., Anyaegbu, C. C., Nguyen, T. T. H., Rahman, M. R., Stephan, B. C. M., Tessema, G. A., Nyholt, D. R., & Pereira, G. F. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27114792
Altered microglial communication in brains with Alzheimer’s Disease pathologyPreprint
Santos, L. D., Vialle, R. A., Comandante-Lou, N., Green, G. S., Wang, Y., Tasaki, S., Habib, N., Menon, V., Jager, P. L. D., Raittz, R. T., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.08.13.744723
Peripheral Immune Alterations and T Cell Clonal Dynamics Across the Parkinson’s Disease SpectrumPreprint
Rosen, M. R., Majos, J. O. N., Mattei, D., Mejia, E., Mandry, C. P., Jang, B., Kailash, B. P., Naito, T., Allan, A., Khashan, T., et al. (2026) · medRxiv · doi:10.64898/2026.09.23.26363800
Self-citationThomas, P. (2026) · ImmPort · doi:10.21430/m3mqjhhu58
Metadata
- Authors
- Raj, T., Rothamel, K., Mostafavi, S., Ye, C., Lee, M. N., Replogle, J. M., Feng, T., Lee, M., Asinovski, N., Frohlich, I., Imboywa, S., Von Korff, A., Okada, Y., Patsopoulos, N. A., Davis, S., McCabe, C., Paik, H.-I., Srivastava, G. P., Raychaudhuri, S., Hafler, D. A., Koller, D., Regev, A., Hacohen, N., Mathis, D., Benoist, C., Stranger, B. E., & De Jager, P. L.
- Affiliations
- Broad Institute (US)
- Harvard University (US)
- Stanford University (US)
- Brigham and Women's Hospital (US)
- Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women’s Hospital, Boston, MA 02115, USA.
- University of Chicago (US)
- Corresponding author
- Benoist, Christophe
- Stranger, Barbara E.
- ORCID
- Venue
- Science
- Published
- 2014-05-02
- Volume
- 344
- Issue
- 6183
- Pages
- 519-523
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC4910825
- OpenAlex
- W2101280135
- Cited by
- 506
- References
- 31
- Citations by year
- 2026: 11 · 2025: 18 · 2024: 17 · 2023: 34 · 2022: 43 · 2021: 38 · 2020: 58 · 2019: 46 · 2018: 56 · 2017: 54 · 2016: 53 · 2015: 53 · 2014: 24
- FWCI
- 40.18
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Research Explorer (The University of Manchester) (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- eScholarship (California Digital Library) (submittedVersion)
- PMC
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health (5r01ar063759-07)
- National Institute on Aging (F32AG043267)
- National Institute of General Medical Sciences (RC2GM093080)
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (K08AR055688, R01-AR063759)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Health Sciences › Medicine › Clinical Neurology › Multiple Sclerosis Research Studies
- Keywords
- expression quantitative trait loci, CD4+ T cells, monocytes, Alzheimer's disease, Parkinson's disease, cis-eQTL, trans-eQTL, cell-autonomous effects, multi-ethnic cohort
- MeSH terms
- Alleles, Alzheimer Disease, Autoimmune Diseases, Ethnicity, Humans, Immunity, Innate, Monocytes, Multiple Sclerosis, Parkinson Disease, Rheumatic Fever, CD4-Positive T-Lymphocytes, Autoimmunity, Neurodegenerative Diseases, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study, Adaptive Immunity, Transcriptome
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