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Cited by 296Neuroinflammation and Neurodegeneration MechanismsGenetic Associations and EpidemiologySingle-cell and spatial transcriptomics

Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies

Open access
Lopes, Katia de Paiva, Snijders, Gijsje J. L., Humphrey, Jack, Allan, Amanda, Sneeboer, Marjolein A. M., Navarro, Elisa, Schilder, Brian M., Vialle, Ricardo A. +12 more·2022·Nature Genetics
DOI 10.1038/s41588-021-00976-yPMC PMC9245609

Published version of a preprint

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Abstract

Microglia have emerged as important players in brain aging and pathology. To understand how genetic risk for neurological and psychiatric disorders is related to microglial function, large transcriptome studies are essential. Here we describe the transcriptome analysis of 255 primary human microglial samples isolated at autopsy from multiple brain regions of 100 individuals. We performed systematic analyses to investigate various aspects of microglial heterogeneities, including brain region and aging. We mapped expression and splicing quantitative trait loci and showed that many neurological disease susceptibility loci are mediated through gene expression or splicing in microglia. Fine-mapping of these loci nominated candidate causal variants that are within microglia-specific enhancers, finding associations with microglial expression of USP6NL for Alzheimer's disease and P2RY12 for Parkinson's disease. We have built the most comprehensive catalog to date of genetic effects on the microglial transcriptome and propose candidate functional variants in neurological and psychiatric disorders.

Integrity signals

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Crossref · 10.1038/s41588-021-00976-y

Cites

130 of 130 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

7 of 109 cited sources checked · 0 supported · 0 flagged · accuracy not yet measured

  • Interpretationreasoning

    The lead QTL SNP rs3732765-A acts through downregulating P2RY12 expression in microglia.

    “The lead QTL SNP rs3732765-A decreases PD risk (β = −0.06; P = 2.4×10−10; 58), and we propose that it acts through downregulating P2RY12 expression in microglia.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [58] Hollingworth, P. et al. Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer’s disease. Nat. Genet. 43, 429–435 (2011). source

      The paper’s association results (Abstract; page unavailable) concern Alzheimer’s disease and report SNPs at ABCA7 and the MS4A gene cluster. Searches for rs3732765, P2RY12, microglia, and Parkinson’s disease found no passage addressing the cited PD-risk result. The proposed expression mechanism is the citing authors’ own proposal, not a finding established by this source. (LLM, conf=0.78)

      Experimental — accuracy not yet measured
  • Findingcitation

    MS4A6A showed a region-specific effect of age.

    “MS4A6A, a gene related to AD risk22,68,69, was one of the genes that showed a region-specific effect of age68,70.”
    Quote in the paperNot a substantial claim4 of 4 sources checked
    • cites [22] Raj, T. et al. Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes. Science 344, 519–523 (2014). source

      The paper’s Abstract describes gene-expression analyses in blood T cells and monocytes, including cell-type-specific effects of Alzheimer’s disease risk variants. It does not report a region-specific effect of age for MS4A6A; searches for MS4A6A and age-related brain-region effects found no passage addressing that claim. (LLM, conf=0.75)

      Experimental — accuracy not yet measured
    • cites [68] Huang, K.-L. et al. A common haplotype lowers PU.1 expression in myeloid cells and delays onset of Alzheimer’s disease. Nat. Neurosci. 20, 1052–1061 (2017). source

      The Results sections report an association of the MS4A locus with age at Alzheimer’s onset and an association of MS4A6A expression with genetic variants in myeloid cells. The Discussion mentions aging in relation to a microglial signature, but neither passage reports a region-specific effect of age on MS4A6A expression. Searches for that effect and for age-dependent expression across brain regions found no supporting passage in our copy. (LLM, conf=0.74)

      Experimental — accuracy not yet measured
    • cites [69] Deming, Y. et al. The MS4A gene cluster is a key modulator of soluble TREM2 and Alzheimer’s disease risk. Sci. Transl. Med. 11, eaau2291 (2019). source

      The Results section on functional annotation reports tissue-specific effects of rs1582763 on MS4A6A expression, but does not examine whether age affects MS4A6A differently across regions. The Discussion mentions age at Alzheimer’s disease onset, which is a different outcome. Searches for a region-specific effect of age and age-dependent MS4A6A expression found no supporting passage in our copy; page numbers were unavailable. (LLM, conf=0.77)

      Experimental — accuracy not yet measured
    • cites [70] Novikova, G. et al. Integration of Alzheimer’s disease genetics and myeloid genomics identifies disease risk regulatory elements and genes. Nat. Commun. 12, 1610 (2021). source

      The Results section on the MS4A locus links MS4A6A expression to an Alzheimer’s disease risk allele, but does not report an effect of age that differs by brain region. Searches for “MS4A6A region-specific effect of age” and “age brain regions MS4A6A expression” found no passage addressing that claim. (LLM, conf=0.75)

      Experimental — accuracy not yet measured
  • Findingown data

    A subset of genes were strongly variable between brain regions.

    “Brain region explained comparatively little variance overall (mean 2.95%), but we identified a subset of genes that were strongly variable between regions.”
    Quote in the paperSubstantial claim
  • Findingown data

    Cluster 4 included genes involved in biological functions related to hormonal signaling and interferon response.

    “Cluster 4 included genes that were involved in biological functions related to hormonal signaling and interferon response (Fig. 2f).”
    Quote in the paperNot a substantial claim
  • Findingown data

    k=4 was the optimal clustering partitioning after minimizing total within-cluster sum of squares.

    “We identified k = 4 as the optimal clustering partitioning after minimizing the total within-cluster sum of squares (WSS) (Fig. 2d).”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim. 36
  • May combine two claims. 60

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Previous analyses have prioritized ECHDC3, as it is upregulated in AD post-mortem brains and an eQTL for ECHDC3 was seen in whole blood, though it did not colocalize with the GWAS SNP.

    “Previous analyses have prioritized ECHDC3, as it is upregulated in AD post-mortem brains53,54, and an eQTL for ECHDC3 was seen in whole blood55, though it did not colocalize with the GWAS SNP23.”
    Quote in the paperNot a substantial claim2 of 4 sources checked
    • cites [53] Zhang, B. et al. Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer’s disease. Cell 153, 707–720 (2013). source

      The citation to this paper is attached to the claim that the ECHDC3 eQTL did not colocalize with the GWAS SNP. The Results section discusses brain cis eSNPs, but our copy does not report that ECHDC3-specific colocalization result (searched for ECHDC3, colocalization, and the whole-blood eQTL). (LLM, conf=0.75)

      Experimental — accuracy not yet measured
    • cites [54] Desikan, R. S. et al. Polygenic overlap between C-reactive protein, plasma lipids, and Alzheimer disease. Circulation 131, 2061–2069 (2015). source
    • cites [55] Zhernakova, D. V. et al. Identification of context-dependent expression quantitative trait loci in whole blood. Nat. Genet. 49, 139–145 (2017). source
    • cites [23] Kunkle, B. W. et al. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat. Genet. 51, 414–430 (2019). source

      The citation is attached to the claim that the ECHDC3 eQTL did not colocalize with the GWAS SNP. The Results (Meta-analysis of Alzheimer’s disease GWAS) identify an ECHDC3 risk signal, and the Methods (Regulatory variant and eQTL analysis) describe colocalization testing, but neither reports a colocalization result for ECHDC3. Searches for ECHDC3 with eQTL and colocalization terms did not locate that result in our copy; page numbers were unavailable. (LLM, conf=0.72)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Analysis of upstream regulators of the four clusters using IPA was inconclusive.

    “Analysis of upstream regulators of the four clusters using Ingenuity Pathway Analysis (IPA) was inconclusive (Supplementary Table 9).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Cluster 1 contained genes upregulated in cortical regions compared to subcortical regions, and was enriched in genes downregulated in AD brain and in response to in vitro culture.

    “Cluster 1 contained genes that were upregulated in the cortical regions compared to subcortical regions, such as P2RY12, CD36, and MRC1, and was enriched in genes that were downregulated in AD brain33 and in response to in vitro culture34.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [33] Srinivasan, K. et al. Alzheimer’s patient microglia exhibit enhanced aging and unique transcriptional activation. Cell Rep. 31, 107843 (2020). source

      Not checked in the free run.

    • cites [34] Gosselin, D. et al. An environment-dependent transcriptional network specifies human microglia identity. Science 356, eaal3222 (2017). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Cluster 3 contained genes specifically downregulated in SVZ and cluster 4 contained genes upregulated in SVZ compared to the other three regions.

    “Cluster 3 contained genes specifically downregulated in the SVZ (e.g. CX3CL1, CCR2, FCGR3B) and cluster 4 contained genes upregulated in SVZ (e.g. IL10, CLU, CD83), compared to the other three regions (Fig. 2e).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Genes implicated in inflammatory processes were highly expressed in cluster 2, whereas genes related to homeostatic functions of microglial cells were mainly present in cluster 1.

    “We found that genes implicated in inflammatory processes were highly expressed in cluster 2 (Fig. 2f), whereas genes related to homeostatic functions of microglial cells were mainly present in cluster 1.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    Cluster 1 genes were enriched in genes downregulated in AD brain and in response to in vitro culture.

    “Cluster 1 genes were enriched in genes that were downregulated in AD brain and in response to in vitro culture.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [33] Srinivasan, K. et al. Alzheimer’s patient microglia exhibit enhanced aging and unique transcriptional activation. Cell Rep. 31, 107843 (2020). source

      Not checked in the free run.

    • cites [34] Gosselin, D. et al. An environment-dependent transcriptional network specifies human microglia identity. Science 356, eaal3222 (2017). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    176 transcripts in 132 genes had evidence of differential transcript usage between microglia regions, with a majority of transcripts coming from comparisons with the SVZ.

    “176 transcripts in 132 genes had evidence of DTU (log odds ratio > 1; empirical FDR < 0.1), with a majority of transcripts coming from comparisons with the SVZ (Extended Data Fig. 1a).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    eQTLs for CASS4 are significant in both MiGA and monocytes (MyND) but with opposite directions of effect.

    “eQTLs for CASS4 are significant in both MiGA and monocytes (MyND) but with opposite directions of effect (Fig. 4g), suggesting that the causal variant is located in a complex regulatory element where both enhancing and repressing mechanisms are at play.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    We observed colocalization with eQTLs and sQTLs in MS4A6A, as well as eQTLs in MS4A4A and MS4A4E.

    “We observed colocalization with eQTLs and sQTLs in MS4A6A, as well as eQTLs in MS4A4A and MS4A4E (Fig. 5f).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    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).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [26] Young, A. M. H. et al. A map of transcriptional heterogeneity and regulatory variation in human microglia. Nat. Genet. 53, 861–868 (2021). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Sharing with monocyte eQTLs was generally slightly lower than with microglia, and sharing with bulk DLPFC eQTLs was lowest.

    “Sharing with monocyte eQTLs was generally slightly lower than with microglia and sharing with bulk DLPFC eQTLs was lowest.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    No colocalization was observed in any other QTL dataset, though USP6NL is expressed five-fold higher in microglia than in monocytes.

    “No colocalization was observed in any other QTL dataset, though we note that USP6NL is expressed five-fold higher in microglia than in monocytes (MiGA median TPM = 15.77; MyND42 monocyte median TPM = 3.13).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [42] Navarro, E. et al. Dysregulation of mitochondrial and proteolysosomal genes in Parkinson’s disease myeloid cells. Nat. Aging 1, 850–863 (2021). source

  • May combine two claims.

    Findingown data

    Disease associations that may act through splicing were added, including MS4A6A in AD, SIPA1L2 and FAM49B in PD, IRF3 in SCZ, STK4 and GMIP in BD, and CD37 and EFCAB13 in MS.

    “By mapping sQTLs we have shown that the known AD risk association with CD33 exon 2 splicing is also present in microglia, and added disease associations that may act through splicing, such as MS4A6A in AD, SIPA1L2 and FAM49B in PD, IRF3 in SCZ, STK4 and GMIP in BD, and CD37 and EFCAB13 in MS.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The meta-analyzed eQTL colocalizes with the ECHDC3 locus in all 4 AD GWAS used in this study, with highest PP4 (0.95) seen in one.

    “The meta-analyzed eQTL colocalizes with the ECHDC3 locus in all 4 AD GWAS used in this study, with the highest PP4 (0.95) seen in 46 (Fig. 6c; Extended Data Fig. 3–4).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [46] Marioni, R. E. et al. GWAS on family history of Alzheimer’s disease. Transl. Psychiatry 8, 99 (2018). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Upregulated genes in chronological aging showed overrepresentation for genes in AD or PD GWAS loci, but not for genes in SCZ or BD.

    “The upregulated genes in chronological aging showed overrepresentation for genes in AD (e.g. MS4A6A, FCER1G, and CR1) or PD (e.g. BST1, PTPN22, and TNFSF13) GWAS loci, but not for genes in schizophrenia (SCZ) or bipolar disorder (BD) (Fig. 3d).”
    Quote in the paperSubstantial claim0 of 4 sources checked
    • cites [35] Stahl, E. A. et al. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat. Genet. 51, 793–803 (2019). source

      Not checked in the free run.

    • cites [36] Gusev, A. et al. Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights. Nat. Genet. 50, 538–548 (2018). source

      Not checked in the free run.

    • cites [37] Raj, T. et al. Integrative transcriptome analyses of the aging brain implicate altered splicing in Alzheimer’s disease susceptibility. Nat. Genet. 50, 1584–1592 (2018). source
    • cites [38] Li, Y. I., Wong, G., Humphrey, J. & Raj, T. Prioritizing Parkinson’s disease genes using population-scale transcriptomic data. Nat. Commun. 10, 994 (2019). source

  • May combine two claims.

    Findingown data

    Multiple splicing QTLs were observed, some previously reported (CD33, FAM49B), and some unreported (MS4A6A, BST1).

    “We also observe multiple splicing QTLs, some previously reported (CD33, FAM49B), and some unreported (MS4A6A, BST1).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    PLAC-seq revealed long-range connections between the enhancer and the P2RY12 promoter but not to MED12L.

    “PLAC-seq56 revealed long-range connections between the enhancer and the P2RY12 promoter but not to MED12L (Fig. 6g).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [56] Nott, A. et al. Brain cell type-specific enhancer-promoter interactome maps and disease-risk association. Science 366, 1134–1139 (2019). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Downregulated genes were significantly enriched for cell motility, polarity, IL-6 cytokine signaling, and for genes also downregulated following in vitro culture and in AD-derived microglia.

    “The downregulated genes were significantly enriched for cell motility, polarity, IL-6 cytokine signaling (Fig. 3b), and for genes also downregulated following in vitro culture34 and in AD-derived microglia33 (Fig. 3c).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [34] Gosselin, D. et al. An environment-dependent transcriptional network specifies human microglia identity. Science 356, eaal3222 (2017). source

      Not checked in the free run.

    • cites [33] Srinivasan, K. et al. Alzheimer’s patient microglia exhibit enhanced aging and unique transcriptional activation. Cell Rep. 31, 107843 (2020). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    10 out of 17 genes colocalizing in AD, 8 out of 18 in PD, 4 out of 9 in SCZ, and 3 out of 17 in MS include SNPs that overlap with microglial enhancers.

    “We found that 10 out of 17 genes colocalizing in AD, 8 out of 18 in PD, 4 out of 9 in SCZ, and 3 out of 17 in MS include SNPs that overlap with microglial enhancers (Fig. 6a; Extended Data Fig. 7; Supplementary Fig. 20).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Between 67 and 199 genes had a cis-eQTL and 253 to 426 genes had a cis-sQTL per region.

    “In the region-specific analysis, we observed between 67 and 199 genes with a cis-eQTL (eGenes) and 253 to 426 genes with a cis-sQTL (sGenes) per region (FDR < 0.05; Supplementary Table 17, Supplementary Fig. 11).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Fine-mapping revealed that the lead GWAS SNP rs11707416 was suggested as a causal SNP by multiple fine-mapping tools and is in perfect LD (r2 = 1) with the lead QTL SNP rs3732765.

    “Fine-mapping revealed that the lead GWAS SNP rs11707416 was suggested as a causal SNP by multiple fine-mapping tools (a consensus SNP) and is in perfect LD (r2 = 1) with the lead QTL SNP rs3732765 (Fig. 6g).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The GWAS lead SNP and the QTL lead SNP are in moderate LD (r2 = 0.65), as are two of the three fine-mapped SNPs.

    “The GWAS lead SNP and the QTL lead SNP are in moderate LD (r2 = 0.65), as are two of the three fine-mapped SNPs (Fig. 6d; Supplementary Table 22).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Microglia from SVZ exhibited lower pairwise sharing of eQTLs with other regions, with the lowest sharing by magnitude between SVZ and MFG (41%).

    “Microglia from SVZ exhibited lower pairwise sharing of eQTLs with other regions, with the lowest sharing by magnitude observed between SVZ and MFG (41%), consistent with observed transcriptomic differences between these two regions.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    11% of MiGA eQTL colocalizations could be reproduced in Young et al. data, and 15% of Young et al. colocalizations could be found in MiGA data, at PP4 > 0.5, whereas sharing between two monocyte datasets was 17-24%.

    “Overall, 11% of MiGA eQTL colocalizations could be reproduced in the Young et al. data, and 15% of the Young et al. colocalizations could be found in the MiGA data, at a relaxed PP4 > 0.5, whereas sharing between the two monocyte datasets41,42 was 17–24% with the same parameters (Supplementary Fig. 13).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [41] Fairfax, B. P. et al. Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression. Science 343, 1246949 (2014). source

      Not checked in the free run.

    • cites [42] Navarro, E. et al. Dysregulation of mitochondrial and proteolysosomal genes in Parkinson’s disease myeloid cells. Nat. Aging 1, 850–863 (2021). source

  • May combine two claims.

    Findingown data

    In each disease there are genes that appear to be microglia-specific (BIN1, PYCR2), shared between microglia and monocytes (CASS4, CTSB), and shared between microglia and brain (ZNF646, P2RY12).

    “In each disease there are genes that appear to be microglia-specific (BIN1, PYCR2), shared between microglia and monocytes (CASS4, CTSB), and shared between microglia and brain (ZNF646, P2RY12).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The strongest colocalization signals highlighted a cluster of introns in the middle of MS4A6A, with the 5' intron in the cluster having the strongest colocalization.

    “We overlaid all sQTL junctions that colocalized with the AD risk locus and found that the strongest colocalization signals highlighted a cluster of introns in the middle of the gene, with the 5’ intron in the cluster having the strongest colocalization.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    P2RY12 is an eQTL (lead SNP rs3732765) identified in the METASOFT meta-analysis, with lead QTL SNP rs3732765-A decreasing P2RY12 expression.

    “P2RY12 is an eQTL (lead SNP rs3732765) identified in the METASOFT meta-analysis, with the lead QTL SNP rs3732765-A decreasing P2RY12 expression (Fig. 6e).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    AD and PD had the highest number of colocalizing loci in each QTL dataset compared to other diseases, with 10-30% of loci containing at least one colocalized gene, and lower proportions in BD, SCZ and MS.

    “AD and PD had the highest number of colocalizing loci in each QTL dataset, compared to the other diseases (Fig. 5a, Supplementary Table 21), with 10–30% of loci containing at least one colocalized gene, depending on the stringency of the H4 posterior probability (PP4), with lower proportions observed in BD, SCZ and MS.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    225 transcripts from 150 genes exhibited DTU with age, where the balance between a long and short isoform shifts over age.

    “Similarly, we found 225 transcripts from 150 genes exhibiting DTU with age (FDR < 0.1) (Extended Data Fig. 2a), where the balance between a long and short isoform shifts over age (Extended Data Fig. 2b).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Age-related downregulation was observed for C2, P2RY12, and P2RY13, key players in microglia-neuron interactions, as well as for genes related to age-related disorders: MS4A4A, MS4A6A, BST1 and P2RY12.

    “Of interest also are a downregulation of C2, P2RY12, and P2RY13, key players in microglia-neuron interactions63,64, as well as genes related to age-related disorders: MS4A4A, MS4A6A, BST1 and P2RY12.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [63] Badimon, A. et al. Negative feedback control of neuronal activity by microglia. Nature 586, 417–423 (2020). source

      Not checked in the free run.

    • cites [64] Savage, J. C. et al. Nuclear receptors license phagocytosis by TREM2+ myeloid cells in mouse models of Alzheimer’s disease. J. Neurosci. 35, 6532–6543 (2015). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    USP6NL harbors an expression QTL observed in all four microglial regions, with lead QTL SNP rs7912495-G increasing USP6NL expression.

    “USP6NL harbors an expression QTL observed in all four microglial regions, with the lead QTL SNP rs7912495-G increasing USP6NL expression (Fig. 6b).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    sQTLs showed overall higher regional sharing effects compared to eQTLs, but followed the same trends.

    “For sQTLs, we found overall higher regional sharing effects compared to eQTLs, but still following the same trends as for eQTLs (Fig. 4b, lower triangle).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingreasoning

    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.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [26] Young, A. M. H. et al. A map of transcriptional heterogeneity and regulatory variation in human microglia. Nat. Genet. 53, 861–868 (2021). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Transcription factor binding motif analysis was inconclusive, with three tested SNPs predicted to disrupt multiple motifs in different directions.

    “Transcription factor binding motif analysis was inconclusive, with three of the tested SNPs rs143807787, rs74347557, and rs7912495 predicted to disrupt multiple motifs in different directions (Supplementary Table 23).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    There are 4 other SNPs prioritized by fine-mapping, 2 of which were in perfect or very high LD with the lead QTL SNP.

    “In addition, there are 4 other SNPs prioritized by fine-mapping, 2 of which were in perfect or very high LD with the lead QTL SNP.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Specific disease colocalizations were identified that may not be captured in monocytes or bulk brain tissue, including BIN1, USP6NL, and PICALM in AD, P2RY12 in PD, PLXNB2 in MS, and IFRD1 in SCZ.

    “We have identified specific disease colocalizations that may not be captured in monocytes or bulk brain tissue, like BIN1, USP6NL, and PICALM in AD, P2RY12 in PD, PLXNB2 in MS, and IFRD1 in SCZ.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    For sQTL mapping, 5 PEER factors were optimal in MFG, STG and THA, and 0 PEER factors were used for SVZ.

    “We mapped sQTLs with between 0 and 20 PEER factors as covariates in our QTL model and determined 5 to be optimal in MFG, STG and THA. 0 PEER factors were used for SVZ (Supplementary Fig. 11).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    The 176 transcripts form 2 k-means clusters.

    “Transcripts form 2 k-means clusters”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Between 5 and 10 PEER factors produced the largest number of eGenes in each region.

    “We tested numbers of PEER factors from 0 to 20 and found that between 5 and 10 factors produced the largest number of eGenes in each region (Supplementary Fig. 11).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    There are 176 transcripts from pairwise comparisons of differential transcript usage between regions at empirical FDR < 0.1.

    “Heatmap of relative transcript usage between regions using all 176 transcripts from pairwise comparisons of differential transcript usage (DTU; empirical FDR < 0.1)”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Microglial functions vary across different ages, disease pathologies, and between sexes.

    “In addition, microglial functions vary across different ages, disease pathologies, and between sexes10–16.”
    Quote in the paperSubstantial claim0 of 7 sources checked
    • cites [10] Olah, M. et al. A transcriptomic atlas of aged human microglia. Nat. Commun. 9, 539 (2018). source

      Not checked in the free run.

    • cites [11] Mathys, H. et al. Single-cell transcriptomic analysis of Alzheimer’s disease. Nature 570, 332–337 (2019). source

      Not checked in the free run.

    • cites [12] Mrdjen, D. et al. High-dimensional single-cell mapping of central nervous system immune cells reveals distinct myeloid subsets in health, aging, and disease. Immunity 48, 599 (2018). source

      Not checked in the free run.

    • cites [13] Hammond, T. R. et al. Single-cell RNA sequencing of microglia throughout the mouse lifespan and in the injured brain reveals complex cell-state changes. Immunity 50, 253–271.e6 (2019). source

      Not checked in the free run.

    • cites [14] Keren-Shaul, H. et al. A unique microglia type associated with restricting development of Alzheimer’s disease. Cell 169, 1276–1290.e17 (2017). source

      Not checked in the free run.

    • cites [15] Masuda, T. et al. Author correction: spatial and temporal heterogeneity of mouse and human microglia at single-cell resolution. Nature 568, E4 (2019). source
    • cites [16] Galatro, T. F. et al. Transcriptomic analysis of purified human cortical microglia reveals age-associated changes. Nat. Neurosci. 20, 1162–1171 (2017). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Genetic risk can also be mediated through mRNA splicing.

    “In addition, it is becoming increasingly clear that genetic risk can also be mediated through mRNA splicing28,29.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [28] Li, Y. I. et al. RNA splicing is a primary link between genetic variation and disease. Science 352, 600–604 (2016). source

      Not checked in the free run.

    • cites [29] Raj, T. et al. CD33: increased inclusion of exon 2 implicates the Ig V-set domain in Alzheimer’s disease susceptibility. Hum. Mol. Genet. 23, 2729–2736 (2014). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    The CD33 locus in AD influences CD33 splicing, resulting in isoforms with different biological and likely pathological functions.

    “For instance, the CD33 locus in AD influences CD33 splicing, resulting in isoforms with different biological and likely pathological functions29.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [29] Raj, T. et al. CD33: increased inclusion of exon 2 implicates the Ig V-set domain in Alzheimer’s disease susceptibility. Hum. Mol. Genet. 23, 2729–2736 (2014). source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Microglia are highly dynamic cells strongly influenced by environmental signals, resulting in distinct phenotypes and functions across brain regions.

    “Microglia are highly dynamic cells that are strongly influenced by different environmental signals which result in distinct phenotypes and functions across brain regions4–9.”
    Quote in the paperSubstantial claim0 of 6 sources checked
    • cites [4] Tan, Y.-L., Yuan, Y. & Tian, L. Microglial regional heterogeneity and its role in the brain. Mol. Psychiatry 25, 351–367 (2020). source

      Not checked in the free run.

    • cites [5] van der Poel, M. et al. Transcriptional profiling of human microglia reveals grey–white matter heterogeneity and multiple sclerosis-associated changes. Nat. Commun. 10, 1139 (2019). source

      Not checked in the free run.

    • cites [6] Grabert, K. et al. Microglial brain region-dependent diversity and selective regional sensitivities to aging. Nat. Neurosci. 19, 504–516 (2016). source

      Not checked in the free run.

    • cites [7] De Biase, L. M. et al. Local cues establish and maintain region-specific phenotypes of basal ganglia microglia. Neuron 95, 341–356.e6 (2017). source

      Not checked in the free run.

    • cites [8] Soreq, L. et al. Major shifts in glial regional identity are a transcriptional hallmark of human brain aging. Cell Rep. 18, 557–570 (2017). source

      Not checked in the free run.

    • cites [9] Masuda, T. et al. Spatial and temporal heterogeneity of mouse and human microglia at single-cell resolution. Nature 566, 388–392 (2019). source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Changes in microglial density, morphology, and transcriptional state have been observed in postmortem brain tissue of patients with neurological and psychiatric disorders.

    “For decades, changes in microglial density, morphology, and transcriptional state have been observed in postmortem brain tissue of patients with neurological and psychiatric disorders17–21.”
    Quote in the paperNot a substantial claim0 of 5 sources checked
    • cites [17] McGeer, P. L. et al. Microglia in degenerative neurological disease. Glia 7, 84–92 (1993). source
    • cites [18] Kreutzberg, G. W. Microglia: a sensor for pathological events in the CNS. Trends Neurosci. 19, 312–318 (1996). source
    • cites [19] Trépanier, M. O., Hopperton, K. E., Mizrahi, R., Mechawar, N. & Bazinet, R. P. Postmortem evidence of cerebral inflammation in schizophrenia: a systematic review. Mol. Psychiatry 21, 1009–1026 (2016). source

      Not checked in the free run.

    • cites [20] Hopperton, K. E., Mohammad, D., Trépanier, M. O., Giuliano, V. & Bazinet, R. P. Markers of microglia in post-mortem brain samples from patients with Alzheimer’s disease: a systematic review. Mol. Psychiatry 23, 177–198 (2018). source

      Not checked in the free run.

    • cites [21] Parikshak, N. N. et al. Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism. Nature 540, 423–427 (2016). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    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.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [26] Young, A. M. H. et al. A map of transcriptional heterogeneity and regulatory variation in human microglia. Nat. Genet. 53, 861–868 (2021). source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    There was no colocalization of the upstream ECHDC3 gene in any tested cell type, suggesting that USP6NL is the AD risk gene at this locus.

    “Notably, there was no colocalization of the upstream ECHDC3 gene in any tested cell type, suggesting that USP6NL is the AD risk gene at this locus.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The CD33 risk locus has been implicated in AD susceptibility.

    “The CD33 risk locus has been implicated in AD susceptibility59.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [59] Böttcher, C. et al. Human microglia regional heterogeneity and phenotypes determined by multiplexed single-cell mass cytometry. Nat. Neurosci. 22, 78–90 (2019). source

  • May combine two claims.

    Interpretationown data

    The transcriptomic profile of SVZ is most distinct, likely explaining the most region-specific effects.

    “Microglia from the SVZ had the most region-specific effects with 1,045, most likely because the transcriptomic profile of this region is most distinct (Supplementary Table 20).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    These results highlight shared genetic regulation between microglia and monocytes, which is only partly captured in whole-tissue brain data.

    “Together, these results highlight shared genetic regulation between microglia and monocytes, which is only partly captured in whole-tissue brain data22.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [22] Raj, T. et al. Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes. Science 344, 519–523 (2014). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The ECHDC3 locus has been associated with AD risk in several GWAS.

    “The ECHDC3 locus has been associated with AD risk in several GWAS23,46,49.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [23] Kunkle, B. W. et al. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat. Genet. 51, 414–430 (2019). source

      Not checked in the free run.

    • cites [46] Marioni, R. E. et al. GWAS on family history of Alzheimer’s disease. Transl. Psychiatry 8, 99 (2018). source

      Not checked in the free run.

    • cites [49] Jansen, I. E. et al. Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer’s disease risk. Nat. Genet. 51, 404–413 (2019). source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    Transcriptional heterogeneity in human microglia varies between brain regions and across aging.

    “We demonstrate that transcriptional heterogeneity in human microglia varies between brain regions and across aging.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    P2RY12 expression is lost upon microglia activation and culture.

    “P2RY12 expression is lost upon microglia activation74, culture34”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [74] Haynes, S. E. et al. The P2Y12 receptor regulates microglial activation by extracellular nucleotides. Nat. Neurosci. 9, 1512–1519 (2006). source
    • cites [34] Gosselin, D. et al. An environment-dependent transcriptional network specifies human microglia identity. Science 356, eaal3222 (2017). source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    The fine-mapping approach allowed identification of candidate functional variants in multiple disease susceptibility loci that modulate microglia-specific enhancer activity and regulate causal gene expression, which likely modify disease risk by altering microglial function.

    “This approach allowed us to identify candidate functional variants in multiple disease susceptibility loci that modulate microglia-specific enhancer activity and regulate causal gene expression, which in turn likely modify disease risk by altering the function of microglia (or other myeloid cells) in the brain.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    The microglial phenotype ages in a generally uniform manner across brain regions, with a distinct aging trajectory observed in a minority of genes.

    “Together, our results indicate that the microglial phenotype ages in a generally uniform manner across brain regions, with a distinct aging trajectory observed in a minority of genes.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Regional and age-related differences in microglial density, morphology, gene, and protein expression have previously been described for both animals and humans.

    “Regional and age-related differences in microglial density, morphology, gene, and protein expression have previously been described for both animals and humans5,6,9,60,61.”
    Quote in the paperNot a substantial claim0 of 5 sources checked
    • cites [5] van der Poel, M. et al. Transcriptional profiling of human microglia reveals grey–white matter heterogeneity and multiple sclerosis-associated changes. Nat. Commun. 10, 1139 (2019). source

      Not checked in the free run.

    • cites [6] Grabert, K. et al. Microglial brain region-dependent diversity and selective regional sensitivities to aging. Nat. Neurosci. 19, 504–516 (2016). source

      Not checked in the free run.

    • cites [9] Masuda, T. et al. Spatial and temporal heterogeneity of mouse and human microglia at single-cell resolution. Nature 566, 388–392 (2019). source
    • cites [60] Mittelbronn, M., Dietz, K., Schluesener, H. J. & Meyermann, R. Local distribution of microglia in the normal adult human central nervous system differs by up to one order of magnitude. Acta Neuropathol. 101, 249–255 (2001). source
    • cites [61] Olah, M. et al. Identification of a microglia phenotype supportive of remyelination. Glia 60, 306–321 (2012). source

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    Splicing QTLs are less cell type-specific, presumably due to association with distinct types of regulatory elements.

    “This suggests that splicing QTLs are less cell type-specific, presumably due to the association with distinct types of regulatory elements.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    We generated a catalog of eQTLs and sQTLs in microglia and thereby validated and extended the list of disease genes and putative causal variants underlying risk for neurodegenerative and psychiatric diseases.

    “We generated a catalog of eQTLs and sQTLs in microglia and thereby validated and extended the list of disease genes and putative causal variants underlying risk for neurodegenerative and psychiatric diseases.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Previous analyses in peripheral monocytes found association between lead GWAS SNP rs3865444 and inclusion of CD33 exon 2.

    “Previous analyses in peripheral monocytes found association between lead GWAS SNP rs3865444 and the inclusion of CD33 exon 259.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [59] Böttcher, C. et al. Human microglia regional heterogeneity and phenotypes determined by multiplexed single-cell mass cytometry. Nat. Neurosci. 22, 78–90 (2019). source

  • May combine two claims.

    Interpretationreasoning

    Increased usage of this intron may result in increased production of shorter isoforms, which could have a downstream consequence on MS4A6A protein function.

    “rs2162254-A is associated with an increased usage of this intron, which may result in increased production of the shorter isoforms, which could have a downstream consequence on MS4A6A protein function.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    A previous study prioritized P2RY12 at this locus due to an overlap with eQTLs in blood and brain.

    “A previous study prioritized P2RY12 at this locus due to an overlap with eQTLs in blood and brain57.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [57] Grenn, F. P. et al. The Parkinson’s disease genome-wide association study locus browser. Mov. Disord. 35, 2056–2067 (2020). source

  • May combine two claims.

    Interpretationown data

    We have generated an atlas of genetic effects on the human microglia transcriptome, which allowed us to identify potential causal genes and variants underlying risk for neurodegenerative and psychiatric diseases.

    “We have generated an atlas of genetic effects on the human microglia transcriptome, which allowed us to identify potential causal genes and variants underlying risk for neurodegenerative and psychiatric diseases.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    The investigators were not blinded for group allocation (diagnosis, sex, age etc.) during data analysis.

    “The investigators were not blinded for group allocation (diagnosis, sex, age etc.) during data analysis since adjustment for these factors was necessary for the data analyses.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    All autopsies were performed with written consent from the legal next-of-kin.

    “All autopsies were performed with written consent from the legal next-of-kin.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Our ability to detect additional disease-associated eQTLs may be obscured due to the use of bulk RNA-sequencing data.

    “Furthermore, our ability to detect additional disease-associated eQTLs may be obscured due to the use of bulk RNA-sequencing data.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationreasoning

    Our findings represent mechanistic hypotheses that can now be tested with further experimental work at both the level of individual variants and the candidate genes.

    “Our findings represent mechanistic hypotheses that can now be tested with further experimental work at both the level of individual variants and the candidate genes.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    The study included 100 donors with ages ranging from 21 to 103 years.

    “The age range of the 100 donors is between 21 and 103 years old”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Besides neuroinflammation, hypoxia, and long postmortem intervals, technical artifacts (enzymatic digestion, temperature changes, sorting) may cause microglial activation.

    “Besides neuroinflammation, hypoxia, and long postmortem intervals, technical artifacts (enzymatic digestion, temperature changes, sorting) may cause microglial activation.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Of the 100 donors, 58 were female.

    “58 of them were female”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductnone given

    Microglial cells were sorted with CD11b+ beads, a marker not restricted to microglia that may capture small fractions of other myeloid cells.

    “We sorted the microglial cells with CD11b+ beads. This marker is not restricted to microglia and may capture small fractions of other myeloid cells.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductreasoning

    We increased power by combining the four regions in a meta-analysis, with the caveat of not adjusting for shared donors, which will have increased our false discovery rate.

    “We increased power by combining the four regions in a meta-analysis, with the caveat of not adjusting for shared donors, which will have increased our false discovery rate.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The study was performed under IRB-approved guidance and regulations to keep all patient information strictly de-identified.

    “The study was performed under IRB-approved guidance and regulations to keep all patient information strictly de-identified.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given

    RNA-seq quality control was performed applying filters to remove samples with less than 10M reads aligned from STAR, more than 20% of reads aligned to ribosomal regions, less than 10% of reads mapping to coding regions, or from brain regions with fewer than 20 donors.

    “RNA-seq quality control was performed applying filters to remove samples: 1) samples with less than 10M reads aligned from STAR; 2) samples with more than 20% of the reads aligned to ribosomal regions; 3) samples with less than 10% of the reads mapping to coding regions; 4) samples from brain regions with fewer than 20 donors.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given

    Permission to collect human brain material was obtained from the Ethical Committee of the VU University Medical Center, Amsterdam, The Netherlands, and the Mount Sinai Institutional Review Board (IRB).

    “The permission to collect human brain material was obtained from the Ethical Committee of the VU University Medical Center, Amsterdam, The Netherlands, and the Mount Sinai Institutional Review Board (IRB).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    All research conformed to the principles of the Helsinki Declaration.

    “All research conformed to the principles of the Helsinki Declaration.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductcitation

    Duplicated and up to third-degree related samples were removed based on pairwise kinship coefficients estimated using KING.

    “Duplicated and up to third-degree related samples were removed based on pairwise kinship coefficients estimated using KING97 (Supplementary Fig. 10a).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [97] Chang, C. C. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7 (2015). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    All analyses were adjusted for age, gender, and other covariates.

    “All analyses were adjusted for age, gender, and other covariates.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    In total, 59 out of 314 samples were excluded due to insufficient RNA-seq quality or insufficient sample size by brain region.

    “In total, 59 out of 314 samples were excluded due to insufficient RNA-seq quality or insufficient sample size by brain region.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    P2RY12 has been shown to play a role in microglia migration, activation, and neuronal activity.

    “P2RY12 has been shown to play a role in microglia migration, activation, and neuronal activity64,75.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [64] Savage, J. C. et al. Nuclear receptors license phagocytosis by TREM2+ myeloid cells in mouse models of Alzheimer’s disease. J. Neurosci. 35, 6532–6543 (2015). source

      Not checked in the free run.

    • cites [75] Marsh, S. E. et al. Single cell sequencing reveals glial specific responses to tissue processing & enzymatic dissociation in mice and humans. Preprint at bioRxiv https://doi.org/10.1101/2020.12.03.408542 (2020). source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Informed consent for autopsy, the use of brain tissue and accompanied clinical information for research purposes was obtained per donor ante-mortem.

    “Informed consent for autopsy, the use of brain tissue and accompanied clinical information for research purposes was obtained per donor ante-mortem.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductown data

    DNA samples were matched to the RNA-seq data to confirm the same donor origin, and sex mismatching samples were removed.

    “DNA samples were matched to the RNA-seq data to confirm the same donor origin using the MBV tool from QTLtools98 (Supplementary Fig. 10b) and sex mismatching samples were removed by comparing DNA inferred sex from PLINK to RNA gene expression of the UTY and XIST genes (Supplementary Fig. 10c).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [98] Das, S. et al. Next-generation genotype imputation service and methods. Nat. Genet. 48, 1284–1287 (2016). source

  • May combine two claims.

    Study design and conductreasoning

    We could not control for all these potential confounders, even though these factors could contribute to gene expression changes.

    “We could not control for all these potential confounders, even though these factors could contribute to gene expression changes76,77.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [76] Mattei, D. et al. Enzymatic dissociation induces transcriptional and proteotype bias in brain cell populations. Int. J. Mol. Sci. 21, 7944 (2020). source
    • cites [77] Lee, M. N. et al. Common genetic variants modulate pathogen-sensing responses in human dendritic cells. Science 343, 1246980 (2014). source

  • Classified as probably not a substantial claim.

    Study design and conductown data

    An initial genotyping quality control was applied, keeping SNPs with call rate > 95%, MAF > 5%, HWE P-value > 1 × 10−6, and sample call rate > 95%.

    “To select high-quality data, we applied an initial genotyping quality control using bcftools (v1.9) and vcftools (v0.1.15), keeping SNPs with call rate > 95%, minor allele frequency (MAF) > 5%, Hardy-Weinberg equilibrium (HWE) P-value > 1 × 10−6, and sample call rate > 95%.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Genetic ancestry of samples was confirmed by principal components analysis and MDS values compared to 1000 Genome Project samples.

    “Genetic ancestry of samples was confirmed by principal components analysis using the PLINK program99 and MDS (multidimensional scaling) values of study subjects were compared to those of 1000 Genome Project samples (Phase 3) (Supplementary Fig. 10d).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [99] Loh, P.-R. et al. Reference-based phasing using the Haplotype Reference Consortium panel. Nat. Genet. 48, 1443–1448 (2016). source
84 of 84

  • The paper relies on this without support.

    Investigations of QTLs in microglia have been limited by the availability of microglial samples from the number of subjects required to perform well-powered genomic analyses.

    “Investigations of QTLs in microglia have been limited by the availability of microglial samples from the number of subjects required to perform well-powered genomic analyses.”

  • The paper relies on this without support.

    Most of the common variants that have been identified are located outside protein-coding regions.

    “This is a complicated task, as most of the common variants that have been identified are located outside protein-coding regions.”

  • The paper relies on this without support.

    These variants influence gene expression through complex regulatory mechanisms, such as altering enhancer activity, which often affect a gene beyond the nearest gene.

    “These variants influence gene expression through complex regulatory mechanisms, such as altering enhancer activity, which often affect a gene beyond the nearest gene.”

  • The paper relies on this without support.

    P2RY12 is highly expressed in microglia in comparison to other brain and myeloid cell types.

    “P2RY12 is one of the P2Y metabotropic G-protein-coupled purinergic receptors, which is highly expressed in microglia in comparison to other brain and myeloid cell types.”

  • The paper relies on this without support.

    P2RY12 is one of the P2Y metabotropic G-protein-coupled purinergic receptors.

    “P2RY12 is one of the P2Y metabotropic G-protein-coupled purinergic receptors, which is highly expressed in microglia in comparison to other brain and myeloid cell types.”

  • The paper relies on this without support.

    The AD risk association with CD33 exon 2 splicing is known.

    “By mapping sQTLs we have shown that the known AD risk association with CD33 exon 2 splicing is also present in microglia, and added disease associations that may act through splicing, such as MS4A6A in AD, SIPA1L2 and FAM49B in PD, IRF3 in SCZ, STK4 and GMIP in BD, and CD37 and EFCAB13 in MS.”
6 of 6

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?

  • Very few transcriptomic studies provide information on acute premortem variables or cause of death, which may potentially have a much larger effect on RNA quality and gene expression.

    “Additionally, very few transcriptomic studies provide information on acute premortem variables or cause of death, which are particularly important as they may potentially have a much larger effect on RNA quality and gene expression71–76,78–80.”

    From Dissection of artifactual and confounding glial signatures by single-cell sequencing of mouse and human brain (2022) · cites this paper as [80]

    The Discussion (page unavailable) says pre- and post-mortem factors affect the microglial transcriptome, and Methods > Sources of transcriptomic variation (page unavailable) includes cause of death among the covariates examined. The paper does not establish that very few transcriptomic studies report acute premortem variables or cause of death, or that these variables have a much larger effect on RNA quality and gene expression. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • The directional effect of the AD risk allele of rs10792832 on PICALM expression was consistent with other hMG eQTL findings.

    “The directional effect of the AD risk allele of rs10792832 on PICALM expression was consistent with other hMG eQTL findings8,9,25.”

    From PICALM Alzheimer’s risk allele causes aberrant lipid droplets in microglia (2025) · cites this paper as [8]

    The Results sections on genetic regulatory effects and disease loci identify PICALM as an AD-associated microglial eQTL and report that PICALM colocalization was shared with a previously published microglial dataset. They do not identify rs10792832 or state the direction of its AD risk allele’s effect on PICALM expression, so the specific directional-consistency claim is not established. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

  • Alzheimer's disease risk loci are enriched in genes expressed in myeloid cells, including microglia.

    “Recent human genetic studies revealed that Alzheimer's disease risk loci are enriched in genes expressed in myeloid cells, including microglia, the brain's resident immune cells.”

    From Targeting Microglial Transcriptional Reprogramming as a Therapy Strategy for Alzheimer's Disease (2026) · cites this paper as [6]

    The Introduction identifies microglia as myeloid immune cells and says genetic evidence suggests some neurological disease risk acts through myeloid cells. The Results report Alzheimer’s disease risk loci that colocalize with microglial gene-expression signals, but do not establish that Alzheimer’s risk loci are enriched in genes expressed in myeloid cells. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Many AD risk genes are primarily expressed in microglia.

    “Most notably, these genetic studies implicate central roles for the innate immune system, with many AD risk genes being primarily expressed in microglia (Efthymiou and Goate, 2017; Karch and Goate, 2015; Lopes et al., 2022).”

    From Alzheimer’s genetic risk factor CASS4 controls microglial focal adhesion biology and amyloidosis (2026) · cites this paper as Lopes et al., 2022

    The Results section ('Neurological disease loci regulate microglia gene expression'; page not available) links multiple AD-associated genes to microglial regulatory regions and reports that the candidate AD risk gene USP6NL is expressed more highly in microglia than in monocytes. It does not establish that many AD risk genes are primarily expressed in microglia rather than other cell types. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

  • Lowering APOE levels may confer protection against AD.

    “Previous studies suggest that lowering APOE levels may confer protection against AD56–59.”

    From Deletion of SPI1 in microglia exacerbates amyloid pathology by impairing microglial response in Alzheimer’s disease models (2026) · cites this paper as [59]

    The Results section links altered microglial gene expression to Alzheimer’s disease risk, but its specific example concerns USP6NL, not APOE. Searches for APOE and for lowered APOE expression found no passage in our copy saying that lowering APOE levels may protect against Alzheimer’s disease. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

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Authors
Lopes, K. D. P., Snijders, G. J. L., Humphrey, J., Allan, A., Sneeboer, M. A. M., Navarro, E., Schilder, B. M., Vialle, R. A., Parks, M., Missall, R., van Zuiden, W., Gigase, F. A. J., Kübler, R., van Berlekom, A. B., Hicks, E. M., Bӧttcher, C., Priller, J., Kahn, R. S., de Witte, L. D., & Raj, T.
Affiliations
  • James J. Peters VA Medical Center (US)
  • Icahn School of Medicine at Mount Sinai (US)
  • Utrecht University (NL)
  • Charité – Universitätsmedizin Berlin (DE)
Corresponding author
Raj, Towfique
ORCID
Venue
Nature Genetics
Publisher
Springer Science and Business Media LLC
Published
2022-01
Volume
54
Issue
1
Pages
4-17
ISSN
  • 1061-4036 (ISSN-L)
  • 1546-1718
DOI
10.1038/s41588-021-00976-y
PMC
PMC9245609
OpenAlex
W4205777871
Cited by
273
References
127
Citations by year
2026: 57 · 2025: 58 · 2024: 68 · 2023: 46 · 2022: 37 · 2021: 7
FWCI
5.89
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Genetics (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
Funders
  • Icahn School of Medicine at Mount Sinai (S10OD026880)
  • Stichting de Drie Lichten
  • ZonMw
  • National Institutes of Health (1r21ag063130-01a1, 1s10od026880-01, 1rf1ag065926-01a1, 1r56ag055824-01a1)
  • Medical Research Council (MC_PC_16031)
  • National Institute on Aging (R21-AG063130, U01AG068880, NIA R21-AG063130, R01AG054005, R56- AG055824, RF1-AG065926)
  • National Institute of Neurological Disorders and Stroke (U01NS107016, R01NS116006)
Topics
  • Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords
microglia, brain aging, splicing quantitative trait loci, expression quantitative trait loci, microglial heterogeneity, Alzheimer's disease, Parkinson's disease, P2Y12 receptor, mental illness, sex differences
MeSH terms
Aging, Alzheimer Disease, Atlases as Topic, Brain, Female, Humans, Male, Parkinson Disease, RNA Splicing, Microglia, Genetic Heterogeneity, Genetic Predisposition to Disease, Gene Expression Profiling, Quantitative Trait Loci, Transcriptome, Datasets as Topic

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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.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-11-06.

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