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Cited by 509Alzheimer's disease research and treatmentsDementia and Cognitive Impairment ResearchBioinformatics and Genomic Networks

A molecular network of the aging human brain provides insights into the pathology and cognitive decline of Alzheimer’s disease

Open access
Mostafavi, Sara, Gaiteri, Chris, Sullivan, Sarah E., White, Charles C., Tasaki, Shinya, Xu, Jishu, Taga, Mariko, Klein, Hans-Ulrich +13 more·2018·Nature Neuroscience
DOI 10.1038/s41593-018-0154-9PMC PMC6599633

Published version of a preprint

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Abstract

There is a need for new therapeutic targets with which to prevent Alzheimer’s disease (AD), a major contributor to aging-related cognitive decline. Here we report the construction and validation of a molecular network of the aging human frontal cortex. Using RNA sequence data from 478 individuals, we first build a molecular network using modules of coexpressed genes and then relate these modules to AD and its neuropathologic and cognitive endophenotypes. We confirm these associations in two independent AD datasets. We also illustrate the use of the network in prioritizing amyloid- and cognition-associated genes for in vitro validation in human neurons and astrocytes. These analyses based on unique cohorts enable us to resolve the role of distinct cortical modules that have a direct effect on the accumulation of AD pathology from those that have a direct effect on cognitive decline, exemplifying a network approach to complex diseases. The authors constructed and validated a molecular network of the aging human cortex from RNA sequencing data from 478 individuals and identified genes that affect cognitive decline or neuropathology in Alzheimer’s disease.

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Claims the paper makes

0 of 26 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    Using the π1 statistic, 55-90% of associated genes are shared among correlated Alzheimer's disease-related traits.

    “Overall, using the π1 statistic20, we estimated that 55–90% of the associated genes are shared amongst these correlated AD-related (Figure S2).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [20] Gaiteri, C. et al. Identifying robust communities and multi-community nodes by combining top-down and bottom-up approaches to clustering. Sci. Rep. 5, 16361 (2015). source

      Not checked in the free run.

  • Findingown data

    Expression levels of thousands of genes associate with Alzheimer's disease-related traits at FDR<0.05.

    “We found that the expression levels of thousands of genes associate (FDR<0.05) with these traits (Table S2; Figure 2A).”
    Quote in the paperSubstantial claim
  • Findingown data

    Applying SpeakEasy consensus clustering to the RNA-Seq data identified 47 mutually exclusive modules ranging in size from 20 to 556 gene members.

    “we applied the SpeakEasy consensus clustering algorithm21 to our RNA-Seq data and identified 47 mutually exclusive modules ranging in size between 20 and 556 gene members (Table S3; Figure S3; Supplementary methods).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [21] Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9, 559 (2008). source

      Not checked in the free run.

  • Findingown data

    29 (62%) of the 47 modules were enriched for at least one GO functional category (Bonferroni p<0.01).

    “we find that 29 (62%) of the modules were enriched for at least one GO functional category (Bonferroni p<0.01, Table S5)”
    Quote in the paperNot a substantial claim
  • Findingown data

    45 of 47 modules showed significant preservation in an independent DLPFC microarray dataset of 229 persons with pathologic and clinical Alzheimer's disease.

    “we observed significant evidence for preservation in 45 of the 47 modules in the independent microarray dataset”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [12] Zhang, B. et al. Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer’s disease. Cell 153, 707–720 (2013). source

      Not checked in the free run.

  • Classified as probably not a substantial claim. 18
  • May combine two claims. 22

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

    Findingown data

    The clustering assignment from SpeakEasy overlapped significantly with WGCNA.

    “We note that the clustering assignment identified by the SpeakEasy algorithm overlapped significantly with those proposed by the frequently used WGCNA algorithm22 (Supplementary methods; Table S4)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [22] Langfelder, P., Luo, R., Oldham, M. C. & Horvath, S. Is my network module preserved and reproducible? PLOS Comput. Biol. 7, e1001057 (2011). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    The module-trait associations were confirmed in two independent Alzheimer's disease datasets and in epigenomic data.

    “We confirm these associations in two independent AD datasets as well as in epigenomic data.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The other 21 Alzheimer's disease susceptibility variants together explain 2.1% of ClinAD and 7.6% of cognitive decline.

    “Subsequent inclusion of the other 21 AD susceptibility variants to represent the known genetic architecture of AD only explains 2.1% of ClinAD and 7.6% of cognitive decline.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    APOE ε4 explains only 2.2% of variance in ClinAD and 5.1% of variance in cognitive decline.

    “but even this unique genetic risk factor explains little of the variance in ClinAD (2.2% variance explained) or cognitive decline (5.1% variance explained).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    After accounting for INPPL1 and PLXNB1, some effect of m109 remains for β-amyloid (0.95% variance, p=0.029) and more of the effect on cognitive decline persists (3.5% variance, p=2.7e-5).

    “after accounting for INPPL1 and PLXNB1, we see that some of the effect of m109 remains for β-amyloid (0.95% variance, p=0.029), and more of the effect on cognitive decline persists (3.5% variance, p=2.7×10−5).”
    Quote in the paperSubstantial claim

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

    Findingown data

    m109 consists of 390 genes with diverse functions.

    “It consists of 390 genes with diverse functions.”
    Quote in the paperNot a substantial claim

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

    Findingown data

    AKT is a member of the m109 module.

    “and AKT is also a member of the m109 module.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    INPPL1 explains 5.5% of variance in cognitive decline; PLXNB1 explains 4.4%; together they explain 5.4% (adjusted R2).

    “The effect of INPPL1 and PLXNB1 is somewhat stronger on cognitive decline: 5.5% of variance is explained by INPPL1, 4.4% for PLXNB1, and 5.4% (adjusted R2) for both.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Module m116 is enriched for genes near AD variants (p=0.0018 by INRICH) and mostly contains microglial genes.

    “We also assessed whether any of the modules are enriched for genes found in the vicinity of AD variants (nearest genes, as previously reported4) and found one enriched module, m116, (p=0.0018 using the INRICH algorithm33) which mostly contains microglial genes (Table S6).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [33] Chibnik, L. B. et al. CR1 is associated with amyloid plaque burden and age-related cognitive decline. Ann. Neurol. 69, 560–569 (2011). source

      Not checked in the free run.

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

    Findingnone given

    INPPL1 and PLXNB1 are also expressed in other cell types, such as neurons.

    “These genes also are expressed in other cell types, such as neurons”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Modules enriched for immunity, mitochondria, cell cycle, and transcriptional regulation show positive correlation with β-amyloid, Alzheimer's disease, and cognitive decline, while neuronal or synaptic modules show negative correlation.

    “In general, modules enriched for GO categories related to immunity, mitochondria, cell cycle and transcriptional regulation show a positive correlation with β-amyloid, AD and cognitive decline, while modules for neuronal or synaptic function showed a negative correlation.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The m109 meta-feature explains 4.3% of variance in β-amyloid burden and 8.5% of variance in cognitive decline.

    “The m109 meta-feature explains 4.3% variance in β-amyloid burden and 8.5% variance in cognitive decline”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    INPPL1 accounts for 2.8% of variance in β-amyloid load; PLXNB1 accounts for 3.1%; together they explain 3.1% (adjusted R2).

    “Separately, they each account for a small proportion of the variance in β-amyloid load - 2.8% for INPPL1 and 3.1% for PLXNB1 – and, as is anticipated from the network model, are largely redundant as, together, they explain 3.1% (adjusted R2) of the variance in β-amyloid load (Figure 5D).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    INPPL1 and PLXNB1 are directly connected to one another and are two major hubs in the m109 coexpression network.

    “are directly connected to one another and are two of the major hubs in the m109 coexpression network (Figure 4B).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In this dataset, m116 shows no direct association with cognitive decline, AD pathology, or AD dementia.

    “However, m116 is not directly associated with cognitive decline, AD pathology, or AD dementia in this dataset (Table S7).”
    Quote in the paperNot a substantial claim

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

    Premisecitation

    Coexpressed gene sets represent the outcome of transcriptional regulatory mechanisms including transcription factors, chromatin conformation, and latent factors such as cell type proportions.

    “Coexpressed gene sets represent the outcome of transcriptional regulatory mechanisms that include transcription factors, chromatin conformation and latent factors that generate correlations, such as the proportion of different cell types present in the sampled tissue10.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [10] Gaiteri, C., Ding, Y., French, B., Tseng, G. C. & Sibille, E. Beyond modules and hubs: the potential of gene coexpression networks for investigating molecular mechanisms of complex brain disorders. Genes Brain Behav. 13, 13–24 (2014). source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    Known Alzheimer's disease susceptibility variants capture only a small fraction of the disease biology, much of which may be influenced by non-genetic risk factors.

    “Thus, while these robustly validated susceptibility variants provide important insights into risk factors that contribute to AD, they capture only a small fraction of the biology of the disease, much of which may be influenced by non-genetic risk factors.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    RNA-Seq data were normalized to account for many known biological and technical confounding factors.

    “RNA-Seq data were then normalized to account for the effect of a large number of known biological and technical confounding factors (Supplementary Methods; Figure S1).”
    Quote in the paperSubstantial claim

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

    Premisecitation

    PLXNB1 is a member of a family of proteins that mediate Semaphorin signalling, which plays a role in neuronal processes including neurite outgrowth, remodelling and synaptic plasticity.

    “PLXNB1 is a member of a family of proteins that mediate Semaphorin signalling, which plays a role in a number of neuronal processes including neurite outgrowth, remodelling and synaptic plasticity35.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [35] Suwa, A., Kurama, T. & Shimokawa, T. SHIP2 and its involvement in various diseases. Expert Opin. Ther. Targets 14, 727–737 (2010). source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Transgenic mice overexpressing INPPL1 show disruption in insulin/IGF1 signalling via AKT in cultured neurons, and these mice show impaired memory.

    “Transgenic mice overexpressing INPPL1 show a disruption in insulin/IGF1 signalling mediated via AKT in cultured neurons, and these mice show impaired memory37.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [37] Talbot, K. et al. Demonstrated brain insulin resistance in Alzheimer’s disease patients is associated with IGF-1 resistance, IRS-1 dysregulation, and cognitive decline. J. Clin. Invest. 122, 1316–1338 (2012). source

      Not checked in the free run.

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

    Premisecitation

    APOE ε4 is known to associate with accumulation of β-amyloid pathology and cognitive decline.

    “consistent with this haplotype’s known associations with accumulation of β-amyloid pathology and cognitive decline29.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [29] Beecham, G. W. et al. Genome-wide association meta-analysis of neuropathologic features of Alzheimer’s disease and related dementias. PLoS Genet. 10, e1004606 (2014). source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    The five validations indicate that gene membership of the modules is reproducible and biologically meaningful.

    “Each of these 5 validations in parallel and orthogonal datasets indicates that gene membership of these modules is reproducible and biologically meaningful.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    The identified processes differ from and complement those from GWAS-derived genes, because GWAS-derived SNPs have limited effects on gene expression here.

    “These processes are different and complementary to those identified by GWAS-derived genes, as the effect of GWAS-derived SNPs on gene expression in this case is limited.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: GWAS-derived SNPs have limited effects on gene expression in this case.

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

    Premisecitation

    Levels of posttranslationally modified IGF1 receptor were positively related to β-amyloid and negatively related to episodic and working memory, after adjusting for AD pathology.

    “Specifically, levels of postranslationally modified forms of the IGF1 receptor were positively related to β-amyloid and negatively related to episodic and working memory, after adjusting for AD pathology.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [38] Schneider, J. A. et al. Cognitive impairment, decline and fluctuations in older community-dwelling subjects with Lewy bodies. Brain 135, 3005–3014 (2012). source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductreasoning

    The identification of cell type-specific modules enabled the authors to guide functional validation and to model and account for changes in cell type composition.

    “the identification of “cell type-specific modules” enabled us to guide functional validation efforts and to comprehensively model and account for changes in cell type composition that may drive large-scale transcriptomic changes in AD at the bulk tissue level.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    The H3K9Ac histone mark is found near active transcription start sites and enhancers.

    “The H3K9Ac histone mark is found near active transcription start sites and enhancers24”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [24] Matarin, M. et al. A genome-wide gene-expression analysis and database in transgenic mice during development of amyloid or tau pathology. Cell Rep. 10, 633–644 (2015). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductown data

    The Bayesian network included four modules representing proportions of four major brain cell types to account for effects of changes in cell population frequencies.

    “We also included four modules representing the proportions of four major brain cell types - microglia, astrocytes, oligodendrocytes, and neurons – to account for the effects of changes in cell population frequencies (Supplementary methods).”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Prior work found decreased response to IGF1 in brains from persons with MCI and AD dementia relative to controls, regardless of diabetes status.

    “In prior work, we found evidence of decreased response to insulin growth factor 1 (IGF1) in brains from persons with mild cognitive impairment and AD dementia relative to controls, regardless of diabetes status.38”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [38] Schneider, J. A. et al. Cognitive impairment, decline and fluctuations in older community-dwelling subjects with Lewy bodies. Brain 135, 3005–3014 (2012). source

      Not checked in the free run.

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

    Premisecitation

    The 21 common Alzheimer's disease variants displayed very little or no association with neuropathologic features of Alzheimer's disease in earlier studies.

    “which, in earlier studies, displayed very little or no association with neuropathologic features of AD30,31.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [30] Farfel, J. M. et al. Relation of genomic variants for Alzheimer disease dementia to common neuropathologies. Neurology 87, 489–496 (2016). source

      Not checked in the free run.

    • cites [31] Battle, A. et al. Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals. Genome Res. 24, 14–24 (2014). source

      Not checked in the free run.

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

    Premisecitation

    Polymorphisms in INPPL1 are associated with type 2 diabetes mellitus.

    “polymorphisms in the INPPL1 gene are associated with type 2 diabetes mellitus (T2D)36.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [36] Soeda, Y. et al. The inositol phosphatase SHIP2 negatively regulates insulin/IGF-I actions implicated in neuroprotection and memory function in mouse brain. Mol. Endocrinol. 24, 1965–1977 (2010). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    The SpeakEasy algorithm has state-of-the-art performance on benchmark and real-world datasets.

    “we chose to use SpeakEasy because of its state-of-the-art performance on benchmark and real-world datasets21.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [21] Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9, 559 (2008). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    Coacetylation would be expected for genes coexpressed at the RNA level.

    “and so coacetylation would be expected for genes that are coexpressed at the RNA level.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    12 genes (37 shRNA constructs) met the >50% knockdown criterion in neurons; 14 genes (41 constructs) met it in astrocytes; 11 genes were tested in both cell types.

    “12 genes (with 37 shRNA constructs) met this criterion in neurons and 14 genes (with 41 shRNA constructs) met this criterion in astrocytes, 11 genes were tested in both cell types (Table S10).”
    Quote in the paperSubstantial claim

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

    Premisecitation

    Trans-eQTL associations are sparse, as reported in larger studies.

    “consistent with the observed sparsity of trans-associations (trans-eQTLs) reported in studies with larger sample sizes32.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [32] Lee, P. H., O’Dushlaine, C., Thomas, B. & Purcell, S. M. INRICH: interval-based enrichment analysis for genome-wide association studies. Bioinformatics 28, 1797–1799 (2012). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given

    Variation in cell type proportions across individuals can drive coexpression patterns between genes.

    “Because variation in cell type proportions across individuals can drive coexpression patterns between genes, some module-trait associations may be due to changes in cell type proportions that occur over the course of the disease (Figure S5A–B).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    The 21 common AD susceptibility alleles are strong risk factors yet explain only a minor portion of variance in AD-related traits.

    “consistent with the observation noted earlier that, while these susceptibility alleles are robust risk factors, they capture only a small fraction of the variance in these AD-related traits.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [4] Lambert, J.-C. et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nat. Genet. 45, 1452–1458 (2013). source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductreasoning

    The MTN framework models networks at two resolutions, increasing accuracy but including only a subset of modules, resulting in potential loss of information.

    “the MTN framework acts to increase network accuracy by modeling networks at two resolutions (a zoomed-out module/trait network and a zoomed-in gene network within selected modules), but increased accuracy comes at the price of including only a subset of modules in the inference process, resulting in potential loss of information.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Our study provides evidence that INPPL1 plays a role in cognitive decline and β-amyloid accumulation.

    “our study provides evidence that the INPPL1 gene plays a role in cognitive decline and β-amyloid accumulation”
    Quote in the paperSubstantial claim
38 of 38

  • The paper relies on this without support.

    Previous coexpression approaches have never been applied to large cohorts with quantitative measurements of both Alzheimer's disease neuropathology and cognitive decline.

    “However, these approaches have never been applied to large cohorts with quantitative measurements of both AD neuropathology and cognitive decline.”

  • The paper relies on this without support.

    It has been difficult to transition from mostly non-coding susceptibility variants to molecular mechanisms that lead to Alzheimer's disease pathology and cognitive decline.

    “However, it has been difficult to transition from mostly non-coding susceptibility variants to molecular mechanisms that lead to the characteristic accumulation of β-amyloid and helical filament tau (PHFtau) pathology as well as the subsequent cognitive decline of AD.”

  • The paper relies on this without support.

    There is no cellular model of cognitive decline.

    “Due to the absence of a cellular model of cognitive decline, we focused our validation effort on m109’s association with β-amyloid load.”

  • The paper relies on this without support.

    Extracellular Aβ42 levels can be readily assayed in vitro and are related to the defining pathologic lesion in AD.

    “we measured extracellular levels of the pathogenic β-amyloid Aβ42 peptide, that can be readily assayed in vitro and is related to the defining pathologic lesion in AD”

  • The paper relies on this without support.

    Little is known about PLXNB1's potential contribution to cognitive decline and AD.

    “However, little is known about its potential contribution to cognitive decline and AD.”

  • The paper relies on this without support.

    GWAS-derived SNPs have limited effects on gene expression in this case.

    “as the effect of GWAS-derived SNPs on gene expression in this case is limited.”
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?

  • The two bulk RNA-seq studies used AD samples and controls from the same patient cohorts but took unique approaches for co-expression network analysis.

    “These studies both used AD samples and controls from the same patient cohorts (Religious Orders Study and Memory and Aging Project, Mayo Clinic, Mount Sinai School of Medicine),64,65,66 but they took unique approaches for co-expression network analysis.”

    From hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data (2023) · cites this paper as [64]

    The Results section, “Data origin and phenotypes” (page unavailable), identifies this study’s participants as coming from the Religious Orders Study and Rush Memory and Aging Project; the RNA-Seq results describe analysis of 478 participants. The Introduction and “Constructing the nodes of our module-trait network” describe its co-expression network approach and how it differs from prior approaches. Our copy does not establish that both studies used the same cohorts, including Mayo Clinic and Mount Sinai, so that comparison is not supported by this source. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • The overlap of m109 with four clusters suggests it may represent a coordinated brain transcriptional response involving multiple cell types.

    “Interestingly, m109 showed significant overlap with four of the five consensus clusters (Figure 1C), suggesting that it may represent a coordinated brain transcriptional response involving multiple cell types.”

    From Meta-Analysis of the Alzheimer’s Disease Human Brain Transcriptome and Functional Dissection in Mouse Models (2020) · cites this paper as Mostafavi et al., 2018

    The Results sections identify m109 as a gene-expression module and report that selected m109 genes were studied in astrocytes and neurons. Our copy does not report m109 overlapping four of five consensus clusters or interpret that overlap as a coordinated response across cell types; those appear to be the citing authors’ analysis and interpretation. Page numbers are unavailable in our copy. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

  • Many human brain gene expression changes associated with AD, including neuronal- and microglial-enriched modules, may represent common transcriptional programs activated by the aging process itself.

    “This result suggests that many human brain gene expression changes associated with AD, including neuronal- and microglial-enriched modules reported in other studies (Conway et al., 2018; Mostafavi et al., 2018; Zhang et al., 2013), may represent common transcriptional programs activated by the aging process itself.”

    From Meta-Analysis of the Alzheimer’s Disease Human Brain Transcriptome and Functional Dissection in Mouse Models (2020) · cites this paper as Mostafavi et al., 2018

    The Results (‘Constructing the nodes of our module-trait network’; page not provided) identify neuronal-function modules associated with AD traits. The Results (‘Relation of RNA derived modules to the genetic architecture of AD’; page not provided) identify an age-associated, mostly microglial module enriched near AD risk variants, but explicitly say it is not directly associated with AD pathology, dementia, or cognitive decline. The paper does not establish that many AD-associated expression changes are common transcriptional programs activated by aging itself. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • PLXNB1 was identified as a key node in a gene module highly associated with cognitive decline in AD patients of the ROS-MAP cohort.

    “PLXNB1 was identified as a key node in a gene module highly associated with cognitive decline in AD patients of the ROS-MAP cohort26.”

    From Regulation of cell distancing in peri-plaque glial nets by Plexin-B1 affects glial activation and amyloid compaction in Alzheimer’s disease (2024) · cites this paper as [26]

    The Results sections on module 109 identify PLXNB1 as a major hub in a module strongly associated with cognitive decline in ROSMAP. But the Data origin and phenotypes section says the analysis included participants with and without AD dementia, so describing the finding as specifically being in “AD patients” narrows the study population inaccurately. Page numbers were not provided in our copy. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • Some studies have identified selected overlaps in expression changes between AD mouse models and human brains.

    “Although some studies have identified selected overlaps in expression changes between AD mouse models and human brains (Bennett et al., 2018; Castillo et al., 2017; Mostafavi et al., 2018; Neuner et al., 2019; Rojo et al., 2017), other studies have questioned the overall degree of conservation (Burns et al., 2015; Galatro et al., 2017; Hargis and Blalock, 2017).”

    From Meta-Analysis of the Alzheimer’s Disease Human Brain Transcriptome and Functional Dissection in Mouse Models (2020) · cites this paper as Mostafavi et al., 2018

The citation lists haven’t been fetched yet

References 94 · Cited by 509

Research works printed but not linked: 1

  1. Koller, D. & Friedman, N. ProbabilisticGraphical Models: Principles and Techniques. (MIT Press, Cambridge, MA, USA, 2009).

Authors
Mostafavi, S., Gaiteri, C., Sullivan, S. E., White, C. C., Tasaki, S., Xu, J., Taga, M., Klein, H.-U., Patrick, E., Komashko, V., McCabe, C., Smith, R., Bradshaw, E. M., Root, D. E., Regev, A., Yu, L., Chibnik, L. B., Schneider, J. A., Young-Pearse, T. L., Bennett, D. A., & De Jager, P. L.
Affiliations
  • Canadian Institute for Advanced Research (CA)
  • Rush University Medical Center (US)
  • Brigham and Women's Hospital (US)
  • Broad Institute (US)
  • The University of Sydney (AU)
Corresponding author
Bennett, David A.
ORCID
Venue
Nature Neuroscience
Publisher
Springer Science and Business Media LLC
Published
2018-05-25
Volume
21
Issue
6
Pages
811-819
ISSN
  • 1097-6256 (ISSN-L)
  • 1546-1726
DOI
10.1038/s41593-018-0154-9
PMC
PMC6599633
OpenAlex
W2804633924
Semantic Scholar
ea95fe35016fc8176c21ee88ba4bd14d2fab7468
Cited by
509
References
94
Citations by year
2026: 32 · 2025: 53 · 2024: 64 · 2023: 68 · 2022: 74 · 2021: 82 · 2020: 62 · 2019: 51 · 2018: 19 · 2017: 2 · 2012: 1
FWCI
39.02
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Neuroscience (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, public-domain)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institutes of Health (R01AG03-6836)
  • National Institute on Aging (R01AG017917, R01AG036836, U01AG046152, R01AG057911, R01AG015819, P30AG010161, RC2AG036547)
Topics
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Keywords
Alzheimer's disease, brain aging, frontal cortex, gene co-expression modules, molecular networks, cognitive decline, amyloid pathology, neuropathology, therapeutic target, human neurons, astrocytes, gene prioritization
MeSH terms
Aged, Aged, 80 and over, Aging, Alzheimer Disease, Astrocytes, Female, Gene Expression Regulation, Humans, Male, Neurons, Databases, Factual, Amyloid beta-Peptides, tau Proteins, Metabolic Networks and Pathways, Genetic Association Studies, Neural Stem Cells, Transcriptome, Cognitive Dysfunction

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.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.

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 ›

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