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Cited by 232Alzheimer's disease research and treatmentsAdvanced Proteomics Techniques and ApplicationsDementia and Cognitive Impairment Research

Deep proteomic network analysis of Alzheimer’s disease brain reveals alterations in RNA binding proteins and RNA splicing associated with disease

Open access
Johnson, Erik C. B., Dammer, Eric B., Duong, Duc M., Yin, Luming, Thambisetty, Madhav, Troncoso, Juan C., Lah, James J., Levey, Allan I. +1 more·2018·Molecular Neurodegeneration
DOI 10.1186/s13024-018-0282-4PMC PMC6172707
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Abstract

BACKGROUND: The complicated cellular and biochemical changes that occur in brain during Alzheimer's disease are poorly understood. In a previous study we used an unbiased label-free quantitative mass spectrometry-based proteomic approach to analyze these changes at a systems level in post-mortem cortical tissue from patients with Alzheimer's disease (AD), asymptomatic Alzheimer's disease (AsymAD), and controls. We found modules of co-expressed proteins that correlated with AD phenotypes, some of which were enriched in proteins identified as risk factors for AD by genetic studies. METHODS: The amount of information that can be obtained from such systems-level proteomic analyses is critically dependent upon the number of proteins that can be quantified across a cohort. We report here a new proteomic systems-level analysis of AD brain based on 6,533 proteins measured across AD, AsymAD, and controls using an analysis pipeline consisting of isobaric tandem mass tag (TMT) mass spectrometry and offline prefractionation. RESULTS: Our new TMT pipeline allowed us to more than double the depth of brain proteome coverage. This increased depth of coverage greatly expanded the brain protein network to reveal new protein modules that correlated with disease and were unrelated to those identified in our previous network. Differential protein abundance analysis identified 350 proteins that had altered levels between AsymAD and AD not caused by changes in specific cell type abundance, potentially reflecting biochemical changes that are associated with cognitive decline in AD. RNA binding proteins emerged as a class of proteins altered between AsymAD and AD, and were enriched in network modules that correlated with AD pathology. We developed a proteogenomic approach to investigate RNA splicing events that may be altered by RNA binding protein changes in AD. The increased proteome depth afforded by our TMT pipeline allowed us to identify and quantify a large number of alternatively spliced protein isoforms in brain, including AD risk factors such as BIN1, PICALM, PTK2B, and FERMT2. Many of the new AD protein network modules were enriched in alternatively spliced proteins and correlated with molecular markers of AD pathology and cognition. CONCLUSIONS: Further analysis of the AD brain proteome will continue to yield new insights into the biological basis of AD.

AI snapshot

Written from the paper’s full text.

TL;DR

A TMT-SPS-MS3 proteomic pipeline quantified 6,533 proteins in post-mortem DLPFC from AD, AsymAD, and control cases, more than doubling prior LFQ depth and expanding the co-expression network from 16 to 50 modules. The deeper network implicated RNA binding proteins and alternative exon–exon splicing, including in AD risk genes such as BIN1, PTK2B, and FERMT2, as features of symptomatic AD.

Key findings

  • The TMT pipeline quantified 6,533 proteins across 47 DLPFC cases versus 3,069 proteins by the previous single-shot LFQ approach; the protein co-expression network expanded from 16 modules to 50 modules, with module M27 containing >70% new protein members, being predominantly glial, and correlating positively with tau tangle burden.
  • Four TMT network modules were enriched for AD GWAS risk loci: M4, M7, M27, and M33; M4, M7, and M27 were predominantly glial and positively correlated with amyloid plaque and tau tangle burden, whereas M33 was more oligodendrocyte/neuronal and negatively correlated with both.
  • Cell-type deconvolution showed astrocytes and microglia increased in AD compared with AsymAD and control and correlated strongly with Braak stage; neurons decreased in both AsymAD and AD. AsymAD–AD unique protein changes were largely preserved after deconvolution (from 290 to 263 proteins; the abstract reports 350 proteins altered between AsymAD and AD independent of cell-type abundance).
  • RNA binding proteins were enriched in modules 10, 15, 17, 18, 29, and 40, most of which correlated with tau tangle burden. Proteogenomic analysis identified 4,830 TMT-LysC alternative exon–exon junction peptides versus 5,746 LFQ-trypsin peptides, with TMT better for quantification across case groups; alt-EEjxns in BIN1, PTK2B, and FERMT2 differed by case status.

Methods

  • Post-mortem dorsolateral prefrontal cortex (Brodmann area 9) from the Baltimore Longitudinal Study of Aging: 20 AD, 14 AsymAD, and 13 control cases after excluding 11 MCI cases due to a preparation batch effect; the same homogenates were used for prior LFQ and new TMT analysis.
  • Proteins were digested with LysC, labeled with isobaric tandem mass tags, prefractionated by offline ERLIC, and analyzed by LC-MS/MS with SPS-MS3; data were searched in Proteome Discoverer 2.1, then analyzed by weighted protein correlation network analysis, digital sorting algorithm cell-type deconvolution, and ANOVA with Tukey post hoc for differential abundance.
  • For alternative splicing, RNA-seq from 3 control and 3 AD University of Kentucky brain bank cases was realigned with GSNAP novel-splicing mode, exon–exon junctions were summarized with spliceSites, peptides spanning alternative junctions were generated by in silico LysC digestion, appended to the Uniprot database, and quantified across TMT batches.

Limitations

  • Stated: 11 MCI cases were excluded because of a preparation batch effect; MMSE scores were skewed toward 30; the RNA-seq database came from relatively few control and AD brains; alt-EEjxn quantification was limited to the peptide level and represents splicing “decisions”; TMT still has missing values; trypsin and LysC identified largely separate alt-EEjxn subsets; cell-type deconvolution was not applied to alt-EEjxn analysis.
  • Stated: the relationship between RNA binding protein abundance and alternative splicing remained unresolved, and U1 spliceosome proteins were not strongly enriched in the network, possibly because they shift in solubility and aggregate in AD brain.
  • Evident from the text: the design is cross-sectional and correlational in post-mortem tissue from one cohort and brain region, so causal direction and generalization to other cohorts or regions are not established.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1186/s13024-018-0282-4

Cites

53 of 53 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 70 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    RNA binding proteins emerged as a class of proteins altered between AsymAD and AD.

    “RNA binding proteins emerged as a class of proteins altered between AsymAD and AD, and were enriched in network modules that correlated with AD pathology.”
    Quote in the paperSubstantial claim
  • Findingown data

    Differential expression analysis on the enlarged proteomic dataset identified proteins that have altered levels among AD, AsymAD, and control brains, even after accounting for changes in cellular abundance.

    “We also used differential expression analysis on the enlarged proteomic dataset to identify proteins that have altered levels among AD, AsymAD, and control brains, even after accounting for changes in cellular abundance.”
    Quote in the paperSubstantial claim
  • Findingown data

    RNA binding proteins emerged as a family of proteins that was increased in abundance in AD.

    “RNA binding proteins emerged as a family of proteins that was increased in abundance in AD, and these proteins were enriched in modules that correlated with tau tangle pathology.”
    Quote in the paperSubstantial claim
  • Findingown data

    The increased proteome depth afforded by the TMT pipeline allowed the authors to identify and quantify a large number of alternatively spliced protein isoforms in brain, including AD risk factors such as BIN1, PICALM, PTK2B, and FERMT2.

    “The increased proteome depth afforded by our TMT pipeline allowed us to identify and quantify a large number of alternatively spliced protein isoforms in brain, including AD risk factors such as BIN1, PICALM, PTK2B, and FERMT2.”
    Quote in the paperSubstantial claim
  • Findingown data

    Differential protein abundance analysis identified 350 proteins that had altered levels between AsymAD and AD not caused by changes in specific cell type abundance.

    “Differential protein abundance analysis identified 350 proteins that had altered levels between AsymAD and AD not caused by changes in specific cell type abundance, potentially reflecting biochemical changes that are associated with cognitive decline in AD.”
    Quote in the paperSubstantial claim
  • May combine two claims. 59
  • Classified as probably not a substantial claim. 44

  • May combine two claims.

    Findingown data

    One of the most unique modules contained strong enrichment in AD risk loci identified by the IGAP GWAS, correlated with tau tangle burden, and contained more glial than neuronal proteins.

    “One of the most unique modules contained strong enrichment in AD risk loci identified by the International Genetics of Alzheimer’s Project (IGAP) GWAS [12], correlated with tau tangle burden, and contained more glial than neuronal proteins.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [12] Lambert JC, Ibrahim-Verbaas CA, Harold D, Naj AC, Sims R, Bellenguez C, DeStafano AL, Bis JC, Beecham GW, Grenier-Boley B, et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat Genet. 2013;45:1452–8. source

      Not checked in the free run.

  • May combine two claims.

    Findingreasoning

    The proteogenomic approach, coupled with increased depth of proteome coverage and superior quantitation afforded by the TMT pipeline compared to the previous LFQ approach, allowed the authors to identify and quantify a number of alternative exon-exon splicing events in brain at the protein level, including alternative exon-exon junctions in AD risk factor proteins such as BIN1, PICALM, PTK2B, and

    “This proteogenomic approach, coupled with the increased depth of proteome coverage and superior quantitation afforded by our TMT pipeline compared to our previous LFQ approach, allowed us to identify and quantify a number of alternative exon-exon splicing events in brain at the protein level, including alternative exon-exon junctions in AD risk factor proteins such as BIN1, PICALM, PTK2B, and FER”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The increased depth of coverage greatly expanded the brain protein network to reveal new protein modules that correlated with disease and were unrelated to those identified in the previous network.

    “This increased depth of coverage greatly expanded the brain protein network to reveal new protein modules that correlated with disease and were unrelated to those identified in our previous network.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Many identified alternative exon-exon junction splicing events were highly enriched in modules unique to the TMT network and correlated with disease.

    “Many of the identified alternative exon-exon junction splicing events were highly enriched in modules unique to the TMT network, and correlated with disease, suggesting a potential role for aberrant RNA splicing in AD pathogenesis.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The increased depth of proteome coverage allowed the authors to build a protein network that consisted of approximately threefold more protein modules, two-thirds of which shared little overlap with the modules previously identified in the LFQ network.

    “The increased depth of proteome coverage allowed us to build a protein network that consisted of approximately threefold more protein modules, two-thirds of which shared little overlap with the modules previously identified in our LFQ network.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Many of the new AD protein network modules were enriched in alternatively spliced proteins and correlated with molecular markers of AD pathology and cognition.

    “Many of the new AD protein network modules were enriched in alternatively spliced proteins and correlated with molecular markers of AD pathology and cognition.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Other modules unique to the TMT network that were significantly correlated with AD neuropathology included M17 and M29, which were associated with increased tau tangle burden, and M47, which was associated with decreased tau tangle burden.

    “Other modules unique to the TMT network that were significantly correlated with AD neuropathology included M17 and M29, which were associated with increased tau tangle burden, and M47, which was associated with decreased tau tangle burden.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The oligodendrocyte population increased in AsymAD, and then decreased slightly in AD compared to AsymAD.

    “The oligodendrocyte population increased in AsymAD, and then decreased slightly in AD compared to AsymAD.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    TMT modules with cognate modules in the LFQ network that were strongly associated with AD traits included M1 and M3, which were negatively correlated with AD pathology, and M4 and M7, which were positively correlated with AD pathology, among others.

    “TMT modules with cognate modules in the LFQ network that were strongly associated with AD traits included M1 and M3, which were negatively correlated with AD pathology, and M4 and M7, which were positively correlated with AD pathology, among others.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    While most of the new modules did not display a strong association with any of the four brain cell types analyzed (microglia, astrocytes, oligodendrocytes, or neurons), M27 was predominantly glial in nature and correlated positively with tau tangle burden (Braak stage).

    “While most of the new modules did not display a strong association with any of the four brain cell types we analyzed (microglia, astrocytes, oligodendrocytes, or neurons), M27 was predominantly glial in nature and correlated positively with tau tangle burden (Braak stage).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Tau had a number of alt-EEjxn peptides that were significantly increased in AD, and these mapped to the 3- and 4- microtubule binding domain repeat isoforms of the protein.

    “Tau had a number of alt-EEjxn peptides that were significantly increased in AD, and these mapped to the 3- and 4- microtubule binding domain repeat isoforms of the protein in this analysis because either isoform can be considered constitutively expressed in humans.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Either the 3-repeat or the 4-repeat microtubule binding domain isoform of tau can be considered constitutively expressed in humans.

  • May combine two claims.

    Findingown data

    Modules M27 and M33 were enriched in alt-EEjxn peptides, with M33 being highly enriched.

    “Modules 4 and 7—glial modules enriched in AD risk factors from GWAS—did not contain more alt-EEjxn peptides than expected, but two other GWAS modules, M27 and M33, were enriched, with M33 being highly enriched.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Three of the five GWAS proteins had alt-EEjxns that were different in abundance by case status, and included BIN1, PTK2B, and FERMT2.

    “Three of the five GWAS proteins had alt-EEjxns that were different in abundance by case status, and included BIN1, PTK2B, and FERMT2 (Additional file 7: Table S7).”
    Quote in the paperSubstantial claim

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

    Findingown data

    There were slightly more proteins that were significantly lower in abundance compared to those that were higher in abundance in AD compared to AsymAD after cell type deconvolution.

    “There were slightly more proteins that were significantly lower in abundance compared to those that were higher in abundance in AD compared to AsymAD after cell type deconvolution (Additional file 14: Figure S7).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    There were more alt-EEjxn peptides that were reduced in AD compared to AsymAD, similar to the total protein abundance differences between AD and AsymAD.

    “As shown in Fig. 4d, we found there were more alt-EEjxn peptides that were reduced in AD compared to AsymAD, similar to the total protein abundance differences between AD and AsymAD.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    After cell type deconvolution, RNA binding proteins were preserved as hubs of differentially abundant proteins between control and AsymAD, and between AsymAD and AD.

    “After cell type deconvolution of protein abundance changes, we noted with keen interest the preservation of RNA binding proteins as hubs of differentially abundant proteins between control and AsymAD (Additional file 15: Figure S8), and between AsymAD and AD (Fig. 3e and Additional file 16: Figure S9).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    All of these modules were strongly glial in nature, with M35 a strongly astrocytic module.

    “All of these modules were strongly glial in nature, with M35 a strongly astrocytic module.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingreasoning

    TMTs allow relative protein measurements across multiple case groups within a single batch, minimizing the missing value problem for quantification across case groups.

    “TMTs also allow for relative protein measurements across multiple case groups within a single batch, minimizing the missing value problem for quantification across case groups.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Module 35 showed strong correlation to Aβ as well as to tau pT231, and correlated with worsened cognitive function.

    “Module 35, which contained a number of differentially abundant alt-EEjxns, showed strong correlation to Aβ as well as to tau pT231, and correlated with worsened cognitive function.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The tau pT231 peptide lies within the proline-rich region of tau and is separate from the microtubule-binding region that aggregates into neurofibrillary tangles.

  • May combine two claims.

    Findingown data

    A number of alternative splicing events strongly correlated with network modules enriched in AD GWAS risk factor proteins, and some of these isoforms differed in abundance in AsymAD and AD.

    “We therefore identified a number of alternative splicing events that strongly correlated with network modules enriched in AD GWAS risk factor proteins, and some of these isoforms differed in abundance in AsymAD and AD.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Most of the common alternatively spliced transcripts present in DLPFC control and AD brain were represented in the RNAseq-based database used to identify alt-EEjxn peptides.

  • Classified as probably not a substantial claim.

    Findingnone given

    Prefractionation significantly increases the depth of proteome coverage achievable by LC-MS/MS of complex tissues such as brain.

    “Prefractionation significantly increases the depth of proteome coverage achievable by LC-MS/MS of complex tissues such as brain.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Modules 11 and 20 had corrected p values for enrichment of 4.1e−15 and 1.7e−13, respectively.

    “Modules 11 and 20 had corrected p values for enrichment of 4.1e− 15 and 1.7e− 13, respectively, and by GO analysis were most likely to be involved in regulation of immune system processes (data not shown).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    This region of the TMT network was not strongly associated with a particular cell type or strongly correlated with standard histopathological measures of AD.

    “This region of the TMT network was not strongly associated with a particular cell type or strongly correlated with standard histopathological measures of AD.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The neuron population decreased between control and AsymAD, with a further decrease between AsymAD and AD.

    “Interestingly, the neuron population decreased between control and AsymAD, with a further decrease between AsymAD and AD.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Module M18, although not enriched in alt-EEjxn peptides, was strongly enriched in RNA binding proteins.

    “From the molecular analyses we also identified modules such as M18 that, although not enriched in alt-EEjxn peptides, were observed to be strongly enriched in RNA binding proteins (Additional file 22: Figure S15), were strongly correlated in a positive direction with tau pT231, U1-70K, and TDP-43, and were correlated in a negative direction with cognitive function.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The deeper protein coexpression network analysis revealed new protein modules that correlated with pathological measures of AD and were enriched in AD risk factors identified by GWAS.

    “The deeper protein coexpression network analysis revealed new protein modules that correlated with pathological measures of AD and were enriched in AD risk factors identified by GWAS.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Splicing events in other proteins correlated with network modules enriched in AD risk factor proteins and were altered in AD.

    “as well as splicing events in other proteins that correlated with network modules enriched in AD risk factor proteins and were altered in AD.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Most of the common alternatively spliced transcripts present in DLPFC control and AD brain were represented in the RNAseq-based database used to identify alt-EEjxn peptides.

  • May combine two claims.

    Findingown data

    The highly related modules 11 and 36 showed opposite correlation with cognition, with increases in M11 associated with worsened cognitive function and increases in M36 associated with improved cognitive function.

    “Interestingly, the highly related modules 11 and 36 showed opposite correlation with cognition, with increases in M11 associated with worsened cognitive function and increases in M36 associated with improved cognitive function, suggesting that protein splicing changes may be highly specific in their relationships to different types of AD pathology and cognitive function.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    M27 was enriched for AD GWAS risk factors and correlated with AD pathology.

    “This module was also enriched for AD GWAS risk factors and correlated with AD pathology”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Alt-EEjxns at a global level tended to cluster into the unique area of the TMT-LysC network, but did not significantly overlap with modules enriched in RNA binding proteins.

    “We found that alt-EEjxns at a global level tended to cluster into the unique area of the TMT-LysC network, but did not significantly overlap with modules enriched in RNA binding proteins.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Most of the common alternatively spliced transcripts present in DLPFC control and AD brain were represented in the RNAseq-based database used to identify alt-EEjxn peptides.

  • May combine two claims.

    Findingown data

    The TMT-LysC approach was slightly superior to LFQ-trypsin for quantification of alt-EEjxns, and even better when quantifying alt-EEjxns across case groups.

    “Our comparison between LFQ-trypsin and TMT-LysC analytical pipelines found that the TMT-LysC approach was slightly superior to LFQ-trypsin for quantification of alt-EEjxns, and even better when quantifying alt-EEjxns across case groups.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Most of the common alternatively spliced transcripts present in DLPFC control and AD brain were represented in the RNAseq-based database used to identify alt-EEjxn peptides.

  • May combine two claims.

    Findingown data

    M18 was significantly correlated with phosphorylated tau, U1-70K, TDP-43, and cognitive decline.

    “M18 was significantly correlated with phosphorylated tau, U1-70K, TDP-43, and cognitive decline”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Module 29 contained five snRNPs and was annotated as involved in mRNA splicing by GO analysis, but did not show enrichment of alt-EEjxn peptides.

    “Module 29 contained five snRNPs and was annotated as being involved in mRNA splicing by GO analysis, but did not show enrichment of alt-EEjxn peptides.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Most of the common alternatively spliced transcripts present in DLPFC control and AD brain were represented in the RNAseq-based database used to identify alt-EEjxn peptides.

  • May combine two claims.

    Findingnone given

    The study developed a TMT-based quantification pipeline for proteomic analysis of brain tissue that significantly increased depth of proteome coverage of control and AD brain and led to additional insights into protein changes characterizing AD pathophysiology, including changes in RNA splicing.

    “We developed a TMT-based quantification pipeline for proteomic analysis of brain tissue that significantly increased our depth of proteome coverage of control and AD brain and led to additional insights into the protein changes that characterize AD pathophysiology, including changes in RNA splicing.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Most of the common alternatively spliced transcripts present in DLPFC control and AD brain were represented in the RNAseq-based database used to identify alt-EEjxn peptides.

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

    Study design and conductown data

    MCI cases (n=11) were homogenized separately on a different day and included in the batched TMT-MS design, but were later excluded from the analysis due to a preparation batch effect that was refractory to post-hoc correction.

    “In addition to these n = 47 cases, mild cognitive impairment (MCI) cases (n = 11) were homogenized separately on a different day and included in the batched TMT-MS design, but were later excluded from the analysis due to a preparation batch effect that was refractory to post-hoc correction.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    These modules were enriched for AD risk loci identified by GWAS and contained a large number of glial proteins.

    “These modules were enriched for AD risk loci identified by genome-wide association studies (GWAS), and contained a large number of glial proteins.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [5] Seyfried NT, Dammer EB, Swarup V, Nandakumar D, Duong DM, Yin L, Deng Q, Nguyen T, Hales CM, Wingo T, et al. A multi-network approach identifies protein-specific co-expression in asymptomatic and symptomatic Alzheimer's disease. Cell Syst. 2017;4:60–72 e64. source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductcitation

    Spectra matches were filtered by Percolator to a peptide-spectrum match false discovery rate of <1%.

    “Spectra matches were filtered by Percolator [15] to a peptide-spectrum match false discovery rate of < 1%.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [15] Kall L, Canterbury JD, Weston J, Noble WS, MacCoss MJ. Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nat Methods. 2007;4:923–5. source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    The most recent generation of TMTs can be used to report the relative levels of a given peptide from a pool consisting of up to 11 separate and independent samples.

    “The most recent generation of TMTs can be used to report the relative levels of a given peptide from a pool consisting of up to 11 separate and independent samples [10].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [10] Ping L, Duong DM, Yin L, Gearing M, Lah JJ, Levey AI, Seyfried NT: Global quantitative analysis of the human brain proteome in Alzheimer’s and Parkinson’s Disease. Nature Scientific Data 2018.

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Using an appropriate pooled sample study design and mass spectrometry instrumentation that can perform MS3 reporter quantitation, missing values can be minimized within an experimental cohort using a TMT approach while avoiding dynamic range compression effects.

    “Using an appropriate pooled sample study design and mass spectrometry instrumentation that can perform MS3 reporter quantitation, missing values can be minimized within an experimental cohort using a TMT approach while avoiding dynamic range compression effects [8].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [8] Ting L, Rad R, Gygi SP, Haas W. MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics. Nat Methods. 2011;8:937–40. source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    A naïve first pass regression was performed by considering age, sex, post-mortem interval (PMI), and disease status group contributions to each sample-specific protein abundance measurement set (n=47), explicitly modeled using 1000 iterations of ordinary nonparametric bootstrap regression.

    “A naïve first pass regression was performed by considering age, sex, post-mortem interval (PMI), and disease status group contributions to each sample-specific protein abundance measurement set (n = 47), explicitly modeled using 1000 iterations of ordinary nonparametric bootstrap regression.”
    Quote in the paperSubstantial claim

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

    Premisenone given

    The amount of information obtainable from systems-level proteomic analyses is critically dependent upon the number of proteins that can be quantified across a cohort.

    “The amount of information that can be obtained from such systems-level proteomic analyses is critically dependent upon the number of proteins that can be quantified across a cohort.”
    Quote in the paperNot a substantial claim

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

    Study design and conductown data

    Proteins with more than 23 missing log2(ratio) values were excluded from analysis, leaving a matrix of n=47 control, AsymAD, and AD cases with no more than 23 missing values (<50%) per protein measurement, for a total of 6532 proteins.

    “Finally, proteins with more than 23 missing log2(ratio) values were excluded from analysis, and then 11 MCI cases were dropped, leaving a matrix of n = 47 control, AsymAD, and AD cases with no more than 23 missing values (< 50%) per protein measurement, for a total of 6532 proteins.”
    Quote in the paperSubstantial claim

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

    Study design and conductnone given

    Proteins with more than 4 unquantifiable batches (out of 8) due to 0 or NA value for the GIS channel 126 reporter were excluded from consideration.

    “Furthermore, proteins with more than 4 unquantifiable batches (out of a total of 8 batches) due to 0 or NA value for the GIS channel 126 reporter Proteome Discoverer 2.1-normalized value (pre-ratio calculation) were excluded from consideration.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    One strategy to minimize the missing value problem is to measure peptide and protein levels using a multiplex tagging approach with isobaric tandem mass tags (TMTs).

    “One strategy to minimize the missing value problem is to measure peptide and protein levels using a multiplex tagging approach with isobaric tandem mass tags (TMTs) [8–11].”
    Quote in the paperSubstantial claim0 of 4 sources checked
    • cites [8] Ting L, Rad R, Gygi SP, Haas W. MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics. Nat Methods. 2011;8:937–40. source

      Not checked in the free run.

    • cites [9] Rauniyar N, Yates JR 3rd. Isobaric labeling-based relative quantification in shotgun proteomics. J Proteome Res. 2014;13:5293–309. source

      Not checked in the free run.

    • cites [10] Ping L, Duong DM, Yin L, Gearing M, Lah JJ, Levey AI, Seyfried NT: Global quantitative analysis of the human brain proteome in Alzheimer’s and Parkinson’s Disease. Nature Scientific Data 2018.

      Not checked in the free run.

    • cites [11] Rangaraju S, Dammer EB, Raza SA, Gao T, Xiao H, Betarbet R, Duong DM, Webster JA, Hales CM, Lah JJ, et al. Quantitative proteomics of acutely-isolated mouse microglia identifies novel immune Alzheimer's disease-related proteins. Mol Neurodegener. 2018;13:34. source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    The previous study found modules of co-expressed proteins that correlated with AD phenotypes, some enriched in proteins identified as AD risk factors by genetic studies.

    “We found modules of co-expressed proteins that correlated with AD phenotypes, some of which were enriched in proteins identified as risk factors for AD by genetic studies.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [5] Seyfried NT, Dammer EB, Swarup V, Nandakumar D, Duong DM, Yin L, Deng Q, Nguyen T, Hales CM, Wingo T, et al. A multi-network approach identifies protein-specific co-expression in asymptomatic and symptomatic Alzheimer's disease. Cell Syst. 2017;4:60–72 e64. source

      Not checked in the free run.

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

    Premisecitation

    Systems-based approaches such as WGCNA can be used to analyze biochemical and cellular changes in brain and are useful to capture the complexity of perturbations in biological networks related to disease.

    “Systems-based approaches such as weighted gene co-expression network analysis (WGCNA) can be used to analyze biochemical and cellular changes in brain, and are useful to help capture the complexity of perturbations in biological networks that are related to disease [2–4].”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [2] Huan T, Zhang B, Wang Z, Joehanes R, Zhu J, Johnson AD, Ying S, Munson PJ, Raghavachari N, Wang R, et al. A systems biology framework identifies molecular underpinnings of coronary heart disease. Arterioscler Thromb Vasc Biol. 2013;33:1427–34. source

      Not checked in the free run.

    • cites [3] Miller JA, Oldham MC, Geschwind DH. A systems level analysis of transcriptional changes in Alzheimer's disease and normal aging. J Neurosci. 2008;28:1410–20. source

      Not checked in the free run.

    • cites [4] Oldham MC, Konopka G, Iwamoto K, Langfelder P, Kato T, Horvath S, Geschwind DH. Functional organization of the transcriptome in human brain. Nat Neurosci. 2008;11:1271–82. source

      Not checked in the free run.

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

    Premisecitation

    In a previous study, the authors used an unbiased label-free quantitative mass spectrometry-based proteomic approach to analyze cellular and biochemical changes at a systems level in post-mortem cortical tissue from AD, AsymAD, and control patients.

    “In a previous study we used an unbiased label-free quantitative mass spectrometry-based proteomic approach to analyze these changes at a systems level in post-mortem cortical tissue from patients with Alzheimer’s disease (AD), asymptomatic Alzheimer’s disease (AsymAD), and controls.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [5] Seyfried NT, Dammer EB, Swarup V, Nandakumar D, Duong DM, Yin L, Deng Q, Nguyen T, Hales CM, Wingo T, et al. A multi-network approach identifies protein-specific co-expression in asymptomatic and symptomatic Alzheimer's disease. Cell Syst. 2017;4:60–72 e64. source

      Not checked in the free run.

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

    Study design and conductnone given

    Peptides from different genomic sites that were 100% homologous to the junction-spanning peptides were considered duplicates and were removed from consideration.

    “Peptides from different genomic sites that were 100% homologous to the junction-spanning peptides were considered duplicates and were removed from consideration.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    The Aβ17-28 peptide is a proteolytic fragment of Aβ generated by both trypsin and LysC enzymatic digestion of the full-length Aβ peptide, and therefore represents a peptide with a very large change in abundance across the sample cohort due to aggregation of Aβ into amyloid plaques in AsymAD and AD cases.

    “The Aβ17–28 peptide is a proteolytic fragment of Aβ generated by both trypsin and LysC enzymatic digestion of the full-length Aβ peptide, and therefore represents a peptide with a very large change in abundance across the sample cohort due to aggregation of Aβ into amyloid plaques in AsymAD and AD cases [5].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [5] Seyfried NT, Dammer EB, Swarup V, Nandakumar D, Duong DM, Yin L, Deng Q, Nguyen T, Hales CM, Wingo T, et al. A multi-network approach identifies protein-specific co-expression in asymptomatic and symptomatic Alzheimer's disease. Cell Syst. 2017;4:60–72 e64. source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    For the purposes of avoiding spurious correlations, no more than 25 out of 47 missing values were allowed for any peptide.

    “For the purposes of avoiding spurious correlations, no more than 25 out of 47 missing values were allowed for any peptide.”
    Quote in the paperSubstantial claim

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

    Premisecitation

    The asymptomatic phase of AD (AsymAD) is currently considered a preclinical stage of the disease.

    “This asymptomatic phase of AD (AsymAD) is currently considered a preclinical stage of the disease [27, 28].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [27] Dubois B, Hampel H, Feldman HH, Scheltens P, Aisen P, Andrieu S, Bakardjian H, Benali H, Bertram L, Blennow K, et al. Preclinical Alzheimer's disease: definition, natural history, and diagnostic criteria. Alzheimers Dement. 2016;12:292–323. source

      Not checked in the free run.

    • cites [28] Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, Iwatsubo T, Jack CR Jr, Kaye J, Montine TJ, et al. Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7:280–92. source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Neuropathological changes (amyloid plaques and tau tangles) are considered to develop years before onset of the cognitive changes that characterize AD dementia.

    “The neuropathological changes that are quintessential for AD diagnosis—namely, the development of amyloid plaques and tau tangles—are considered to develop years before onset of the cognitive changes that characterize AD dementia [26].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [26] Jack CR, Jr., Knopman DS, Jagust WJ, Shaw LM, Aisen PS, Weiner MW, Petersen RC, Trojanowski JQ: Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade. Lancet Neurol 2010, 9:119–128. source

      Not checked in the free run.

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

    Study design and conductnone given

    Threshold power Beta for reduction of false positive correlations was sampled in increments of 0.5 and selected as the lowest power at which scale free topology R2 was approximately 0.80, or in the case of the cell type weight-regressed network, the power at which a horizontal asymptote (plateau) was nearly approached, near a scale free topology R2 of (0.80).

    “Threshold power Beta for reduction of false positive correlations (i.e. the beneficial effect of enforcing scale free topology) was sampled in increments of 0.5 and selected as the lowest power at which scale free topology R2 was approximately 0.80, or in the case of the cell type weight-regressed network, the power at which a horizontal asymptote (plateau) was nearly approached, near a scale free”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Regression for age, sex, and PMI covariation was performed in R on all log2 transformed values except for 781 that could not be regressed due to a high number of missing values.

    “Regression for age, sex, and PMI covariation was performed in R on all log2 transformed values except for 781 that could not be regressed due to a high number of missing values.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Changes associated with progression to AsymAD are a decrease in neurons and an increase in oligodendrocytes mostly associated with amyloid burden.

    “Therefore, the changes associated with progression to AsymAD are a decrease in neurons and an increase in oligodendrocytes mostly associated with amyloid burden.”
    Quote in the paperSubstantial claim

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

    Study design and conductnone given

    All junction-spanning peptides considered were ones that had alternative events represented by other gapped reads that shared a left (5′) or right (3′) end with another set of gapped reads, and not "singleton" or brain constitutive exon-exon junctions.

    “All junction-spanning peptides considered were ones that had alternative events represented by other gapped reads that shared a left (5′) or right (3′) end with another set of gapped reads, and not “singleton” or brain constitutive exon-exon junctions.”
    Quote in the paperSubstantial claim

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

    Study design and conductnone given

    A second, two-pass regression scheme was performed by first considering DSA estimated cell type weight for the four Sharma dataset brain cell types (microglia, astrocytes, neurons, and oligodendroglia) as four sets of variables for regression.

    “A second, two-pass regression scheme was performed by first considering DSA estimated cell type weight for the four Sharma dataset brain cell types (microglia, astrocytes, neurons, and oligodendroglia) as four sets of variables for regression.”
    Quote in the paperNot a substantial claim

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

    Premisecitation

    GWAS have collectively identified over 20 genetic loci associated with AD at genome-wide significance, and many other loci that fall below genome-wide significance.

    “Genetic variants that impart increased or decreased risk for AD have been mapped by genome wide association studies (GWAS), which collectively have identified over 20 genetic loci associated with AD at genome-wide significance, and many other loci that fall below genome-wide significance [12, 25].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [12] Lambert JC, Ibrahim-Verbaas CA, Harold D, Naj AC, Sims R, Bellenguez C, DeStafano AL, Bis JC, Beecham GW, Grenier-Boley B, et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat Genet. 2013;45:1452–8. source

      Not checked in the free run.

    • cites [25] Sims R, van der Lee SJ, Naj AC, Bellenguez C, Badarinarayan N, Jakobsdottir J, Kunkle BW, Boland A, Raybould R, Bis JC, et al. Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease. Nat Genet. 2017;49:1373–84. source

      Not checked in the free run.

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

    Premisecitation

    The cell type "character" of each module can be assessed by examining the overlap of module protein membership with cell type specific protein expression data.

    “The cell type “character” of each module can be assessed by examining the overlap of module protein membership with cell type specific protein expression data [5, 17].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [5] Seyfried NT, Dammer EB, Swarup V, Nandakumar D, Duong DM, Yin L, Deng Q, Nguyen T, Hales CM, Wingo T, et al. A multi-network approach identifies protein-specific co-expression in asymptomatic and symptomatic Alzheimer's disease. Cell Syst. 2017;4:60–72 e64. source

      Not checked in the free run.

    • cites [17] Sharma K, Schmitt S, Bergner CG, Tyanova S, Kannaiyan N, Manrique-Hoyos N, Kongi K, Cantuti L, Hanisch UK, Philips MA, et al. Cell type- and brain region-resolved mouse brain proteome. Nat Neurosci. 2015;18:1819–31. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Study design and conductnone given

    Missing values did not require imputation for bootstrap covariate regression.

    “Importantly, missing values did not require imputation for bootstrap covariate regression.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Quantitations of within-batch normalized abundances were then scaled across batches to set the average of all GIS measurements within batch to be identical across batches.

    “Quantitations of within-batch normalized abundances were then scaled across batches to set the average of all GIS measurements within batch to be identical across batches.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Following normalization of cell type abundance variation across the samples, the prior age, sex, and PMI regression scheme was used to remove these covariate effects.

    “Following normalization of cell type abundance variation across the samples, the prior age, sex, and PMI regression scheme was used to remove these covariate effects.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Age, sex, and PMI covarying components of the measurement were subtracted to arrive at a regressed protein abundance measurement set.

    “Then age, sex, and PMI covarying components of the measurement were subtracted to arrive at a regressed protein abundance measurement set.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductreasoning

    As part of the new analysis approach, the authors relaxed the data inclusion criteria to require missing values in <50% rather than <10% of the samples, given that the WGCNA algorithm for coexpression network analysis well-tolerates missing values up to 50%.

    “As part of the new analysis approach, we also relaxed the data inclusion criteria to require missing values in < 50% rather than < 10% of the samples, given that the WGCNA algorithm for coexpression network analysis well-tolerates missing values up to 50%.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The WGCNA algorithm for coexpression network analysis well-tolerates missing values up to 50%.

  • May combine two claims.

    Interpretationown data

    Progression from AsymAD to AD (symptom onset) is associated with an increase in astrocytes and microglia, and with neurofibrillary tangle burden.

    “Progression from AsymAD to AD—that is, symptom onset—is associated with an increase in astrocytes and microglia, and is associated with neurofibrillary tangle burden.”
    Quote in the paperSubstantial claim

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

    Premisecitation

    The approach of using cell type deconvolution to remove confounding effects of cell type changes on gene expression has previously been applied to transcriptomic data, but to our knowledge has not previously been applied to proteomic data.

    “This approach has previously been applied to transcriptomic data to remove the confounding effects of cell type changes on gene expression [30], but to our knowledge has not previously been applied to proteomic data.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [30] Allen M, Wang X, Burgess JD, Watzlawik J, Serie DJ, Younkin CS, Nguyen T, Malphrus KG, Lincoln S, Carrasquillo MM, et al. Conserved brain myelination networks are altered in Alzheimer's and other neurodegenerative diseases. Alzheimers Dement. 2018;14:352–66. source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    A number of alternative splicing decisions at the protein level in brain significantly change in AD, including in AD risk factor proteins identified from GWAS.

    “In summary, we identified a number of alternative splicing decisions at the protein level in brain that significantly change in AD, including in AD risk factor proteins identified from GWAS.”
    Quote in the paperSubstantial claim

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

    Premisecitation

    Accumulation of insoluble snRNPs correlates strongly with both amyloid and Tau pathology.

    “Interestingly, our previous studies demonstrated that many of the U1 snRNPs colocalize with neurofibrillary tangles and paired helical filaments in AD brain [24, 32–34], and that accumulation of insoluble snRNPs correlates strongly with both amyloid and Tau pathology [32–37].”
    Quote in the paperNot a substantial claim0 of 6 sources checked
    • cites [32] Hales CM, Dammer EB, Deng Q, Duong DM, Gearing M, Troncoso JC, Thambisetty M, Lah JJ, Shulman JM, Levey AI, Seyfried NT. Changes in the detergent-insoluble brain proteome linked to amyloid and tau in Alzheimer's disease progression. Proteomics. 2016;16:3042–53. source

      Not checked in the free run.

    • cites [33] Hales CM, Dammer EB, Diner I, Yi H, Seyfried NT, Gearing M, Glass JD, Montine TJ, Levey AI, Lah JJ. Aggregates of small nuclear ribonucleic acids (snRNAs) in Alzheimer's disease. Brain Pathol. 2014;24:344–51. source

      Not checked in the free run.

    • cites [34] Hales CM, Seyfried NT, Dammer EB, Duong D, Yi H, Gearing M, Troncoso JC, Mufson EJ, Thambisetty M, Levey AI, Lah JJ. U1 small nuclear ribonucleoproteins (snRNPs) aggregate in Alzheimer's disease due to autosomal dominant genetic mutations and trisomy 21. Mol Neurodegener. 2014;9:15. source

      Not checked in the free run.

    • cites [35] Ash PE, Vanderweyde TE, Youmans KL, Apicco DJ, Wolozin B. Pathological stress granules in Alzheimer's disease. Brain Res. 2014;1584:52–8. source

      Not checked in the free run.

    • cites [36] Maziuk BF, Apicco DJ, Cruz AL, Jiang L, Ash PEA, da Rocha EL, Zhang C, Yu WH, Leszyk J, Abisambra JF, et al. RNA binding proteins co-localize with small tau inclusions in tauopathy. Acta Neuropathol Commun. 2018;6:71. source

      Not checked in the free run.

    • cites [37] Vanderweyde T, Yu H, Varnum M, Liu-Yesucevitz L, Citro A, Ikezu T, Duff K, Wolozin B. Contrasting pathology of the stress granule proteins TIA-1 and G3BP in tauopathies. J Neurosci. 2012;32:8270–83. source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    A majority of the differences in protein abundance between AsymAD and AD appear to be independent of simple brain cell type abundance changes, in contrast to the protein abundance differences between control and AsymAD and control and AD.

    “In summary, these findings suggest that a majority of the differences in protein abundance between AsymAD and AD appear to be independent of simple brain cell type abundance changes, in contrast to the protein abundance differences between control and AsymAD and control and AD.”
    Quote in the paperSubstantial claim

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

    Interpretationown data

    The anti-correlated modules potentially reflect AD resilience modules.

    “potentially reflecting AD “resilience” modules.”
    Quote in the paperNot a substantial claim

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

    Premisecitation

    U1 snRNPs are a major component of the AD insoluble proteome.

    “We have previously shown that U1 snRNPs are a major component of the AD insoluble proteome [24, 32–34].”
    Quote in the paperNot a substantial claim0 of 4 sources checked
    • cites [24] Bai B, Hales CM, Chen PC, Gozal Y, Dammer EB, Fritz JJ, Wang X, Xia Q, Duong DM, Street C, et al. U1 small nuclear ribonucleoprotein complex and RNA splicing alterations in Alzheimer's disease. Proc Natl Acad Sci U S A. 2013;110:16562–7. source

      Not checked in the free run.

    • cites [32] Hales CM, Dammer EB, Deng Q, Duong DM, Gearing M, Troncoso JC, Thambisetty M, Lah JJ, Shulman JM, Levey AI, Seyfried NT. Changes in the detergent-insoluble brain proteome linked to amyloid and tau in Alzheimer's disease progression. Proteomics. 2016;16:3042–53. source

      Not checked in the free run.

    • cites [33] Hales CM, Dammer EB, Diner I, Yi H, Seyfried NT, Gearing M, Glass JD, Montine TJ, Levey AI, Lah JJ. Aggregates of small nuclear ribonucleic acids (snRNAs) in Alzheimer's disease. Brain Pathol. 2014;24:344–51. source

      Not checked in the free run.

    • cites [34] Hales CM, Seyfried NT, Dammer EB, Duong D, Yi H, Gearing M, Troncoso JC, Mufson EJ, Thambisetty M, Levey AI, Lah JJ. U1 small nuclear ribonucleoproteins (snRNPs) aggregate in Alzheimer's disease due to autosomal dominant genetic mutations and trisomy 21. Mol Neurodegener. 2014;9:15. source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    Modules enriched in alt-EEjxns do not overlap significantly with RNA binding protein modules, but many are located within the unique region of the TMT network and correlate with molecular markers of AD pathology.

    “Modules that are enriched in alt-EEjxns do not overlap significantly with RNA binding protein modules, but many are located within the unique region of the TMT network and correlate with molecular markers of AD pathology.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Some of these modules are strongly enriched with alt-EEjxns and correlate with cognitive function.

    “Some of these modules are strongly enriched with alt-EEjxns and correlate with cognitive function.”
    Quote in the paperSubstantial claim

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

    Premisecitation

    The correlation between inflammation and tangle formation has also been noted in other tauopathies, such as frontotemporal dementia and chronic traumatic encephalopathy.

    “The correlation between inflammation and tangle formation has also been noted in other tauopathies, such as frontotemporal dementia and chronic traumatic encephalopathy [42–45].”
    Quote in the paperNot a substantial claim0 of 4 sources checked
    • cites [42] Bellucci A, Bugiani O, Ghetti B, Spillantini MG. Presence of reactive microglia and neuroinflammatory mediators in a case of frontotemporal dementia with P301S mutation. Neurodegener Dis. 2011;8:221–9. source

      Not checked in the free run.

    • cites [43] Cherry JD, Tripodis Y, Alvarez VE, Huber B, Kiernan PT, Daneshvar DH, Mez J, Montenigro PH, Solomon TM, Alosco ML, et al. Microglial neuroinflammation contributes to tau accumulation in chronic traumatic encephalopathy. Acta Neuropathol Commun. 2016;4:112. source

      Not checked in the free run.

    • cites [44] Maphis N, Xu G, Kokiko-Cochran ON, Jiang S, Cardona A, Ransohoff RM, Lamb BT, Bhaskar K. Reactive microglia drive tau pathology and contribute to the spreading of pathological tau in the brain. Brain. 2015;138:1738–55. source

      Not checked in the free run.

    • cites [45] Yoshiyama Y, Higuchi M, Zhang B, Huang SM, Iwata N, Saido TC, Maeda J, Suhara T, Trojanowski JQ, Lee VM. Synapse loss and microglial activation precede tangles in a P301S tauopathy mouse model. Neuron. 2007;53:337–51. source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    RNA binding proteins are enriched within specific network modules, and these modules are generally positively correlated with AD pathology and negatively correlated with cognitive function.

    “Overall, we found that RNA binding proteins are enriched within specific network modules, and that these modules are generally positively correlated with AD pathology and negatively correlated with cognitive function.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    The recapitulation of the LFQ network by the TMT-LysC network lends validity to the previous LFQ network from the BLSA cohort and by extension to LFQ-based networks of other cohorts.

    “This finding lends validity to the previous LFQ network generated from the BLSA cohort, and by extension to LFQ-based networks of other cohorts we have analyzed ([41], unpublished data).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [41] Umoh ME, Dammer EB, Dai J, Duong DM, Lah JJ, Levey AI, Gearing M, Glass JD, Seyfried NT. A proteomic network approach across the ALS-FTD disease spectrum resolves clinical phenotypes and genetic vulnerability in human brain. EMBO Mol Med. 2018;10:48–62. source

      Not checked in the free run.

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

    Premisecitation

    TPI1 is involved in gluconeogenesis and has been identified as interacting directly with Parkin, potentially affecting mitochondrial function.

    “TPI1 is involved in gluconeogenesis, but has also been identified as interacting directly with the Parkin protein, a ubiquitin protein ligase, and potentially affecting mitochondrial function [39].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [39] Davison EJ, Pennington K, Hung CC, Peng J, Rafiq R, Ostareck-Lederer A, Ostareck DH, Ardley HC, Banks RE, Robinson PA. Proteomic analysis of increased Parkin expression and its interactants provides evidence for a role in modulation of mitochondrial function. Proteomics. 2009;9:4284–97. source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductreasoning

    Missing values are not eliminated in the TMT approach because it relies on data-dependent acquisition, so not all batches contain the protein measurement of interest.

    “However, missing values are not eliminated in the TMT approach as it still relies on data-dependent acquisition techniques within each batch, and therefore not all batches contain the protein measurement of interest.”
    Quote in the paperNot a substantial claim

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

    Premisecitation

    Phosphorylation of tau at T231 has been associated with AD.

    “Phosphorylation of tau at T231 has been associated with AD [38], and levels of this peptide are moderately correlated with tau tangle burden (Additional file 10: Figure S3D).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [38] Hampel H, Blennow K, Shaw LM, Hoessler YC, Zetterberg H, Trojanowski JQ. Total and phosphorylated tau protein as biological markers of Alzheimer's disease. Exp Gerontol. 2010;45:30–40. source

      Not checked in the free run.

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

    Study design and conductown data

    The databases generated to identify alt-EEjxn peptides from brain were based on RNAseq data from relatively few control and AD brains from the University of Kentucky Brain Bank.

    “The databases we generated to identify alt-EEjxn peptides from brain were based on RNAseq data from relatively few control and AD brains from the University of Kentucky Brain Bank.”
    Quote in the paperNot a substantial claim

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

    Premisecitation

    U1-70K is a low complexity domain protein that binds RNA and has been associated with frontotemporal dementia.

    “as well as proteins with low complexity domains such as U1-70K that bind to RNA and that have been associated with other neurodegenerative conditions such as frontotemporal dementia [49].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [49] King OD, Gitler AD, Shorter J. The tip of the iceberg: RNA-binding proteins with prion-like domains in neurodegenerative disease. Brain Res. 2012;1462:61–80. source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Tangle burden is more closely correlated with cortical atrophy and cognitive decline than amyloid plaque burden.

    “given that tangle burden is more closely correlated with cortical atrophy and cognitive decline [46]”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [46] Nelson PT, Alafuzoff I, Bigio EH, Bouras C, Braak H, Cairns NJ, Castellani RJ, Crain BJ, Davies P, Del Tredici K, et al. Correlation of Alzheimer disease neuropathologic changes with cognitive status: a review of the literature. J Neuropathol Exp Neurol. 2012;71:362–81. source

      Not checked in the free run.

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

    Premisecitation

    M4 and M7 were previously found to be astroglial and strongly associated with AD.

    “unlike modules such as M4 and M7 which we have previously found to be astroglial and strongly associated with AD [5].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [5] Seyfried NT, Dammer EB, Swarup V, Nandakumar D, Duong DM, Yin L, Deng Q, Nguyen T, Hales CM, Wingo T, et al. A multi-network approach identifies protein-specific co-expression in asymptomatic and symptomatic Alzheimer's disease. Cell Syst. 2017;4:60–72 e64. source

      Not checked in the free run.

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

    Premisecitation

    snRNP alterations are associated with deficits in RNA splicing in AD brain, a finding recently confirmed by others.

    “Although we have previously observed that snRNP alterations are associated with deficits in RNA splicing in AD brain [24, 32]—a finding recently confirmed by others [52]”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [24] Bai B, Hales CM, Chen PC, Gozal Y, Dammer EB, Fritz JJ, Wang X, Xia Q, Duong DM, Street C, et al. U1 small nuclear ribonucleoprotein complex and RNA splicing alterations in Alzheimer's disease. Proc Natl Acad Sci U S A. 2013;110:16562–7. source

      Not checked in the free run.

    • cites [32] Hales CM, Dammer EB, Deng Q, Duong DM, Gearing M, Troncoso JC, Thambisetty M, Lah JJ, Shulman JM, Levey AI, Seyfried NT. Changes in the detergent-insoluble brain proteome linked to amyloid and tau in Alzheimer's disease progression. Proteomics. 2016;16:3042–53. source

      Not checked in the free run.

    • cites [52] Raj T, Li Y, Wong G, Ramdhani S, Wang Y-c, Ng B, Wang M, Gupta I, Haroutunian V, Zhang B, et al: Integrative analyses of splicing in the aging brain: role in susceptibility to Alzheimer's disease. bioRxiv 2017.

      Not checked in the free run.

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

    Interpretationnone given

    Trypsin digestion is more efficient than LysC and provides deeper coverage of the proteome.

    “This is likely the case because trypsin digestion is more efficient than LysC and provides deeper coverage of the proteome”
    Quote in the paperSubstantial claim

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

    Premisecitation

    Brain contains a large number of alternatively spliced proteins.

    “Because brain contains a large number of alternatively spliced proteins [50]”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [50] Yeo G, Holste D, Kreiman G, Burge CB. Variation in alternative splicing across human tissues. Genome Biol. 2004;5. source

      Not checked in the free run.

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

    Interpretationreasoning

    Deeper characterization of protein splice variants in brain will likely uncover more local splice variations that are translated into protein, with some being potentially relevant to disease.

    “we consider it likely that deeper characterization of protein splice variants in brain will uncover even more local splice variations that are translated into protein, with some being potentially relevant to disease.”
    Quote in the paperNot a substantial claim

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

    Interpretationreasoning

    It seems likely based on abundant steady state transcript levels that a majority of these splice isoforms are translated into protein.

    “but it seems likely based on abundant steady state transcript levels that a majority of these splice isoforms are translated into protein.”
    Quote in the paperNot a substantial claim

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

    Premisecitation

    Recent transcriptomic data suggest alterations in oligodendrocyte and myelination biology in AD brain.

    “which is consistent with recent transcriptomic data suggesting alterations in oligodendrocyte and myelination biology in AD brain [30, 47].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [30] Allen M, Wang X, Burgess JD, Watzlawik J, Serie DJ, Younkin CS, Nguyen T, Malphrus KG, Lincoln S, Carrasquillo MM, et al. Conserved brain myelination networks are altered in Alzheimer's and other neurodegenerative diseases. Alzheimers Dement. 2018;14:352–66. source

      Not checked in the free run.

    • cites [47] McKenzie AT, Moyon S, Wang M, Katsyv I, Song WM, Zhou X, Dammer EB, Duong DM, Aaker J, Zhao Y, et al. Multiscale network modeling of oligodendrocytes reveals molecular components of myelin dysregulation in Alzheimer's disease. Mol Neurodegener. 2017;12:82. source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    U1 spliceosome proteins undergo a dramatic shift in solubility in AD brain and aggregate in close proximity to neurofibrillary tangles.

    “This may be due to the fact that U1 spliceosome proteins undergo a dramatic shift in solubility in AD brain, and aggregate in close proximity to neurofibrillary tangles [24, 32–34].”
    Quote in the paperSubstantial claim0 of 4 sources checked
    • cites [24] Bai B, Hales CM, Chen PC, Gozal Y, Dammer EB, Fritz JJ, Wang X, Xia Q, Duong DM, Street C, et al. U1 small nuclear ribonucleoprotein complex and RNA splicing alterations in Alzheimer's disease. Proc Natl Acad Sci U S A. 2013;110:16562–7. source

      Not checked in the free run.

    • cites [32] Hales CM, Dammer EB, Deng Q, Duong DM, Gearing M, Troncoso JC, Thambisetty M, Lah JJ, Shulman JM, Levey AI, Seyfried NT. Changes in the detergent-insoluble brain proteome linked to amyloid and tau in Alzheimer's disease progression. Proteomics. 2016;16:3042–53. source

      Not checked in the free run.

    • cites [33] Hales CM, Dammer EB, Diner I, Yi H, Seyfried NT, Gearing M, Glass JD, Montine TJ, Levey AI, Lah JJ. Aggregates of small nuclear ribonucleic acids (snRNAs) in Alzheimer's disease. Brain Pathol. 2014;24:344–51. source

      Not checked in the free run.

    • cites [34] Hales CM, Seyfried NT, Dammer EB, Duong D, Yi H, Gearing M, Troncoso JC, Mufson EJ, Thambisetty M, Levey AI, Lah JJ. U1 small nuclear ribonucleoproteins (snRNPs) aggregate in Alzheimer's disease due to autosomal dominant genetic mutations and trisomy 21. Mol Neurodegener. 2014;9:15. source

      Not checked in the free run.

90 of 90

  • The paper relies on this without support.

    The altered biochemical and cellular processes that eventually lead to changes in cognition and pathology in AD are not well understood.

    “While AD is currently defined by cognitive decline in the presence of amyloid plaque and tau tangle accumulation within the brain, the altered biochemical and cellular processes that eventually lead to changes in cognition and pathology are not well understood.”

  • The paper relies on this without support.

    The WGCNA algorithm for coexpression network analysis well-tolerates missing values up to 50%.

    “As part of the new analysis approach, we also relaxed the data inclusion criteria to require missing values in < 50% rather than < 10% of the samples, given that the WGCNA algorithm for coexpression network analysis well-tolerates missing values up to 50%.”

  • The paper relies on this without support.

    Changes in RNA splicing leading to the expression of different protein isoforms may be a useful indicator of AD pathology and cause downstream cellular and network dysfunction leading to cognitive decline.

    “Changes in RNA splicing leading to the expression of different protein isoforms may be a useful indicator of AD pathology and cause downstream cellular and network dysfunction leading to cognitive decline.”

  • The paper relies on this without support.

    Either the 3-repeat or the 4-repeat microtubule binding domain isoform of tau can be considered constitutively expressed in humans.

    “because either isoform can be considered constitutively expressed in humans.”

  • The paper relies on this without support.

    The tau pT231 peptide lies within the proline-rich region of tau and is separate from the microtubule-binding region that aggregates into neurofibrillary tangles.

    “which lies within the proline-rich region of tau and is separate from the microtubule-binding region that aggregates into neurofibrillary tangles.”

  • The paper relies on this without support.

    Most of the common alternatively spliced transcripts present in DLPFC control and AD brain were represented in the RNAseq-based database used to identify alt-EEjxn peptides.

    “However, most of the common alternatively spliced transcripts present in DLPFC control and AD brain were likely represented in this database.”

  • The paper relies on this without support.

    FERMT2 is an AD risk factor protein.

    “with the exception of FERMT2, which has been identified as an AD risk factor protein.”
7 of 7

Claims other papers make about this one

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Cites

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Research works printed but not linked: 1

  1. Prince M, Wimo A, Guerchet M, Ali G, Wu Y, Prina M. World Alzheimer report 2015: the global impact of dementia. In book world Alzheimer report 2015: the global impact of dementia (editor ed.^eds.). City: Alzheimer's Disease International; 2015.

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Related

Authors
Johnson, E. C. B., Dammer, E. B., Duong, D. M., Yin, L., Thambisetty, M., Troncoso, J. C., Lah, J. J., Levey, A. I., & Seyfried, N. T.
Affiliations
  • Emory University (US)
  • National Institutes of Health (US)
  • Johns Hopkins University (US)
Corresponding author
  • Johnson, Erik C. B.
  • Seyfried, Nicholas T.
ORCID
Venue
Molecular Neurodegeneration
Publisher
Springer Science and Business Media LLC
Published
2018-10-04
Volume
13
Issue
1
Pages
52-52
ISSN
1750-1326 (ISSN-L)
DOI
10.1186/s13024-018-0282-4
PMC
PMC6172707
OpenAlex
W2895694428
Cited by
225
References
53
Citations by year
2026: 17 · 2025: 23 · 2024: 37 · 2023: 29 · 2022: 22 · 2021: 45 · 2020: 36 · 2019: 11 · 2018: 3
FWCI
16.50
Type
journal article
Language
en
Open access
Licence
Locations
  • Molecular Neurodegeneration (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Accelerating Medicine Partnership AD (U01AG046161-02)
  • National Institute on Aging (5R01AG053960, RF1AG057471, P50AG05146, P50AG025688, R21AG054206, RF1AG057470)
  • National Institute of Neurological Disorders and Stroke (P30NS055077)
  • Alzheimer's Association (11060)
  • Alzheimer’s Research UK
  • Michael J. Fox Foundation for Parkinson's Research
  • Weston Brain Institute
  • BrightFocus Foundation (A2015332S)
  • NIA Division of Intramural Research
Topics
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
Keywords
Alzheimer's disease, brain proteome, RNA-binding proteins, RNA splicing, alternative splicing, protein isoforms, asymptomatic Alzheimer's disease, proteogenomics, BIN1, PICALM, Pyk2, FERMT2, differential protein abundance, cognitive decline
MeSH terms
Alzheimer Disease, Brain, Cognition, Humans, RNA Splicing, RNA-Binding Proteins, Alternative Splicing, Proteomics, Tandem Mass Spectrometry, 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 2026-10-10.

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

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