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Cited by 2,946Alzheimer's disease research and treatmentsDementia and Cognitive Impairment ResearchGenetic Associations and Epidemiology

Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

Open access
Alzheimer Disease Genetics Consortium (ADGC),, Kunkle, Brian W., The European Alzheimer’s Disease Initiative (EADI),, Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE),, Genetic and Environmental Risk in AD/Defining Genetic, Polygenic and Environmental Risk for Alzheimer’s Disease Consortium (GERAD/PERADES),, Grenier-Boley, Benjamin, Sims, Rebecca, Bis, Joshua C. +464 more·2019·Nature Genetics
DOI 10.1038/s41588-019-0358-2PMC PMC6463297
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Abstract

Risk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10-7), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.

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Crossref · 10.1038/s41588-019-0358-2

Cites

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Claims the paper makes

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  • Findingown data

    The study identifies important genetic correlations between LOAD and traits such as family history of dementia and education.

    “We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.”
    Quote in the paperNot a substantial claim
  • Findingown data

    Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10−7).

    “Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10−7)”
    Quote in the paperSubstantial claim
  • Findingown data

    Fine-mapping of the HLA region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD.

    “Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD.”
    Quote in the paperSubstantial claim
  • Findingown data

    The study confirms 20 previous LOAD risk loci.

    “We confirm 20 previous LOAD risk loci”
    Quote in the paperNot a substantial claim
  • Findingown data

    Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and APP metabolism.

    “Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism”
    Quote in the paperSubstantial claim
  • May combine two claims. 63
  • Classified as probably not a substantial claim. 57
  • The quote only partly states this claim. 1

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    Findingown data

    Meta-analysis of Stages 1 and 2 produced 21 genome-wide-significant associations (P ≤ 5 × 10−8), 18 of which were previously reported as genome-wide significant in Lambert et al.

    “Meta-analysis of Stages 1 and 2 produced 21 genome-wide-significant associations (P ≤ 5 × 10−8) (Table 1 and Fig. 1), 18 of which were previously reported as genome-wide significant in Lambert et al.1.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [1] 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.

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    Findingown data

    Stage 1 discovery meta-analysis produced 12 loci with genome-wide significance (P ≤ 5 × 10−8), all previously described.

    “The Stage 1 discovery meta-analysis produced 12 loci with genome-wide significance (P ≤ 5 × 10−8) (Table 1), all of which are previously described1,4–11.”
    Quote in the paperNot a substantial claim0 of 9 sources checked
    • cites [1] 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

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    • cites [4] Naj, A. C. et al. Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer’s disease. Nat. Genet. 43, 436–441 (2011). source

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    • cites [5] Seshadri, S. et al. Genome-wide analysis of genetic loci associated with Alzheimer disease. JAMA 303, 1832–1840 (2010). source

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    • cites [6] Hollingworth, P. et al. Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer’s disease. Nat. Genet. 43, 429–435 (2011). source

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    • cites [7] Jonsson, T. et al. Variant of TREM2 associated with the risk of Alzheimer’s disease. N. Engl. J. Med. 368, 107–116 (2013). source

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    • cites [8] Guerreiro, R. et al. TREM2 variants in Alzheimer’s disease. N. Engl. J. Med. 368, 117–127 (2013). source

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    • cites [9] Jun, G. et al. Meta-analysis confirms CR1, CLU, and PICALM as alzheimer disease risk loci and reveals interactions with APOE genotypes. Arch. Neurol. 67, 1473–1484 (2010). source

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    • cites [10] Harold, D. et al. Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer’s disease. Nat. Genet. 41, 1088–1093 (2009). source

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    • cites [11] Lambert, J. C. et al. Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer’s disease. Nat. Genet. 41, 1094–1099 (2009). source

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  • May combine two claims.

    Findingown data

    There were no eQTLs in Alzheimer's disease-relevant tissues in the WWOX or ACE locus, although several eQTLs for PSMC5 in coronary artery tissue were found for the ACE locus.

    “There were no eQTLs in Alzheimer’s disease–relevant tissues in the WWOX or ACE locus, although several eQTLs for PSMC5 in coronary artery tissue were found for the ACE locus.”
    Quote in the paperNot a substantial claim

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    Findingown data

    Genes driving these enrichments included SCNA for the tau pathway; apolipoprotein genes (APOM, APOA5) and ABCA1 for the lipid metabolism pathways; and 52 immune pathway genes.

    “Genes driving these enrichments (that is, having a gene-wide P < 0.05) included SCNA, a Parkinson’s risk gene that encodes alpha-synuclein, the main component of Lewy bodies, whch may play a role in tauopathies62,63, for the tau pathway; apolipoprotein genes (APOM, APOA5) and ABCA1, a major regulator of cellular cholesterol, for the lipid metabolism pathways; and 52 immune pathway genes”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [62] Stefanis, L. alpha-Synuclein in Parkinson’s disease. Cold Spring Harb. Perspect. Med. 2, 1–23 (2012). source

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    • cites [63] Takeda, A. et al. C-terminal alpha-synuclein immunoreactivity in structures other than Lewy bodies in neurodegenerative disorders. Acta Neuropathol. 99, 296–304 (2000). source

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    Findingown data

    When APOE-region genes and genes near genome-wide-significant genes were removed, tau showed moderate association (P = 0.027), and lipid metabolism and immune-related pathways showed strong associations (P < 0.001).

    “When APOE-region genes and genes near genome-wide-significant genes were removed, tau showed moderate association (P = 0.027), and lipid metabolism and immune-related pathways showed strong associations (P < 0.001)”
    Quote in the paperSubstantial claim

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    Findingown data

    Two of the four other signals approached genome-wide significance: miR142/TSPOAP1-AS1 (P = 5.3 × 10−8) and NDUFAF6 (P = 9.2 × 10−8).

    “Two of the four other signals approached genome-wide significance: miR142/TSPOAP1-AS1 (P = 5.3 × 10−8) and NDUFAF6 (P = 9.2 × 10−8) (Table 2).”
    Quote in the paperSubstantial claim

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    Findingown data

    Only 2% of 1,073 variants across the 24 loci (excluding APOE) were exonic, with a majority (58%) being intronic.

    “only 2% of 1,073 variants across the 24 loci (excluding APOE) were exonic variants, with a majority (58%) being intronic”
    Quote in the paperNot a substantial claim

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    Findingown data

    Co-localization analysis confirmed evidence of a shared causal variant affecting expression and disease risk in 66 genes over 20 loci, including 31 genes over 13 loci in LOAD-relevant tissue.

    “Co-localization analysis confirmed evidence of a shared causal variant affecting expression and disease risk in 66 genes over 20 loci, including 31 genes over 13 loci in LOAD-relevant tissue”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    For newly identified loci, there were significant eQTLs in Alzheimer's disease-relevant tissue for ADAM10, FAM63B, and SLTM (ADAM10 locus); ADAMTS1 (ADAMTS1 locus); and ACSM1, ANKS4B, C16orf62, GDE1, GPRC5B, IQCK, and KNOP1 (IQCK locus).

    “For our newly identified loci, there were significant eQTLs in Alzheimer’s disease–relevant tissue for ADAM10, FAM63B, and SLTM (in the ADAM10 locus); ADAMTS1 (ADAMTS1 locus); and ACSM1, ANKS4B, C16orf62, GDE1, GPRC5B, IQCK, and KNOP1 (IQCK locus).”
    Quote in the paperSubstantial claim

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    Findingown data

    Nominal enrichment for risk from rare variants was found for the pathway 'aggregation of Aβ: chaperone' and 23 of the 335 genes.

    “Nominal enrichment for risk from rare variants was found for the pathway ‘aggregation of Aβ: chaperone’ and 23 of the 335 genes.”
    Quote in the paperNot a substantial claim

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    Findingown data

    Overlapping cis-acting eQTLs were found for 153 of the 400 protein-coding genes, with 136 eQTL-controlled genes in Alzheimer's disease-relevant tissues.

    “we found overlapping cis-acting eQTLs for 153 of the 400 protein-coding genes, with 136 eQTL-controlled genes in Alzheimer’s disease–relevant tissues”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Several sub-pathways were significantly enriched in the common variants, including 'clearance and degradation of Aβ', and 'aggregation of Aβ', along with its subcategory 'microglia'.

    “Several ‘sub-pathways’ were also significantly enriched in the common variants, including ‘clearance and degradation of Aβ’, and ‘aggregation of Aβ’, along with its subcategory ‘microglia’”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    A low-frequency variant in the TREM2 region (rs114812713) in OARD1 was replicated (MAF = 0.03, P = 7.2 × 10−3; combined P = 2.1 × 10−13) and may represent an independent signal.

    “replicated a low-frequency variant in the TREM2 region (rs114812713; NC_000006.11: g.41034000G>C, MAF = 0.03, P = 7.2 × 10−3; combined P = 2.1 × 10−13) in the gene OARD1 that may represent an independent signal according to our conditional analysis”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Analysis of 335 APP metabolism genes observed significant enrichment of this gene set in common variants (P = 2.27 × 10−4; P = 3.19 × 10−4 excluding APOE), with both ADAM10 and ACE nominally significant drivers.

    “We observed significant enrichment of this gene set in common variants (P = 2.27 × 10−4; P = 3.19 × 10−4 excluding APOE), with both ADAM10 and ACE nominally significant drivers of this result”
    Quote in the paperSubstantial claim

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    Findingown data

    When not considering fetal astrocytes, mature astrocytes (21%) and microglial cells (20.3%) became the highest expressed cell types in the genome-wide set of genes, with 5.3% of the 400 genes showing high microglial expression.

    “When not considering fetal astrocytes, mature astrocytes (21%), and microglial cells (20.3%), the resident macrophage cells of the brain thought to play a key role in the pathologic immune response in LOAD8,14,60, became the highest expressed cell types in the genome-wide set of genes, with 5.3% of the 400 genes showing high microglial expression”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [8] Guerreiro, R. et al. TREM2 variants in Alzheimer’s disease. N. Engl. J. Med. 368, 117–127 (2013). source

      Not checked in the free run.

    • cites [14] Sims, R. C. et al. Novel rare coding variants in PLCG2, ABI3 and TREM2 implicate microglial-mediated innate immunity in Alzheimer’s disease. Nat. Genet. 49, 1373–1387 (2017). source

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    • cites [60] Gjoneska, E. et al. Conserved epigenomic signals in mice and humans reveal immune basis of Alzheimer’s disease. Nature 518, 365–369 (2015). source

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  • May combine two claims.

    Findingown data

    No pathways were significantly enriched for rare variants, but lipid and Aβ pathways reached nominal significance in rare-variant-only analyses.

    “While no pathways were significantly enriched for rare variants, lipid and Aβ pathways did reach nominal significance in rare-variant-only analyses.”
    Quote in the paperNot a substantial claim

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

    Findingcitation

    The sentinel variant in WWOX is just 2.4 mega-bases from PLCG2, which contains a rare variant recently associated with Alzheimer's disease.

    “the sentinel variant (defined as the variant with the lowest P value) is just 2.4 mega-bases from PLCG2, which contains a rare variant that we recently associated with Alzheimer’s disease14.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [14] Sims, R. C. et al. Novel rare coding variants in PLCG2, ABI3 and TREM2 implicate microglial-mediated innate immunity in Alzheimer’s disease. Nat. Genet. 49, 1373–1387 (2017). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    There was a highly significant correlation between common and rare pathway gene results (P = 1.32 × 10−7), suggesting that risk Alzheimer's disease genes and pathways are enriched for rare variants.

    “we also observed a highly significant correlation between common and rare pathway gene results (P = 1.32 × 10−7), suggesting that risk Alzheimer’s disease genes and pathways are enriched for rare variants.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    80% of the 400 genes were expressed in at least one type of brain cell, and the genes were most highly expressed in fetal astrocytes (26%), followed by microglia/macrophages (15.8%), neurons (14.8%), astrocytes (11.5%), and oligodendrocytes (6.5%).

    “80% were expressed in at least one type of brain cell, and the genes were most highly expressed in fetal astrocytes (26%), followed by microglia/ macrophages (15.8%), neurons (14.8%), astrocytes (11.5%), and oligodendrocytes (6.5%).”
    Quote in the paperNot a substantial claim

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    Findingown data

    Potentially deleterious variants include the rare R47H missense variant in TREM2, common missense variants in CR1, SPI1, MS4A2, and IQCK, and a relatively common (MAF = 0.16) splicing variant in IQCK.

    “Potentially deleterious variants include the rare R47H missense variant in TREM2, common missense variants in CR1, SPI1, MS4A2, and IQCK, and a relatively common (MAF = 0.16) splicing variant in IQCK.”
    Quote in the paperSubstantial claim

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

    Findingown data

    Stage 3A extended the analysis of two loci (NME8 and MEF2C) that were previously genome-wide significant in the 2013 meta-analysis.

    “Stage 3A also extended the analysis of two loci (NME8 and MEF2C) that were previously genome-wide significant in our 2013 meta-analysis.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Three signals not initially described in the initial IGAP GWAS were the rare R47H TREM2 coding variant, ECHDC3, and ACE.

    “Three other signals were not initially described in the initial IGAP GWAS: the rare R47H TREM2 coding variant previously reported by others7,8,14; ECHDC3 (rs7920721; NC_000010.10: g.11720308A>G), which was recently identified as a potential genome-wide-significant Alzheimer’s disease risk locus in several studies15–17, and ACE (rs138190086; NC_000017.10: g.61538148G>A)”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [7] Jonsson, T. et al. Variant of TREM2 associated with the risk of Alzheimer’s disease. N. Engl. J. Med. 368, 107–116 (2013). source

      Not checked in the free run.

    • cites [8] Guerreiro, R. et al. TREM2 variants in Alzheimer’s disease. N. Engl. J. Med. 368, 117–127 (2013). source

      Not checked in the free run.

    • cites [14] Sims, R. C. et al. Novel rare coding variants in PLCG2, ABI3 and TREM2 implicate microglial-mediated innate immunity in Alzheimer’s disease. Nat. Genet. 49, 1373–1387 (2017). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Using a large whole-exome-sequencing study, ten genes located in genome-wide loci were identified as having rare deleterious coding, splicing or LOF burden associations with LOAD (FDR P < 0.01), including ABCA7, TREM2, SORL1, TREML4, TAP2, PSMB8, PIP, STYX, RIN3, and KCNH6.

    “we also identified ten genes located in our genome-wide loci as having rare deleterious coding, splicing or LOF burden associations with LOAD (false discovery rate (FDR) P < 0.01), including previously implicated rare-variant signals in ABCA7, TREM2, and SORL1 (refs. 14,49–55), and additional associations with TREML4 in the TREM2 locus, TAP2 and PSMB8 in the HLA-DRB1 locus, PIP in the EPHA1 locus,”
    Quote in the paperSubstantial claim0 of 8 sources checked
    • cites [14] Sims, R. C. et al. Novel rare coding variants in PLCG2, ABI3 and TREM2 implicate microglial-mediated innate immunity in Alzheimer’s disease. Nat. Genet. 49, 1373–1387 (2017). source

      Not checked in the free run.

    • cites [49] Bis, J. C. et al. Whole exome sequencing study identifies novel rare and common Alzheimer’s-associated variants involved in immune response and transcriptional regulation. Mol. Psychiatry https://doi.org/10.1038/s41380-018-0112-7 (2018). source

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    • cites [50] Vardarajan, B. N. et al. Coding mutations in SORL1 and Alzheimer disease. Ann. Neurol. 77, 215–227 (2015). source

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    • cites [51] Verheijen, J. et al. A comprehensive study of the genetic impact of rare variants in SORL1 in European early-onset Alzheimer’s disease. Acta Neuropathol. 132, 213–224 (2016). source

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    • cites [52] Bellenguez, C. et al. Contribution to Alzheimer’s disease risk of rare variants in TREM2, SORL1, and ABCA7 in 1779 cases and 1273 controls. Neurobiol. Aging. 59, 220.e1–220.e9 (2017). source

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    • cites [53] Kunkle, B. W. et al. Targeted sequencing of ABCA7 identifies splicing, stop-gain and intronic risk variants for Alzheimer disease. Neurosci. Lett. 649, 124–129 (2017). source

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    • cites [54] May, P. et al. Rare ABCA7 variants in 2 German families with Alzheimer disease. Neurol. Genet. 4, e224 (2018). source

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    • cites [55] Guennec, K. Le et al. ABCA7 rare variants and Alzheimer disease risk. Neurology 86, 1–4 (2016). source

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    Findingown data

    These alleles form the HLA-DQA1*01:02~HLA-DQB1*06:02~HLA-DRB1*15:01 (DR15) haplotype, which is also associated with Alzheimer's disease in our sample (FDR P = 0.013).

    “These alleles form the HLA-DQA1*01:02~HLA-DQB1*06:02~HLA-DRB1*15:01 (DR15) haplotype, which is also associated with Alzheimer’s disease in our sample (FDR P = 0.013)”
    Quote in the paperSubstantial claim

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    Findingown data

    Of the 22 genes in the ACE locus, PSMC5 has a top score of 4, while DDX42, MAP3K3, and CD79B each have a score of 3.

    “Of the 22 genes in the ACE locus, PSMC5, a key regulator of major histocompatibility complex (MHC)75,76, has a top score of 4, while DDX42, MAP3K3, an important regulator of macrophages and innate immunity77,78, and CD79B, a B lymphocyte antigen receptor subunit, each have a score of 3.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [75] Bhat, K. et al. The 19S proteasome ATPase Sug1 plays a critical role in regulating MHC class II transcription. Mol. Immunol. 45, 2214–2224 (2008). source

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    • cites [76] Inostroza-Nieves, Y., Venkatraman, P. & Zavala-Ruiz, Z. Role of Sug1, a 19S proteasome ATPase, in the transcription of MHC I and the atypical MHC II molecules, HLA-DM and HLA-DO. Immunol. Lett. 147, 67–74 (2012). source

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    • cites [77] Kim, K., Duramad, O., Qin, X. F. & Su, B. MEKK3 is essential for lipopolysaccharide-induced interleukin-6 and granulocyte-macrophage colony-stimulating factor production in macrophages. Immunology 120, 242–250 (2007). source

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    Findingown data

    The 53 genes are overexpressed in 'adolescence' and 'young adult' brain tissues in BrainSpan, consistent with accumulating evidence suggesting Alzheimer's disease may start decades before the onset of disease.

    “the 53 genes are overexpressed in ‘adolescence’ and ‘young adult’ brain tissues in BrainSpan103, a transcriptomic atlas of the developing human brain, which is consistent with accumulating evidence suggesting Alzheimer’s disease may start decades before the onset of disease104,105”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [103] Miller, J. A. et al. Transcriptional landscape of the prenatal human brain. Nature 508, 199–206 (2014). source

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    • cites [104] Knickmeyer, R. C. & Ross, M. E. Imaging and rare APOE alleles. Neurology 87, 558–559 (2016). source

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    • cites [105] Douaud, G. et al. A common brain network links development, aging, and vulnerability to disease. Proc. Natl Acad. Sci. USA 111, 17648–17653 (2014). source

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    Findingown data

    Two additional alleles, HLA-DQA1*03:01 and HLA-DQB1*03:02, show a protective effect on Alzheimer's disease, but their signal was lost after conditioning on HLA-DQA1*01:02, and the HLA-DQA1*03:01~HLA-DQB1*03:02 haplotype is not associated with Alzheimer's disease (FDR P = 0.651).

    “Two additional alleles, HLA-DQA1*03:01 and HLA-DQB1*03:02, belonging to another haplotype, show a protective effect on Alzheimer’s disease, but their signal was lost after conditioning on HLA-DQA1*01:02, and the HLA-DQA1*03:01~HLA-DQB1*03:02 haplotype is not associated with Alzheimer’s disease (FDR P = 0.651).”
    Quote in the paperNot a substantial claim

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    Findingown data

    WWOX and MAF were both prioritized for the WWOX locus, with MAF highly expressed in microglia and WWOX expressed most highly in astrocytes and neurons.

    “WWOX and MAF, which surround an intergenic signal in an obesity associated locus91, were both prioritized for the WWOX locus, with MAF, another important regulator of macrophages92,93, being highly expressed in microglia in the Brain RNA-seq database, and WWOX, a high-density-lipoprotein cholesterol and triglyceride–associated gene94,95, being expressed most highly in astrocytes and neurons.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [91] Wang, K. et al. A genome-wide association study on obesity and obesity-related traits. PLoS ONE 6, 3–8 (2011). source

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    • cites [92] Kang, K. et al. Interferon-γ represses M2 gene expression in human macrophages by disassembling enhancers bound by the transcription factor MAF. Immunity 47, 235–250.e4 (2017). source

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    • cites [93] Cao, S., Liu, J., Song, L. & Ma, X. The protooncogene c-Maf Is an essential transcription factor for IL-10 gene expression in macrophages. J. Immunol. 174, 3484–3492 (2005). source

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    Findingcitation

    These studies yielded inconsistent results, and our work reports a clear genome-wide association in NHW at the ACE locus.

    “However, these studies yielded inconsistent results23, and our work reports a clear genome-wide association in NHW at this locus.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [23] Wang, X.-B. et al. Angiotensin-converting enzyme insertion/deletion polymorphism is not a major determining factor in the development of sporadic Alzheimer disease: evidence from an updated meta-analysis. PLoS ONE 9, e111406 (2014). source

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    Findingown data

    DEG set enrichment analysis of prioritized genes using GTEx tissues identified significant differential expression in immune-related tissues (upregulation in blood and spleen), obesity-related tissue (upregulation in adipose), heart tissues (upregulation in left ventricle and atrial appendage), and brain tissues (downregulation in cortex, cerebellum, hippocampus, basal ganglia, and amygdala).

    “we identified significant differential expression in several potentially relevant Alzheimer’s disease tissues including immune-related tissues (upregulation in blood and spleen), obesity-related tissue (upregulation in adipose), heart tissues (upregulation in left ventricle and atrial appendage), and brain tissues (dowregulation in cortex, cerebellum, hippo-campus, basal ganglia, and amygdala).”
    Quote in the paperSubstantial claim

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    Findingown data

    Fine-mapping found risk effects of HLA-DQA1*01:02 (FDR P = 0.014), HLA-DRB1*15:01 (FDR P = 0.083), and HLA-DQB1*06:02 (FDR P = 0.010).

    “We found risk effects of HLA-DQA1*01:02 (FDR P = 0.014), HLA-DRB1*15:01 (FDR P = 0.083), and HLA-DQB1*06:02 (FDR P = 0.010)”
    Quote in the paperSubstantial claim

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    Findingown data

    After conditioning on the sentinel meta-analysis variant rs78738018, association signals were lost for the three alleles, suggesting that the signal observed at the variant level is due to the association of these three alleles.

    “After conditioning on the sentinel meta-analysis variant in this region (rs78738018), association signals were lost for the three alleles, suggesting that the signal observed at the variant level is due to the association of these three alleles.”
    Quote in the paperSubstantial claim

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    Findingown data

    For the IQCK signal, IQCK was ranked top, although four of the other 11 genes in the locus have a priority rank ≥ 4, including KNOP1 and GPRC5B.

    “For the IQCK signal, which is also an obesity locus70,71, IQCK, a relatively uncharacterized gene, was ranked top, although four of the other 11 genes in the locus have a priority rank ≥ 4, including KNOP1 and GPRC5B”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [70] Hinney, A. et al. Genetic variation at the CELF1 (CUGBP, elav-like family member 1 gene) locus is genome-wide associated with Alzheimer’s disease and obesity. Am. J. Med. Genet. B. 165B, 283–293 (2014). source

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    • cites [71] Speliotes, E. K. et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat. Genet. 42, 937–948 (2010). source

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  • May combine two claims.

    Findingown data

    Pathway, tissue and disease trait enrichment analyses support the utility of the prioritization method, as the 53 prioritized genes with a score ≥ 5 are enriched in substantially more Alzheimer's disease-relevant pathways, processes and dementia-related traits; enriched in candidate Alzheimer's disease cell types such as monocytes (adjusted P = 9.0 × 10−6) and macrophages (adjusted P = 5.6 × 10−3;

    “Pathway, tissue and disease trait enrichment analyses support the utility of our prioritization method, as the 53 prioritized genes with a score ≥ 5 are (1) enriched in substantially more Alzheimer’s disease–relevant pathways, processes and dementia-related traits; (2) enriched in candidate Alzheimer’s disease cell types such as monocytes (adjusted P = 9.0 × 10−6) and macrophages (adjusted P = 5.6”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Use of blood pressure medication shows a negative genetic correlation with Alzheimer's disease (rg = −0.12; P = 0.035), although this result does not survive FDR correction.

    “use of blood pressure medication does show a negative genetic correlation with Alzheimer’s disease in our study (rg = −0.12; P = 0.035), although this result does not survive FDR correction.”
    Quote in the paperNot a substantial claim

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

    Findingown data

    The average size of the LD blocks was 123 kb.

    “The average size of the LD blocks was 123 kb.”
    Quote in the paperNot a substantial claim

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

    Findingnone given

    A total of 1,180,989 variants were used in the correlation analyses.

    “A total of 1,180,989 variants were used in the correlation analyses.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). The quote only partly states this claim.

    Findingown data

    After imputation quality control, a total of 14,776 cases and 23,047 controls were available for HLA analysis.

    “After imputation quality control, a total of 14,776 cases and 23,047 controls were available for analysis (Supplementary Table 27).”
    Quote in the paperNot a substantial claim

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

    Findingown data

    Removal of the APOE region reduced the heritability estimate slightly from 0.071 (s.e.m. = 0.011) to 0.0637 (s.e.m. = 0.009).

    “Removal of the APOE region reduced the heritability estimate slightly from 0.071 (s.e.m. = 0.011) to 0.0637 (s.e.m. = 0.009).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductown data

    LDSC regression estimates indicated that the majority of inflation was due to polygenic signal, with intercept close to 1 (1.026, s.e.m. = 0.006).

    “univariate linkage disequilibrium score (LDSC) regression12,13 estimates indicated that the majority of this inflation was due to a polygenic signal, with the intercept being close to 1 (1.026, s.e.m. = 0.006).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [12] Zheng, J. et al. LD Hub: A centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics 33, 051094 (2017).

      Not checked in the free run.

    • cites [13] Bulik-Sullivan, B. K. et al. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015). source

      Not checked in the free run.

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

    Premisecitation

    ACE and ADAM10 were previously reported as Alzheimer's disease candidate genes but were not replicated in some subsequent studies.

    “ACE and ADAM10 were previously reported as Alzheimer’s disease candidate genes18–22 but were not replicated in some subsequent studies23–25.”
    Quote in the paperNot a substantial claim0 of 8 sources checked
    • cites [18] Vassar, R. ADAM10 prodomain mutations cause late-onset Alzheimer’s disease: not just the latest FAD. Neuron 80, 250–253 (2013). source

      Not checked in the free run.

    • cites [19] Kim, M. et al. Potential late-onset Alzheimer’s disease-associated mutations in the ADAM10 gene attenuate alpha-secretase activity. Hum. Mol. Genet. 18, 3987–3996 (2009). source

      Not checked in the free run.

    • cites [20] Kehoe, P. G. et al. Variation in DCP1, encoding ACE, is associated with susceptibility to Alzheimer disease. Nat. Genet. 21, 71–72 (1999). source

      Not checked in the free run.

    • cites [21] Meng, Y. et al. Association of polymorphisms in the Angiotensin-converting enzyme gene with Alzheimer disease in an Israeli Arab community. Am. J. Hum. Genet. 78, 871–877 (2006). source

      Not checked in the free run.

    • cites [22] Lehmann, D. J. et al. Large meta-analysis establishes the ACE insertion-deletion polymorphism as a marker of Alzheimer’s disease. Am. J. Epidemiol. 162, 305–317 (2005). source

      Not checked in the free run.

    • cites [23] Wang, X.-B. et al. Angiotensin-converting enzyme insertion/deletion polymorphism is not a major determining factor in the development of sporadic Alzheimer disease: evidence from an updated meta-analysis. PLoS ONE 9, e111406 (2014). source

      Not checked in the free run.

    • cites [24] Cai, G. et al. Evidence against a role for rare ADAM10 mutations in sporadic Alzheimer disease. Neurobiol. Aging. 33, 416–417.e3 (2012).

      Not checked in the free run.

    • cites [25] Belbin, O. et al. A multi-center study of ACE and the risk of late-onset Alzheimer’s disease. J. Alzheimers. Dis. 24, 587–597 (2011). source

      Not checked in the free run.

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

    Premisecitation

    WWOX may play a role in Alzheimer's disease through its interaction with tau.

    “WWOX may play a role in Alzheimer’s disease through its interaction with tau28,29”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [28] Chang, J.-Y. & Chang, N.-S. WWOX dysfunction induces sequential aggregation of TRAPPC6AΔ, TIAF1, tau and amyloid β, and causes apoptosis. Cell Death Discov. 1, 15003 (2015). source

      Not checked in the free run.

    • cites [29] Sze, C. I. et al. Down-regulation of WW domain-containing oxidoreductase induces tau phosphorylation in vitro: a potential role in Alzheimer’s disease. J. Biol. Chem. 279, 30498–30506 (2004). source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    ADAM10 is the most important α-secretase in the brain, is a component of the non-amyloidogenic pathway of APP metabolism, and sheds TREM2.

    “ADAM10, the most important α-secretase in the brain, is a component of the non-amyloidogenic pathway of APP metabolism67 and sheds TREM2 (ref. 68)”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [67] Haass, C., Kaether, C., Thinakaran, G. & Sisodia, S. Trafficking and proteolytic processing of APP. Cold Spring Harb. Perspect. Med. 2, a006270 (2012). source

      Not checked in the free run.

    • cites [68] Kleinberger, G. et al. TREM2 mutations implicated in neurodegeneration impair cell surface transport and phagocytosis. Sci. Transl. Med. 6, 243ra86 (2014). source

      Not checked in the free run.

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

    Premisecitation

    Overexpression of ADAM10 in mouse models can halt Aβ production and subsequent aggregation.

    “Overexpression of ADAM10 in mouse models can halt Aβ production and subsequent aggregation69.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [69] Postina, R. et al. A disintegrin-metalloproteinase prevents amyloid plaque formation and hippocampal defects in an Alzheimer disease mouse model. J. Clin. Invest. 113, 1456–1464 (2004). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Previous analyses in the ADGC have linked both HLA class I and II haplotypes with Alzheimer's disease risk.

    “Previous analyses in the ADGC (5,728 Alzheimer’s disease cases and 5,653 controls) have linked both HLA class I and II haplotypes with Alzheimer’s disease risk106.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [106] Steele, N. Z. et al. Fine-mapping of the human leukocyte antigen locus as a risk factor for Alzheimer disease: a case-control study. PLoS Med. 14, 1–25 (2017). source

      Not checked in the free run.

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

    Premisecitation

    Angiotensin II, a product of ACE function, mediates a number of neuropathological processes in Alzheimer's disease and is now a target for intervention in phase II clinical trials.

    “angiotensin II, a product of ACE function, mediates a number of neuropathological processes in Alzheimer’s disease84 and is now a target for intervention in phase II clinical trials of Alzheimer’s disease85.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [84] Kehoe, P. G. The coming of age of the angiotensin hypothesis in Alzheimer’s disease: progress toward disease prevention and treatment? J. Alzheimers. Dis. 62, 1443–1466 (2018). source

      Not checked in the free run.

    • cites [85] Kehoe, P. G. et al. The rationale and design of the reducing pathology in Alzheimer’s disease through Angiotensin TaRgeting (RADAR) Trial. J. Alzheimers. Dis. 61, 803–814 (2017). source

      Not checked in the free run.

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

    Premisecitation

    The DR15 haplotype and its component alleles also associate with protection against diabetes, a high risk for multiple sclerosis, and risk or protective effects with many other immune-mediated diseases.

    “the DR15 haplotype and its component alleles also associate with protection against diabetes108, a high risk for multiple sclerosis109,110, and risk or protective effects with many other immune-mediated diseases”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [108] Pugliese, A. et al. HLA-DRB1 15:01-DQA1 01:02-DQB1 06:02 haplotype protects autoantibody-positive relatives from type 1 diabetes throughout the stages of disease progression. Diabetes 65, 1109–1119 (2016). source

      Not checked in the free run.

    • cites [109] Patsopoulos, Na et al. Fine-mapping the genetic association of the major histocompatibility complex in multiple sclerosis: HLA and non-HLA effects. PLoS Genet. 9, e1003926 (2013). source

      Not checked in the free run.

    • cites [110] Schmidt, H., Williamson, D. & Ashley-Koch, A. HLA-DR15 haplotype and multiple sclerosis: a HuGE review. Am. J. Epidemiol. 165, 1097–1109 (2007). source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Two rare ADAM10 alterations segregating with disease in LOAD families increased Aβ plaque load in 'Alzheimer-like' mice, with diminished α-secretase activity from the alterations probably the causal mechanism.

    “two rare ADAM10 alterations segregating with disease in LOAD families increased Aβ plaque load in ‘Alzheimer-like’ mice, with diminished α-secretase activity from the alterations probably the causal mechanism19,44.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [19] Kim, M. et al. Potential late-onset Alzheimer’s disease-associated mutations in the ADAM10 gene attenuate alpha-secretase activity. Hum. Mol. Genet. 18, 3987–3996 (2009). source

      Not checked in the free run.

    • cites [44] Suh, J. et al. ADAM10 missense mutations potentiate beta-amyloid accumulation by impairing prodomain chaperone function. Neuron 80, 385–401 (2013). source

      Not checked in the free run.

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

    Premisecitation

    Research shows dementia risk to be associated with lower socio-economic status, independently of education status.

    “research shows dementia risk to be associated with lower socio-economic status, independently of education status118,119.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [118] Cadar, D. et al. Individual and area-based socioeconomic factors associated with dementia incidence in England: evidencefrom a 12-year follow-up in the English longitudinal study of ageing. JAMA Psychiatry 75, 723–732 (2018). source

      Not checked in the free run.

    • cites [119] Marden, J. R., Tchetgen Tchetgen, E. J., Kawachi, I. & Glymour, M. M. Contribution of socioeconomic status at 3 life-course periods to late-life memory function and decline: early and late predictors of dementia risk. Am. J. Epidemiol. 186, 805–814 (2017). source

      Not checked in the free run.

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

    Interpretationcitation

    While ACE was not prioritized, it should not be rejected as a candidate gene, as its expression in Alzheimer's disease brain tissue is associated with Aβ load and Alzheimer's disease severity.

    “While ACE was not prioritized, it should not be rejected as a candidate gene, as its expression in Alzheimer’s disease brain tissue is associated with Aβ load and Alzheimer’s disease severity80.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [80] Miners, J. S. et al. Angiotensin-converting enzyme levels and activity in Alzheimer’s disease: differences in brain and CSF ACE and association with ACE1 genotypes. Am. J. Transl. Res. 1, 163–177 (2009).

      Not checked in the free run.

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

    Premisecitation

    WWOX has been implicated in several neurological phenotypes; it binds tau and may play a critical role in regulating tau hyper-phosphorylation, neurofibrillary formation and Aβ aggregation.

    “WWOX has been implicated in several neurological phenotypes96; in addition, it binds tau and may play a critical role in regulating tau hyper-phosphorylation, neurofibrillary formation and Aβ aggregation28,29.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [96] Chang, H. T. et al. WW domain-containing oxidoreductase in neuronal injury and neurological diseases. Oncotarget 5, 11792–11799 (2014). source

      Not checked in the free run.

    • cites [28] Chang, J.-Y. & Chang, N.-S. WWOX dysfunction induces sequential aggregation of TRAPPC6AΔ, TIAF1, tau and amyloid β, and causes apoptosis. Cell Death Discov. 1, 15003 (2015). source

      Not checked in the free run.

    • cites [29] Sze, C. I. et al. Down-regulation of WW domain-containing oxidoreductase induces tau phosphorylation in vitro: a potential role in Alzheimer’s disease. J. Biol. Chem. 279, 30498–30506 (2004). source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    The associated diseases include a large number of traits queried from an HLA-specific Phewas, including neurological diseases and diseases with risk factors for Alzheimer's disease, pointing to potential shared and/or interacting mechanisms and co-morbidities.

    “the associated diseases include a large number of traits queried from an HLA-specific Phewas111, including neurological diseases (for example, Parkinson’s disease112,113) and diseases with risk factors for Alzheimer’s disease (for example, hyperthyroidism114), pointing to potential shared and/or interacting mechanisms and co-morbidities”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [111] Karnes, J. H. et al. Phenome-wide scanning identifies multiple diseases and disease severity phenotypes associated with HLA variants. Sci. Transl. Med. 9, 1–14 (2017). source

      Not checked in the free run.

    • cites [112] Wissemann, W. T. et al. Association of Parkinson disease with structural and regulatory variants in the HLA region. Am. J. Hum. Genet. 93, 984–993 (2013). source

      Not checked in the free run.

    • cites [113] Misra, M. K., Damotte, V. & Hollenbach, J. A. The immunogenetics of neurological disease. Immunology 153, 399–414 (2018). source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    Of three genes at the ADAMTS1 locus, analyses nominate ADAMTS1 as the likely risk gene, although the signal could be a regulatory element for APP.

    “Of three genes at this locus, our analyses nominate ADAMTS1 as the likely risk gene, although we cannot rule out that this signal is a regulatory element for APP.”
    Quote in the paperSubstantial claim

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

    Premisecitation

    GPRC5B is a regulator of neurogenesis and inflammatory signaling in obesity.

    “the latter being a regulator of neurogenesis72,73 and inflammatory signaling in obesity74.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [72] Kurabayashi, N., Nguyen, M. D. & Sanada, K. The G protein-coupled receptor GPRC5B contributes to neurogenesis in the developing mouse neocortex. Development 140, 4335–4346 (2013). source

      Not checked in the free run.

    • cites [73] Cool, B. H. et al. A flanking gene problem leads to the discovery of a Gprc5b splice variant predominantly expressed in C57BL/6J mouse brain and in maturing neurons. PLoS ONE 5, e10351 (2010). source

      Not checked in the free run.

    • cites [74] Kim, Y.-J., Sano, T., Nabetani, T., Asano, Y. & Hirabayashi, Y. GPRC5B activates obesity-associated inflammatory signaling in adipocytes. Sci. Signal. 5, ra85–ra85 (2012).

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    CSF levels of ACE are associated with Aβ levels and LOAD risk, and ACE can inhibit Aβ toxicity and aggregation.

    “cerebrospinal fluid (CSF) levels of the angiotensin-converting enzyme (ACE) are associated with Aβ levels81 and LOAD risk82, and studies show ACE can inhibit Aβ toxicity and aggregation83.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [81] Jochemsen, H. M. et al. The association of angiotensin-converting enzyme with biomarkers for Alzheimer’s disease. Alzheimers Res. Ther. 6, 1–10 (2014). source

      Not checked in the free run.

    • cites [82] Kauwe, J. S. K. et al. Genome-wide association study of CSFl Levels of 59 Alzheimer’s disease candidate proteins: significant associations with proteins involved in amyloid processing and inflammation. PLoS Genet. 10, e1004758 (2014). source

      Not checked in the free run.

    • cites [83] Baranello, R. J. et al. Amyloid-beta protein clearance and degradation (ABCD) pathways and their role in Alzheimer’s disease. Curr. Alzheimers Res 12, 32–46 (2015). source

      Not checked in the free run.

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

    Premisecitation

    Marioni et al. family proxy analyses found maternal genetic correlation with Alzheimer's disease to be higher than that for paternal Alzheimer's disease (rg = 0.91 and 0.66, respectively).

    “similar to the Marioni et al. family proxy analyses26, which found maternal genetic correlation with Alzheimer’s disease to be higher than that for paternal Alzheimer’s disease (rg = 0.91 and 0.66, respectively).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [26] Marioni, R. E. et al. GWAS on family history of Alzheimeras disease. Transl. Psychiatry 8, 99 (2018). source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    ADAMTS1 is elevated in Down's syndrome with neurodegeneration and Alzheimer's disease, and it is a potential neuroprotective or neuroinflammatory gene.

    “ADAMTS1 is elevated in Down’s syndrome with neurodegeneration and Alzheimer’s disease86, and it is a potential neuroprotective gene87–89 or a neuroinflammatory gene important to microglial response90.”
    Quote in the paperNot a substantial claim0 of 5 sources checked
    • cites [86] Miguel, R. F., Pollak, A. & Lubec, G. Metalloproteinase ADAMTS-1 but not ADAMTS-5 is manifold overexpressed in neurodegenerative disorders as Down syndrome, Alzheimer’s and Pick’s disease. Brain. Res. Mol. Brain. Res. 133, 1–5 (2005). source

      Not checked in the free run.

    • cites [87] Suttkus, A. et al. Aggrecan, link protein and tenascin-R are essential components of the perineuronal net to protect neurons against iron-induced oxidative stress. Cell Death Dis. 5, e1119 (2014). source

      Not checked in the free run.

    • cites [88] Végh, M. J. et al. Reducing hippocampal extracellular matrix reverses early memory deficits in a mouse model of Alzheimer’s disease. Acta Neuropathol. Commun. 2, 76 (2014).

      Not checked in the free run.

    • cites [89] Morawski, M., Filippov, M., Tzinia, A., Tsilibary, E. & Vargova, L. ECM in brain aging and dementia. Prog. Brain. Res. 214, 207–227 (2014). source

      Not checked in the free run.

    • cites [90] Wilcock, D. M. Neuroinflammation in the aging down syndrome brain; lessons from Alzheimer’s disease. Curr. Gerontol. Geriatr. Res. 2012, 170276 (2012). source

      Not checked in the free run.

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

    Premisecitation

    Candidate gene studies have associated ACE variants with Alzheimer's disease risk, including a strong association in the Wadi Ara community.

    “Candidate gene studies have associated ACE variants with Alzheimer’s disease risk20,22,79, including a strong association in the Wadi Ara, an Israeli Arab community with high risk of Alzheimer’s disease21.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [20] Kehoe, P. G. et al. Variation in DCP1, encoding ACE, is associated with susceptibility to Alzheimer disease. Nat. Genet. 21, 71–72 (1999). source

      Not checked in the free run.

    • cites [22] Lehmann, D. J. et al. Large meta-analysis establishes the ACE insertion-deletion polymorphism as a marker of Alzheimer’s disease. Am. J. Epidemiol. 162, 305–317 (2005). source

      Not checked in the free run.

    • cites [79] Farrer, L. A. et al. Association between angiotensin-converting enzyme and Alzheimer disease. New Engl. J. Med. 57, 210–214 (2000).

      Not checked in the free run.

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

    Premisecitation

    Treatment of mice with WWOX's binding partner restores memory deficits.

    “treatment of mice with its binding partner restores memory deficits97”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [97] Lee, M. H. et al. Zfra restores memory deficits in Alzheimer’s disease triple-transgenic mice by blocking aggregation of TRAPPC6AΔ, SH3GLB2, tau, and amyloid β, and inflammatory NF-κB activation. Alzheimers Dement. Transl. Res. Clin. Interv 3, 189–204 (2017). source

      Not checked in the free run.

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

    Study design and conductreasoning

    Before analyses in LD Hub, all SNPs with extremely large effect sizes including the MHC and APOE region were removed, as outliers can overly influence the regression analyses.

    “Before analyses in LD Hub, we removed all SNPs with extremely large effect sizes including the MHC (Chr6:26,000,000–34,000,000) and APOE region, as outliers can overly influence the regression analyses.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    The FDR threshold was set to 10%.

    “The FDR threshold was set to 10%.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    Adjusted P values were computed using the FDR method and the R p.adjust function, and applied to the meta-analysis P values.

    “Adjusted P values were computed using the FDR method and the R ‘p.adjust’ function, and applied to the meta-analysis P values.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    Per-study analysis for Stage 2 and Stage 3 followed the same analysis procedures described for Stage 1, except for covariate adjustments per cohort, where all analyses were adjusted on sex and age apart from the Italian, Swedish, and Gr@ACE cohorts, which were also adjusted for principal components.

    “Per-study analysis for Stage 2 and Stage 3 followed the same analysis procedures described for Stage 1, except for covariate adjustments per cohort, where all analyses were adjusted on sex and age apart from the Italian, Swedish, and Gr@ACE cohorts, which were also adjusted for principal components.”
    Quote in the paperNot a substantial claim

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

    Study design and conductcitation

    Alleles with an imputation posterior probability lower than 0.5 were considered as undetermined as recommended by HIBAG developers.

    “Alleles with an imputation posterior probability lower than 0.5 were considered as undetermined as recommended by HIBAG developers.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    Each variant was required to be present in 30% of cases and 30% of controls across all datasets.

    “We also required the presence of each variant in 30% of cases and 30% of controls across all datasets.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    Sex mismatches or individuals showing a high degree of relatedness (identical-by-descent value of 0.98 or greater) were removed from the analysis.

    “Sex mismatches or individuals showing a high degree of relatedness (identical-by-descent value of 0.98 or greater) were removed from the analysis.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Within-study results for Stage 1 were meta-analyzed in METAL using an inverse-variance-based model with genomic control.

    “Within-study results for Stage 1 were meta-analyzed in METAL141 using an inverse-variance-based model with genomic control.”
    Quote in the paperSubstantial claim

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

    Study design and conductcitation

    Genomic inflation was calculated for lambda in the GenABEL package.

    “Genomic inflation was calculated for lambda (λ) in the GenABEL package142.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    Individuals with more than two undetermined HLA alleles were excluded.

    “Individuals with more than two undetermined HLA alleles were excluded.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    Standard quality control was performed on all datasets individually, including exclusion of individuals with low call rate, high relatedness, and variants with low call rate.

    “Standard quality control was performed on all datasets individually, including exclusion of individuals with low call rate, individuals with a high degree of relatedness, and variants with low call rate.”
    Quote in the paperSubstantial claim

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

    Study design and conductnone given

    The q value, which is the adjusted P value using the Benjamini-Hochberg FDR method with a 5% cutoff, was used for correction for multiple hypotheses testing.

    “We used the q value, which is the adjusted P value using the Benjamini–Hochberg FDR method with a 5% cutoff for correction for multiple hypotheses testing.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    Adaptive permutation was used to produce an empirical P value and an FDR-corrected q value.

    “Adaptive permutation was used to produce an empirical P value and an FDR-corrected q value.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    Per-sample quality checks for genetic sex and relatedness were performed in PLINK.

    “Per-sample quality checks for genetic sex and relatedness were performed in PLINK.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    A panel of ancestry-informative markers was used to perform principal component analysis with SMARTPCA from EIGENSOFT 4.2, and individuals with non-European ancestry were excluded.

    “A panel of ancestry-informative markers was used to perform principal component analysis with SMARTPCA from EIGENSOFT 4.2 software145, and individuals with non-European ancestry were excluded.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    Family datasets were tested using GWAF, with generalized estimating equations for common variants and a general linear mixed effects model for rare variants, because preliminary data showed GEE test statistics were inflated for rare variants while GLMM controlled this inflation.

    “Family datasets were tested using GWAF140, with generalized estimating equations (GEE) implemented for common variants (MAF ≥ 0.01), and a general linear mixed effects model (GLMM) implemented for rare variants (MAF < 0.01), per our preliminary data showing that the behavior of the test statistics for GEE was fine for common variants but inflated for rare variants, while GLMM controlled this rare-”
    Quote in the paperSubstantial claim

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

    Study design and conductown data

    Associations of HLA alleles with disease were tested using logistic regressions, adjusting for age, sex, and principal components.

    “Associations of HLA alleles with disease were tested using logistic regressions, adjusting for age, sex, and principal components as specified above for single variant association analysis.”
    Quote in the paperNot a substantial claim

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

    Study design and conductown data

    All 400 protein-coding genes within the LD-defined genome-wide loci were annotated with the gene-based results from the ADSP study, and the results were corrected using a 1% FDR P as a cutoff for significance.

    “All 400 protein-coding genes within our LD-defined genome-wide loci were annotated with the gene-based results from this study, and the results were corrected using a 1% FDR P as a cutoff for significance.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Genes located less than 1 Mb from the GWAS sentinel variants that pass a 5% Benjamini-Hochberg FDR-corrected SMR P-value significance threshold and a HEIDI P-value greater than 0.05 threshold were considered significant.

    “Genes located less than 1 Mb from the GWAS sentinel variants that pass a 5% Benjamini–Hochberg FDR-corrected SMR P-value significance threshold and a HEIDI P-value > 0.05 threshold were considered significant.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Splicing variants with high splicing potential according to MaxEntScan and protein-coding variants predicted to be deleterious by two or more programs were considered to be potentially causal variants for a locus.

    “Splicing variants with high splicing potential according to MaxEntScan159 and protein-coding variants predicted to be deleterious by two or more programs were considered to be potentially causal variants for a locus.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Statistical significance of the genetic correlations was estimated using 5% Benjamini-Hochberg FDR corrected P values.

    “Statistical significance of the genetic correlations was estimated using 5% Benjamini−Hochberg FDR corrected P values.”
    Quote in the paperSubstantial claim

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

    Study design and conductnone given

    For haplotypes analysis, only individuals with no undetermined HLA alleles and only datasets with more than 100 cases or controls were included.

    “For haplotypes analysis, only individuals with no undetermined HLA alleles and only datasets with more than 100 cases or controls were included.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    While rare variants from imputation were included in the analyses, many rare causal variants may be missing in this study.

    “It should be noted that while we do include rare variants from imputation in our analyses, we may be missing many rare causal variants in this study.”
    Quote in the paperNot a substantial claim

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

    Study design and conductown data

    LDSC regression was performed to calculate the LD score regression intercept and derive a heritability estimate for the inverse-variance weighted meta-analysis summary statistics.

    “In addition, we performed LDSC regression via LD Hub v.1.9.0 (refs. 12,13) to calculate the LD score regression intercept and derive a heritability estimate for the inverse-variance weighted meta-analysis summary statistics.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [12] Zheng, J. et al. LD Hub: A centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics 33, 051094 (2017).

      Not checked in the free run.

    • cites [13] Bulik-Sullivan, B. K. et al. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015). source

      Not checked in the free run.

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

    Study design and conductnone given

    The individuals in the ADSP study largely overlap with individuals in the ADGC and CHARGE cohorts included in the Stage 1 meta-analysis.

    “The individuals in the ADSP study largely overlap with individuals in the ADGC and CHARGE cohorts included in our Stage 1 meta-analysis.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Individuals with non-European ancestry according to principal components analysis of ancestry-informative markers were excluded from further analysis.

    “Individuals with non-European ancestry according to principal components analysis of ancestry-informative markers were excluded from the further analysis.”
    Quote in the paperSubstantial claim

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

    Study design and conductnone given

    Variants with regression coefficient absolute value greater than 5 or P value equal to 0 or 1 were excluded from further analysis.

    “Variants with regression coefficient |β| > 5 or P value equal to 0 or 1 were excluded from further analysis.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    Significant enrichment was defined by Bonferonni-corrected P less than or equal to 0.05.

    “Significant enrichment was defined by Bonferonni-corrected P ≤ 0.05.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Common variants with MAF at least 0.01% and an r2 or information measure below 0.40 were excluded from further analyses.

    “Common variants (MAF ≥ 0.01%) with an r2 or an information measure <0.40 from MaCH and IMPUTE2 were excluded from further analyses.”
    Quote in the paperSubstantial claim

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

    Study design and conductown data

    The Westra eQTL and CAGE eQTL summary data are large eQTL studies conducted in whole blood, with some sample overlap between the two datasets, and CAGE provides finer coverage.

    “These datasets, conducted in whole blood, are large eQTL studies (Westra: discovery phase n = 5,311, replication phase n = 2,775; CAGE: n = 2,765), and while there is some overlap in samples between the two datasets, CAGE provides finer coverage.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductcitation

    Stage 1 single variant association analysis employed an additive genotype model adjusting for age, sex, and population substructure using principal components.

    “Stage 1 single variant-based association analysis employed an additive genotype model adjusting for age (defined as age-at-onset for cases and age-at-last exam for controls), sex, and population substructure using principal components138.”
    Quote in the paperSubstantial claim

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

    Study design and conductnone given

    Genes with a Bonferonni-corrected P less than 0.05 and absolute log(fold change) at least 0.58 were considered differentially expressed genes.

    “Genes with a Bonferonni-corrected P < 0.05 and absolute log(fold change) ≥ 0.58 were considered DEGs.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    The APOE region was removed to calculate the intercept.

    “The APOE region (Chr19:45,116,911–46,318,605) was removed to calculate the intercept.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    For Stages 1, 2, and 3, samples did not overlap.

    “For Stages 1, 2, and 3, samples did not overlap.”
    Quote in the paperSubstantial claim

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

    Study design and conductnone given

    Variant quality control was performed separately in each country including removal of variants missing in more than 10% of individuals, having a Hardy-Weinberg P value in controls lower than 1 × 10−6 or a P value for missingness between cases and controls lower than 1 × 10−6.

    “Variant quality control was also performed separately in each country including removal of variants missing in more than 10% of individuals, having a Hardy−Weinberg P value in controls lower than 1 × 10−6 or a P value for missingness between cases and controls lower than 1 × 10−6.”
    Quote in the paperSubstantial claim

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

    Study design and conductnone given

    Rare variants with MAF below 0.01% and a global weighted imputation quality score below 0.70 were excluded from analyses.

    “Rare variants (MAF < 0.01%) with a ‘global’ weighted imputation quality score of <0.70 were also excluded from analyses.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    Haplotype estimations and association analyses with disease were performed using the haplo.glm function from the haplo.stats R package with age, sex, and principal components as covariates.

    “Haplotype estimations and association analyses with disease were performed using the ‘haplo.glm’ function from the haplo.stats R package185 with age, sex, and principal components as covariates.”
    Quote in the paperNot a substantial claim

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

    Study design and conductnone given

    Adjustments on HLA significant variants and HLA alleles were performed by introducing the variant or alleles as covariates in the regression models.

    “Adjustments on HLA significant variants and HLA alleles were performed by introducing the variant or alleles as covariates in the regression models.”
    Quote in the paperNot a substantial claim

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

    Study design and conductreasoning

    Considering the high LD in the MHC region, only haplotypes predicted with posterior probabilities higher than 0.2 were considered for analysis.

    “Considering the high LD in the MHC region, only haplotypes predicted with posterior probabilities higher than 0.2 were considered for analysis.”
    Quote in the paperNot a substantial claim
98 of 98

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 most significant gene sets are related to amyloid and tau.

    “the most significant gene sets are related to amyloid and tau5”

    From New insights into the genetic etiology of Alzheimer’s disease and related dementias (2022) · cites this paper as [5]

    The Results section (Candidate gene prioritization at genome-wide loci; page unavailable) reports significantly enriched gene sets related to Aβ formation and tau protein binding. It does not establish that these are the most significant: a lipid-related pathway has a lower P value than either, and immune-related pathways are also significant. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • The pathway enrichment analyses removed ambiguities concerning the involvement of tau-binding proteins and APP/Aβ peptide metabolism in late-onset AD processes at a much higher level than had been described previously.

    “Our pathway enrichment analyses removed ambiguities concerning the involvement of tau-binding proteins and APP/Aβ peptide metabolism in late-onset AD processes at a much higher level than had been described previously5.”

    From New insights into the genetic etiology of Alzheimer’s disease and related dementias (2022) · cites this paper as [5]

    The Results (Candidate gene prioritization at genome-wide loci; page unavailable) report significant common-variant enrichment for tau protein binding and APP metabolism/Aβ formation. The Discussion says these analyses support involvement of tau and APP metabolism in late-onset Alzheimer’s disease. The paper does not say that they removed ambiguities or establish the claimed degree of advance over earlier work. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • SPI1 has a genome-wide significant genic association with Alzheimer's disease in the IGAP GWAS (rs3740688 odds ratio 0.92, meta p = 5.4 × 10−13), comprising 35,274 Alzheimer's disease cases and 59,163 controls.

    “SPI1 encodes PU.1, a central transcription factor in microglial development and activation, and has a genome-wide significant genic association with AD in the IGAP GWAS (rs3740688 Odds Ratio 0.92 Meta p = 5.4 × 10−13), comprising 35,274 Alzheimer’s disease cases and 59,163 controls4.”

    From Modest changes in Spi1 dosage reveal the potential for altered microglial function as seen in Alzheimer’s disease (2021) · cites this paper as [4]

    The Results (Meta-analysis of Alzheimer’s disease GWAS; page unavailable) give the stated sample size of 35,274 cases and 59,163 controls. Candidate gene prioritization (page unavailable) identifies SPI1 as a gene implicated at a genome-wide AD risk locus. The passages in our copy do not verify rs3740688, its odds ratio of 0.92, or the stated P value of 5.4 × 10−13. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • GWAS have identified more than 40 risk loci associated with pathways including lipid metabolism, immune regulation, and endosomal trafficking.

    “Over the last two decades, genome-wide association studies (GWAS) have identified more than 40 risk loci associated with pathways including lipid metabolism, immune regulation, and endosomal trafficking128,129,150,151.”

    From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [128]

    The Results section, under ‘Candidate gene prioritization at genome-wide loci’ (page unavailable), reports Alzheimer’s disease GWAS loci and pathway enrichment for lipid metabolism and immune response. Our copy does not establish the claim’s ‘more than 40’ count or identify endosomal trafficking as an implicated pathway; the paper analyzes 24 associated loci excluding APOE. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • The APOE ε4 allele significantly increases susceptibility to AD.

    “The APOE gene remains the prominent genetic risk factor, with the ε4 allele significantly increasing susceptibility.”

    From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [128]

    The Results section (‘Candidate gene prioritization at genome-wide loci’; page unavailable) identifies APOE as an Alzheimer’s disease risk gene. The passages found do not establish that the ε4 allele specifically increases susceptibility or give an allele-specific significance result. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Imputation methods give a different frequency cutoff for common and rare variants

    Minor

    The methods classify variants using a 0.01% minor-allele-frequency cutoff, whereas the study description and Stage 1 analysis use 0.01 as the cutoff. These differ by a factor of 100, leaving the reported classification criterion unclear.

1 of 1

Cites

Flagged first, then by citations

3 of the 201 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. Vardarajan, B. N. et al. Coding mutations in SORL1 and Alzheimer disease. Ann. Neurol. 77, 215–227 (2015). · DOI · Paper page

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Authors
Alzheimer Disease Genetics Consortium (ADGC), Kunkle, B. W., The European Alzheimer’s Disease Initiative (EADI), Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE), Genetic and Environmental Risk in AD/Defining Genetic, P. A. E. R. F. A. D. C. (., Grenier-Boley, B., Sims, R., Bis, J. C., Damotte, V., Naj, A. C., Boland, A., Vronskaya, M., van der Lee, S. J., Amlie-Wolf, A., Bellenguez, C., Frizatti, A., Chouraki, V., Martin, E. R., Sleegers, K., Badarinarayan, N., Jakobsdottir, J., Hamilton-Nelson, K. L., Moreno-Grau, S., Olaso, R., Raybould, R., Chen, Y., Kuzma, A. B., Hiltunen, M., Morgan, T., Ahmad, S., Vardarajan, B. N., Epelbaum, J., Hoffmann, P., Boada, M., Beecham, G. W., Garnier, J.-G., Harold, D., Fitzpatrick, A. L., Valladares, O., Moutet, M.-L., Gerrish, A., Smith, A. V., Qu, L., Bacq, D., Denning, N., Jian, X., Zhao, Y., Del Zompo, M., Fox, N. C., Choi, S.-H., Mateo, I., Hughes, J. T., Adams, H. H., Malamon, J., Sanchez-Garcia, F., Patel, Y., Brody, J. A., Dombroski, B. A., Naranjo, M. C. D., Daniilidou, M., Eiriksdottir, G., Mukherjee, S., Wallon, D., Uphill, J., Aspelund, T., Cantwell, L. B., Garzia, F., Galimberti, D., Hofer, E., Butkiewicz, M., Fin, B., Scarpini, E., Sarnowski, C., Bush, W. S., Meslage, S., Kornhuber, J., White, C. C., Song, Y., Barber, R. C., Engelborghs, S., Sordon, S., Voijnovic, D., Adams, P. M., Vandenberghe, R., Mayhaus, M., Cupples, L. A., Albert, M. S., De Deyn, P. P., Gu, W., Himali, J. J., Beekly, D., Squassina, A., Hartmann, A. M., Orellana, A., Blacker, D., Rodriguez-Rodriguez, E., Lovestone, S., Garcia, M. E., Doody, R. S., Munoz-Fernadez, C., Sussams, R., Lin, H., Fairchild, T. J., Benito, Y. A., Holmes, C., Karamujić-Čomić, H., Frosch, M. P., Thonberg, H., Maier, W., Roshchupkin, G., Ghetti, B., Giedraitis, V., Kawalia, A., Li, S., Huebinger, R. M., Kilander, L., Moebus, S., Hernández, I., Kamboh, M. I., Brundin, R., Turton, J., Yang, Q., Katz, M. J., Concari, L., Lord, J., Beiser, A. S., Keene, C. D., Helisalmi, S., Kloszewska, I., Kukull, W. A., Koivisto, A. M., Lynch, A., Tarraga, L., Larson, E. B., Haapasalo, A., Lawlor, B., Mosley, T. H., Lipton, R. B., Solfrizzi, V., Gill, M., Longstreth, W. T., Montine, T. J., Frisardi, V., Diez-Fairen, M., Rivadeneira, F., Petersen, R. C., Deramecourt, V., Alvarez, I., Salani, F., Ciaramella, A., Boerwinkle, E., Reiman, E. M., Fievet, N., Rotter, J. I., Reisch, J. S., Hanon, O., Cupidi, C., Andre Uitterlinden, A. G., Royall, D. R., Dufouil, C., Maletta, R. G., de Rojas, I., Sano, M., Brice, A., Cecchetti, R., George-Hyslop, P. S., Ritchie, K., Tsolaki, M., Tsuang, D. W., Dubois, B., Craig, D., Wu, C.-K., Soininen, H., Avramidou, D., Albin, R. L., Fratiglioni, L., Germanou, A., Apostolova, L. G., Keller, L., Koutroumani, M., Arnold, S. E., Panza, F., Gkatzima, O., Asthana, S., Hannequin, D., Whitehead, P., Atwood, C. S., Caffarra, P., Hampel, H., Quintela, I., Carracedo, Á., Lannfelt, L., Rubinsztein, D. C., Barnes, L. L., Pasquier, F., Frölich, L., Barral, S., McGuinness, B., Beach, T. G., Johnston, J. A., Becker, J. T., Passmore, P., Bigio, E. H., Schott, J. M., Bird, T. D., Warren, J. D., Boeve, B. F., Lupton, M. K., Bowen, J. D., Proitsi, P., Boxer, A., Powell, J. F., Burke, J. R., Kauwe, J. S. K., Burns, J. M., Mancuso, M., Buxbaum, J. D., Bonuccelli, U., Cairns, N. J., McQuillin, A., Cao, C., Livingston, G., Carlson, C. S., Bass, N. J., Carlsson, C. M., Hardy, J., Carney, R. M., Bras, J., Carrasquillo, M. M., Guerreiro, R., Allen, M., Chui, H. C., Fisher, E., Masullo, C., Crocco, E. A., DeCarli, C., Bisceglio, G., Dick, M., Ma, L., Duara, R., Graff-Radford, N. R., Evans, D. A., Hodges, A., Faber, K. M., Scherer, M., Fallon, K. B., Riemenschneider, M., Fardo, D. W., Heun, R., Farlow, M. R., Kölsch, H., Ferris, S., Leber, M., Foroud, T. M., Heuser, I., Galasko, D. R., Giegling, I., Gearing, M., Hüll, M., Geschwind, D. H., Gilbert, J. R., Morris, J., Green, R. C., Mayo, K., Growdon, J. H., Feulner, T., Hamilton, R. L., Harrell, L. E., Drichel, D., Honig, L. S., Cushion, T. D., Huentelman, M. J., Hollingworth, P., Hulette, C. M., Hyman, B. T., Marshall, R., Jarvik, G. P., Meggy, A., Abner, E., Menzies, G. E., Jin, L.-W., Leonenko, G., Real, L. M., Jun, G. R., Baldwin, C. T., Grozeva, D., Karydas, A., Russo, G., Kaye, J. A., Kim, R., Jessen, F., Kowall, N. W., Vellas, B., Kramer, J. H., Vardy, E., LaFerla, F. M., Jöckel, K.-H., Lah, J. J., Dichgans, M., Leverenz, J. B., Mann, D., Levey, A. I., Pickering-Brown, S., Lieberman, A. P., Klopp, N., Lunetta, K. L., Wichmann, H.-E., Lyketsos, C. G., Morgan, K., Marson, D. C., Brown, K., Martiniuk, F., Medway, C., Mash, D. C., Nöthen, M. M., Masliah, E., Hooper, N. M., McCormick, W. C., Daniele, A., McCurry, S. M., Bayer, A., McDavid, A. N., Gallacher, J., McKee, A. C., van den Bussche, H., Mesulam, M., Brayne, C., Miller, B. L., Riedel-Heller, S., Miller, C. A., Miller, J. W., Al-Chalabi, A., Morris, J. C., Shaw, C. E., Myers, A. J., Wiltfang, J., O’Bryant, S., Olichney, J. M., Alvarez, V., Parisi, J. E., Singleton, A. B., Paulson, H. L., Collinge, J., Perry, W. R., Mead, S., Peskind, E., Cribbs, D. H., Rossor, M., Pierce, A., Ryan, N. S., Poon, W. W., Nacmias, B., Potter, H., Sorbi, S., Quinn, J. F., Sacchinelli, E., Raj, A., Spalletta, G., Raskind, M., Caltagirone, C., Bossù, P., Orfei, M. D., Reisberg, B., Clarke, R., Reitz, C., Smith, A. D., Ringman, J. M., Warden, D., Roberson, E. D., Wilcock, G., Rogaeva, E., Bruni, A. C., Rosen, H. J., Gallo, M., Rosenberg, R. N., Ben-Shlomo, Y., Sager, M. A., Mecocci, P., Saykin, A. J., Pastor, P., Cuccaro, M. L., Vance, J. M., Schneider, J. A., Schneider, L. S., Slifer, S., Seeley, W. W., Smith, A. G., Sonnen, J. A., Spina, S., Stern, R. A., Swerdlow, R. H., Tang, M., Tanzi, R. E., Trojanowski, J. Q., Troncoso, J. C., Van Deerlin, V. M., Van Eldik, L. J., Vinters, H. V., Vonsattel, J. P., Weintraub, S., Welsh-Bohmer, K. A., Wilhelmsen, K. C., Williamson, J., Wingo, T. S., Woltjer, R. L., Wright, C. B., Yu, C.-E., Yu, L., Saba, Y., Pilotto, A., Bullido, M. J., Peters, O., Crane, P. K., Bennett, D., Bosco, P., Coto, E., Boccardi, V., De Jager, P. L., Lleo, A., Warner, N., Lopez, O. L., Ingelsson, M., Deloukas, P., Cruchaga, C., Graff, C., Gwilliam, R., Fornage, M., Goate, A. M., Sanchez-Juan, P., Kehoe, P. G., Amin, N., Ertekin-Taner, N., Berr, C., Debette, S., Love, S., Launer, L. J., Younkin, S. G., Dartigues, J.-F., Corcoran, C., Ikram, M. A., Dickson, D. W., Nicolas, G., Campion, D., Tschanz, J., Schmidt, H., Hakonarson, H., Clarimon, J., Munger, R., Schmidt, R., Farrer, L. A., Van Broeckhoven, C., C. O’Donovan, M., DeStefano, A. L., Jones, L., Haines, J. L., Deleuze, J.-F., Owen, M. J., Gudnason, V., Mayeux, R., Escott-Price, V., Psaty, B. M., Ramirez, A., Wang, L.-S., Ruiz, A., van Duijn, C. M., Holmans, P. A., Seshadri, S., Williams, J., Amouyel, P., Schellenberg, G. D., Lambert, J.-C., & Pericak-Vance, M. A.
Affiliations
  • University of Miami (US)
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  • Children's Hospital of Philadelphia (US)
  • Universitat Autònoma de Barcelona (ES)
  • Case Western Reserve University (US)
  • Cardiff University (GB)
  • Université de Lille (FR)
Corresponding author
Kunkle, Brian W.
ORCID
Venue
Nature Genetics
Publisher
Springer Science and Business Media LLC
Published
2019-02-28
Volume
51
Issue
3
Pages
414-430
ISSN
  • 1061-4036 (ISSN-L)
  • 1546-1718
DOI
10.1038/s41588-019-0358-2
PMC
PMC6463297
OpenAlex
W2916749909
Cited by
2,946
References
201
Citations by year
2026: 278 · 2025: 431 · 2024: 475 · 2023: 410 · 2022: 448 · 2021: 445 · 2020: 343 · 2019: 112 · 2018: 1
FWCI
40.80
Type
journal article
Language
en
Update notices
correction (2019-08-15)
Open access
Licence
www.springer.com/tdm (tdm)
Locations
  • Nature Genetics (publishedVersion)
  • PubMed (publishedVersion)
  • ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (acceptedVersion)
  • Kölner Universitäts PublikationsServer (Universität zu Köln) (acceptedVersion)
  • Bristol Research (University of Bristol) (acceptedVersion, other-oa)
  • eScholarship (California Digital Library) (submittedVersion, other-oa)
  • Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
  • HAL (submittedVersion)
  • HAL (submittedVersion, other-oa)
  • Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
  • CINECA IRIS Institutial research information system (University of Pisa) (submittedVersion)
  • ePrints Soton (University of Southampton) (submittedVersion)
  • UCL Discovery (University College London) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
  • Florence Research (University of Florence) (submittedVersion)
  • ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
  • Repository@Nottingham (University of Nottingham) (submittedVersion)
  • UNICA IRIS Institutional Research Information System (University of Cagliari) (submittedVersion)
  • Research Portal (King's College London) (submittedVersion)
  • Lirias (submittedVersion)
  • Open Repository and Bibliography (University of Luxembourg) (submittedVersion, cc-by-nc-sa)
  • Oskar-Bordeaux (Universite de Bordeaux) (submittedVersion)
  • DZNE Pub (submittedVersion)
  • Research Explorer (The University of Manchester) (submittedVersion)
  • Research Portal (Queen's University Belfast) (submittedVersion)
  • PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
  • Explore Bristol Research (submittedVersion, other-oa)
  • CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro) (submittedVersion)
  • IUScholarWorks (Indiana University) (submittedVersion)
  • Purdue University Indianapolis (Indiana University) (submittedVersion)
  • VUBIR (Vrije Universiteit Brussel) (submittedVersion)
  • Data Archiving and Networked Services (DANS) (submittedVersion)
Funders
  • Wellcome Trust (203249/Z/16/Z)
  • National Institute for Health and Care Research (NF-SI-0616-10090, NF-SI-0617-10175, NF-SI-0611-10084)
  • Parkinson's UK (G-0907)
  • Motor Neurone Disease Association (ALCHALABI-DOBSON/APR14/829-791, Shaw/Nov14/985-797)
  • Rosetrees Trust
  • Agence Nationale de la Recherche (ANR-10-LABX-0013, ANR-17-EURE-0019)
  • National Institutes of Health (1r01hl120393-01a1, UL1TR001414, UL1TR002369)
  • Medical Research Council (MR/L023784/2, MR/K01417X/1, MR/L501517/1, MR/L501542/1, MR/M024784/1, MR/L021803/1, MR/N012453/1, MR/R024804/1, MR/L501529/1, MR/N026004/1, MR/L010305/1, MR/K013041/1, MR/M009076/1, MR/L023784/1)
  • National Institute on Aging (R01AG017917, P30AG053760, P30AG010129, U01AG049505, RF1AG051504, U01AG016976, R01AG054060, RF1AG015473, U01AG052409, K25AG055620, P30AG010124, P01AG017586, R01AG041232, R01AG015819, P30AG010161, R01AG054076, U01AG032984, RF1AG054023, R01AG018454, P50AG005681, P50AG005142, P01AG003991, U01AG046139, R01AG061796, P30AG013854, U01AG032438, U24AG056270, P01AG019724, P30AG017266, P30AG044271, P01AG026276, U24AG021886)
  • National Heart, Lung, and Blood Institute (R01-HL120393, U01HL120393, R01HL105756)
  • National Institute of Neurological Disorders and Stroke (R01NS017950)
  • National Center for Advancing Translational Sciences
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 › Genetics › Genetic Associations and Epidemiology
Keywords
Alzheimer's disease, genetic susceptibility loci, amyloid-beta, tau protein, immunity, lipid metabolism, genetic correlation, family history of dementia, rare variants
MeSH terms
Aged, Alzheimer Disease, Female, Genetic Testing, Haplotypes, Humans, Immunity, Lipids, Male, Case-Control Studies, Amyloid beta-Peptides, tau Proteins, Genetic Predisposition to Disease, Lipid Metabolism, Genome-Wide Association Study, Genetic Loci

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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