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Cited by 41Genetic Associations and EpidemiologyAlzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Multi-trait association studies discover pleiotropic loci between Alzheimer’s disease and cardiometabolic traits

Open access
The VA Million Veteran Program, Bone, William P., Siewert, Katherine M., Jha, Anupama, Klarin, Derek, Damrauer, Scott M., Chang, Kyong-Mi, Tsao, Philip S. +3 more·2021·Alzheimer's Research & Therapy
DOI 10.1186/s13195-021-00773-zPMC PMC7860582

Published version of a preprint

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Abstract

Background: Identification of genetic risk factors that are shared between Alzheimer’s disease (AD) and other traits, i.e., pleiotropy, can help improve our understanding of the etiology of AD and potentially detect new therapeutic targets. Previous epidemiological correlations observed between cardiometabolic traits and AD led us to assess the pleiotropy between these traits. Methods: We performed a set of bivariate genome-wide association studies coupled with colocalization analysis to identify loci that are shared between AD and eleven cardiometabolic traits. For each of these loci, we performed colocalization with Genotype-Tissue Expression (GTEx) project expression quantitative trait loci (eQTL) to identify candidate causal genes. Results: We identified three previously unreported pleiotropic trait associations at known AD loci as well as four novel pleiotropic loci. One associated locus was tagged by a low-frequency coding variant in the gene DOCK4 and is potentially implicated in its alternative splicing. Colocalization with GTEx eQTL data identified additional candidate genes for the loci we detected, including ACE , the target of the hypertensive drug class of ACE inhibitors. We found that the allele associated with decreased ACE expression in brain tissue was also associated with increased risk of AD, providing human genetic evidence of a potential increase in AD risk from use of an established anti-hypertensive therapeutic. Conclusion: Our results support a complex genetic relationship between AD and these cardiometabolic traits, and the candidate causal genes identified suggest that blood pressure and immune response play a role in the pleiotropy between these traits.

AI snapshot

Written from the paper’s full text.

TL;DR

Bivariate GWAS plus colocalization between Alzheimer’s disease and eleven cardiometabolic traits identified seven pleiotropic loci, including three at known AD loci and four novel loci, with candidate causal genes mapped for all. The ACE and DOCK4 loci were highlighted as clinically or therapeutically relevant, with ACE findings suggesting reduced brain ACE expression may increase AD risk.

Key findings

  • AD-centric analysis: 39 bivariate genome-wide significant loci met filters; 3 colocalized as novel pleiotropic associations at known AD loci: ADAM10 with DBP (rs442495, conditional posterior probability of colocalization 0.88), ADAMTS4 with WHRadjBMI (rs4575098, 0.87), and ACE with DBP and SBP (rs4308, 0.98).
  • Locus discovery analysis: 13 independent loci remained after filters; 3 colocalized plus DOCK4 with DBP (colocalization not applicable due to low-frequency lead SNP): DOC2A with LDL (rs11642612, 0.98), SPPL2A with HDL (rs12595082, 0.95), CCNT2 with BFP (rs10496731, 0.94), and DOCK4 with DBP (rs144867634, bivariate P = 8.33e−08; AD P = 5.36e−05; DBP P = 1.089e−07).
  • Candidate causal genes from GTEx eQTL colocalization included MINDY2 in tibial nerve at ADAM10; NDUFS2 across multiple tissues and FCER1G in tibial nerve at ADAMTS4; ACE at ACE; DOC2A in pancreatic tissue at DOC2A; multiple nearby genes at SPPL2A; CCNT2 in skin and AC016725.4 in testis at CCNT2; and DOCK4 at DOCK4.
  • At ACE, the allele associated with decreased ACE expression in brain tissue was also associated with increased AD risk, while showing opposite direction of effect for blood pressure. At DOCK4, the low-frequency missense lead SNP is near the 3′ splice junction of exon 11 and was predicted in silico to alter DOCK4 splicing, leading to exon 11 being spliced out.

Methods

  • Design: two bivariate GWAS experiments—AD-centric and locus discovery—using metaMANOVA bivariate_scan on publicly available single-trait GWAS summary statistics for AD and eleven cardiometabolic traits (CHD, T2D, SBP, DBP, BMI, WHRadjBMI, BFP, TC, LDL, HDL, TG). AD sample: 71,880 cases and 383,378 controls; other trait sample sizes are listed in Table 1.
  • Analysis: independent loci were defined as SNPs within 1 MB of the bivariate lead SNP and in LD r2 > 0.2 using 1kG EUR. Trait-trait colocalization used COLOC in a 500 kb window (±250 kb), with conditional probability of colocalization ≥0.8; HLA and APOE regions were excluded. Single-tissue eQTL colocalization used GTEx v7, and approximate conditional analysis used GCTA-COJO when LD structure suggested allelic series.
  • Filters: AD-centric loci required AD P < 1 × 10−6 and cardiometabolic trait P < 5 × 10−3. Locus discovery required lead SNP r2 < 0.2 and >500 kb from known single-trait loci for AD or the cardiometabolic trait and previous pleiotropic GWAS, plus AD P < 5 × 10−3 and cardiometabolic trait P < 5 × 10−3.

Limitations

  • Stated: sample overlap between the Jansen et al. AD GWAS and many cardiometabolic trait GWAS, including UK Biobank, increases estimated covariance; bivariate P values are more conservative for same-direction effects and less conservative for opposite-direction effects, and overlap may inflate posterior probability of colocalization.
  • Stated: phenotypic limitation—it is difficult to differentiate AD, vascular dementia, and mixed dementia, so some detected pleiotropic loci may reflect vascular or mixed dementia patients in the AD cohorts, particularly since Jansen et al. includes Proxy-AD patients.
  • Evident in the text: no experiments were performed to identify causal variants; the DOCK4 low-frequency lead SNP had little LD, which was not conducive to colocalization; and at ACE, two causal variants in LD (1kG EUR r2 > 0.8) with rs4308 could not be excluded.

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

Integrity signals

Registry

Crossref · 10.1186/s13195-021-00773-z

Cites

77 of 77 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

50 of 56 cited sources checked · 22 supported · 1 flagged · accuracy not yet measured

  • Premisecitation

    Many cardiometabolic traits are genetically correlated with one another.

    “Due to the epidemiological correlation between AD and cardiometabolic traits, coupled with the fact that many cardiometabolic traits are genetically correlated with one another, additional broader-scale pleiotropic studies are warranted, and recently the field has begun to do so [4, 11].”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [4] Broce IJ, Chin ·, Tan H, Fan CC, Jansen I, Savage JE, et al. Dissecting the genetic relationship between cardiovascular risk factors and Alzheimer’s disease. Acta Neuropathol. 2018;20. doi: https://doi.org/10.1007/s00401-018-1928-6. [cited 2019 Jan 8] source
    • cites [11] Bulik-Sullivan BK, Loh P-R, Finucane HK, Ripke S, Yang J, Patterson N, et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015;47(3):291–5. Available from: http://www.nature.com/articles/ng.3211. [cited 2019 Mar 8] source

      The Results (Real Data; page unavailable) discuss polygenicity across more than 20 phenotypes, but do not report genetic correlations between cardiometabolic traits. The Discussion (page unavailable) describes estimating genetic correlation as research in progress. Searches for cardiometabolic genetic correlations and shared genetic architecture found no passage establishing the claim. (LLM, conf=0.76)

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  • Premisecitation

    There is a positive epidemiological correlation between Alzheimer's disease and cardiometabolic traits.

    “Studies have consistently found a positive epidemiological correlation between Alzheimer’s disease (AD) and cardiometabolic traits, yet the biological mechanisms behind this correlation is not well understood [1–4].”
    Quote in the paperSubstantial claim4 of 4 sources checked
    • cites [1] Attems J, Jellinger KA. The overlap between vascular disease and Alzheimer’s disease - lessons from pathology. BMC Med. 2014;12(1):206. Available from: http://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-014-0206-2. [cited 2019 Jan 8] source
    • cites [2] Santos CY, Snyder PJ, Wu W-C, Zhang M, Echeverria A, Alber J. Pathophysiologic relationship between Alzheimer’s disease, cerebrovascular disease, and cardiovascular risk: a review and synthesis. Alzheimer’s Dement Diagnosis, Assess Dis Monit. 2017;7:69–87. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28275702. [cited 2019 Aug 21] source
    • cites [3] Reitz C. Dyslipidemia and the risk of Alzheimer’s disease. Curr Atheroscler Rep. 2013;15(3):307. Available from: http://link.springer.com/10.1007/s11883-012-0307-3. [cited 2019 Aug 21] source

      The Conclusions say that metabolic syndrome and its individual factors have repeatedly been associated with cognitive decline and dementia, but that is broader than AD specifically. The section “Prospective Epidemiological Studies Relating Plasma Cholesterol Levels to AD” reports harmful associations for some midlife lipid measures while saying results across studies have been inconsistent. The source therefore does not support the claim that studies consistently find a positive correlation between AD and cardiometabolic traits. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
    • cites [4] Broce IJ, Chin ·, Tan H, Fan CC, Jansen I, Savage JE, et al. Dissecting the genetic relationship between cardiovascular risk factors and Alzheimer’s disease. Acta Neuropathol. 2018;20. doi: https://doi.org/10.1007/s00401-018-1928-6. [cited 2019 Jan 8] source
  • Premisecitation

    The biological mechanisms behind the positive epidemiological correlation between Alzheimer's disease and cardiometabolic traits are not well understood.

    “Studies have consistently found a positive epidemiological correlation between Alzheimer’s disease (AD) and cardiometabolic traits, yet the biological mechanisms behind this correlation is not well understood [1–4].”
    Quote in the paperSubstantial claim4 of 4 sources checked
    • cites [1] Attems J, Jellinger KA. The overlap between vascular disease and Alzheimer’s disease - lessons from pathology. BMC Med. 2014;12(1):206. Available from: http://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-014-0206-2. [cited 2019 Jan 8] source
    • cites [2] Santos CY, Snyder PJ, Wu W-C, Zhang M, Echeverria A, Alber J. Pathophysiologic relationship between Alzheimer’s disease, cerebrovascular disease, and cardiovascular risk: a review and synthesis. Alzheimer’s Dement Diagnosis, Assess Dis Monit. 2017;7:69–87. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28275702. [cited 2019 Aug 21] source
    • cites [3] Reitz C. Dyslipidemia and the risk of Alzheimer’s disease. Curr Atheroscler Rep. 2013;15(3):307. Available from: http://link.springer.com/10.1007/s11883-012-0307-3. [cited 2019 Aug 21] source

      The Conclusions state that mechanisms linking dyslipidemia to dementia remain unclear and that metabolic-syndrome factors have repeatedly been associated with cognitive decline and dementia. But the paper does not establish a consistently positive association between AD and cardiometabolic traits broadly; its Abstract describes epidemiological findings for dyslipidemia and AD as conflicting. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [4] Broce IJ, Chin ·, Tan H, Fan CC, Jansen I, Savage JE, et al. Dissecting the genetic relationship between cardiovascular risk factors and Alzheimer’s disease. Acta Neuropathol. 2018;20. doi: https://doi.org/10.1007/s00401-018-1928-6. [cited 2019 Jan 8] source
  • Premisecitation

    These loci have previously been identified as genome-wide significant for AD in recent single-trait AD GWAS.

    “All of these loci are novel pleiotropic loci between AD and the respective cardiometabolic traits, but have previously been identified as genome-wide significant for AD in recent single-trait AD GWAS [4, 17, 31].”
    Quote in the paperSubstantial claim3 of 3 sources checked
    • cites [4] Broce IJ, Chin ·, Tan H, Fan CC, Jansen I, Savage JE, et al. Dissecting the genetic relationship between cardiovascular risk factors and Alzheimer’s disease. Acta Neuropathol. 2018;20. doi: https://doi.org/10.1007/s00401-018-1928-6. [cited 2019 Jan 8] source

      The Results (page unavailable) link some loci to previously reported AD variants, including one in the CELF1 region. But the paper calls four AD-associated loci novel, and three did not reach genome-wide significance in its meta-analysis. It therefore does not support the claim that all the loci had previously been genome-wide significant in single-trait AD GWAS. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [17] Jansen IE, Savage JE, Watanabe K, Bryois J, Williams DM, Steinberg S, et al. Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer’s disease risk. Nat Genet. 2019;51(3):404–13. Available from: http://www.nature.com/articles/s41588-018-0311-9. [cited 2019 May 5] source

      The Results section (‘Genome-wide meta-analysis for AD status’; page not provided) reports 29 genome-wide-significant AD loci, supporting the claim that loci had been identified in an AD GWAS. The citing sentence does not name ‘these loci,’ so our copy cannot establish that every locus in that group appears among the 29 reported here. (LLM, conf=0.74)

      Experimental — accuracy not yet measured
    • cites [31] Kunkle BW, Grenier-Boley B, Sims R, Bis JC, Damotte V, Naj AC, et al. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat Genet. 2019;51(3):414–30. source
  • Premisecitation

    The ADAMTS4 locus was also discovered in Jansen et al. [17] AD GWAS.

    “also discovered in Jansen et al. [17] AD GWAS”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Jansen et al. [17] Jansen IE, Savage JE, Watanabe K, Bryois J, Williams DM, Steinberg S, et al. Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer’s disease risk. Nat Genet. 2019;51(3):404–13. Available from: http://www.nature.com/articles/s41588-018-0311-9. [cited 2019 May 5] source
  • Classified as probably not a substantial claim. 12
  • May combine two claims. 14
  • The quote only partly states this claim. 1

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

    Premisecitation

    Previous studies at this locus observed the same relationship between ACE expression in brain tissue and ACE expression in plasma.

    “Previous studies at this locus observed this same relationship between ACE expression in brain tissue and ACE expression in plasma [33].”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [33] Miners JS, Ashby E, Baig S, Harrison R, Tayler H, Speedy E, 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. 2009;1(2):163–77. Available from: www.ajtr.org/AJTR901003. [cited 2020 Dec 3]

      The Introduction says that a shared relationship between ACE1 genotype and ACE expression in the brain and periphery had been assumed, not observed. The Brain and CSF ACE levels and activity and ACE1 variation section reports the highest brain ACE activity in insertion-allele homozygotes, whereas the Influence of ACE1 genotypic variations section describes the highest plasma ACE levels in DD homozygotes. The Conclusions state that peripheral ACE measurements are not a reliable indicator of ACE in the CNS. Page numbers are unavailable in our copy. (LLM, conf=0.88)

      Checked by a reasoning model — may be wrong.

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  • Classified as probably not a substantial claim.

    Premisecitation

    Pleiotropy is pervasive, as uncovered through genome-wide association studies.

    “However, the topic has received renewed attention, given the pervasiveness of pleiotropy that has been uncovered through genome-wide association studies (GWAS) [8–10].”
    Quote in the paperSubstantial claim3 of 3 sources checked
    • cites [8] Hackinger S, Zeggini E. Statistical methods to detect pleiotropy in human complex traits. Open Biol. 2017;7(11):170125. Available from: http://www.ncbi.nlm.nih.gov/pubmed/29093210. [cited 2019 Mar 15] source
    • cites [9] Jordan DM, Verbanck M, Do R. HOPS: A quantitative score reveals pervasive horizontal pleiotropy in human genetic variation is driven by extreme polygenicity of human traits and diseases. Genome Biol. 2019;20(1):222. Available from: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1844-7. [cited 2020 Apr 28] source
    • cites [10] Watanabe K, Stringer S, Frei O, Umićević Mirkov M, de Leeuw C, Polderman TJC, et al. A global overview of pleiotropy and genetic architecture in complex traits. Nat Genet. 2019;51(9):1339–48. source

  • Classified as probably not a substantial claim.

    Premisecitation

    At some pleiotropic loci, there is no shared causal SNP; instead, different SNPs are causal for different traits.

    “However, recent studies have shown that at some pleiotropic loci there is no shared causal SNP, but instead different SNPs are causal for the different traits. These loci are associated with multiple traits but there is no shared causal genetic variant behind the associations [9, 15].”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [9] Jordan DM, Verbanck M, Do R. HOPS: A quantitative score reveals pervasive horizontal pleiotropy in human genetic variation is driven by extreme polygenicity of human traits and diseases. Genome Biol. 2019;20(1):222. Available from: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1844-7. [cited 2020 Apr 28] source

      The Results (‘Defining pleiotropy’; page unavailable) define pleiotropy as one variant associated with multiple traits. The Methods (‘Genome-wide significant pleiotropy loci’; page unavailable) describe clustering linked variants, but neither passage establishes loci where different traits have different causal SNPs and no shared causal variant. Searches for distinct causal variants, colocalization, and linkage disequilibrium did not find that claim in our copy. (LLM, conf=0.73)

      Experimental — accuracy not yet measured
    • cites [15] Solovieff N, Cotsapas C, Lee PH, Purcell SM, Smoller JW. Pleiotropy in complex traits: challenges and strategies. Nat Rev Genet. 2013;14:483–95. source

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

    Premisecitation

    The ACE locus is a known blood pressure and AD association.

    “which is a known blood pressure and AD association”
    Quote in the paperNot a substantial claim4 of 6 sources checked
    • cites [20] Evangelou E, Warren HR, Mosen-Ansorena D, Mifsud B, Pazoki R, Gao H, et al. Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nat Genet. 2018;50(10):1412–25. Available from: http://www.nature.com/articles/s41588-018-0205-x. [cited 2019 Aug 22] source

      The Results section on associations with other traits and diseases identifies APOE as a blood-pressure locus associated with Alzheimer’s disease, but does not make that claim for ACE. A search for ACE in our copy found no passage establishing the attributed ACE association; the APOE finding alone does not rule it out. (LLM, conf=0.73)

      Experimental — accuracy not yet measured
    • cites [31] Kunkle BW, Grenier-Boley B, Sims R, Bis JC, Damotte V, Naj AC, et al. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat Genet. 2019;51(3):414–30. source

      The Results sections on the Alzheimer’s disease GWAS and candidate-gene prioritization report an association between the ACE locus and Alzheimer’s disease. The genetic-correlations section discusses blood pressure, but does not link blood-pressure association specifically to the ACE locus; that part of the claim is unsupported by our copy. (LLM, conf=0.85)

      Experimental — accuracy not yet measured
    • cites [32] Lehmann DJ, Cortina-Borja M, Warden DR, Smith AD, Sleegers K, Prince JA, et al. Large meta-analysis establishes the ACE insertion-deletion polymorphism as a marker of Alzheimer’s disease. Am J Epidemiol. 2005;162(4):305–17. Available from: https://pubmed.ncbi.nlm.nih.gov/16033878/. [cited 2020 Dec 3] source
    • cites [33] Miners JS, Ashby E, Baig S, Harrison R, Tayler H, Speedy E, 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. 2009;1(2):163–77. Available from: www.ajtr.org/AJTR901003. [cited 2020 Dec 3]
    • cites [34] Walker VM, Kehoe PG, Martin RM, Davies NM. Repurposing antihypertensive drugs for the prevention of Alzheimer’s disease: a Mendelian randomization study. Int J Epidemiol 2019 ; Available from: http://www.ncbi.nlm.nih.gov/pubmed/31335937. [cited 2020 May 12] source
    • cites [35] Kehoe PG, Russ C, McIlroy S, Williams H, Holmans P, Holmes C, et al. Variation in DCP1, encoding ACE, is associated with susceptibility to Alzheimer disease [2]. Nat Genet. 1999;21:71–2. Available from: https://pubmed.ncbi.nlm.nih.gov/9916793/. [cited 2020 Dec 8] source

  • May combine two claims.

    Findingown data

    The ACE locus (lead SNP rs4308) is a pleiotropic locus between AD and SBP, with a conditional posterior probability of colocalization of 0.98.

    “| SBP | ACE | rs4308 | 17 | 61559625 | G/A | +/− | 0.63 | 8.01e−15 | 8.52e−07 | 1.00e−16 | 0.98 | Evangelou et al. [20] |”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Evangelou et al. [20] Evangelou E, Warren HR, Mosen-Ansorena D, Mifsud B, Pazoki R, Gao H, et al. Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nat Genet. 2018;50(10):1412–25. Available from: http://www.nature.com/articles/s41588-018-0205-x. [cited 2019 Aug 22] source

      The Results report blood-pressure loci generally and identify APOE, not ACE, as a locus associated with both blood pressure and Alzheimer’s disease. Searches for rs4308, the ACE locus, and a 0.98 colocalization probability found no passage in our copy establishing the specific table entry or the claimed colocalization. (LLM, conf=0.76)

      Experimental — accuracy not yet measured

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

    Premisecitation

    There is already evidence that DOCK4 could be involved with AD and DBP.

    “There is already evidence that DOCK4 could be involved with AD and DBP.”
    Quote in the paperNot a substantial claim3 of 3 sources checked
    • cites [49] Chen Q, Kimura H, Schubert D. A novel mechanism for the regulation of amyloid precursor protein metabolism. J Cell Biol. 2002;158(1):79–89. Available from: http://www.ncbi.nlm.nih.gov/pubmed/12093789. [cited 2019 Sep 10] source

      The Introduction and Results discuss MOCA and its relationship to DOCK180, not DOCK4. The passages retrieved for “DOCK4 DBP” and “DOCK4 involvement Alzheimer disease bipolar disorder” provide no evidence about DOCK4 or DBP, so this copy does not establish the claimed involvement. (LLM, conf=0.76)

      Experimental — accuracy not yet measured
    • cites [50] Shi L. Dock protein family in brain development and neurological disease. Commun Integr Biol. 2013;6(6):e26839. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24563715. [cited 2019 Feb 26] source

      In the Dock-A and Dock-B section (page unavailable), the paper links DOCK4 to autism, dyslexia, and schizophrenia, while its discussion of AD concerns DOCK2 and DOCK3. Searches for DOCK4 with AD, DBP, and blood pressure found no passage linking DOCK4 to either condition; the copy does not establish or rule out the claimed involvement. (LLM, conf=0.76)

      Experimental — accuracy not yet measured
    • cites [51] Srinivasan K, Friedman BA, Larson JL, Lauffer BE, Goldstein LD, Appling LL, et al. Untangling the brain’s neuroinflammatory and neurodegenerative transcriptional responses. Nat Commun. 2016;7(1):11295. Available from: http://www.nature.com/articles/ncomms11295. [cited 2019 Aug 12] source

      The Results section on the Alzheimer’s mouse model discusses changes in microglial gene expression, but the passages available do not link DOCK4 to AD or DBP. Searches of our copy for “DOCK4” and “DBP diastolic blood pressure” found no passage addressing that proposed involvement. (LLM, conf=0.74)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    The presence of multiple associated variants in a region violates the assumptions of COLOC and can lead to false positives or false negatives.

    “because the presence of multiple associated variants in a region violates the assumptions of COLOC and can lead to false positives or false negatives [13].”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [13] Giambartolomei C, Vukcevic D, Schadt EE, Franke L, Hingorani AD, Wallace C, et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. Williams SM, editor. Plos Genet. 2014;10(5):e1004383. https://doi.org/10.1371/journal.pgen.1004383. [cited 2018 Apr 30] source

      The Results sections on several independent associations and on comparison with existing tests state that COLOC assumes at most one causal variant per trait per locus, and that multiple signals can affect PP4 or give strong support to either H3 or H4. They do not establish both false positives and false negatives as stated: the paper cautions that high PP4 in this setting supports ‘at least one causal variant’ being shared, while weaker secondary signals have negligible impact. (LLM, conf=0.84)

      Experimental — accuracy not yet measured

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

    Premisecitation

    Previous single-trait GWAS have identified several other cardiometabolic trait associations, including BMI and CHD, near the ADAM10 locus (within a 1-Mb window around the lead SNP).

    “Previous single-trait GWAS have identified several other cardiometabolic trait associations, including BMI and CHD, near this locus (within a 1-Mb window around the lead SNP)”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [26] Buniello A, MacArthur JAL, Cerezo M, Harris LW, Hayhurst J, Malangone C, et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 2019;47(D1):D1005–12. Available from: http://www.ncbi.nlm.nih.gov/pubmed/30445434. [cited 2019 Aug 26] source

      The Introduction (p. D1006) describes the GWAS Catalog’s variant–trait associations, and New Visualization Tools describes viewing associations by genomic region. Neither passage identifies BMI or CHD associations near ADAM10 or within a 1-Mb window. Searches for ADAM10 with BMI, CHD, and the window size found no passage establishing the specific claim. (LLM, conf=0.76)

      Experimental — accuracy not yet measured

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

    Premisecitation

    Previous genetic studies have shown that DOCK4 variants are associated with multiple neurological phenotypes.

    “Previous genetic studies have shown that DOCK4 variants are associated with multiple neurological phenotypes, and DOCK2, the other member of DOCK4’s protein subfamily, expression is increased in the microglia of patient’s with AD [49, 50].”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [49] Chen Q, Kimura H, Schubert D. A novel mechanism for the regulation of amyloid precursor protein metabolism. J Cell Biol. 2002;158(1):79–89. Available from: http://www.ncbi.nlm.nih.gov/pubmed/12093789. [cited 2019 Sep 10] source

      The Introduction discusses MOCA, its similarity to DOCK180, and presenilin mutations linked to familial Alzheimer’s disease; it does not report genetic studies of DOCK4 variants. Searches for DOCK4 variants and neurological phenotypes found no passage addressing the claimed association in our copy. (LLM, conf=0.76)

      Experimental — accuracy not yet measured
    • cites [50] Shi L. Dock protein family in brain development and neurological disease. Commun Integr Biol. 2013;6(6):e26839. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24563715. [cited 2019 Feb 26] source

  • May combine two claims.

    Findingown data

    The ADAM10 locus (lead SNP rs442495) is a pleiotropic locus between AD and DBP, with a conditional posterior probability of colocalization of 0.88.

    “| DBP | ADAM10 | rs442495 | 15 | 59022615 | T/C | +/+ | 0.65 | 1.98e−10 | 1.31e−09 | 9.71e−05 | 0.88 | Evangelou et al. [20] |”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Evangelou et al. [20] Evangelou E, Warren HR, Mosen-Ansorena D, Mifsud B, Pazoki R, Gao H, et al. Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nat Genet. 2018;50(10):1412–25. Available from: http://www.nature.com/articles/s41588-018-0205-x. [cited 2019 Aug 22] source

      The Results section on associations with other traits identifies APOE, not ADAM10, as a blood-pressure locus associated with Alzheimer’s disease. Searches of our copy for ADAM10, rs442495, and the 0.88 colocalization probability found no passage addressing the claimed ADAM10–DBP finding. (LLM, conf=0.76)

      Experimental — accuracy not yet measured

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

    Study design and conductcitation

    Some of the pleiotropic loci detected may be due to vascular or mixed dementia patients being included in the AD cohorts, particularly since Jansen et al. include some Proxy-AD patients.

    “It is possible that some of the pleiotropic loci we detected are due to vascular or mixed dementia patients being included in this AD cohorts, particular since Jansen et al. include some Proxy-AD patients [17] .”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [17] Jansen IE, Savage JE, Watanabe K, Bryois J, Williams DM, Steinberg S, et al. Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer’s disease risk. Nat Genet. 2019;51(3):404–13. Available from: http://www.nature.com/articles/s41588-018-0311-9. [cited 2019 May 5] source

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

    Premisecitation

    DOCK2 expression is increased in the microglia of patients with AD.

    “Previous genetic studies have shown that DOCK4 variants are associated with multiple neurological phenotypes, and DOCK2, the other member of DOCK4’s protein subfamily, expression is increased in the microglia of patient’s with AD [49, 50].”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [49] Chen Q, Kimura H, Schubert D. A novel mechanism for the regulation of amyloid precursor protein metabolism. J Cell Biol. 2002;158(1):79–89. Available from: http://www.ncbi.nlm.nih.gov/pubmed/12093789. [cited 2019 Sep 10] source

      The Introduction and Results discuss MOCA and DOCK180, while the Abstract describes MOCA in Alzheimer’s disease. Searches for DOCK2 expression and microglia in patients with Alzheimer’s disease found no passage addressing the claimed increase. (LLM, conf=0.76)

      Experimental — accuracy not yet measured
    • cites [50] Shi L. Dock protein family in brain development and neurological disease. Commun Integr Biol. 2013;6(6):e26839. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24563715. [cited 2019 Feb 26] source

      The Dock2 subsection reports that the number of DOCK2-expressing microglia is abnormally increased in the brains of patients with Alzheimer’s disease. It does not establish that DOCK2 expression is increased within individual microglial cells, as the claim could imply. (LLM, conf=0.83)

      Experimental — accuracy not yet measured

  • May combine two claims. The quote only partly states this claim.

    Findingown data

    Three previously unreported pleiotropic trait associations at known AD loci and four novel pleiotropic loci were identified between AD and eleven cardiometabolic traits.

    “We identified three previously unreported pleiotropic trait associations at known AD loci as well as four novel pleiotropic loci.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The ACE eQTLs in kidney and cerebellum share the same causal SNP, which has opposite directions of effect in these tissues.

    “These results also support that the ACE eQTLs in kidney and cerebellum share the same causal SNP, which has opposite directions of effect in these tissues”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The rare allele at the DOCK4 locus is associated with lower risk of AD and reduced DBP.

    “the fact that the rare allele is associated with lower risk of AD and reduced DBP”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning

    Due to the lead SNP being a low-frequency SNP, it had very little LD with other SNPs, which was not conducive to colocalization analyses.

    “Due to the lead SNP being a low-frequency SNP, it had very little LD with other SNPs, which was not conducive to colocalization analyses”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The AD signal colocalized with all three ACE eQTLs, but the evidence for colocalization was stronger for the cerebellum and kidney ACE eQTLs.

    “The AD signal colocalized with all three ACE eQTLs, but the evidence for colocalization was stronger for the cerebellum and kidney ACE eQTLs”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The DBP and SBP signals colocalized with the cerebellum and kidney ACE eQTLs, but not the lung ACE eQTL.

    “The DBP and SBP signals colocalized with the cerebellum and kidney ACE eQTLs, but not the lung ACE eQTL.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The ADAMTS4 locus (lead SNP rs4575098) is a pleiotropic locus between AD and WHRadjBMI, with a conditional posterior probability of colocalization of 0.87.

    “| WHRadjBMI | ADAMTS4 | rs4575098 | 1 | 161155392 | A/G | +/+ | 0.22 | 4.45e−13 | 2.05e−10 | 1.99e−06 | 0.87 | Pulit et al. [22] |”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Pulit et al. [22]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Findingown data

    We identified a total of 39 independent loci that were bivariate genome-wide significant, met our AD-centric single-trait P value threshold of P value < 1 × 10− 6 and a cardiometabolic trait P value < 5 × 10− 3, and were outside of the HLA and APOE regions.

    “We identified a total of 39 independent loci that were bivariate genome-wide significant, met our AD-centric single-trait P value threshold of P value < 1 × 10− 6 and a cardiometabolic trait P value < 5 × 10− 3, and were outside of the HLA and APOE regions (Additional file 1 Supplementary Table 2).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Pleiotropic signals were detected at the ACE locus between both DBP and AD and SBP and AD.

    “we detected pleiotropic signals at the ACE locus, which is a known blood pressure and AD association, between both DBP and AD and SBP and AD”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The T2D signal colocalized with the lung ACE eQTL, but not with the kidney and cerebellum ACE eQTLs.

    “The T2D signal colocalized with the lung ACE eQTL, but not with the kidney and cerebellum ACE eQTLs.”
    Quote in the paperSubstantial claim

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

    Premisecitation

    The available therapeutics for AD have only limited efficacy in slowing the progression of the disease.

    “The identification of new therapeutic targets for AD is of particular importance since AD afflicts approximately 50 million people, and there exist only a handful of therapeutics available for AD that have only limited efficacy in slowing the progression of the disease [5].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [5] Treatments for Alzheimer’s Disease | BrightFocus Foundation. Available from: https://www.brightfocus.org/alzheimers/article/treatments-alzheimers-disease. [cited 2020 Feb 18]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

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

    Premisecitation

    There are only a handful of therapeutics available for AD.

    “The identification of new therapeutic targets for AD is of particular importance since AD afflicts approximately 50 million people, and there exist only a handful of therapeutics available for AD that have only limited efficacy in slowing the progression of the disease [5].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [5] Treatments for Alzheimer’s Disease | BrightFocus Foundation. Available from: https://www.brightfocus.org/alzheimers/article/treatments-alzheimers-disease. [cited 2020 Feb 18]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    Loci in the HLA region and near the APOE locus were excluded from the colocalization experiments due to difficulty in interpreting the independent contribution of these loci to these traits.

    “We excluded loci in the HLA region and near the APOE locus from these experiments due to the difficulty in interpreting the independent contribution of these loci to these traits.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductnone given

    The sample overlap will increase the estimated covariance between the traits, making the resulting bivariate P value more conservative for a locus that has the same direction of effect as the phenotypic correlation and less conservative when a locus has an opposite direction of effect.

    “This sample overlap will increase the estimated covariance between our traits making the resulting bivariate P value more conservative for a locus that has the same direction of effect as the phenotypic correlation and less conservative when a locus has an opposite direction of effect.”
    Quote in the paperNot a substantial claim
26 of 26

  • The paper relies on this without support.

    The effect of the AD-risk allele on decreased ACE expression in brain tissue is comparable to the effect of ACE inhibitor use on ACE expression/activity in the brain.

    “We found that the allele associated with decreased ACE expression in brain tissue was also associated with increased risk of AD, providing human genetic evidence of a potential increase in AD risk from use of an established anti-hypertensive therapeutic.”

  • The paper relies on this without support.

    An epidemiological correlation exists between AD and blood pressure, against which the observed direction of effect can be judged as opposite.

    “We noted a direction of effect opposite to the epidemiological correlation for both of these signals”

  • The paper relies on this without support.

    The skin-tissue eQTL for CCNT2 is relevant to the BFP and AD association.

    “Single-tissue-eQTL colocalization analysis detected colocalization between the bivariate signal and an eQTL for CCNT2 in skin tissue (Table 5 and Additional file 1 – Figure S6).”

  • The paper relies on this without support.

    The predicted exon 11 splicing effect of the DOCK4 lead SNP alters DOCK4 function.

    “the lead SNP is a low-frequency exonic variant in DOCK4 that is predicted to lead to exon 11 of DOCK4 being spliced out of the DOCK4 transcript (Fig. 3a)”
4 of 4

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.

  • DOCK4 bivariate P value differs between text and table

    Minor

    The low-frequency exonic locus is DOCK4. The text gives its bivariate P value as 7 × 10− 8, while Table 5 gives 8.33e−08; the difference is greater than rounding to one significant figure.

1 of 1

Cites

Flagged first, then by citations

2 of the 79 references couldn’t be matched to a known paper.

Research works printed but not linked: 2

  1. Bellenguez C, Küçükali F, Jansen I, Andrade V, Morenau-Grau S, Amin N, et al. Large meta-analysis of genome-wide association studies expands knowledge of the genetic etiology of Alzheimer’s disease and highlights potential translational opportunities. medRxiv. 2020
  2. Carithers LJ, Ardlie K, Barcus M, Branton PA, Britton A, Buia SA, et al. A novel approach to high-quality postmortem tissue procurement: The GTEx Project. Biopreserv Biobank. 2015;13(5):311–9. Available from: http://www.liebertpub.com/doi/10.1089/bio.2015.0032. [cited 2019 Sep 9] · DOI · Paper page

Cited by

Sorted by citations

Related

Authors
Program, T. V. M. V., Bone, W. P., Siewert, K. M., Jha, A., Klarin, D., Damrauer, S. M., Chang, K.-M., Tsao, P. S., Assimes, T. L., Ritchie, M. D., & Voight, B. F.
Affiliations
  • University of Pennsylvania (US)
  • Broad Institute (US)
  • Philadelphia VA Medical Center (US)
  • VA Palo Alto Health Care System (US)
Corresponding author
Voight, Benjamin F.
ORCID
Venue
Alzheimer's Research & Therapy
Publisher
Springer Science and Business Media LLC
Published
2021-02-04
Volume
13
Issue
1
Pages
34-34
ISSN
1758-9193 (ISSN-L)
DOI
10.1186/s13195-021-00773-z
PMC
PMC7860582
OpenAlex
W3128596874
Semantic Scholar
89d89f5c291dc60a7e01d767019774421a8ea188
Cited by
41
References
79
Citations by year
2026: 10 · 2025: 7 · 2024: 8 · 2023: 11 · 2022: 3 · 2021: 2
FWCI
3.02
Type
journal article
Language
en
Open access
Licence
Locations
  • Alzheimer s Research & Therapy (publishedVersion, cc-by)
  • medRxiv (acceptedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (submittedVersion, other-oa)
  • PubMed Central (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
Funders
  • American Heart Association (20PRE35120109)
  • U.S. Department of Veterans Affairs (I01-BX003362, IK2-CX001780)
  • Foundation for the National Institutes of Health (DK101478, P50GM115318-01)
  • Linda Pechenik Montague Investigator Award
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
Keywords
Alzheimer's disease, cardiometabolic traits, pleiotropy, shared genetic risk loci, colocalization, expression quantitative trait loci, DOCK4, ACE, ACE inhibitors, blood pressure, immune response, alternative splicing, therapeutic target
MeSH terms
Alzheimer Disease, Cardiovascular Diseases, Humans, Phenotype, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Genome-Wide Association Study

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

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-14.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-14.

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