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Challenges at the APOE locus: a robust quality control approach for accurate APOE genotyping

Belloy, Michael E., Eger, Sarah J., Le Guen, Yann, Damotte, Vincent, Ahmad, Shahzad, Ikram, M. Arfan, Ramirez, Alfredo, Tsolaki, Anthoula C., Rossi, Giacomina, Jansen, Iris E., de Rojas, Itziar, Parveen, Kayenat, Sleegers, Kristel, Ingelsson, Martin, Hiltunen, Mikko, Amin, Najaf, Andreassen, Ole, Sánchez-Juan, Pascual, Kehoe, Patrick, Amouyel, Philippe, Sims, Rebecca, Frikke-Schmidt, Ruth, van der Flier, Wiesje M., Lambert, Jean-Charles, for the European Alzheimer & Dementia BioBank (EADB), He, Zihuai, Han, Summer S., Napolioni, Valerio, Greicius, Michael D.·2022·Alzheimer's Research & Therapy
DOI 10.1186/s13195-022-00962-4PMC PMC8815198

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Abstract

Background: Genetic variants within the APOE locus may modulate Alzheimer’s disease (AD) risk independently or in conjunction with APOE *2/3/4 genotypes. Identifying such variants and mechanisms would importantly advance our understanding of APOE pathophysiology and provide critical guidance for AD therapies aimed at APOE . The APOE locus however remains relatively poorly understood in AD, owing to multiple challenges that include its complex linkage structure and uncertainty in APOE *2/3/4 genotype quality. Here, we present a novel APOE *2/3/4 filtering approach and showcase its relevance on AD risk association analyses for the rs439401 variant, which is located 1801 base pairs downstream of APOE and has been associated with a potential regulatory effect on APOE . Methods: We used thirty-two AD-related cohorts, with genetic data from various high-density single-nucleotide polymorphism microarrays, whole-genome sequencing, and whole-exome sequencing. Study participants were filtered to be ages 60 and older, non-Hispanic, of European ancestry, and diagnosed as cognitively normal or AD ( n = 65,701). Primary analyses investigated AD risk in APOE *4/4 carriers. Additional supporting analyses were performed in APOE *3/4 and 3/3 strata. Outcomes were compared under two different APOE *2/3/4 filtering approaches. Results: Using more conventional APOE *2/3/4 filtering criteria (approach 1), we showed that, when in-phase with APOE *4, rs439401 was variably associated with protective effects on AD case-control status. However, when applying a novel filter that increases the certainty of the APOE *2/3/4 genotypes by applying more stringent criteria for concordance between the provided APOE genotype and imputed APOE genotype (approach 2), we observed that all significant effects were lost. Conclusions: We showed that careful consideration of APOE genotype and appropriate sample filtering were crucial to robustly interrogate the role of the APOE locus on AD risk. Our study presents a novel APOE filtering approach and provides important guidelines for research into the APOE locus, as well as for elucidating genetic interaction effects with APOE *2/3/4.

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Fig. 1 Schematic overview of the study design and two APOE*2/3/4 filtering approaches
Fig. 1 Schematic overview of the study design and two APOE*2/3/4 filtering approachesCC BY · PubMed Central
Fig. 2 Limitations in APOE filtering approach 1 are reflected in discordance between imputed and provided APOE genotypes, particularly in APOE*4/4 carriers. A APOE*4/4-rs439401 carrier cohort distributions. The top section shows the distribution of prioritized APOE genotype source in approach 1, indicating that APOE*4/4 carriers of rs439401 had very few WGS/WES-verified APOE*4/4 data. The bottom section shows pie charts for carrier distributions across cohorts (Additional data in Table S8). The red arrow indicates that a large fraction of control rs439401 carriers was contributed by MIRAGE. B Concordance rates between provided and imputed APOE per cohort (additional data in Table S9). The red arrow indicates that MIRAGE had the lowest concordance rate, suggesting potential limitations with its provided APOE data that could explain observations in A. C Concordance rates between provided and imputed APOE for the discovery sample, considering multiple strata (additional data in Table S10). APOE*4/4 strata considered provided APOE*4/4 genotypes after applying APOE filtering approach 1. Note decreased concordance in APOE*4/4 controls compared to cases. Note strongly decreased concordance for rs439401 carriers, specifically controls. Simulations confirmed that APOE*4/4 controls are more likely than cases to not actually be APOE*4/4 carriers (cf. Fig. S6-7). Abbreviations: CN, cognitively normal; AD, Alzheimer’s disease; OR
Fig. 2 Limitations in APOE filtering approach 1 are reflected in discordance between imputed and provided APOE genotypes, particularly in APOE*4/4 carriers. A APOE*4/4-rs439401 carrier cohort distributions. The top section shows the distribution of prioritized APOE genotype source in approach 1, indicating that APOE*4/4 carriers of rs439401 had very few WGS/WES-verified APOE*4/4 data. The bottom section shows pie charts for carrier distributions across cohorts (Additional data in Table S8). The red arrow indicates that a large fraction of control rs439401 carriers was contributed by MIRAGE. B Concordance rates between provided and imputed APOE per cohort (additional data in Table S9). The red arrow indicates that MIRAGE had the lowest concordance rate, suggesting potential limitations with its provided APOE data that could explain observations in A. C Concordance rates between provided and imputed APOE for the discovery sample, considering multiple strata (additional data in Table S10). APOE*4/4 strata considered provided APOE*4/4 genotypes after applying APOE filtering approach 1. Note decreased concordance in APOE*4/4 controls compared to cases. Note strongly decreased concordance for rs439401 carriers, specifically controls. Simulations confirmed that APOE*4/4 controls are more likely than cases to not actually be APOE*4/4 carriers (cf. Fig. S6-7). Abbreviations: CN, cognitively normal; AD, Alzheimer’s disease; ORCC BY · PubMed Central
Fig. 3 Overview of rs439401 frequencies and case-control association findings, comparing APOE filtering approach 1 to approach 2. A Carrier frequencies across both approaches for APOE*4/4 and APOE*3/4 WT vs HOM groups, as well as in the Haplotype reference consortium v1.1 (HRC). Note decreased frequencies for rs439401 in approach 2 that appear concordant with the HRC. B, C Overview of association findings for all evaluated strata, comparing B approach 1 to C approach 2. Significant effects are denoted by an asterisk (*). Error bars show 95% confidence intervals. Note loss of significant effects in approach 2
Fig. 3 Overview of rs439401 frequencies and case-control association findings, comparing APOE filtering approach 1 to approach 2. A Carrier frequencies across both approaches for APOE*4/4 and APOE*3/4 WT vs HOM groups, as well as in the Haplotype reference consortium v1.1 (HRC). Note decreased frequencies for rs439401 in approach 2 that appear concordant with the HRC. B, C Overview of association findings for all evaluated strata, comparing B approach 1 to C approach 2. Significant effects are denoted by an asterisk (*). Error bars show 95% confidence intervals. Note loss of significant effects in approach 2CC BY · PubMed Central

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Research works printed but not linked: 56

  1. Farrer LA, Cuppples LA, Haines JL, et al. Effects of age, sex, and ethnicity on the association between Apolipoprotein E genotype and Alzheimer disease. JAMA. 1997;278:1349–56. · DOI · Paper page
  2. Reiman EM, Arboleda-Velasquez JF, Quiroz YT, et al. Exceptionally low likelihood of Alzheimer’s dementia in APOE2 homozygotes from a 5,000-person neuropathological study. Nat Commun. 2020;11:667. · DOI · Paper page
  3. Arboleda-Velasquez JF, Lopera F, O’Hare M, et al. Resistance to autosomal dominant Alzheimer’s disease in an APOE3 Christchurch homozygote: a case report. Nat Med. 2019. https://doi.org/10.1038/s41591-019-0611-3. · DOI · Paper page
  4. Babenko VN, Afonnikov DA, Ignatieva EV, Klimov AV, Gusev FE, Rogaev EI. Haplotype analysis of APOE intragenic SNPs. BMC Neurosci. 2018;19. https://doi.org/10.1186/s12868-018-0413-4. · DOI
  5. Kulminski AM, Philipp I, Loika Y, He L, Culminskaya I. Protective association of the ε2/ε3 heterozygote with Alzheimer’s disease is strengthened by TOMM40–APOE variants in men. Alzheimer’s Dement. 2021:1–9. · DOI
  6. Xiao H, Gao Y, Liu L, Li Y. Association between polymorphisms in the promoter region of the apolipoprotein e (Apoe) gene and Alzheimer’s disease: a meta-analysis. Excli J. 2017;16:921–38.
  7. Zhang A, Zhao Q, Xu D, Jiang S. Brain APOE expression quantitative trait loci-based association study identified one susceptibility locus for Alzheimer’s disease by interacting with APOE ϵ4. Sci Rep. 2018;8:8–12. · DOI
  8. Kulminski AM, Huang J, Wang J, He L, Loika Y, Culminskaya I. Apolipoprotein E region molecular signatures of Alzheimer’s disease. Aging Cell. 2018;17:e12779. · DOI
  9. Kulminski AM, Philipp I, Loika Y, He L, Culminskaya I. Haplotype architecture of the Alzheimer’s risk in the APOE region via co-skewness. Alzheimer’s Dement Diagnosis, Assess Dis Monit. 2020;12:e12129.
  10. Limon-sztencel A, Lipska-zi BS, Chmara M, et al. The algorithm for Alzheimer risk assessment based on APOE promoter polymorphisms. Alzheimers Res Ther. 2016;8:1–7. · DOI
  11. Blue EE, Cheng A, Chen S, Yu C-E. Association of uncommon, noncoding variants in the APOE region with risk of Alzheimer disease in adults of European ancestry. JAMA Netw Open. 2020;3:e2017666. · DOI
  12. Zhao N, Liu C, Qiao W, Bu G, Apolipoprotein E. Receptors, and modulation of Alzheimer’s disease. Biol Psychiatry. 2018;83:347–57. · DOI · Paper page
  13. Williams T, Borchelt DR, Chakrabarty P. Therapeutic approaches targeting Apolipoprotein e function in Alzheimer’s disease. Mol Neurodegener. 2020;15:1–19. · DOI
  14. Kulminski AM, Shu L, Loika Y, et al. Genetic and regulatory architecture of Alzheimer’s disease in the APOE region. Alzheimer’s Dement Diagnosis, Assess Dis Monit. 2020;12:1–10.
  15. Candás-Estébanez B, Padró-Miquel A, Ruiz-Iruela C, Corbella-Inglés E, Pintó-Sala X, Alía-Ramos P. APOE variants E2, E3, and E4 can be miscalled by classical PCR-RFLP when the Christchurch variant is also present. J Clin Lab Anal. 2017;31:31–3. · DOI
  16. Main BF, Jones PJH, MacGillivray RTA, Banfield DK. Apolipoprotein E genotyping using the polymerase chain reaction and allele-specific oligonucleotide primers. J Lipid Res. 1991;32:183–7. · DOI
  17. Ingelsson M, Shin Y, Irizarry MC, et al. Genotyping of apolipoprotein E: comparative evaluation of different protocols. Curr Protoc Hum Genet. 2003;Chapter 9:1–13.
  18. Zhong L, Xie YZ, Cao TT, et al. A rapid and cost-effective method for genotyping apolipoprotein e gene polymorphism. Mol Neurodegener. 2016;11:1–8. · DOI
  19. Ghebranious N, Ivacic L, Mallum J, Dokken C. Detection of ApoE E2, E3 and E4 alleles using MALDI-TOF mass spectrometry and the homogeneous mass-extend technology. Nucleic Acids Res. 2005;33:1–6. · DOI
  20. Huang J, Pallotti S, Zhou Q, et al. PERHAPS: paired-end short reads-based HAPlotyping from next-generation sequencing data. Brief Bioinform. 2021;22:1–13. · DOI
  21. Naj AC, Jun G, Beecham GW, et al. Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer’s disease. Nat Genet. 2011;43:436–43. · DOI · Paper page
  22. Wittwer CT, Ririe KM, Andrew RV, David DA, Gundry RA, Balis UJ. The LightCycler(TM): a microvolume multisample fluorimeter with rapid temperature control. Biotechniques. 1997;22:176–81. · DOI
  23. Hixson JE, Vernier DT. Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with HhaI. J Lipid Res. 1990;31:545–8. · DOI · Paper page
  24. Lai E, Riley J, Purvis I, Roses A. A 4-Mb high-density single nucleotide polymorphism-based map around human APOE. Genomics. 1998;54:31–8. · DOI
  25. Ahmadian A, Gharizadeh B, Gustafsson AC, et al. Single-nucleotide polymorphism analysis by pyrosequencing. Anal Biochem. 2000;280:103–10. · DOI
  26. Ardlie KG, DeLuca DS, Segrè AV, et al. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science. 2015;348:648–60. · DOI · Paper page
  27. Bellenguez C, Küçükali F, Jansen I, 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. https://doi.org/10.1101/2020.10.01.20200659. · DOI
  28. Weiner MW, Aisen PS, Clifford RJJ, et al. The Alzheimer’s disease neuroimaging initiative: progress report and future plans. Alzheimers Dement. 2010;6:202–11. · DOI
  29. Lee JH, Cheng R, Graff-radford N, Foroud T. Analyses of the National Institute on aging late-onset Alzheimer’s disease family study: implication of additional loci. Arch Neurol. 2008;65:1518–26. · DOI
  30. Kamboh MI, Minster RL, Demirci FY, et al. Association of CLU and PICALM variants with Alzheimer’s disease. Neurobiogy of Aging. 2012;33:518–21. · DOI
  31. Weiner MW, Veitch DP, Hayes J, et al. Effects of traumatic brain injury and posttraumatic stress disorder on Alzheimer’s disease in veterans, using the Alzheimer’s Disease Neuroimaging Initiative. Alzheimer’s Dement. 2014;10:S226–35.
  32. Li H, Wetten S, Li L, et al. Candidate single-nucleotide polymorphisms from a genomewide association study of Alzheimer disease. Arch Intern Med. 2008;65:45–53.
  33. Hofman A, Breteler MMB, Van Duijn CM, et al. The Rotterdam study: 2010 objectives and design update. Eur J Epidemiol. 2009;24:553–72. · DOI · Paper page
  34. Alpérovitch A, Amouyel P, Dartigues JF, et al. Vascular factors and risk of dementia: design of the Three-City Study and baseline characteristics of the study population. Neuroepidemiology. 2003;22:316–25. · DOI · Paper page
  35. Bis JC, Jian X, Chen BWK, et al. Whole exome sequencing study identifies novel rare and common Alzheimer’s-associated variants involved in immune response and transcriptional regulation. Mol Psychiatry. 2020;25:1859–75. · DOI · Paper page
  36. De Jager PL, Ma Y, McCabe C, et al. A multi-omic atlas of the human frontal cortex for aging and Alzheimer’s disease research. Sci Data. 2018;5:180142. · DOI · Paper page
  37. Wang M, Beckmann ND, Roussos P, et al. The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer’s disease. Sci Data. 2018;5:180185. · DOI · Paper page
  38. Bennett DA, Schneider JA, Buchman AS, Barnes LL, Boyle PA, Wilson RS. Overview and findings from the rush memory and aging project. Curr Alzheimer Res. 2012;9:646–63. · DOI
  39. Beecham GW, Bis JC, Martin ER, et al. The Alzheimer’s disease sequencing project: study design and sample selection. Neurol Genet. 2017;3:e194. · DOI · Paper page
  40. Crane PK, Foroud T, Montine TJ, Larson EB. Alzheimer’s disease sequencing project discovery and replication criteria for cases and controls: data from a community-based prospective cohort study with autopsy follow-up. Alzheimers Dement. 2017;13:1410–3. · DOI
  41. Lee JH, Cheng R, Barral S, et al. Identification of novel loci for Alzheimer disease and replication of CLU, PICALM, and BIN1 in Caribbean Hispanic individuals. Arch Neurol. 2011;68:320–8. · DOI · Paper page
  42. Lovestone S, Francis P, Kloszewska I, et al. AddNeuroMed - the European collaboration for the discovery of novel biomarkers for Alzheimer’s disease. Ann N Y Acad Sci. 2009;1180:36–46. · DOI
  43. Allen M, Carrasquillo MM, Funk C, et al. Human whole genome genotype and transcriptome data for Alzheimer’s and other neurodegenerative diseases. Sci Data. 2016;3:160089. · DOI · Paper page
  44. Carrasquillo MM, Zou F, Pankratz VS, et al. Genetic variation in PCDH11X is associated with susceptibility to late onset Alzheimer’s disease. Nat Genet. 2009;41:192–8. · DOI · Paper page
  45. Besser L, Kukull W, Knopman DS, et al. Version 3 of the national Alzheimer’s coordinating center’s uniform data set. Alzheimer Dis Assoc Disord. 2018;32:351–8. · DOI
  46. Kunkle BW, Grenier-Boley B, Sims R, 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;51:414–30. · DOI · Paper page
  47. Naj AC, Jun G, Beecham GW, et al. Common variants in MS4A4/MS4A6E, CD2uAP, CD33, and EPHA1 are associated with late-onset Alzheimer’s disease. Nat Genet. 2011;43:436–41. · DOI · Paper page
  48. Beecham GW, Martin ER, Li Y, et al. Genome-wide association study implicates a chromosome 12 risk locus for late-onset Alzheimer disease. Am J Hum Genet. 2009;84:35–43. · DOI · Paper page
  49. Chen CY, Pollack S, Hunter DJ, Hirschhorn JN, Kraft P, Price AL. Improved ancestry inference using weights from external reference panels. Bioinformatics. 2013;29:1399–406. · DOI
  50. Conomos MP, Miller MB, Thornton TA. Robust inference of population structure for ancestry prediction and correction of stratification in the presence of relatedness. Genet Epidemiol. 2015;39:276–93. · DOI
  51. Gogarten SM, Sofer T, Chen H, et al. Genetic association testing using the GENESIS R/Bioconductor package. Bioinformatics. 2019;35:5346–8. · DOI
  52. Taliun D, Harris DN, Kessler MD, et al. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature. 2021;590:290–9. · DOI · Paper page
  53. Das S, Forer L, Schönherr S, et al. Next-generation genotype imputation service and methods. Nat Genet. 2016;48:1284–7. · DOI · Paper page
  54. McCarthy S, Das S, Kretzschmar W, et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet. 2016;48:1279–83. · DOI · Paper page
  55. Auton A, Abecasis GR, Altshuler DM, et al. A global reference for human genetic variation. Nature. 2015;526:68–74. · DOI · Paper page
  56. Adelson RP, Renton AE, Li W, et al. Empirical design of a variant quality control pipeline for whole genome sequencing data using replicate discordance. Sci Rep. 2019;9:1–12. · DOI

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Metadata

Authors
Belloy, M. E., Eger, S. J., Le Guen, Y., Damotte, V., Ahmad, S., Ikram, M. A., Ramirez, A., Tsolaki, A. C., Rossi, G., Jansen, I. E., de Rojas, I., Parveen, K., Sleegers, K., Ingelsson, M., Hiltunen, M., Amin, N., Andreassen, O., Sánchez-Juan, P., Kehoe, P., Amouyel, P., Sims, R., Frikke-Schmidt, R., van der Flier, W. M., Lambert, J.-C., (EADB), F. T. E. A. &. D. B., He, Z., Han, S. S., Napolioni, V., & Greicius, M. D.
ORCID
Belloy, Michael E.
Venue
Alzheimer's Research & Therapy
Publisher
Springer Science and Business Media LLC
Published
2022-02-04
Volume
14
Issue
1
ISSN
1758-9193
DOI
10.1186/s13195-022-00962-4
PMC
PMC8815198
Cited by
22
References
8
Language
en
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CoChat. (2026). Citation check: Challenges at the APOE locus: a robust quality control approach for accurate APOE genotyping. https://app.cochat.ai/papers/10.1186/s13195-022-00962-4
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Belloy, M. E., Eger, S. J., Le Guen, Y., Damotte, V., Ahmad, S., Ikram, M. A., Ramirez, A., Tsolaki, A. C., Rossi, G., Jansen, I. E., de Rojas, I., Parveen, K., Sleegers, K., Ingelsson, M., Hiltunen, M., Amin, N., Andreassen, O., Sánchez-Juan, P., Kehoe, P., . . . Greicius, M. D. (2022). Challenges at the APOE locus: a robust quality control approach for accurate APOE genotyping. Alzheimer's Research & Therapy. https://doi.org/10.1186/s13195-022-00962-4