Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jan 29:11:629373.
doi: 10.3389/fgene.2020.629373. eCollection 2020.

Recent Consanguinity and Outbred Autozygosity Are Associated With Increased Risk of Late-Onset Alzheimer's Disease

Affiliations

Recent Consanguinity and Outbred Autozygosity Are Associated With Increased Risk of Late-Onset Alzheimer's Disease

Valerio Napolioni et al. Front Genet. .

Abstract

Prior work in late-onset Alzheimer's disease (LOAD) has resulted in discrepant findings as to whether recent consanguinity and outbred autozygosity are associated with LOAD risk. In the current study, we tested the association between consanguinity and outbred autozygosity with LOAD in the largest such analysis to date, in which 20 LOAD GWAS datasets were retrieved through public databases. Our analyses were restricted to eight distinct ethnic groups: African-Caribbean, Ashkenazi-Jewish European, European-Caribbean, French-Canadian, Finnish European, North-Western European, South-Eastern European, and Yoruba African for a total of 21,492 unrelated subjects (11,196 LOAD and 10,296 controls). Recent consanguinity determination was performed using FSuite v1.0.3, according to subjects' ancestral background. The level of autozygosity in the outbred population was assessed by calculating inbreeding estimates based on the proportion (FROH) and the number (NROH) of runs of homozygosity (ROHs). We analyzed all eight ethnic groups using a fixed-effect meta-analysis, which showed a significant association of recent consanguinity with LOAD (N = 21,481; OR = 1.262, P = 3.6 × 10-4), independently of APOE 4 (N = 21,468, OR = 1.237, P = 0.002), and years of education (N = 9,257; OR = 1.274, P = 0.020). Autozygosity in the outbred population was also associated with an increased risk of LOAD, both for F ROH (N = 20,237; OR = 1.204, P = 0.030) and N ROH metrics (N = 20,237; OR = 1.019, P = 0.006), independently of APOE 4 [(F ROH, N = 20,225; OR = 1.222, P = 0.029) (N ROH, N = 20,225; OR = 1.019, P = 0.007)]. By leveraging the Alzheimer's Disease Sequencing Project (ADSP) whole-exome sequencing (WES) data, we determined that LOAD subjects do not show an enrichment of rare, risk-enhancing minor homozygote variants compared to the control population. A two-stage recessive GWAS using ADSP data from 201 consanguineous subjects in the discovery phase followed by validation in 10,469 subjects led to the identification of RPH3AL p.A303V (rs117190076) as a rare minor homozygote variant increasing the risk of LOAD [discovery: Genotype Relative Risk (GRR) = 46, P = 2.16 × 10-6; validation: GRR = 1.9, P = 8.0 × 10-4]. These results confirm that recent consanguinity and autozygosity in the outbred population increase risk for LOAD. Subsequent work, with increased samples sizes of consanguineous subjects, should accelerate the discovery of non-additive genetic effects in LOAD.

Keywords: Alzheimer disease; autozygosity; directional dominance; ethnic differences; inbreeding; recessive inheritance; runs of homozygosity (ROH); uniparental isodisomy.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Flow-chart of the workflow adopted in the data QC/harmonization/ancestry-determination processing of the full dataset.
FIGURE 2
FIGURE 2
Analysis of the genetic structure confirmed the effectiveness of our ancestry-determination pipeline. Ancestry proportions of the 21,492 unrelated subjects studied (from the eight determined ethnic groups) as revealed by the ADMIXTURE software (Alexander et al., 2009), using pruned (MAF ≥ 0.01, r2 ≤ 0.1) SNPs at K = 6. Each color represents a different ancestral component, and each ancestry is a mixture of different components. ACD, African–Caribbean from Dominican Republic; AJE, Ashkenazi-Jewish Europeans; ECD, European–Caribbean from Dominican Republic; FCN, French–Canadians; FIN, Finnish Europeans; NWE, North-Western Europeans; SEE, South-Eastern Europeans; YRI, African Yoruba.
FIGURE 3
FIGURE 3
The eight ethnic groups analyzed showed ethnic-specific differences in Alzheimer’s-relevant risk factors. (A) mean age, (B) EDU, (C) APOE2 frequency, (D) APOE4 frequency, (E) inbreeding coefficient, and (F) number of ROHs (>1 Mb) differ significantly across the eight ethnic groups analyzed (P < 0.00001).
FIGURE 4
FIGURE 4
Numerous cases of putative isodisomy misidentified as consanguineous subjects. Fifty-six subjects identified as consanguineous by FSuite v1.0.3 (Gazal et al., 2014) showed a single homozygous region over 10 Mb on just one chromosome, the homozygosity cut-off previously reported to define the presence of putative uniparental isodisomy (UPD). Two female subjects showing a putative UPD on X-chromosome are not shown. Red = LOAD; Blue = Control.

Similar articles

  • Long runs of homozygosity are associated with Alzheimer's disease.
    Moreno-Grau S, Fernández MV, de Rojas I, Garcia-González P, Hernández I, Farias F, Budde JP, Quintela I, Madrid L, González-Pérez A, Montrreal L, Alarcón-Martín E, Alegret M, Maroñas O, Pineda JA, Macías J; GR@ACE study group; DEGESCO consortium; Marquié M, Valero S, Benaque A, Clarimón J, Bullido MJ, García-Ribas G, Pástor P, Sánchez-Juan P, Álvarez V, Piñol-Ripoll G, García-Alberca JM, Royo JL, Franco-Macías E, Mir P, Calero M, Medina M, Rábano A, Ávila J, Antúnez C, Real LM, Orellana A, Carracedo Á, Sáez ME, Tárraga L, Boada M, Cruchaga C, Ruiz A; Alzheimer’s Disease Neuroimaging Initiative. Moreno-Grau S, et al. Transl Psychiatry. 2021 Feb 24;11(1):142. doi: 10.1038/s41398-020-01145-1. Transl Psychiatry. 2021. PMID: 33627629 Free PMC article.
  • Improved Diagnosis of Rare Disease Patients through Systematic Detection of Runs of Homozygosity.
    Matalonga L, Laurie S, Papakonstantinou A, Piscia D, Mereu E, Bullich G, Thompson R, Horvath R, Pérez-Jurado L, Riess O, Gut I, van Ommen GJ, Lochmüller H, Beltran S; RD–Connect Genome-Phenome Analysis Platform and URD-Cat Data Contributors. Matalonga L, et al. J Mol Diagn. 2020 Sep;22(9):1205-1215. doi: 10.1016/j.jmoldx.2020.06.008. Epub 2020 Jun 30. J Mol Diagn. 2020. PMID: 32619640 Free PMC article.
  • Association between autozygosity and major depression: stratification due to religious assortment.
    Abdellaoui A, Hottenga JJ, Xiao X, Scheet P, Ehli EA, Davies GE, Hudziak JJ, Smit DJ, Bartels M, Willemsen G, Brooks A, Sullivan PF, Smit JH, de Geus EJ, Penninx BW, Boomsma DI. Abdellaoui A, et al. Behav Genet. 2013 Nov;43(6):455-67. doi: 10.1007/s10519-013-9610-1. Epub 2013 Aug 25. Behav Genet. 2013. PMID: 23978897 Free PMC article.
  • Runs of homozygosity: windows into population history and trait architecture.
    Ceballos FC, Joshi PK, Clark DW, Ramsay M, Wilson JF. Ceballos FC, et al. Nat Rev Genet. 2018 Apr;19(4):220-234. doi: 10.1038/nrg.2017.109. Epub 2018 Jan 15. Nat Rev Genet. 2018. PMID: 29335644 Review.
  • Runs of homozygosity: current knowledge and applications in livestock.
    Peripolli E, Munari DP, Silva MVGB, Lima ALF, Irgang R, Baldi F. Peripolli E, et al. Anim Genet. 2017 Jun;48(3):255-271. doi: 10.1111/age.12526. Epub 2016 Dec 1. Anim Genet. 2017. PMID: 27910110 Review.

Cited by

References

    1. 1000 Genomes Project Consortium, Auton A., Brooks L. D., Durbin R. M., Garrison E. P., Kang H. M., et al. (2015). A global reference for human genetic variation. Nature 526 68–74. 10.1038/nature15393 - DOI - PMC - PubMed
    1. Alexander D. H., Novembre J., Lange K. (2009). Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19 1655–1664. 10.1101/gr.094052.109 - DOI - PMC - PubMed
    1. Andrews S. J., Fulton-Howard B., O’Reilly P., Marcora E., Goate A. M. Collaborators of the Alzheimer’s Disease Genetics Consortium (2021). Causal associations between modifiable risk factors and the Alzheimer’s Phenome. Ann. Neurol. 89 54–65. 10.1002/ana.25918 - DOI - PMC - PubMed
    1. Beecham G. W., Bis J. C., Martin E. R., Choi S. H., DeStefano A. L., van Duijn C. M., et al. (2017). The Alzheimer’s disease sequencing project: study design and sample selection. Neurol. Genet. 3:e194. - PMC - PubMed
    1. Bereczki E., Francis P. T., Howlett D., Pereira J. B., Höglund K., Bogstedt A., et al. (2016). Synaptic proteins predict cognitive decline in Alzheimer’s disease and lewy body dementia. Alzheimers Dement. 12 1149–1158. 10.1016/j.jalz.2016.04.005 - DOI - PubMed

Grants and funding

LinkOut - more resources