Background: Genetic studies have primarily been conducted in European ancestry populations, identifying dozens of loci associated with late-onset Alzheimer's disease (AD). However, much of AD's heritability remains unexplained; as the prevalence of AD varies across populations, the genetic architecture of the disease may also vary by population with the presence of novel variants or loci.
Methods: We conducted genome-wide analyses of AD in a sample of 2565 Caribbean Hispanics to better understand the genetic contribution to AD in this population. Statistical analysis included both admixture mapping and association testing. Evidence for differential gene expression within regions of interest was collected from independent transcriptomic studies comparing AD cases and controls in samples with primarily European ancestry.
Results: Our genome-wide association study of AD identified no loci reaching genome-wide significance. However, a genome-wide admixture mapping analysis that tests for association between a haplotype's ancestral origin and AD status detected a genome-wide significant association with chromosome 3q13.11 (103.7-107.7Mb, P = 8.76E-07), driven by a protective effect conferred by the Native American ancestry (OR = 0.58, 95%CI = 0.47-0.73). Within this region, two variants were significantly associated with AD after accounting for the number of independent tests (rs12494162, P = 2.33E-06; rs1731642, P = 6.36E-05). The significant admixture mapping signal is composed of 15 haplotype blocks spanning 5 protein-coding genes (ALCAM, BBX, CBLB, CCDC54, CD47) and four brain-derived topologically associated domains, and includes markers significantly associated with the expression of ALCAM, BBX, CBLB, and CD47 in the brain. ALCAM and BBX were also significantly differentially expressed in the brain between AD cases and controls with European ancestry.
Conclusion: These results provide multiethnic evidence for a relationship between AD and multiple genes at 3q13.11 and illustrate the utility of leveraging genetic ancestry diversity via admixture mapping for new insights into AD.
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http://dx.doi.org/10.1186/s13195-021-00866-9 | DOI Listing |
Hum Genome Var
January 2025
Faculty of Medicine and Health Sciences, UCSI University, Negeri Sembilan, Federal Territory of Kuala Lumpur, Malaysia.
Jakun, a Proto-Malay subtribe from Peninsular Malaysia, is believed to have inhabited the Malay Archipelago during the period of agricultural expansion approximately 4 thousand years ago (kya). However, their genetic structure and population history remain inconclusive. In this study, we report the genome structure of a Jakun female, based on whole-genome sequencing, which yielded an average coverage of 35.
View Article and Find Full Text PDFThe admixture model is widely applied to estimate and interpret population structure among individuals. Here we consider a "standard admixture" model that assumes the admixed populations are unrelated and also a generalized model, where the admixed populations themselves are related via coancestry (or covariance) of allele frequencies. The generalized model yields a potentially more realistic and substantially more flexible model that we call "super admixture".
View Article and Find Full Text PDFFront Plant Sci
December 2024
Genoscope, Institut de Biologie François-Jacob, Commissariat à l'Energie Atomique (CEA), Université Paris-Saclay, Evry, France.
Introduction: Useful germplasm for citrus breeding includes all sexually compatible species of the former genera , and , now merged in the single genus. An improved knowledge on the synteny/collinearity between the genome of these different species, and on their recombination landscapes, is essential to optimize interspecific breeding schemes.
Method: We have performed a large comparative genetic mapping study including several main clades of the genus.
Genet Sel Evol
December 2024
State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, China.
Background: The genome-wide association study (GWAS) is a powerful method for mapping quantitative trait loci (QTL). However, standard GWAS can detect only QTL that segregate in the mapping population. Crossing populations with different characteristics increases genetic variability but F2 or back-crosses lack mapping resolution due to the limited number of recombination events.
View Article and Find Full Text PDFHGG Adv
January 2025
Division of Human Genetics, Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; McKusick-Nathans Institute, and Department of Genetic Medicine, Johns Hopkins University, School of Medicine, Baltimore, MD, USA. Electronic address:
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