Genetic basis for resistance or susceptibility to Alzheimer disease conferred by the HLA and KIR loci
- PI
- Viard, Mathias
- DAR ID
- 12190
- Initial Approval Date
- April 1, 2026
- Current DAR Status
- Active
- PI Institution
- LEIDOS BIOMEDICAL RESEARCH, INC.
- PI Institution Country
- United States
- PI Institution Type
- For-Profit
Requested Datasets (18)
NG00067Alzheimer's Disease Sequencing Project Umbrella StudyNG00117NCRAD Families GWASNG00127A longitudinal study of Alzheimer's Disease and other dementing illnesses – KnightADRC GWASNG00022ADC1 - Alzheimer's Disease Center Dataset 1NG00023ADC2 - Alzheimer's Disease Center Dataset 2NG00024ADC3 - Alzheimer's Disease Center Dataset 3NG00068ADC4 - Alzheimer's Disease Center Dataset 4NG00069ADC5 - Alzheimer's Disease Center Dataset 5NG00070ADC6 - Alzheimer's Disease Center Dataset 6NG00071ADC7 - Alzheimer's Disease Center Dataset 7NG00136ADC8 - Alzheimer's Disease Center Dataset 8NG00137ADC9 - Alzheimer's Disease Center Dataset 9
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NG00138ADC10 - Alzheimer's Disease Center Dataset 10NG00139ADC11 - Alzheimer's Disease Center Dataset 11NG00140ADC12 - Alzheimer's Disease Center Dataset 12NG00149ADC13 - Alzheimer's Disease Center Dataset 13NG00150ADC14 - Alzheimer's Disease Center Dataset 14NG00151ADC15 - Alzheimer's Disease Center Dataset 15
Research Use Statement
The purpose of our study is to use the great resources of these datasets to study the involvement of HLA and KIR in the development of Alzheimer disease. Using the HLA regions of chromosome 6 and KIR regions of chromosome 19, we can input HLA and KIR, although KIR requires WES or WGS within chromosome 19 rather than genotyping due to the abundance of structural variants along with the SNP polymorphisms for this locus. Once we call HLA and KIR for the different participants, we will, beyond allelic analyses, derive from them broader immune properties that will allow us to group individuals and study the association of those properties with Alzheimer disease. With case/control, we will use logistic regressions. We will also try to look into progression to disease and death using cox regressions to see if parameters we can associate with onset of disease also correlate with the progression of the disease and understand what parameter of the immune system is associated with one step, or the other, or both. All the results will be conditioned by the apolipoprotein E genotyping of the individuals. The use of different datasets will allow us to get enough numbers to evaluate the reproducibility of the results which we will adjust for differences in population background through the use of principal components. The interpretation of the results will be dependent on the associations we can identify. HLA and KIR are at the center of the innate and acquired immune system so we will be able to evaluate which arm of the immune system is involved in the disease. For example, we showed that HIV disease can associate with compound HLA class I (HLA-I)-KIR genotypes, allele-specific HLA-I binding to the inhibitory receptor LILRB2 as well as HLA-C expression levels. In addition, allele-specific HLA-A expression levels have been suggested to modulate NK cell activity and HIV control through modulation of cell surface expression of HLA-E, which bind peptides derived from HLA-I signal sequences. In addition, HLA-I alleles have been characterized for their tapasin dependence level, which influences the breadth of peptide repertoire and can modulate immune responses.
Non-Technical Summary
Alzheimer’s disease is influenced by many factors, including how the immune system works. This study examines whether natural differences in immune-related genes help explain who develops Alzheimer’s disease and how the disease changes over time. We focus on two groups of genes that are important for immune responses, HLA and KIR. Using large genetic datasets, we will identify shared immune patterns across individuals, rather than focusing on single genetic changes. We will compare people with and without Alzheimer’s disease to see whether certain immune patterns are linked to disease risk. We will also examine whether these immune features are associated with how quickly the disease progresses and with survival after diagnosis. All analyses will take into account known genetic risk factors for Alzheimer’s disease. By using multiple datasets from different populations, we can test whether results are consistent and reliable. This research aims to improve understanding of how the immune system may contribute to Alzheimer’s disease and inform future prevention and treatment efforts.
Reported Publications
Publications shown are those reported by investigators through NIAGADS DAR reporting and renewal processes and may not represent a complete list of publications associated with the project.
No publications have been reported for this DAR.