| Application: | 15175, Further defining the genetic architecture of Alzheimer's disease |
| Title: | Age-dependent effect of APOE and polygenic component on Alzheimer's disease |
| Size: | 4.5 MB |
| Archived: | 22 Feb 2021 |
| Stability: | Complete |
| Personal: | Contains individual-level data |
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Notes
Alzheimer s disease (AD) is a devastating neurodegenerative condition with significant genetic heritability. Several genes have been implicated in the onset of AD with apolipoprotein E (APOE) gene being the strongest single genetic risk loci. Evidence suggests that the effect of APOE alters with age during disease progression. Here, we aim to investigate the impact of APOE and other variants outside the APOE region on AD risk in younger and older participants. Using data from both the Alzheimer s Disease Neuroimaging Initiative (ADNI) and the UK Biobank (UKBB) we computed the polygenic risk score (PRS) of each individual informed by the latest genetic study from the International Genomics of Alzheimer s Project (IGAP). Our analysis showed that the effect of APOE is greater in younger participants and reduces as participant age increases. It also indicates the increased impact of PRS as participant age increases. Therefore, AD in older individuals can potentially be triggered by the cumulative effect of genes which are outside the APOE region.Application 15175
Further defining the genetic architecture of Alzheimer's disease
Our studies of Alzheimer?s disease (AD) genetics indicate that diseased individuals display a risk gene burden spectrum(polygenic risk. Our risk gene burden models predict AD with 78% accuracy. We request Biobank data to test our algorithms in population cohorts. We will further explore polygenic risk, investigating relationships between AD risk genes and environmental factors. We will analyse brain imaging data to explore early detection of AD-associated brain changes and correlate these with gene burden. Results will provide insights into disease-critical environmental cues, and further elucidate themes associated with AD including the immune response. The improved knowledge and understanding of the dysfunctional processes in Alzheimer?s disease, as well as the interaction of our genes and environment, elucidated through exploration of the above research questions, will pave the way for precision medicine and allow the forecasting of clinical need and relevant policymaking strategies. Ultimately insights from this work will lead to better understanding of the disease process, improved diagnosis and better treatment. Our studies of Alzheimer?s disease (AD) genetics show that individuals display a spectrum of risk gene burden (polygenic risk), which predicts 78% of AD risk. We wish to explore polygenic risk distribution in populations, looking for relationships between risk genes and environmental factors. This will provide insights into the environmental cues most critical to disease. We will analyse brain imaging data to explore whether changes can be detected at early disease stages and correlated with gene burden. This knowledge and understanding will pave the way for new precision medicines and inform clinical strategies. All participants with available genomic data should be included in this data request. In addition, we request sufficient information to link this genomic data with the full cohort stored in our institution under Biobank projects 6553 and 17044.
| Lead investigator: | Professor Julie Williams |
| Lead institution: | Cardiff University |
1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 3138 | Age-dependent effect of APOE and polygenic component on Alzheimer's disease | Eftychia Bellou (+8) | 2020 | Neurobiology of Aging |
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