Polygenic risk and genomic prediction of Alzheimer’s disease

Developing ancestry-aware genomic prediction across cognition, biomarkers, pathology, and clinical outcomes

Alzheimer’s disease is highly polygenic: beyond APOE, many common genetic variants each contribute a small amount of risk. Polygenic risk scores combine these effects into a single measure of inherited susceptibility. My work has evaluated what these scores capture across the disease course, from cognitive performance in people without dementia to clinical impairment and Alzheimer’s disease pathology, while also addressing their limited transferability across ancestry groups.

My early longitudinal studies followed community-dwelling older adults for up to 12 years. I showed that selected Alzheimer’s disease risk variants and an aggregate genetic risk score were associated with episodic memory and cognitive decline. When genetic and modifiable risk scores were compared directly, they captured different aspects of impairment: modifiable risk was broadly associated with general cognitive ability and progression to mild cognitive impairment, whereas genetic risk was more closely related to dementia-specific cognitive variation and later clinical progression. These studies established that polygenic scores provide meaningful information, but that their interpretation depends on the outcome and stage of disease being predicted.

A major limitation is that most Alzheimer’s disease genome-wide association studies have included predominantly European-ancestry participants, reducing the accuracy of conventional scores in other populations. As senior author, I led work comparing single-ancestry, multi-ancestry, and cross-ancestry polygenic risk models. A cross-ancestry Bayesian model performed best in non-European populations and was associated not only with Alzheimer’s disease diagnosis, but also with poorer cognition, lower cerebrospinal-fluid amyloid, and more severe amyloid and tau neuropathology. Together, this work advances polygenic risk scores from simple counts of risk alleles toward ancestry-aware measures that connect inherited susceptibility to cognition, biomarkers, pathology, and clinical outcomes. It also demonstrates that more inclusive genetic discovery datasets are essential if genomic prediction is to benefit diverse populations.

Selected publications

  • Andrews SJ, Das D, Cherbuin N, Anstey KJ, Easteal S. (2016). “Association of genetic risk factors with cognitive decline: the PATH through life project.” Neurobiology of Aging. doi:10.1016/j.neurobiolaging.2016.02.016.
  • Andrews SJ, Eramudugolla R, Velez JI, et al. (2017). “Validating the role of the Australian National University Alzheimer’s Disease Risk Index (ANU-ADRI) and a genetic risk score in progression to cognitive impairment in a population-based cohort of older adults followed for 12 years.” Alzheimer’s Research & Therapy. doi:10.1186/s13195-017-0240-3.
  • Andrews SJ, McFall GP, Dixon RA, et al. (2019). “Alzheimer’s Environmental and Genetic Risk Scores are Differentially Associated With General Cognitive Ability and Dementia Severity.” Alzheimer Disease & Associated Disorders. doi:10.1097/WAD.0000000000000292.
  • Okorie M, Jonson C, Oddi AP, et al. (2026). “Cross-ancestry polygenic risk scores enhance Alzheimer’s disease risk prediction in multiethnic cohorts.” Alzheimer’s & Dementia. doi:10.1002/alz.71529.