The inverse association between cancer and Alzheimers disease: comparing spurious and causal explanations to illuminate the causes of Alzheimers disease

Investigator: Maria Glymour, ScD, MS
Sponsor: NIH National Institute on Aging

Location(s): United States


Several studies report an inverse comorbidity between cancer and Alzheimer’s Disease (AD). Incidence rates of AD are about 30% lower among cancer survivors than individuals with no history of cancer. Recent findings indicate that differential survival after cancer cannot fully explain this inverse association, and biological explanations are hypothesized. Neoplastic cell growth underlying cancer may be the flip side of the cellular process that contributes to neuronal death in AD; for example regulation of apoptosis, immune response, or DNA repair may account for the inverse comorbidity of cancer and AD. If the inverse association between cancer and AD arises from a common physiologic process, explaining this association could reveal novel insights into the pathophysiology of AD and highlight targets for preventive or therapeutic interventions. We propose to evaluate competing explanations for the inverse cancer-AD association : (1) diagnostic bias: individuals with a history of cancer are less likely to be diagnosed with AD; (2) competing risks: both conditions increase mortality, so occurrence of either reduces lifetime risk of the other; (3) survival bias: factors that improve survival of cancer patients are associated with lower AD risk, so cancer survivors are a biased sample of all cancer patients; (4) inverse common causes: cancer incidence is reduced by genetic or environmental factors which increase AD risk; (5) causality: physiologic or treatment responses to cancer reduce risk of AD. We will systematically evaluate these 5 alternative explanations for the inverse comorbidity of cancer and AD, with the aim of improving understanding of the biological events that initiate or maintain the Alzheimer’s cascade. We use longitudinal analyses of two large cohorts (the Health and Retirement Study [HRS] and the UK Biobank [UKB]), genetic quasi-experiments, and simulation models to evaluate the plausibility of competing explanations. In AIM 1, we evaluate the link between cancer and longitudinal rate of cognitive change in HRS and UKB. Only one prior study evaluated cancer and longitudinal cognitive change. We hypothesize that cognitive decline will be slower both before and after cancer diagnosis, even for non-life-threatening cancers, compared to people with no cancer diagnosis. In AIM 2, we test whether cancer shares genetic risk factors with AD or cognitive change. We construct polygenic cancer risk scores both using genome-wide data and using specific variants previously confirmed to influence cancer risk. We then assess whether these polygenic cancer risk scores predict lower risk of AD. We also examine the reverse, whether polygenic AD risk scores predict lower cancer risk. In AIM 3, we combine multiple sources of evidence on cancer type specific mortality rates, genetic correlations, and associations with AD to specify simulation models. In combination, these observations will demonstrate the most likely explanation for the inverse cancer-AD link. We leverage the apparently paradoxical inverse comorbidity of cancer and AD to gain new insights into the biological mechanisms underlying AD and point the way towards novel preventive and therapeutic strategies.