Associations of Alzheimer’s disease with inpatient hospital costs and with quality-adjusted life years: evidence from conventional and Mendelian randomization analyses in the UK Biobank

Alzheimer’s disease is a progressive neurodegenerative disorders with profound impacts on cognitive function. There is a shortage of economic evidence relating to the impact that Alzheimer’s disease has on healthcare costs and quality-adjusted life-years (QALYs). We estimated conventional multivariable models of the association between Alzheimer’s disease and these core economic outcomes. However, these types of model may be confounded by omitted variables. We therefore also explored a causal approach using germline genetic variation as instrumental variables in a two-sample Mendelian randomization analysis including polygenic risk scores in a two-stage least squares model, inverse variance weighted models, and pleiotropy robust models. We studied outcomes in the UK Biobank cohort. Data from up to 310,838 individuals were analyzed. N = 55 cases of Alzheimer’s disease were reported at or before recruitment into UK Biobank. A further N = 284 incident cases were identified over follow-up. Analysis of the prevalent cases suggested significant impacts on costs (£1,140 in cases, 95% Confidence Interval (CI): £825 to £1,456) and QALYs (-25%, 95% CI: -28% to -21%). Mendelian randomization estimates were imprecise for costs (£3,082, 95% CI: -£7,183 to £13,348) and QALYs (-32%, 95% CI: -149% to 85%), likely due to the small proportion of variance (0.9%) explained in Alzheimer’s disease status by the most predictive set of SNPs. Conventional multivariable models suggested important impacts of Alzheimer’s disease on inpatient hospital costs and QALYs, although this finding was based on very few cases. Mendelian randomization was very imprecise. Larger GWAS of clinical cases, improved understanding of the architecture of the disease, and the follow-up of cohorts until old age and death will help overcome these challenges.