A foundation model for sleep-based risk stratification and clinical outcomes.

Between 2025 and 2050, the global number of people aged 60 years and older is projected to nearly double – from approximately 1.2 billion to 2.1 billion – corresponding to an increase from approximately 15% to 22% of the world’s total population []. The demographic shift towards an ageing population comes with an increased prevalence of age-related conditions, such as dementia and cognitive impairment []. Despite increasing evidence of adverse events, older adults are frequently prescribed anticholinergic drugs [–]. Nearly a quarter of the population of adults aged 65 years and older with dementia uses anticholinergic medication, according to a recent systematic review []. Anticholinergic drugs block muscarinic cholinergic receptors, thereby inhibiting the effect of acetylcholine, and are used to treat various conditions, including psychiatric, urinary tract-related, and gastrointestinal disorders. The anticholinergic burden, resulting from the use of these drugs, is a known risk factor for a variety of adverse drug reactions (ADRs), ranging from peripheral to central symptoms. Typical peripheral effects – such as dry mouth, urinary retention, and tachycardia – may be easier to detect in clinical everyday practice due to their physical nature. In contrast, central effects – such as impaired concentration, confusion, and attentional deficits – may be less apparent, particularly in older adults with multiple comorbidities [, ]. Several studies have reported an association between anticholinergic burden and poorer cognitive performance, cognitive impairment, or cognitive decline in older adults [–]. This may be due to the importance of cholinergic pathways for cognition, which are disrupted by anticholinergic medication use [, ]. However, cognitive function in older adults is known to be influenced by multiple factors beyond medication use. Risk factors for poorer cognitive function include low educational attainment, vascular comorbidities (e.g., diabetes, hypertension), sensory impairments (e.g., vision and hearing impairment), psychosocial factors such as loneliness and depression, as well as smoking and obesity [–]. In addition to these risk factors, pharmacokinetic aspects may further contribute to the extent of anticholinergic effects on cognition. Some anticholinergic drugs are metabolised by drug-metabolising cytochrome P450 (CYP) enzymes. Among them, CYP2D6 is particularly important, as it is involved in the metabolism of approximately 25% of clinically used drugs []. CYP2D6 is highly polymorphic, leading to considerable interindividual variation in the metabolism of its substrates and, consequently, differences in drug response and the occurrence of ADRs []. Pharmacogenetic (PGx) variants in the CYP2D6 enzyme result in four different metaboliser phenotype groups: poor (PMs), intermediate (IMs), normal (NMs), and ultrarapid metabolisers (UMs) []. Although CYP2D6 phenotypes can be predicted by genotyping, non-genetic factors such as drug-drug interactions, health conditions, or environmental impacts can alter the actual capacity to metabolise drugs []. This phenomenon, known as phenoconversion, can lead to a conversion of CYP2D6 NMs to CYP2D6 PMs []. Serum anticholinergic activity (SAA) levels in nursing home patients with high anticholinergic drug burden were observed to be significantly higher in those being CYP2D6 or CYP2C19 PMs compared to those with functional metabolism []. However, no other studies have yet explored the role of the polymorphic CYP2D6 pathway and its metabolic variability in the association between anticholinergic burden and cognitive function.