Stratification by a polygenic risk score of common variation aids in Alzheimer's disease rare variant discovery.

Dementia incidence increases rapidly with advancing age. Although disease‐modifying therapies targeting amyloid pathology have demonstrated substantial target engagement, their effects on slowing cognitive decline and disease progression remain modest. Accordingly, there is continued interest in identifying clinically meaningful markers of vulnerability that may inform risk stratification, prognosis, and preventive strategies earlier in the disease course., Dementia has been consistently observed to co‐occur with skeletal muscle loss,, , but this association is potentially confounded by physical inactivity, poor nutrition, cerebrovascular and metabolic dysfunction, systemic inflammation, and other factors that contribute to overall biological vulnerability, including frailty, low educational attainment, genetic predisposition (e.g., apolipoprotein E [ ε4 carrier status), and comorbid medical conditions, all of which contribute to both muscle loss and dementia risk. A meta‐analysis of 15 cross‐sectional studies reported that skeletal muscle loss was associated with a 2.25‐fold increased likelihood of concurrent cognitive impairment. However, longitudinal evidence establishing the temporal relationship between low muscle mass and dementia risk is lacking. If reductions in muscle size occur prior to overt cognitive decline, and if interventions that preserve or restore muscle health favorably influence cognitive trajectories and function, then early detection of skeletal muscle loss may offer a window for risk stratification and preventive intervention., , , , In this context, a widely available and tractable imaging biomarker of skeletal muscle size could facilitate early skeletal muscle loss detection and be used to investigate the potential benefits of modifying interventions (e.g., resistance training, aerobic exercise, nutritional interventions) in mitigating dementia risk and progression. Traditional methods of assessing muscle health, such as clinical assessments, anthropometry, dynamometry, and serum/urine markers, have limited sensitivity, and more importantly are not regularly measured in prospective dementia cohort studies (or clinically)., Current guidelines demonstrate a growing trend towards imaging biomarkers of muscle composition. Dual‐energy X‐ray absorptiometry (DEXA) is recommended as “standard of care” in clinical practice, but is limited by lack of adherence and cost, and is not included in cognitive research studies or clinical evaluation for dementia. During initial cognitive evaluations in older adults, brain MRI is frequently ordered to evaluate for potential neuroanatomic changes. Beyond its role in evaluating neuroanatomy, brain MRI also captures the temporalis muscle (TM), which is anatomically stable, well‐bordered, and easy to segment. As the largest cranial skeletal muscle, the TM's size has been found to correlate with general body skeletal muscle mass,, , providing a unique opportunity to assess overall skeletal muscle health from existing brain MRI data that may otherwise go overlooked. Numerous previous studies showed that TM size predicted outcomes in head and neck cancers,, , strokes,, , Parkinson's disease, and amyotrophic lateral sclerosis (eIntroduction in Supplement ). Cross‐sectional findings also suggest correlations between TM thickness, appendicular muscle mass, and cognitive function., , , , , , However, the TM's longitudinal predictive value for dementia risk has yet to be evaluated.