Spatial navigation is emerging as a critical factor in identifying preclinical Alzheimer's disease (AD). However, the impact of interindi-vidual navigation ability and demographic risk factors (e.g., APOE, age, and sex) on spatial navigation make it difficult to identify persons "at high risk" of AD in the preclinical stages. In the current study, we use spatial navigation big data (n = 27,108) from the Sea Hero Quest (SHQ) game to overcome these challenges by investigating whether big data can be used to benchmark a highly phenotyped healthy aging laboratory cohort into high-vs. low-risk persons based on their genetic (APOE) and demographic (sex, age, and educational attainment) risk factors. Our results replicate previous findings in APOE e4 carriers, indicative of grid cell coding errors in the entorhinal cortex, the initial brain region affected by AD pathophysiology. We also show that although baseline navigation ability differs between men and women, sex does not interact with the APOE genotype to influence the manifestation of AD-related spatial disturbance. Most importantly, we demonstrate that such high-risk preclinical cases can be reliably distinguished from low-risk participants using big-data spatial navigation benchmarks. By contrast, participants were undistinguishable on neuropsychological episodic memory tests. Taken together, we present evidence to suggest that, in the future, SHQ normative benchmark data can be used to more accurately classify spatial impairments in at-high-risk of AD healthy participants at a more individual level, therefore providing the steppingstone for individualized diagnostics and outcome measures of cognitive symptoms in preclinical AD. Alzheimer's disease | spatial navigation | personalized health care | APOE genotype | preclinical diagnosis S patial navigation is a promising cognitive fingerprint for underlying Alzheimer's disease (AD) pathophysiology (1-8) and has been adopted by many high-profile clinical trials (such as the European Prevention of Alzheimer's Dementia Consortium) to improve the sensitivity of neurocognitive testing and assess the efficacy of potentially disease-modifying treatments. In fact, brain areas affected by AD pathophysiology in the preclinical stage (including the entorhinal cortex, posterior cingulate cortex, and precuneus) form the key nodes in the spatial navigation network (6, 9-13). Recent evidence suggests that abnormal spatial navigation patterns may be present before episodic memory deficits, which are the current gold standard for AD diagnosis (6, 14, 15). A major challenge at this stage, however, is to understand how interindividual and demographic factors affect spatial navigation to identify earliest pathological spatial navigation changes in AD (16-19). Understanding diversifying factors that influence variability in spatial ability in the healthy population and individuals at risk to develop AD will advance the diagnostic power of the spatial tests and support more personalized diagnostic and treatment approaches (17, 20-23). Among factors underlying navigation, age is a well-documented predictor of declining spatial abilities, as older adults show a strong bias toward egocentric rather than allocentric strategies (24, 25) leading to suboptimal navigation performance (26). Age-related decline in allocentric process are due to changes in coding patterns of place, grid, border, and head direction cells that underpin our ability to form cognitive maps of the environment and intergrate environmental and self-motion cues to optimize navigational performance (27-29). However, decline in other cognitive domains such as general planning and cognitive control abilities (30) also contribute to spatial deficits in old age, suggesting that, like most diagnostic tests, age-range normative cutoff scores are required (30, 31). Similarly, sex differences in navigation behavior and underlying neuroanatomy have generated arguments for sex-specific clinico-pathological AD phenotypes (17, 21, 32-35). Rodent models of the Morris water maze have shown that male rats consistently outper-form females (36), and human studies display similar sex differences favoring males (37-40) across 57 countries in both map-dependent allocentric and map-independent egocentric navigational strategies (41). Therefore, although spatial navigation tools must retain sensitivity and specificity to preclinical AD pathophysiology, it will be critical to develop diagnostic tools that can adjust for underlying sex differences. Finally, one of the biggest challenges in preclinical AD studies is to identify those who are at high risk to develop symptomatic AD in the future. Genetic variation in the apolipoprotein E 4 allele carriers is currently the strongest known genetic risk factor for sporadic AD (7, 42-44). Compared with the e3e3 carriers, those with the e3e4 show a threefold to fourfold increased risk for AD (44, 45). Phenotypic characteristics of apoE e4 allele show that the cognitive profile of e4 carriers changes over the life span, with some cognitive advantage seen in young adulthood (39) and cognitive disturbances in mnemonic and spatial process in mid-adulthood (46-48). Recent findings also show that temporal grid cell-like representation in the