Digital neuropsychological measures by defense automated neurocognitive assessment: reference values and clinical correlates.

Introduction: Although the growth of digital tools for cognitive health assessment, there's a lack of known reference values and clinical implications for these digital methods. This study aims to establish reference values for digital neuropsychological measures obtained through the smartphone-based cognitive assessment application, Defense Automated Neurocognitive Assessment (DANA), and to identify clinical risk factors associated with these measures. Methods: The sample included 932 cognitively intact participants from the Framingham Heart Study, who completed at least one DANA task. Participants were stratified into subgroups based on sex and three age groups. Reference values were established for digital cognitive assessments within each age group, divided by sex, at the 2.5th, 25th, 50th, 75th, and 97.5th percentile thresholds. To validate these values, 57 cognitively intact participants from Boston University Alzheimer's Disease Research Center were included. Associations between 19 clinical risk factors and these digital neuropsychological measures were examined by a backward elimination strategy. Results: Age- and sex-specific reference values were generated for three DANA tasks. Participants below 60 had median response times for the Go-No-Go task of 796 ms (men) and 823 ms (women), with age-related increases in both sexes. Validation cohort results mostly aligned with these references. Different tasks showed unique clinical correlations. For instance, response time in the Code Substitution task correlated positively with total cholesterol and diabetes, but negatively with high-density lipoprotein and low-density lipoprotein cholesterol levels, and triglycerides. Discussion: This study established and validated reference values for digital neuropsychological measures of DANA in cognitively intact white participants, potentially improving their use in future clinical studies and practice.

Design and Feasibility Analysis of a Smartphone-Based Digital Cognitive Assessment Study in the Framingham Heart Study.

BACKGROUND: Smartphone-based digital technology is increasingly being recognized as a cost-effective, scalable, and noninvasive method of collecting longitudinal cognitive and behavioral data. Accordingly, a state-of-the-art 3-year longitudinal project focused on collecting multimodal digital data for early detection of cognitive impairment was developed. METHODS AND RESULTS: A smartphone application collected 2 modalities of cognitive data, digital voice and screen-based behaviors, from the FHS (Framingham Heart Study) multigenerational Generation 2 (Gen 2) and Generation 3 (Gen 3) cohorts. To understand the feasibility of conducting a smartphone-based study, participants completed a series of questions about their smartphone and app use, as well as sensory and environmental factors that they encountered while completing the tasks on the app. Baseline data collected to date were from 537 participants (mean age=66.6 years, SD=7.0; 58.47% female). Across the younger participants from the Gen 3 cohort (n=455; mean age=60.8 years, SD=8.2; 59.12% female) and older participants from the Gen 2 cohort (n=82; mean age=74.2 years, SD=5.8; 54.88% female), an average of 76% participants agreed or strongly agreed that they felt confident about using the app, 77% on average agreed or strongly agreed that they were able to use the app on their own, and 81% on average rated the app as easy to use. CONCLUSIONS: Based on participant ratings, the study findings are promising. At baseline, the majority of participants are able to complete the app-related tasks, follow the instructions, and encounter minimal barriers to completing the tasks independently. These data provide evidence that designing and collecting smartphone application data in an unsupervised, remote, and naturalistic setting in a large, community-based population is feasible.

Shifting From Active to Passive Monitoring of Alzheimer Disease: The State of the Research.

Most research using digital technologies builds on existing methods for staff-administered evaluation, requiring a large investment of time, effort, and resources. Widespread use of personal mobile devices provides opportunities for continuous health monitoring without active participant engagement. Home-based sensors show promise in evaluating behavioral features in near real time. Digital technologies across these methodologies can detect precise measures of cognition, mood, sleep, gait, speech, motor activity, behavior patterns, and additional features relevant to health. As a neurodegenerative condition with insidious onset, Alzheimer disease and other dementias (AD/D) represent a key target for advances in monitoring disease symptoms. Studies to date evaluating the predictive power of digital measures use inconsistent approaches to characterize these measures. Comparison between different digital collection methods supports the use of passive collection methods in settings in which active participant engagement approaches are not feasible. Additional studies that analyze how digital measures across multiple data streams can together improve prediction of cognitive impairment and early-stage AD are needed. Given the long timeline of progression from normal to diagnosis, digital monitoring will more easily make extended longitudinal follow-up possible. Through the American Heart Association-funded Strategically Focused Research Network, the Boston University investigative team deployed a platform involving a wide range of technologies to address these gaps in research practice. Much more research is needed to thoroughly evaluate limitations of passive monitoring. Multidisciplinary collaborations are needed to establish legal and ethical frameworks for ensuring passive monitoring can be conducted at scale while protecting privacy and security, especially in vulnerable populations.

Comparing Cognitive Tests and Smartphone-Based Assessment in 2 US Community-Based Cohorts.

BACKGROUND: Smartphone-based cognitive assessments have emerged as promising tools, bridging gaps in accessibility and reducing bias in Alzheimer disease and related dementia research. However, their congruence with traditional neuropsychological tests and usefulness in diverse cohorts remain underexplored. METHODS AND RESULTS: A total of 406 FHS (Framingham Heart Study) and 59 BHS (Bogalusa Heart Study) participants with traditional neuropsychological tests and digital assessments using the Defense Automated Neurocognitive Assessment (DANA) smartphone protocol were included. Regression models investigated associations between DANA task digital measures and a neuropsychological global cognitive Z score (Global Cognitive Score [GCS]), and neuropsychological domain-specific Z scores. FHS participants' mean age was 57 (SD, 9.75) years, and 44% (179) were men. BHS participants' mean age was 49 (4.4) years, and 28% (16) were men. Participants in both cohorts with the lowest neuropsychological performance (lowest quartile, GCS1) demonstrated lower DANA digital scores. In the FHS, GCS1 participants had slower average response times and decreased cognitive efficiency scores in all DANA tasks (P<0.05). In BHS, participants in GCS1 had slower average response times and decreased cognitive efficiency scores for DANA Code Substitution and Go/No-Go tasks, although this was not statistically significant. In both cohorts, GCS was significantly associated with DANA tasks, such that higher GCS correlated with faster average response times (P<0.05) and increased cognitive efficiency (all P<0.05) in the DANA Code Substitution task. CONCLUSIONS: Our findings demonstrate that smartphone-based cognitive assessments exhibit concurrent validity with a composite measure of traditional neuropsychological tests. This supports the potential of using smartphone-based assessments in cognitive screening across diverse populations and the scalability of digital assessments to community-dwelling individuals.

Adherence type impacts completion rates of frequent mobile cognitive assessments among older adults with and without cognitive impairment.

Background: Prior to a diagnosis of Alzheimer's disease, many individuals experience cognitive and behavioral fluctuations that are not detected during a single session of traditional neuropsychological assessment. Mobile applications now enable high-frequency cognitive data to be collected remotely, introducing new opportunities and challenges. Emerging evidence suggests cognitively impaired older adults are capable of completing mobile assessments frequently, but no study has observed whether completion rates vary by assessment frequency or adherence type. Methods: Thirty-three older adults were recruited from the Boston University Alzheimer's Disease Research Center (mean age = 73.5 years; 27.3% cognitively impaired; 57.6% female; 81.8% White, 18.2% Black). Participants remotely downloaded and completed the DANA Brain Vital application on their own mobile devices throughout the study. The study schedule included seventeen assessments to be completed over the course of a year. Specific periods during which assessments were expected to be completed were defined as subsegments, while segments consisted of multiple subsegments. The first segment included three subsegments to be completed within one week, the second segment included weekly subsegments and spanned three weeks, and the third and fourth segments included monthly subsegments spanning five and six months, respectively. Three distinct adherence types - subsegment adherence, segment adherence, and cumulative adherence - were examined to determine how completion rates varied depending on assessment frequency and adherence type. Results: Adherence type significantly impacted whether the completion rates declined. When utilizing subsegment adherence, the completion rate significantly declined (p = 0.05) during the fourth segment. However, when considering completion rates from the perspective of segment adherence, a decline in completion rate was not observed. Overall adherence rates increased as adherence parameters were broadened from subsegment adherence (60.6%) to segment adherence (78.8%), to cumulative adherence (90.9%). Conclusions: Older adults, including those with cognitive impairment, are able to complete remote cognitive assessments at a high-frequency, but may not necessarily adhere to prescribed schedules.

Midlife Neuropsychological Profiles and Associated Vascular Risk: The Bogalusa Heart Study.

BACKGROUND: Individuals with Alzheimer's disease (AD) often present with coexisting vascular pathology that is expressed to different degrees and can lead to clinical heterogeneity. OBJECTIVE: To examine the utility of unsupervised statistical clustering approaches in identifying neuropsychological (NP) test performance subtypes that closely correlate with carotid intima-media thickness (cIMT) in midlife. METHODS: A hierarchical agglomerative and k-means clustering analysis based on NP scores (standardized for age, sex, and race) was conducted among 1,203 participants (age 48±5.3 years) from the Bogalusa Heart Study. Regression models assessed the association between cIMT ≥50th percentile and NP profiles, and global cognitive score (GCS) tertiles for sensitivity analysis. RESULTS: Three NP profiles were identified: Mixed-low performance [16%, n = 192], scores ≥1 SD below the mean on immediate, delayed free recall, recognition verbal memory, and information processing; Average [59%, n = 704]; and Optimal [26%, n = 307] NP performance. Participants with greater cIMT were more likely to have a Mixed-low profile [OR = 3.10, 95% CI (2.13, 4.53), p < 0.001] compared to Optimal. After adjusting for education and cardiovascular (CV) risks, results remained. The association with GCS tertiles was more attenuated [lowest (34%, n = 407) versus highest (33%, n = 403) tertile: adjusted OR = 1.66, 95% CI (1.07, 2.60), p = 0.024]. CONCLUSION: As early as midlife, individuals with higher subclinical atherosclerosis were more likely to be in the Mixed-low profile, underscoring the potential malignancy of CV risk as related to NP test performance, suggesting that classification approaches may aid in identifying those at risk for AD/vascular dementia spectrum illness.

Examination of potentially modifiable dementia risk factors across the adult life course: The Framingham Heart Study.

INTRODUCTION: We examined for associations between potentially modifiable risk factors across the adult life course and incident dementia. METHODS: Participants from the Framingham Heart Study were included (n = 4015). Potential modifiable risk factors included education, alcohol intake, smoking, body mass index (BMI), physical activity, social network, diabetes, and hypertension. Cox models were used to examine associations between each factor and incident dementia, stratified by early adult life (33-44 years), midlife (45-65 years), and late life (66-80 years). RESULTS: Increased dementia risk was associated with diabetes (hazard ratio [HR] = 1.62; 95% confidence interval [CI] = 1.07-2.46) and physical inactivity (HR = 1.57; 95% CI = 1.12-2.20) in midlife, and with obesity (HR = 1.76; 95% CI = 1.08-2.87) in late life. Having multiple potential modifiable risk factors in midlife and late life was associated with greater risk. DISCUSSION: Potentially modifiable risk factors individually have limited impact on dementia risk in this population across the adult life course, although in combination they may have a synergistic effect. HIGHLIGHTS: Diabetes and physical inactivity in midlife is associated with increased dementia risk. Obesity in late life is associated with increased dementia risk. Having more potentially modifiable risk factors in midlife and late life is associated with greater dementia risk.

Matching science to reality: how to deploy a participant-driven digital brain health platform.

Introduction: Advances in digital technologies for health research enable opportunities for digital phenotyping of individuals in research and clinical settings. Beyond providing opportunities for advanced data analytics with data science and machine learning approaches, digital technologies offer solutions to several of the existing barriers in research practice that have resulted in biased samples. Methods: A participant-driven, precision brain health monitoring digital platform has been introduced to two longitudinal cohort studies, the Boston University Alzheimer's Disease Research Center (BU ADRC) and the Bogalusa Heart Study (BHS). The platform was developed with prioritization of digital data in native format, multiple OS, validity of derived metrics, feasibility and usability. A platform including nine remote technologies and three staff-guided digital assessments has been introduced in the BU ADRC population, including a multimodal smartphone application also introduced to the BHS population. Participants select which technologies they would like to use and can manipulate their personal platform and schedule over time. Results: Participants from the BU ADRC are using an average of 5.9 technologies to date, providing strong evidence for the usability of numerous digital technologies in older adult populations. Broad phenotyping of both cohorts is ongoing, with the collection of data spanning cognitive testing, sleep, physical activity, speech, motor activity, cardiovascular health, mood, gait, balance, and more. Several challenges in digital phenotyping implementation in the BU ADRC and the BHS have arisen, and the protocol has been revised and optimized to minimize participant burden while sustaining participant contact and support. Discussion: The importance of digital data in its native format, near real-time data access, passive participant engagement, and availability of technologies across OS has been supported by the pattern of participant technology use and adherence across cohorts. The precision brain health monitoring platform will be iteratively adjusted and improved over time. The pragmatic study design enables multimodal digital phenotyping of distinct clinically characterized cohorts in both rural and urban U.S. settings.

Risk Factors for High Symptom Burden Three Months after Traumatic Brain Injury and Implications for Clinical Trial Design: A Transforming Research and Clinical Knowledge in Traumatic Brain Injury Study.

More than 75% of patients presenting to level I trauma centers in the United States with suspicion of TBI sufficient to require a clinical computed tomography scan report injury-related symptoms 3 months later. There are currently no approved treatments, and few clinical trials have evaluated possible treatments. Efficient trials will require subject inclusion and exclusion criteria that balance cost-effective recruitment with enrolling individuals with a higher chance of benefiting from the interventions. Using data from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study, we examined the relationship of 3-month symptoms to pre-injury, demographic, and acute characteristics as well as 2-week symptoms and blood-based biomarkers to identify and evaluate factors that may be used for sample enrichment for clinical trials. Many of the risk factors for TBI symptoms reported in the literature were supported, but the effect sizes of each were small or moderate (< 0.5). The only factors with large effect sizes when predicting 3-month symptom burden were TBI-related (i.e., post-concussive) and post-traumatic stress symptom levels at 2 weeks (respective effect sizes 1.13 and 1.34). TBI severity was not significantly associated with 3-month symptom burden (p = 0.37). Using simulated data to evaluate the effect of enrichment, we showed that including only people with high symptom burden at 2 weeks would permit trials to reduce the sample size by half, with minimal increase in screening, as compared with enrolling an unenriched sample. Clinical trials aimed at reducing symptoms after TBI can be efficiently conducted by enriching the included sample with people reporting a high early symptom burden.

Multimodal deep learning for Alzheimer's disease dementia assessment.

Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer's disease (AD) is the most common. New measures are needed to improve the diagnosis of individuals with cognitive impairment due to various etiologies. Here, we report a deep learning framework that accomplishes multiple diagnostic steps in successive fashion to identify persons with normal cognition (NC), mild cognitive impairment (MCI), AD, and non-AD dementias (nADD). We demonstrate a range of models capable of accepting flexible combinations of routinely collected clinical information, including demographics, medical history, neuropsychological testing, neuroimaging, and functional assessments. We then show that these frameworks compare favorably with the diagnostic accuracy of practicing neurologists and neuroradiologists. Lastly, we apply interpretability methods in computer vision to show that disease-specific patterns detected by our models track distinct patterns of degenerative changes throughout the brain and correspond closely with the presence of neuropathological lesions on autopsy. Our work demonstrates methodologies for validating computational predictions with established standards of medical diagnosis.

Longitudinal Changes in Hearing and Visual Impairments and Risk of Dementia in Older Adults in the United States.

Importance: Hearing and vision problems are individually associated with increased dementia risk, but the impact of having concurrent hearing and vision deficits, ie, dual sensory impairment (DSI), on risk of dementia, including its major subtypes Alzheimer disease (AD) and vascular dementia (VaD), is not well known. Objective: To evaluate whether DSI is associated with incident dementia in older adults. Design, Setting, and Participants: This prospective cohort study from the Cardiovascular Health Study (CHS) was conducted between 1992 and 1999, with as many as 8 years of follow-up. The multicenter, population-based sample was recruited from Medicare eligibility files in 4 US communities with academic medical centers. Of 5888 participants aged 65 years and older in CHS, 3602 underwent cranial magnetic resonance imaging and completed the modified Mini-Mental State Examination in 1992 to 1994 as part of the CHS Cognition Study. A total of 227 participants were excluded due to prevalent dementia, leaving a total of 3375 participants without dementia at study baseline. The study hypothesis was that DSI would be associated with increased risk of dementia compared with no sensory impairment. The association between the duration of DSI with risk of dementia was also evaluated. Data analysis was conducted from November 2019 to February 2020. Exposures: Hearing and vision impairments were collected via self-report at baseline and as many as 5 follow-up visits. Main Outcomes and Measures: All-cause dementia, AD, and VaD, classified by a multidisciplinary committee using standardized criteria. Results: A total of 2927 participants with information on hearing and vision at all available study visits were included in the analysis (mean [SD] age, 74.6 [4.8] years; 1704 [58.2%] women; 455 [15.5%] African American or Black; 2472 [85.5%] White). Compared with no sensory impairment, DSI was associated with increased risk of all-cause dementia (hazard ratio [HR], 2.60; 95% CI, 1.66-2.06; P < .001), AD (HR, 3.67; 95% CI, 2.04-6.60; P < .001) but not VaD (HR, 2.03; 95% CI, 1.00-4.09; P = .05). Conclusions and Relevance: In this cohort study, DSI was associated with increased risk of dementia, particularly AD. Evaluation of hearing and vision in older adults may help to identify those at high risk of developing dementia.

Association Between TBI-Related Hearing Impairment and Cognition: A TRACK-TBI Study.

OBJECTIVE: To examine the association between hearing impairment and cognitive function after traumatic brain injury (TBI). SETTING: A total of 18 level I trauma centers throughout the United States in the T ransforming R esearch a nd C linical K nowledge in TBI (TRACK-TBI) study. PARTICIPANTS: From February 2014 to June 2018, a total of 2697 participants with TBI were enrolled in TRACK-TBI. Key eligibility criteria included external force trauma to the head, presentation to a participating level I trauma center, and receipt of a clinically indicated head computed tomographic (CT) scan within 24 hours of injury. A total of 1267 participants were evaluated in the study, with 216 participants with hearing impairment and 1051 participants without hearing impairment. Those with missing or unknown hearing status or cognitive assessment were excluded from analysis. DESIGN: Prospective, observational cohort study. MAIN MEASURES: Hearing impairment at 2 weeks post-TBI was based on self-report. Participants who indicated worse hearing in one or both ears were defined as having hearing impairment, whereas those who denied worse hearing in either ear were defined as not having hearing impairment and served as the reference group. Cognitive outcomes at 6 months post-TBI included executive functioning and processing speed, as measured by the Trail Making Test (TMT) B/A and the Wechsler Adult Intelligence Scale, Fourth Edition, Processing Speed Index subscale (WAIS-IV PSI), respectively. RESULTS: TBI-related hearing impairment had a small but significantly greater TMT B/A ratio than without TBI-related hearing impairment: mean difference ( B ) = 0.25; 95% CI, 0.07 to 0.43; P = .005. No significant mean differences on WAIS-IV PSI scores were found between participants with and without TBI-related hearing impairment: B = 0.36; 95% CI, -2.07 to 2.60; P = .825. CONCLUSION: We conclude that TBI-related hearing impairment at 6 months postinjury was significantly associated with worse executive functioning but not cognitive processing speed.

Effectiveness of Smartphone-Based Community Case Management on the Urgent Referral, Reconsultation, and Hospitalization of Children Aged Under 5 Years in Malawi: Cluster-Randomized, Stepped-Wedge Trial.

BACKGROUND: Integrated community case management (CCM) has led to reductions in child mortality in Malawi resulting from illnesses such as malaria, pneumonia, and diarrhea. However, adherence to CCM guidelines is often poor, potentially leading to inappropriate clinical decisions and poor outcomes. We determined the impact of an e-CCM app on the referral, reconsultation, and hospitalization rates of children presenting to village clinics in Malawi. OBJECTIVE: We determined the impact of an electronic version of a smartphone-based CCM (e-CCM) app on the referral, reconsultation, and hospitalization rates of children presenting to village clinics in Malawi. METHODS: We used a stepped-wedge, cluster-randomized trial to compare paper-based CCM (control) with and without the use of an e-CCM app on smartphones from November 2016 to February 2017. A total of 102 village clinics from 2 districts in northern Malawi were assigned to 1 of 6 clusters, which were randomized on the sequencing of the crossover from the control phase to the intervention phase as well as the duration of exposure in each phase. Children aged ≥2 months to <5 years who presented with acute illness were enrolled consecutively by health surveillance assistants. The primary outcome of urgent referrals to higher-level facilities was evaluated by using multilevel mixed effects models. A logistic regression model with the random effects of the cluster and the fixed effects for each step was fitted. The adjustment for potential confounders included baseline factors, such as patient age, sex, and the geographical location of the village clinics. Calendar time was adjusted for in the analysis. RESULTS: A total of 6965 children were recruited-49.11% (3421/6965) in the control phase and 50.88% (3544/6965) in the intervention phase. After adjusting for calendar time, children in the intervention phase were more likely to be urgently referred to a higher-level health facility than children in the control phase (odds ratio [OR] 2.02, 95% CI 1.27-3.23; P=.003). Overall, children in the intervention arm had lower odds of attending a repeat health surveillance assistant consultation (OR 0.45, 95% CI 0.34-0.59; P<.001) or being admitted to a hospital (OR 0.75, 95% CI 0.62-0.90; P=.002), but after adjusting for time, these differences were not significant (P=.07 for consultation; P=.30 for hospital admission). CONCLUSIONS: The addition of e-CCM decision support by using smartphones led to a greater proportion of children being referred to higher-level facilities, with no apparent increase in hospital admissions or repeat consultations in village clinics. Our findings provide support for the implementation of e-CCM tools in Malawi and other low- and middle-income countries with a need for ongoing assessments of effectiveness and integration with national digital health strategies. TRIAL REGISTRATION: ClinicalTrials.gov NCT02763345; https://clinicaltrials.gov/ct2/show/NCT02763345.

Ophthalmic conditions associated with dementia risk: The Cardiovascular Health Study.

INTRODUCTION: Ophthalmic conditions and dementia appear to overlap and may share common pathways, but research has not differentiated dementia subtypes. METHODS: Diagnoses of cataracts, age-related macular degeneration (AMD), diabetic retinopathy (DR), and glaucoma were based on medical histories and International Classification of Diseases, Ninth Revision (ICD-9) codes for 3375 participants from the Cardiovascular Health Study. Dementia, including Alzheimer's disease (AD) and vascular dementia (VaD), was classified using standardized research criteria. RESULTS: Cataracts were associated with AD (hazard ratio [HR] = 1.34; 95% confidence interval [CI] = 1.01-1.80) and VaD/mixed dementia (HR = 1.41; 95% CI = 1.02-1.95). AMD was associated with AD only (HR = 1.87; 95% CI = 1.13-3.09), whereas DR was associated with VaD/mixed dementia only (HR = 2.63; 95% CI = 1.10-6.27). DISCUSSION: Differential associations between specific ophthalmic conditions and dementia subtypes may elucidate pathophysiologic pathways. Lack of association between glaucoma and dementia was most surprising from these analyses.

Dual sensory impairment in older adults and risk of dementia from the GEM Study.

INTRODUCTION: Hearing and vision loss are independently associated with dementia, but the impact of dual sensory impairment (DSI) on dementia risk is not well understood. METHODS: Self-reported measures of hearing and vision were taken from 2051 participants at baseline from the Gingko Evaluation of Memory Study. Dementia status was ascertained using standardized criteria. Cox models were used to estimate risk of dementia associated with number of sensory impairments (none, one, or two). RESULTS: DSI was significantly associated with higher risk of all-cause dementia (hazard ratio [HR] = 1.86; 95% confidence interval [CI] = 1.25-2.76) and Alzheimer's disease (HR = 2.12; 95% CI = 1.34-3.36). Individually only visual impairment was independently associated with an increased risk of all-cause dementia (HR = 1.32; 95% CI = 1.02-1.71). DISCUSSION: Older adults with DSI are at a significantly increased risk for dementia. Further studies are needed to evaluate whether treatments can modify this risk.

Alcohol intake and folate antagonism via CYP2E1 and ALDH1: effects on oral carcinogenesis.

The interaction of folate and alcohol consumption has been shown to have an antagonistic effect on the risk of oral cancer. Studies have demonstrated that increased intake of folate decreases the risk of oral cancer, while greater alcohol consumption has an opposite effect. However, what is poorly understood is the biological interaction of these two dietary factors in relation to carcinogenesis. We hypothesize that cytochrome P450 2E1 (CYP2E1) and the family of aldehyde dehydrogenase 1 (ALDH1) enzymes may play a causal role in the occurrence of oral cancer. Chronic and high alcohol use has been implicated in the induction of CYP2E1, which oxidizes ethanol to acetaldehyde. Acetaldehyde is a known carcinogen. As the first metabolite of ethanol, it has been shown to interfere with DNA methylation, synthesis and repair, as well as bind to protein and DNA to form stable adducts, which lead to the eventual formation of damaged DNA and cell proliferation. Studies using liver cells have demonstrated that S-adenosyl methionine (SAM), which is a product of folate metabolism, regulates the expression and catalytic activity of CYP2E1. Our first hypothesis is that as increased levels of folate lead to higher concentrations of SAM, SAM antagonizes the expression of CYP2E1, which results in decreased conversion of ethanol into acetaldehyde. Thus, the lower levels of acetaldehyde may lower risk of oral cancer. There are also two enzymes within the ALDH1 family that play an important role both in ethanol metabolism and the folate one-carbon pathway. The first, ALDH1A1, converts acetaldehyde into its non-carcinogenic byproduct, acetate, as part of the second step in the ethanol metabolism pathway. The second, ALDH1L1, also known as FDH, is required for DNA nucleotide biosynthesis, and is upregulated at high concentrations of folate. ALDH1L1 appears to be a chief regulator of cellular metabolism as it is strongly downregulated at certain physiological and pathological conditions, while its upregulation can produce drastic antiproliferative effects. ALDH1 has three known response elements that regulate gene expression (NF-Y, C/EBPß, and RARα). Our second hypothesis is that folate interacts with one of these response elements to upregulate ALDH1A1 and ALDH1L1 expression in order to decrease acetaldehyde concentrations and promote DNA stability, thereby decreasing cancer susceptibility. Conducting future metabolic and biochemical human studies in order to understand this biological mechanism will serve to support evidence from epidemiologic studies, and ultimately promote the intake of folate to at-risk populations.