OBJECTIVES/GOALS: Metabolic syndrome (MetS), defined as a cluster of cardiometabolic disease risk factors, is seldom coded using the ICD-10 system in electronic medical records (EMR). The goal of this study was to use EMR to construct MetS with a digital phenotype to amplify the pool of patients available to assess risk for neurocognitive disease in this population. METHODS/STUDY POPULATION: A digital phenotype using the EMR platform TriNetX (n=38 million patients between age 50 and 80) was created by clustering codes for the individual components of MetS (insulin resistance, hypertension, dyslipidemia, and central adiposity). The research network database on TriNetX was utilized to elucidate risk ratios for neurocognitive decline, Alzheimer’s disease and related dementias (ADRDs), and cerebrovascular disease between a preclinical sample of older adults with and without MetS. Propensity score matching was used to match cohorts on demographic variables, medication use, and relevant comorbidities. Risk ratios (RR) and confidence intervals (95% CI) were presented for all outcomes. RESULTS/ANTICIPATED RESULTS: The digital phenotype for MetS expanded the sample from 29,830 to 274,703, a 10-fold increase. Sensitivity to the standard MetS ICD-10 code was 95.1%, showing strong agreement between coding schema. Older adults with MetS had higher risk of cognitive decline (RR: 1.30, 95% CI: 1.15–1.48, p <0.001), ADRDs (RR: 1.48, 95% CI: 1.25–1.75, p <0.001), and cerebrovascular issues (RR: 1.62, 95% CI: 1.55–1.70, p <0.001) when controlling for demographics, medication, and comorbidities. MetS individuals with cerebrovascular dysfunction had even greater risks for neurocognitive decline (RR: 1.70, 95% CI: 1.38–2.08, p < 0.001) and ADRDs (RR: 2.09, 95% CI: 1.56–2.80, p < 0.001) than those with only MetS. DISCUSSION/SIGNIFICANCE: Implementing a digital MetS phenotype in EMR effectively increased sample size and power for analyses. Older adults with MetS have higher risk for neurocognitive decline, especially among those with cerebrovascular dysfunction, highlighting a critical intervention window prior to overt cardiometabolic disease.