Objectives/Goals: This review examined if sleep duration is associated with established Alzheimer’s disease (AD) fluid biomarkers, such as amyloid-β peptides (Aβ40 and Aβ42), total-tau (t-tau), phosphorylated tau (p-tau181 and p-tau217), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP). Methods/Study Population: We searched PubMed, CINAHL, and SCOPUS through September 15, 2024, using keywords and appropriate subject headings related to AD, fluid biomarkers, and sleep. The search was developed and conducted in collaboration with a medical librarian. We also searched Google Scholar and screened the reference lists of relevant reviews. Two independent reviewers screened 1,657 peer-reviewed articles, of which 21 met the inclusion criteria (14 with biomarkers measured in cerebrospinal fluid [CSF] and 7 in blood). Two review authors independently extracted study details from included articles using a standardized data extraction template. Results/Anticipated Results: Sample sizes ranged from 18 to 4,712 participants. Sleep duration was assessed using self-reported measures in 8 studies and objective measures in 13. For the 14 studies using CSF biomarkers, lower Aβ42 (3/14), Aβ40 (1/14), or the ratio (1/14) were associated with either short or long sleep duration; t-tau (3/14) and p-tau181 (4/14) levels were mostly associated with short sleep. For the 7 blood-based biomarker studies, Aβ42 (2/7), Aβ40 (2/7), and the ratio (3/7) had mixed results with either short or long sleep. T-tau (1/7) and p-tau181 (1/7) levels were associated with long sleep; NfL (2/7) was associated with both short and long sleep. Six studies reported nonlinear relationships, with both short and long sleep associated with unfavorable biomarker profiles. None of the studies investigated p-tau 217 or GFAP. Discussion/Significance of Impact: Our results suggest that the relationship between sleep duration and AD fluid biomarkers is very complex, and it highlights the importance of sleep in AD risk assessment and prevention. The inconsistency in findings stresses the need for standardized study design and measurement methods to clarify causality and inform clinical guidelines.