Background: Lipid disturbance is a hallmark of cardiometabolic abnormalities and a primary contributor to cardiovascular disease risk. Immunometabolic markers show promise for better risk classification. This study evaluated the uric acid to Platelet ratio (UAPR) as lipid abnormality marker in a broad cohort of Saudi adults. Methods: Data from 7781 adults in the Elta Medical Laboratory database were analysed. Subjects were stratified by lipid status, and UAPR levels were analyzed. Additionally, lipid abnormality distribution across UAPR tertiles and risk profiles, including ROC analysis, were evaluated. Results: UAPR were markedly increased in patients with abnormal lipid profiles while high UAPR (H-UAPR) subjects showed multiple dyslipidemic patterns including elevated levels of triglycerides (TG), low-density lipoprotein (LDL-C), non-high-density lipoprotein (non-HDL-C), and remnant cholesterol (RC), alongside reduced HDL-C levels. Notably, UAPR correlated with all lipid parameters, most strongly and inversely with HDL-C (r = −0.314) and remained independently associated with TG and HDL-C in multivariable regression. Consistently, H-UAPR was common across all dyslipidemic forms, especially low HDL-C, nearly twice as frequent as in N-UAPR (52.4% vs. 35.0%). The odds were specifically increased for low HDL-C (OR = 2.02, p < 0.0001) and a high TC/HDL-C ratio (OR = 2.94, p < 0.0001) in H-UAPR patients. ROC analysis demonstrated that UAPR had moderate yet significant diagnostic performance, particularly for identifying high TC/HDL-C (AUC = 0.671, p < 0.001) and HDL-C (AUC = 0.618, p < 0.001). Conclusions: UAPR shows considerable promise as an immunometabolic marker linked to various dyslipidemic forms with potential for hyperlipidemia screening and stratification, warranting further validation.

Background: The BMI–albumin–neutrophil-to-lymphocyte (BAN) score integrates adiposity, nutritional status, and systemic inflammation, but its role in detecting early cardiometabolic changes remains unclear. This study examined associations of the BAN score with vascular, glycemic, and lipid markers in non-diabetic adults. Methods: This retrospective cross-sectional study included 162 non-diabetic subjects. Associations between the BAN score and vascular, glycemic, and lipid parameters were examined using Spearman’s correlation, ROC analysis, and regression models adjusted for age, sex, smoking status, and medication use. Results: Patients had a median age of 37 years, 72.8% were female, with median BMI 33 kg/m², albumin 4.4 g/dL, and NLR 1.3. Higher BAN scores correlated with systolic blood pressure (SBP) (r = 0.23, p < 0.01), pulse pressure (PP) (r = 0.26, p < 0.001), and HbA1c (r = 0.22, p < 0.01). Compared with the lowest tertile, higher BAN tertiles showed significantly elevated SBP, PP, and HbA1c (p < 0.01). In adjusted models, each one-unit increase in BAN score was associated with higher SBP (β = 1.01, p = 0.037), PP (β = 0.66, p = 0.006), and HbA1c (β = 1.85, p = 0.008). No associations were found with the atherogenic index of plasma (AIP), Castelli risk index I (CRI-I), or Castelli risk index II (CRI-II). ROC analysis showed moderate discriminative ability for hypertension (AUC = 0.66) and HbA1c (AUC = 0.65). Conclusions: The BAN score is associated with a distinctive early cardiometabolic risk, particularly elevated SBP, widened PP, and early glycemic alterations. Further research should define the BAN score’s mechanisms and preventive utility.