medRxiv : the preprint server for health sciences · 2026
APOB to estimated APOB ratio for screening for the APOE2 genotype.
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Auger C, Sampson M, Zubiran R, Cole J, Wolska A, Otvos J, Sniderman A, Remaley A T
Аннотация
BACKGROUND: Familial dysbetalipoproteinemia (FDB) is a genetic lipoprotein disorder that can develop in patients homozygous for the APOE2 genotype (ε2/ε2). It is associated with decreased clearance of remnant lipoproteins and increased atherosclerotic cardiovascular disease (ASCVD) risk disproportionate to their level of LDL-C. A goal of this study was to develop a screening test for the ε2/ε2 genotype based on routinely available lipid tests and to determine those at most risk for ASCVD.
METHODS: After assembly of a primary prevention cohort from the UK Biobank (n= 269,895), gene array and exome data was utilized to classify patients as being ε2/ε2 genotype positive or negative. Lipid profiles and APOB levels were extracted and the number of ASCVD events was tabulated during a 15-year follow-up period.
RESULTS: Using a newly developed equation for estimating APOB (eAPOB) with lipid panel test results, the ratio of measured APOB to eAPOB was better than any other individual lipid test or ratio for identifying patients with the ε2/ε2 genotype (AUC: APOB/eAPOB: 0.990 (0.986-0.994), nonHDL-C/APOB: 0.961 (0.952-0.970), APOB: 0.955 (0.949-0.961), VLDL/TG: 0.788 (0.771-0.804)). The majority of ε2/ε2 patients could be identified with the APOB/eAPOB ratio even before they expressed the FDB phenotype with elevated TG and nonHDL-C. The PCE or PREVENT risk equations were the most accurate method for identifying higher risk patients (AUC: PREVENT: 0.690 (0.637-0.742), PCE: 0.697 (0.645-0.749)).
CONCLUSION: The APOB/eAPOB ratio can be used to accurately identify the ε2/ε2 genotype and conventional risk equations are the best method for determining those at risk for ASCVD.
METHODS: After assembly of a primary prevention cohort from the UK Biobank (n= 269,895), gene array and exome data was utilized to classify patients as being ε2/ε2 genotype positive or negative. Lipid profiles and APOB levels were extracted and the number of ASCVD events was tabulated during a 15-year follow-up period.
RESULTS: Using a newly developed equation for estimating APOB (eAPOB) with lipid panel test results, the ratio of measured APOB to eAPOB was better than any other individual lipid test or ratio for identifying patients with the ε2/ε2 genotype (AUC: APOB/eAPOB: 0.990 (0.986-0.994), nonHDL-C/APOB: 0.961 (0.952-0.970), APOB: 0.955 (0.949-0.961), VLDL/TG: 0.788 (0.771-0.804)). The majority of ε2/ε2 patients could be identified with the APOB/eAPOB ratio even before they expressed the FDB phenotype with elevated TG and nonHDL-C. The PCE or PREVENT risk equations were the most accurate method for identifying higher risk patients (AUC: PREVENT: 0.690 (0.637-0.742), PCE: 0.697 (0.645-0.749)).
CONCLUSION: The APOB/eAPOB ratio can be used to accurately identify the ε2/ε2 genotype and conventional risk equations are the best method for determining those at risk for ASCVD.