A-240 Derivation of Lp(a) contribution to ApoB in Singapore

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Abstract Background ApoB levels have been shown to be better predictors than LDL cholesterol to assess cardiovascular risk. Elevated ApoB levels are associated with an increased risk of cardiovascular disease as it indicates the presence of a higher number of atherogenic particles. Lp(a), a variant of LDL, has an additional apolipoprotein(a) attached to ApoB. Lp(a) is considered an independent risk factor for cardiovascular disease and is more atherogenic than LDL on a per particle basis. As recommended by the 2021 AHA scientific statement, percent of ApoB that is Lp(a) (Lp(a)-ApoB) can be calculated. This preliminary study aims to ascertain the proportion of ApoB that is contributed by Lp(a) across varying levels of Lp(a). Methods We conducted a retrospective analysis of consecutive paired Lp(a) and ApoB results extracted from our LIS between May–Oct 2024. Lp(a)-ApoB was calculated using the formula: [Lp(a)(nmol/L) / ApoB(nmol/L)]*100 where ApoB: 1g/L=20nmol/L [AHA 2021]. Participants were stratified into three groups based on Lp(a) levels, group A Lp(a) <75 nmol/L (normal), group B: Lp(a) 75-125 nmol/L (intermediate), and group C: Lp(a) >125 nmol/L (abnormal) according to the ESC consensus statement. Descriptive statistics were analyzed for each group using MedCalc Statistical Software v23.1.2 (MedCalc Software Ltd, Ostend, Belgium). Lp(a) was measured using the LPA2, tina-quant lipoprotein(a) Gen2 on the Roche c502 instrument (41 CAP subscribers) and ApoB was measured using the APOBT v2 on the Roche c502 instrument (109 CAP subscribers). Our performance in the CAP surveys for Lp(a) and ApoB are satisfactory. LPA2 (standardized against IFCC SRM2B for nmol/L) and APOBT (standardized against IFCC SP3-07) are measured by immunoturbidimetry. Lp(a) precision: 2.39–3.64% @8.95mmol/L and 0.65–2.13% @23.37mmol/L. ApoB precision: 1.36–2.35% @0.53g/L and1.07–1.55% @1.24g/L. Analytical measuring range for LPA2 and APOBT were 7.0–240mmol/L and 0.2–4.0g/L, respectively. Results Results are summarized in Table 1. Of all the results, 82.6% of results were in the Lp(a) <75nmol/L group, 7.7% of results were in the Lp(a) 75–125nmol/L group and 9.7% of results were in the Lp(a) >125nmol/L group. Overall medians were Lp(a)=22.5nmol/L [95%CI 21.08–24.70], ApoB=0.91g/L [95%CI 0.90–0.92], Lp(a)-ApoB=1.2% [95%CI 1.15– 1.31]. ApoB median was similar across groups stratified by Lp(a) where the 95%CI of the medians overlapped. Lp(a)-ApoB increased with Lp(a), with medians of 1.0%, 5.2% and 9.5% for groups A, B and C, respectively. Linear regression (overall): Lp(a)-ApoB=0.094+0.053Lp(a), r=0.96 (95%CI 0.955–0.963). Linear regression (group A): Lp(a)-ApoB=0.013+0.056Lp(a), r=0.93 (95%CI 0.921–0.937). Linear regression (group B): Lp(a)-ApoB=-0.433+0.060Lp(a), r=0.64 (95%CI 0.509–0.737). Linear regression (group C): Lp(a)-ApoB =1.320+0.046Lp(a), r=0.70 (95%CI 0.599–0.775). The 95th, 97.5th and 99th percentiles of Lp(a)-ApoB were 9.4% (95%CI 8.90–10.04), 10.8% (95%CI 10.33–12.28) and 13.7% (95%CI 12.60–15.80), respectively. Conclusion In our population, the 95th percentile of Lp(a)-ApoB was 9.4%. Lp(a) contribution to ApoB increases stepwise with Lp(a) concentration. At Lp(a)<75nmol/L, this increase is linear. Larger datasets for Lp(a) >75nmol/L are needed to provide more insight.

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