Population-Based Cholesterol Screening as a Primordial Prevention Strategy—Breaking the Cycle of Adverse Lipid Levels That Runs in Families and Tracks Through Life

Abstract

Sustar and colleagues 1 assessed the body mass index standard deviation score (BMI SDS), overweight and obesity, and cholesterol levels in a large cohort of prepubertal children from 2 independent populations (n = 12 111 German, n = 3535 Slovenian). In summary, they found a weak but positive correlation between low-density lipoprotein cholesterol (LDL-C) or total cholesterol (TC) levels and BMI SDS (R = 0.037, P < .001; and R = 0.052, P = .002). In a secondary analysis stratifying children by their BMI SDS, they found significant differences between some BMI groups in the German cohort (based on LDL-C values), but none in the Slovenian cohort (based on TC values). The authors conclude that LDL-C, but not TC, is associated with higher BMI SDS or with severe obesity at the population level, but is clinically unimportant at the individual level. This finding, they claim, suggests that genes rather than environment are associated with cholesterol levels in prepubertal children, thus making this an optimal time for a populationwide screening for familial hypercholesterolemia (FH) and other inherited dyslipidemias.The work by Sustar and colleagues 1 provides us with important support for considering a lipid screening program among the general population. We believe that a cholesterol screening program should be based on LDL-C; LDL-C is a more specific measure compared with TC, which is also affected by the level of high-density lipoprotein cholesterol, likely to be biased in populations with obesity and diabetes.Moreover, we agree with Sustar and colleagues 1 that screening for FH at younger ages rather than later in life will likely minimize the number of false-positive findings, for several reasons. First, cholesterol levels in the population tend to increase with age, potentially flagging more people for genetic testing, including individuals without FH. Also, genes likely explain more of the variation in cholesterol levels in younger individuals, compared with later in life. For example, in the Cardiovascular Risk in Young Finns study, for all lipid traits, the variance explained by known genes decreased from early childhood (12%-27% at age 3-6 years) to approximately age 20 years, at which time the variance explained stabilized by approximately 10%. 2 However, an early-life population-wide screening using LDL-C levels as a biomarker would not only detect children with FH-that is, those with a monogenic FH-causing variant-but also children with a high polygenic risk for elevated LDL-C levels 3 and children living in an LDL-C level-increasing environment independently of genetic risk. We know from the Cardiovascular Risk in Young Finns study that lipid levels track through life, meaning that children with high LDL-C levels are more likely to become adults with high LDL-C levels. 4 We also know that there is a correlation between maternal and offspring lipid levels, [5][6][7] meaning that children with high LDL-C levels are more likely to have parents with high LDL-C levels. Therefore, we believe that within any popu...