Rare genetic variants in LDLR, APOB and PCSK9 are known causes of familial hypercholesterolaemia and it is expected that rare variants in other genes will also have effects on hyperlipidaemia risk although such genes remain to be identified. The UK Biobank consists of a sample of 500,000 volunteers and exome sequence data is available for 50,000 of them. 11,490 of these were classified as hyperlipidaemia cases on the basis of having a relevant diagnosis recorded and/or taking lipid-lowering medication while the remaining 38,463 were treated as controls. Variants in each gene were assigned weights according to rarity and predicted impact and overall weighted burden scores were compared between cases and controls, including population principal components as covariates. One biologically plausible gene, HUWE1, produced statistically significant evidence for association after correction for testing 22,028 genes with a signed log10 p value (SLP) of −6.15, suggesting a protective effect of variants in this gene. Other genes with uncorrected p < .001 are arguably also of interest, including LDLR (SLP = 3.67), RBP2 (SLP = 3.14), NPFFR1 (SLP = 3.02) and ACOT9 (SLP = -3.19). Gene set analysis indicated that rare variants in genes involved in metabolism and energy can influence hyperlipidaemia risk. Overall, the results provide some leads which might be followed up with functional studies and which could be tested in additional data sets as these become available. This research has been conducted using the UK Biobank Resource.

LDLR，APOB和PCSK9中的罕见遗传变异已知是家族性高胆固醇血症的病因，预计其他基因中的罕见变体也将对高血脂症风险产生影响，尽管此类基因仍有待确定。UK Biobank由500,000名志愿者组成的样本组成，其中50,000名志愿者可获得外显子组序列数据。根据记录的相关诊断和/或服用降脂药，将其中的11490例归为高脂血症病例，其余38463例作为对照。根据稀有性为每个基因的变体分配权重，并比较预期的影响，并比较病例与对照之间的总体加权负担得分，包括群体主成分作为协变量。一个生物学上可行的基因HUWE1在校正测试22,028个基因的对数log10 p值（SLP）为-6.15的基因后，该蛋白产生了具有统计学意义的关联证据，表明该基因中的变体具有保护作用。其他未经校正的p  <.001的基因也可以引起人们的兴趣，包括LDLR（SLP = 3.67），RBP2（SLP = 3.14），NPFFR1（SLP = 3.02）和ACOT9（SLP = -3.19）。基因集分析表明，参与代谢和能量代谢的基因中的罕见变异会影响高脂血症的风险。总体而言，结果提供了一些线索，可以进行功能研究，并在可用时在其他数据集中进行测试。这项研究是使用UK Biobank资源进行的。