Martin Bird, Antoine Rimbert, Alan M Pittman, Steve E Humphries, Marta Futema
{"title":"LPA 变异与家族性高胆固醇血症有关:10 万基因组计划的全基因组测序分析。","authors":"Martin Bird, Antoine Rimbert, Alan M Pittman, Steve E Humphries, Marta Futema","doi":"10.1093/eurjpc/zwae371","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Familial Hypercholesterolaemia (FH) is an inherited disease of high LDL-cholesterol (LDL-C) caused by defects in LDLR, APOB, APOE and PCSK9 genes. A pathogenic variant cannot be found in ∼60% of clinical FH patients. Using whole genome sequencing (WGS) we examined genetic determinants of FH.</p><p><strong>Methods: </strong>WGS data generated by the 100,000 Genomes Project (100KGP) included 536 FH patients diagnosed using the FH Simon Broome criteria. Rare variants in known FH genes were analysed. Genome-wide association study (GWAS) between 443 FH variant-negative unrelated FH cases and 77,275 control participants of the 100KGP was run using high coverage WGS data. Polygenic risk scores for LDL-C (LDL PRS) and lipoprotein(a) (Lp(a) PRS) were computed.</p><p><strong>Results: </strong>An FH-causing variant was found in 17.4% of FH cases. GWAS identified the LPA gene locus being significantly associated (p<1x10-8). FH variant-negative participants had higher LDL and Lp(a) PRSs in comparison to the controls (p<1.0×10-16 and p<4.09×10-6, respectively). Similar associations were found in the monogenic FH with both LDL and Lp(a) PRSs being higher than in controls (p<4.03×10-4 and p<3.01x10-3, respectively). High LDL PRS was observed in 36.4% of FH variant-negative cases, whereas high Lp(a) PRS in 18.5%, with 7.0% having both high LDL and Lp(a) PRSs.</p><p><strong>Conclusions: </strong>This genome-wide analysis of monogenic and polygenic FH causes confirms a complex and heterogenous architecture of hypercholesterolaemia, with the LPA gene playing a significant role. Both Lp(a) and LDL-C should be measured for precision FH diagnosis. Specific therapies to lower Lp(a) should be targeted to those who will benefit most.</p>","PeriodicalId":12051,"journal":{"name":"European journal of preventive cardiology","volume":" ","pages":""},"PeriodicalIF":8.4000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Variants in LPA are associated with Familial Hypercholesterolaemia: whole genome sequencing analysis in the 100,000 Genomes Project.\",\"authors\":\"Martin Bird, Antoine Rimbert, Alan M Pittman, Steve E Humphries, Marta Futema\",\"doi\":\"10.1093/eurjpc/zwae371\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Familial Hypercholesterolaemia (FH) is an inherited disease of high LDL-cholesterol (LDL-C) caused by defects in LDLR, APOB, APOE and PCSK9 genes. A pathogenic variant cannot be found in ∼60% of clinical FH patients. Using whole genome sequencing (WGS) we examined genetic determinants of FH.</p><p><strong>Methods: </strong>WGS data generated by the 100,000 Genomes Project (100KGP) included 536 FH patients diagnosed using the FH Simon Broome criteria. Rare variants in known FH genes were analysed. Genome-wide association study (GWAS) between 443 FH variant-negative unrelated FH cases and 77,275 control participants of the 100KGP was run using high coverage WGS data. Polygenic risk scores for LDL-C (LDL PRS) and lipoprotein(a) (Lp(a) PRS) were computed.</p><p><strong>Results: </strong>An FH-causing variant was found in 17.4% of FH cases. GWAS identified the LPA gene locus being significantly associated (p<1x10-8). FH variant-negative participants had higher LDL and Lp(a) PRSs in comparison to the controls (p<1.0×10-16 and p<4.09×10-6, respectively). Similar associations were found in the monogenic FH with both LDL and Lp(a) PRSs being higher than in controls (p<4.03×10-4 and p<3.01x10-3, respectively). High LDL PRS was observed in 36.4% of FH variant-negative cases, whereas high Lp(a) PRS in 18.5%, with 7.0% having both high LDL and Lp(a) PRSs.</p><p><strong>Conclusions: </strong>This genome-wide analysis of monogenic and polygenic FH causes confirms a complex and heterogenous architecture of hypercholesterolaemia, with the LPA gene playing a significant role. Both Lp(a) and LDL-C should be measured for precision FH diagnosis. Specific therapies to lower Lp(a) should be targeted to those who will benefit most.</p>\",\"PeriodicalId\":12051,\"journal\":{\"name\":\"European journal of preventive cardiology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":8.4000,\"publicationDate\":\"2024-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European journal of preventive cardiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/eurjpc/zwae371\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European journal of preventive cardiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/eurjpc/zwae371","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Variants in LPA are associated with Familial Hypercholesterolaemia: whole genome sequencing analysis in the 100,000 Genomes Project.
Background: Familial Hypercholesterolaemia (FH) is an inherited disease of high LDL-cholesterol (LDL-C) caused by defects in LDLR, APOB, APOE and PCSK9 genes. A pathogenic variant cannot be found in ∼60% of clinical FH patients. Using whole genome sequencing (WGS) we examined genetic determinants of FH.
Methods: WGS data generated by the 100,000 Genomes Project (100KGP) included 536 FH patients diagnosed using the FH Simon Broome criteria. Rare variants in known FH genes were analysed. Genome-wide association study (GWAS) between 443 FH variant-negative unrelated FH cases and 77,275 control participants of the 100KGP was run using high coverage WGS data. Polygenic risk scores for LDL-C (LDL PRS) and lipoprotein(a) (Lp(a) PRS) were computed.
Results: An FH-causing variant was found in 17.4% of FH cases. GWAS identified the LPA gene locus being significantly associated (p<1x10-8). FH variant-negative participants had higher LDL and Lp(a) PRSs in comparison to the controls (p<1.0×10-16 and p<4.09×10-6, respectively). Similar associations were found in the monogenic FH with both LDL and Lp(a) PRSs being higher than in controls (p<4.03×10-4 and p<3.01x10-3, respectively). High LDL PRS was observed in 36.4% of FH variant-negative cases, whereas high Lp(a) PRS in 18.5%, with 7.0% having both high LDL and Lp(a) PRSs.
Conclusions: This genome-wide analysis of monogenic and polygenic FH causes confirms a complex and heterogenous architecture of hypercholesterolaemia, with the LPA gene playing a significant role. Both Lp(a) and LDL-C should be measured for precision FH diagnosis. Specific therapies to lower Lp(a) should be targeted to those who will benefit most.
期刊介绍:
European Journal of Preventive Cardiology (EJPC) is an official journal of the European Society of Cardiology (ESC) and the European Association of Preventive Cardiology (EAPC). The journal covers a wide range of scientific, clinical, and public health disciplines related to cardiovascular disease prevention, risk factor management, cardiovascular rehabilitation, population science and public health, and exercise physiology. The categories covered by the journal include classical risk factors and treatment, lifestyle risk factors, non-modifiable cardiovascular risk factors, cardiovascular conditions, concomitant pathological conditions, sport cardiology, diagnostic tests, care settings, epidemiology, pharmacology and pharmacotherapy, machine learning, and artificial intelligence.