Genetically Confirmed Familial Hypercholesterolemia in Patients With Acute Coronary Syndrome

BACKGROUND: Genetic screening programs in unselected individuals with increased levels of low-density lipoprotein cholesterol (LDL-C) have shown modest results in identifying individuals with familial hypercholesterolemia (FH). OBJECTIVES: This study assessed the prevalence of genetically confirmed FH in patients with acute coronary syndrome (ACS) and compared the diagnostic performance of FH clinical criteria versus FH genetic testing. METHODS: Genetic study of 7 genes (LDLR, APOB, PCSK9, APOE, STAP1, LDLRAP1, and LIPA) associated with FH and 12 common alleles associated with polygenic hypercholesterolemia was performed in 103 patients with ACS, age ≤65 years, and LDL-C levels ≥160 mg/dl. Dutch Lipid Clinic (DLC) and Simon Broome (SB) FH clinical criteria were also applied. RESULTS: The prevalence of genetically confirmed FH was 8.7% (95% confidence interval [CI]: 4.3% to 16.4%; n = 9); 29% (95% CI: 18.5% to 42.1%; n = 18) of patients without FH variants had a score highly suggestive of polygenic hypercholesterolemia. The prevalence of probable to definite FH according to DLC criteria was 27.2% (95% CI: 19.1% to 37.0%; n = 28), whereas SB criteria identified 27.2% of patients (95% CI: 19.1% to 37.0%; n = 28) with possible to definite FH. DLC and SB algorithms failed to diagnose 4 (44%) and 3 (33%) patients with genetically confirmed FH, respectively. Cascade genetic testing in first-degree relatives identified 6 additional individuals with FH. CONCLUSIONS: The prevalence of genetically confirmed FH in patients with ACS age ≤65 years and with LDL-C levels ≥160 mg/dl is high (approximately 9%). FH clinical algorithms do not accurately classify patients with FH. Genetic testing should be advocated in young patients with ACS and high LDL-C levels to allow prompt identification of patients with FH and relatives at risk.This research was supported in part by the Instituto de Salud Carlos III (grants RD012/0042/0066 and CB16/11/00432), Spanish Ministry of Economy and Competitiveness (grant SAF2015-71863-REDT), and Alexion through an Investigator Initiated Research Grant. Grants from the Instituto de Salud Carlos III and the Spanish Ministry of Economy and Competitiveness are supported by the Plan Estatal de I+D+I 2013-2016 European Regional Development Fund (FEDER), "A way of making Europe." The sponsors played no role in the design, collection, analysis, or interpretation of the data or in the decision to submit the manuscript for publication. Drs. Castillo, Lluis-Ganella, and Quintana are employees of Gendiag.exe/Ferrer inCode.S

Genetic factors associated with coronary heart disease and analysis of their predictive capacity

The main expansion of the discovery of genetic variants associated with complex diseases has occurred during the last decade. This expansion has been accompanied, and in some sense motivated, by the desire to use this information to improve the predictive capacity of many diseases with an unidentified familial component, including coronary heart disease (CHD), with the aim of translating this genetic knowledge into clinical practice. This doctoral thesis is structured in two lines of investigation that address distinct aspects of this issue, first to evaluate the possible role of genetic variation in a candidate gene in modulating CHD risk, and second to evaluate whether genetic information can be used to improve risk assessment tools used in clinical practice. In the first research line (described in Part I), we investigate the contribution of genetic variation in one of the most widely-studied genes in cardiovascular genetics, ESR1, which encodes the Oestrogen receptor α protein. We provide a solid meta-analysis of evidence regarding the most widely-studied variant in this gene and we further explore the role of a broad range of common and uncommon variants in this gene in CHD risk. Using these approaches, we find no evidence of association between the genetic variants studied and CHD risk. However, although we can confidently accept that common genetic polymorphisms are not associated with cardiovascular disease, we cannot discard the possibility that other types of variation in this gene (for instance epigenetic variation) could modify susceptibility to cardiovascular disease, or that other elements of this pathway are associated with an increased risk of CHD. In this research I have provided a reliable answer to this long running unanswered question in cardiovascular genetics, allowing research to re-focus on other elements of this system or other pathways. In the second line, we explored the possible utility of genetic information obtained from genome-wide association studies (GWAS) in prediction of 10-year risk of CHD events by adding this information to cardiovascular risk functions. We have followed the recommendations proposed by the American Heart Association for evaluating the utility of novel biomarkers in clinical practice, and have demonstrated that although the magnitudes of the effects of these genetic variants on CHD risk are modest, there is a tendency towards improvement in the capacity of the risk functions to predict future CHD events. The translation of genetic information into clinical practice was one of the main motivations for the investment in genome-wide association studies, and my research represents one of the first efforts to explore this possibility.L’expansió principal pel que fa al descobriment de variants genètiques associades amb malalties complexes s’ha dut a terme durant la última dècada. Aquesta expansió ha estat acompanyada, i d’alguna forma motivada, pel desig d’usar aquesta informació per millorar la capacitat de predicció d’aquelles malalties on hi és present un cert component familiar però en les que no es coneixien les variants que conferien un major risc de patir la malaltia, entre elles la cardiopatia isquèmica (CI). La present tesis doctoral està estructurada en dues línies d’investigació que avaluen el possible rol d’un gen candidat en la susceptibilitat de la CI i també avalua la millora en la capacitat de predicció d’un esdeveniment coronari de les eines usades habitualment en la pràctica clínica mitjançant la inclusió d’informació genètica. Més concretament, la primera línea d’investigació es centra en la contribució de la variació genètica en un dels gens més estudiats en relació amb CI: el gen que codifica pel receptor d’estrogens alfa (ESR1). En aquesta línea hem proveït un sòlid meta-anàlisis entre la variant més àmpliament estudiada d’aquest gen i risc coronari i també hem explorat el paper de la majoria de les variants comunes descrites en aquest gen i risc de CI. Mitjançant cap dels anàlisis hem trobat evidència d’associació entre les variants genètiques en aquest gen i el risc de CI. No obstant això, i encara que podem acceptar que les variants genètiques comunes d’aquest gen no estan associades amb esdeveniments coronaris, no podem descartar que altres tipus de variació en aquest gen (com per exemple variació epigenètica) pugui estar modificant la susceptibilitat a patir un esdeveniment coronari, ni tampoc que altres elements de la mateixa cadena de senyalització estiguin associats amb la malaltia. En la segona línea d’investigació, hem explorat el possible paper de les variants genètiques, obtingudes mitjançant estudis d’associació global del genoma (GWAS), en la millora de la capacitat de predicció a 10 anys dels esdeveniments coronaris, mitjançant la seva addició en les funcions de risc cardiovascular clàssiques. Hem seguit les recomanacions proposades per la American Heart Association per l’avaluació en la pràctica clínica de nous biomarcadors, i hem demostrat que, tot i que la magnitud de l’associació d’aquestes variants és modesta, hi ha una tendència cap a la millora de la capacitat de predicció de les funcions de risc

DNA methylation and obesity traits: An epigenome-wide association study. The REGICOR study

Obesity is associated with increased risk of several diseases and has become epidemic. Obesity is highly heritable but the genetic variants identified by genome-wide association studies explain only limited variability. Epigenetics could contribute to explain the missing variability. The study aim was to discover differential methylation patterns related to obesity. We designed an epigenome-wide association study with a discovery phase in a subsample of 641 REGICOR study participants, validated by analysis of 2,515 participants in the Framingham Offspring Study. Blood DNA methylation was assessed using Illumina HumanMethylation450 BeadChip. Next, we meta-analyzed the data using the fixed effects method and performed a functional and pathway analysis using the Ingenuity Pathway Analysis software. We were able to validate 94 CpGs associated with body mass index (BMI) and 49 CpGs associated with waist circumference, located in 95 loci. In addition, we newly discovered 70 CpGs associated with BMI and 33 CpGs related to waist circumference. These CpGs explained 25.94% and 29.22% of the variability of BMI and waist circumference, respectively, in the REGICOR sample. We also evaluated 65 of the 95 validated loci in the GIANT genome-wide association data; 10 of them had Tag SNPs associated with BMI. The top-ranked diseases and functions identified in the functional and pathway analysis were neurologic, psychological, endocrine, and metabolic

DNA methylation and high-density lipoprotein functionality-brief report: The REGICOR study (Registre Gironi del Cor)

Objective: The function of high-density lipoproteins (HDLs) may better reflect their atheroprotective role, compared with HDL-cholesterol levels. The association between DNA methylation and HDL function has not yet been established. Approach and results: We designed an epigenome-wide association study including 645 individuals from the REGICOR study (Registre Gironi del Cor). We determined DNA methylation from peripheral blood cells using the HumanMethylation450 array. We analyzed HDL functionality by determining HDL cholesterol efflux capacity and HDL inflammatory index. We discovered 3 methylation sites located in HOXA3, PEX5, and PER3 related to cholesterol efflux capacity and 1 located in GABRR1 related to HDL inflammatory index. Using a candidate gene approach, we also found 2 methylation sites located in CMIP related to cholesterol efflux capacity. Conclusions: We identified 6 potential loci associated with HDL functionality in HOXA3, PEX5, PER3, CMIP, and GABRR1. Additional studies are warranted to validate these findings in other populations

Cardiovascular Risk Factors and Ischemic Heart Disease: Is the Confluence of Risk Factors Greater Than the Parts? A Genetic Approach

BACKGROUND: Cardiovascular risk factors tend to aggregate. The biological and predictive value of this aggregation is questioned and genetics could shed light on this debate. Our aims were to reappraise the impact of risk factor confluence on ischemic heart disease (IHD) risk by testing whether genetic risk scores (GRSs) associated with these factors interact on an additive or multiplicative scale, and to determine whether these interactions provide additional value for predicting IHD risk. METHODS AND RESULTS: We selected genetic variants associated with blood pressure, body mass index, waist circumference, triglycerides, type-2 diabetes mellitus, high-density lipoprotein and low-density lipoprotein cholesterol, and IHD to create GRSs for each factor. We tested and meta-analyzed the impact of additive (synergy index) and multiplicative (βinteraction) interactions between each GRS pair in 1 case-control (n=6042) and 4 cohort studies (n=17 794) and evaluated the predictive value of these interactions. We observed 2 multiplicative interactions: GRSLDL·GRSTriglycerides (βinteraction=-0.096; SE=0.028) and nonpleiotropic GRSIHD·GRSLDL (βinteraction=0.091; SE=0.028). Inclusion of these interaction terms did not improve predictive capacity. CONCLUSIONS: The confluence of low-density lipoprotein cholesterol and triglycerides genetic risk load has an additive effect on IHD risk. The interaction between low-density lipoprotein cholesterol and IHD genetic load is more than multiplicative, supporting the hazardous impact on atherosclerosis progression of the combination of inflammation and increased lipid levels. The capacity of risk factor confluence to improve IHD risk prediction is questionable. Further studies in larger samples are warranted to confirm and expand our results.The MIGen Consortium was funded by grant R01 HL087676 (NIH, USA). The Framingham Heart Study is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with Boston University (Contract No. N01-HC-25195). This manuscript was not prepared in collaboration with investigators of the Framingham Heart Study and does not necessarily reflect the opinions or views of the Framingham Heart Study, Boston University, or NHLBI. Funding for SHARe genotyping was provided by NHLBI Contract N02-HL-6427

Identification of a new locus and validation of previously reported loci showing differential methylation associated with smoking. The REGICOR study.

Smoking increases the risk of many diseases and could act through changes in DNA methylation patterns. The aims of this study were to determine the association between smoking and DNA methylation throughout the genome at cytosine-phosphate-guanine (CpG) site level and genomic regions. A discovery cross-sectional epigenome-wide association study nested in the follow-up of the REGICOR cohort was designed and included 645 individuals. Blood DNA methylation was assessed using the Illumina HumanMethylation450 BeadChip. Smoking status was self-reported using a standardized questionnaire. We identified 66 differentially methylated CpG sites associated with smoking, located in 38 genes. In most of these CpG sites, we observed a trend among those quitting smoking to recover methylation levels typical of never smokers. A CpG site located in a novel smoking-associated gene (cg06394460 in LNX2) was hypomethylated in current smokers. Moreover, we validated two previously reported CpG sites (cg05886626 in THBS1, and cg24838345 in MTSS1) for their potential relation to atherosclerosis and cancer diseases, using several different approaches: CpG site methylation, gene expression, and plasma protein level determinations. Smoking was also associated with higher THBS1 gene expression but with lower levels of thrombospondin-1 in plasma. Finally, we identified differential methylation regions in 13 genes and in four non-coding RNAs. In summary, this study replicated previous findings and identified and validated a new CpG site located in LNX2 associated with smoking.This work was supported by the following sources: Agència de Gestió Ajuts 464 Universitaris de Recerca (2014 SGR 240); the Spanish Ministry of Economy through 465 the Carlos III Health Institute (ISCIII-FIS-FEDER-ERDF PI11-01801, PI08-1327, PI05-466 1251, PI05-1297, PI02-0471, FIS99/0013-01, FIS96/0026-01, FIS93/0568, 467 FIS92/0009-05), and the Red de Investigación Cardiovascular (RD12/0042/0061, 468 RD12/0042/0013). The BAsicMAR study was funded by the Spanish Ministry of 469 Economy through the Carlos III Health Institute (ISCIII-FIS-FEDER-ERDF) PI12/01238 470 and RecerCaixa JJ086116. Sergi Sayols-Baixeras was funded by a contract from 471 Instituto de Salud Carlos III FEDER (IFI14/00007)

Cardiovascular Risk Factors and Ischemic Heart Disease: Is the Confluence of Risk Factors Greater Than the Parts? A Genetic Approach.

BACKGROUND: Cardiovascular risk factors tend to aggregate. The biological and predictive value of this aggregation is questioned and genetics could shed light on this debate. Our aims were to reappraise the impact of risk factor confluence on ischemic heart disease (IHD) risk by testing whether genetic risk scores (GRSs) associated with these factors interact on an additive or multiplicative scale, and to determine whether these interactions provide additional value for predicting IHD risk. METHODS AND RESULTS: We selected genetic variants associated with blood pressure, body mass index, waist circumference, triglycerides, type-2 diabetes mellitus, high-density lipoprotein and low-density lipoprotein cholesterol, and IHD to create GRSs for each factor. We tested and meta-analyzed the impact of additive (synergy index) and multiplicative (βinteraction) interactions between each GRS pair in 1 case-control (n=6042) and 4 cohort studies (n=17 794) and evaluated the predictive value of these interactions. We observed 2 multiplicative interactions: GRSLDL·GRSTriglycerides (βinteraction=-0.096; SE=0.028) and nonpleiotropic GRSIHD·GRSLDL (βinteraction=0.091; SE=0.028). Inclusion of these interaction terms did not improve predictive capacity. CONCLUSIONS: The confluence of low-density lipoprotein cholesterol and triglycerides genetic risk load has an additive effect on IHD risk. The interaction between low-density lipoprotein cholesterol and IHD genetic load is more than multiplicative, supporting the hazardous impact on atherosclerosis progression of the combination of inflammation and increased lipid levels. The capacity of risk factor confluence to improve IHD risk prediction is questionable. Further studies in larger samples are warranted to confirm and expand our results.The MIGen Consortium was funded by grant R01 HL087676 (NIH, USA). The Framingham Heart Study is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with Boston University (Contract No. N01-HC-25195). This manuscript was not prepared in collaboration with investigators of the Framingham Heart Study and does not necessarily reflect the opinions or views of the Framingham Heart Study, Boston University, or NHLBI. Funding for SHARe genotyping was provided by NHLBI Contract N02-HL-6427

Identification and validation of seven new loci showing differential DNA methylation related to serum lipid profile: an epigenome-wide approach. The REGICOR study.

Lipid traits (total, low-densityand high-density lipoproteincholesterol, and triglycerides) are risk factors for cardiovascular disease. DNA methylation is an inherited but also modifiable epigenetic mark that has been related tocardiovascular risk factors. Our aim was to identify loci showing differential DNA methylation related to serum lipid levels. Blood DNA methylation was assessed using the Illumina HumanMethylation450 BeadChip. Atwo-stage epigenome-wide association study was performed, with a discovery sample intheREGICOR study (n=645)and validation in the Framingham Offspring Study (n=2,542).FourteenCpG sites located in 9 genes (SREBF1, SREBF2, PHOSPHO1, SYNGAP1, ABCG1, CPT1A, MYLIP, TXNIP andSLC7A11) and 2 intergenic regions showeddifferential methylation in association with lipid traits. Six of these genes and 1 intergenic region were new discoveries showing differential methylation relatedto total cholesterol (SREBF2), HDL-cholesterol (PHOSPHO1, SYNGAP1 and an intergenic region in chromosome 2) and triglycerides (MYLIP, TXNIP andSLC7A11).These CpGs explained0.7%, 9.5% and18.9% of the variability of total cholesterol, HDL cholesterol and triglycerides in the Framingham Offspring Study, respectively. The expression of the genesSREBF2and SREBF1was inversely associated with methylation of their corresponding CpGs(p-value=0.0042 and 0.0045, respectively) in participants of the GOLDN study(n=98). In turn, SREBF1expression wasdirectly associated with HDL cholesterol(p-value=0.0429). Genetic variants in SREBF1, PHOSPHO1, ABCG1and CPT1Awerealso associated with lipid profile. Further research is warranted to functionally validatethesenew loci and assess the causality ofnew and established associationsbetween these differentially methylated lociand lipid metabolism.This work was supported by the following sources: Agència de Gestio Ajuts Universitaris de Recerca [2014 SGR 240]; the Spanish Ministry of Economy through the Carlos III Health Institute [ISCIII-FIS-FEDER-ERDF PI12-00232, PI12-01238, PI11-01801, PI08-1327, PI05-1251, PI05-1297, PI02-0471, FIS99/0013-01, FIS96/0026-01, FIS93/0568, FIS92/0009-05], and the Red de Investigacion Cardiovascular [RD12/0042/0013, RD12/0042/0020, RD12/0042/0055, RD12/0042/0061]. S.S-B. was funded by a contract from Instituto de Salud Carlos III FEDER [IFI14/00007] and Daniel Bravo Andreu Private Foundation. GOLDN: The GOLDN study (AND, DA, JO, SA, DKA) was funded by the US National Institute of Health (NIH)/National Heart, Lung and Blood Institutes (http://www.nhlbi.nih.gov) grants R01HL104135 and U01HL72524

Identification of a new locus and validation of previously reported loci showing differential methylation associated with smoking. The REGICOR study.

Smoking increases the risk of many diseases and could act through changes in DNA methylation patterns. The aims of this study were to determine the association between smoking and DNA methylation throughout the genome at cytosine-phosphate-guanine (CpG) site level and genomic regions. A discovery cross-sectional epigenome-wide association study nested in the follow-up of the REGICOR cohort was designed and included 645 individuals. Blood DNA methylation was assessed using the Illumina HumanMethylation450 BeadChip. Smoking status was self-reported using a standardized questionnaire. We identified 66 differentially methylated CpG sites associated with smoking, located in 38 genes. In most of these CpG sites, we observed a trend among those quitting smoking to recover methylation levels typical of never smokers. A CpG site located in a novel smoking-associated gene (cg06394460 in LNX2) was hypomethylated in current smokers. Moreover, we validated two previously reported CpG sites (cg05886626 in THBS1, and cg24838345 in MTSS1) for their potential relation to atherosclerosis and cancer diseases, using several different approaches: CpG site methylation, gene expression, and plasma protein level determinations. Smoking was also associated with higher THBS1 gene expression but with lower levels of thrombospondin-1 in plasma. Finally, we identified differential methylation regions in 13 genes and in four non-coding RNAs. In summary, this study replicated previous findings and identified and validated a new CpG site located in LNX2 associated with smoking.This work was supported by the following sources: Agència de Gestió Ajuts 464 Universitaris de Recerca (2014 SGR 240); the Spanish Ministry of Economy through 465 the Carlos III Health Institute (ISCIII-FIS-FEDER-ERDF PI11-01801, PI08-1327, PI05-466 1251, PI05-1297, PI02-0471, FIS99/0013-01, FIS96/0026-01, FIS93/0568, 467 FIS92/0009-05), and the Red de Investigación Cardiovascular (RD12/0042/0061, 468 RD12/0042/0013). The BAsicMAR study was funded by the Spanish Ministry of 469 Economy through the Carlos III Health Institute (ISCIII-FIS-FEDER-ERDF) PI12/01238 470 and RecerCaixa JJ086116. Sergi Sayols-Baixeras was funded by a contract from 471 Instituto de Salud Carlos III FEDER (IFI14/00007)