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A decade of progress on the genetic basis of coronary artery disease. Practical insights for the internist

Published:April 07, 2017DOI:https://doi.org/10.1016/j.ejim.2017.03.019

      Highlights

      • CAD is a complex disease due to an interplay between genetic and lifestyle factors.
      • The genetic basis of CAD has been elusive until a decade ago.
      • GWAS detected >60 common variants associated with CAD risk.
      • Genomic techniques have provided useful insights into CAD pathophysiology.
      • Rare protective mutations paved the way to the development of new biologic drugs.

      Abstract

      Clinicians are well aware of the importance of a positive family history for coronary artery disease (CAD). Nonetheless, elucidation of the genetic basis of CAD has long proven difficult. The scenario changed in the last decade through the application of modern genomic technologies, like genome-wide association studies (GWAS) and next generation sequencing (NGS). GWAS have discovered over 60 common variants highly associated with CAD. For predictive purposes, such variants have been used to build up Genetic Risk Scores (GRSs), but their incorporation into classical prediction models does not appear substantially outperform the simple addition of family history. To date, the only strong case for the utility of incorporating genetic testing into clinical practice is represented by the diagnosis of Familial Hypercholesterolemia (FH). On the other hand, utilization of genomic techniques has driven formidable advances into the knowledge of CAD pathophysiology, particularly by addressing controversies on the causality of some lipid fractions that had long remained unsolved because of limitations of observational epidemiology. For example, NGS-derived rare variants with strong functional effects on key-genes like ANGPTL4, APOA5, APOC3, LPL, and SCARB1, have proven useful as proxies to demonstrate the causality of triglyceride-rich lipoproteins (TRLs) at variance with HDL-cholesterol concentration, thus contributing to tear down a dogma from classical epidemiology. Moreover, such variants have paved the way for the development of new biologic drugs (i.e. monoclonal antibodies or antisense oligonucleotides) targeting key proteins like PCSK9, Lipoprotein(a), and apolipoprotein C3. Such drugs are currently under active investigation, with first results being extremely promising.

      Graphical abstract

      Keywords

      Abbreviations:

      CAD (coronary artery disease), GWAS (genome-wide association studies), NGS (next generation sequencing), GRSs (Genetic Risk Scores), FH (Familial Hypercholesterolemia), TRLs (triglyceride-rich lipoproteins), HDL-C (High Density Lipoprotein cholesterol), MR (Mendelian randomization), SNPs (Single Nucleotide Polymorphisms), mAb (monoclonal antibodies), ASO (antisense oligonucleotides), LoF (loss of function), PCSK9 (Proprotein Convertase Subtilisin/Kexin type 9), Lp(a) (Lipoprotein(a)), ApoC3 (apolipoprotein C3), ApoA5 (apolipoprotein A5), LPL (lipoprotein lipase)

      1. Introduction

      Coronary Artery Disease (CAD), along with its main complication Myocardial Infarction (MI), remain the leading cause of death and disability worldwide (http://www.who.int/mediacentre/factsheets/fs317/en/), including in the developing countries where both lifespan and adoption of Western-like bad lifestyles are rising [
      • Wong N.D.
      Epidemiological studies of CHD and the evolution of preventive cardiology.
      ,
      • Murray C.J.
      • Barber R.M.
      • Foreman K.J.
      • Abbasoglu Ozgoren A.
      • et al.
      DALYs GBD, Collaborators H
      Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990–2013: quantifying the epidemiological transition.
      ].
      Clinicians approaching patients with suspected CAD are well aware of the importance of a positive family history for the disease, and hence of its genetic component. Indeed, classical epidemiological surveys like the Framingham Offspring Study [
      • Lloyd-Jones D.M.
      • Nam B.H.
      • D'Agostino Sr., R.B.
      • Levy D.
      • Murabito J.M.
      • Wang T.J.
      • et al.
      Parental cardiovascular disease as a risk factor for cardiovascular disease in middle-aged adults: a prospective study of parents and offspring.
      ], and the INTERHEART study involving patients from 52 different countries [
      • Chow C.K.
      • Islam S.
      • Bautista L.
      • Rumboldt Z.
      • Yusufali A.
      • Xie C.
      • et al.
      Parental history and myocardial infarction risk across the world: the INTERHEART study.
      ], pointed out that subjects having a parent with premature CAD have a nearly two-fold increased risk, independent of classical risk factors. Studies on monozygotic twins, known as the best “natural experiments” to evaluate the fraction of phenotype variability attributable to genetic factors [
      • Martin N.
      • Boomsma D.
      • Machin G.
      A twin-pronged attack on complex traits.
      ], estimated CAD heritability as high as 40–60% (Fig. 1) [
      • Marenberg M.E.
      • Risch N.
      • Berkman L.F.
      • Floderus B.
      • de Faire U.
      Genetic susceptibility to death from coronary heart disease in a study of twins.
      ,
      • Roberts R.
      A genetic basis for coronary artery disease.
      ,
      • Zdravkovic S.
      • Wienke A.
      • Pedersen N.L.
      • Marenberg M.E.
      • Yashin A.I.
      • de Faire U.
      Genetic influences on CHD-death and the impact of known risk factors: comparison of two frailty models.
      ]. This is not surprising, considering the high heritability of many classical CAD risk factors, i.e. dyslipidemia (up to 60%) [
      • Cole C.B.
      • Nikpay M.
      • McPherson R.
      Gene-environment interaction in dyslipidemia.
      ,
      • Global Lipids Genetics C
      • Willer C.J.
      • Schmidt E.M.
      • Sengupta S.
      • Peloso G.M.
      • Gustafsson S.
      • et al.
      Discovery and refinement of loci associated with lipid levels.
      ], and hypertension (up to 50%) [
      • Munroe P.B.
      • Barnes M.R.
      • Caulfield M.J.
      Advances in blood pressure genomics.
      ,
      • International Consortium for Blood Pressure Genome-Wide Association S
      • Ehret G.B.
      • Munroe P.B.
      • Rice K.M.
      • Bochud M.
      • Johnson A.D.
      • et al.
      Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk.
      ]. With relatively few exceptions represented by monogenic disorders, the most notable of which being familial hypercholesterolemia (FH; MIM #14389 [
      • Kathiresan S.
      • Srivastava D.
      Genetics of human cardiovascular disease.
      ]), CAD is a typical example of “complex disease”, with a polygenic architecture interacting with a myriad of environmental and lifestyle risk factors [
      • Watkins H.
      • Farrall M.
      Genetic susceptibility to coronary artery disease: from promise to progress.
      ]. Elucidation of the genetic basis of CAD has long been elusive until the recent decade, which has witnessed unprecedented progress in genomic medicine driven by both high throughput technologies and increased computational power (Fig. 1). Such advances hold promises of improving three major areas of practical medicine: i) prediction of CAD risk at individual levels; ii) therapeutic approaches based on novel pathophysiological insights; and iii) better use of existing therapies through pharmacogenetic (Fig. 1). Here we briefly review the practical implications of results obtained until now in the first two areas through major technological breakthroughs in genomics, i.e. genome wide association studies (GWAS) [
      • Manolio T.A.
      Genomewide association studies and assessment of the risk of disease.
      ] and next generation sequencing (NGS) (Fig. 1) [
      • Goodwin S.
      • McPherson J.D.
      • McCombie W.R.
      Coming of age: ten years of next-generation sequencing technologies.
      ,
      • Gonzaga-Jauregui C.
      • Lupski J.R.
      • Gibbs R.A.
      Human genome sequencing in health and disease.
      ]. A further tool, i.e. the so-called Mendelian randomization (MR) approach that uses naturally occurring genetic variation to assess causality of risk factors from observational studies [
      • Neeland I.J.
      • Kozlitina J.
      Mendelian randomization: using natural genetic variation to assess the causal role of modifiable risk factors in observational studies.
      ,
      • Jansen H.
      • Samani N.J.
      • Schunkert H.
      Mendelian randomization studies in coronary artery disease.
      ,
      • Evans D.M.
      • Davey Smith G.
      Mendelian randomization: new applications in the coming age of hypothesis-free causality.
      ], has also substantially contributed to major advances. Relevant applications of the advances in cardiovascular pharmacogenomics are reviewed in detail elsewhere [
      • Ross S.
      • Nejat S.
      • Pare G.
      Use of genetic data to guide therapy in arterial disease.
      ].
      Fig. 1
      Fig. 1CAD is a complex disease in which lifestyle factors play a major role (thickened red arrow). Nonetheless, genetic factors also contribute, and CAD heritability has been estimated as high as 40–60% through twin studies in the pre-genomic era. The genetic basis of CAD has been elusive until a decade ago. Starting from 2007, a number of Genome Wide Association Studies (GWAS) have detected more than 60 common variants associated with CAD risk, with only a minor fraction of them being linked to known pathways and/or classical risk factors. By definition, such common alleles are not useful per se as predictors. They have been used to build up genetic risk scores that have been proved to be strongly associated with CAD risk, but still marginally useful (dotted gray arrows) in adding predictive value to classical models including family history. On the other hand, modern genetic approaches including next-generation sequencing (NGS) and Mendelian randomization studies have provided strong pathophysiological insights (thickened red arrows). For example, the LPL pathway is now recognized to play a role in atherogenesis, and HDL-cholesterol concentration is no longer viewed as protective per se, but rather a biomarker of impaired clearance of triglyceride-rich lipoproteins (TRLs), which in turn contain atherogenic, “non-HDL” cholesterol. Moreover, the identification of rare protective mutations has paved the way to the development of new biologic drugs mimicking their effects. Such drugs look very promising to further reduce CAD burden at population level in the coming years.

      2. Methods

      This narrative review is based on articles retrieved by the Authors through automatic weekly e-mail alerts from the National Center for Biotechnology Information (NCBI) at the U.S. National Library of Medicine (NLM), using the research string “coronary artery disease” AND “genetics”, from December 31, 2005 to March 6, 2017. Complete results were viewed in PubMed. The references of the retrieved papers were used to find more literature.

      3. CAD prediction

      3.1 Results from GWAS

      Clinicians traditionally think about CAD genetics as the potential “Holy Grail” that should allow to identify individuals carrying risky mutations, in order to get an early diagnosis and to prescribe treatments able to prevent clinical manifestations [
      • Thanassoulis G.
      • Vasan R.S.
      Genetic cardiovascular risk prediction: will we get there?.
      ]. Early studies until around 2005 using the candidate gene approach were disappointing because of irreproducible associations [
      • Girelli D.
      • Martinelli N.
      • Peyvandi F.
      • Olivieri O.
      Genetic architecture of coronary artery disease in the genome-wide era: implications for the emerging “golden dozen” loci.
      ], leading some Authorities to conclude that “genomics will never useful in arterial diseases” [
      • Reitsma P.H.
      No praise for folly: genomics will never be useful in arterial thrombosis.
      ]. Such skepticism was overturned in 2007 by the advent of the GWAS methodology and its first applications to CAD [
      • Samani N.J.
      • Erdmann J.
      • Hall A.S.
      • Hengstenberg C.
      • Mangino M.
      • Mayer B.
      • et al.
      Genomewide association analysis of coronary artery disease.
      ,
      • McPherson R.
      • Pertsemlidis A.
      • Kavaslar N.
      • Stewart A.
      • Roberts R.
      • Cox D.R.
      • et al.
      A common allele on chromosome 9 associated with coronary heart disease.
      ,
      • Helgadottir A.
      • Thorleifsson G.
      • Manolescu A.
      • Gretarsdottir S.
      • Blondal T.
      • Jonasdottir A.
      • et al.
      A common variant on chromosome 9p21 affects the risk of myocardial infarction.
      ]. In its shortest definition, a GWAS is an unbiased approach that uses chip arrays, containing up to >1,000,000 common (minor allele frequency – MAF > 5%, i.e. 1:20) Single Nucleotide Polymorphisms (SNPs) spanning throughout the human genome, to detect regions (loci) associated with a given phenotype [
      • McCarthy M.I.
      • Abecasis G.R.
      • Cardon L.R.
      • Goldstein D.B.
      • Little J.
      • Ioannidis J.P.
      • et al.
      Genome-wide association studies for complex traits: consensus, uncertainty and challenges.
      ]. An updated catalog of the impressive number of published GWAS on CAD and related traits can be found at http://www.ebi.ac.uk/gwas. Overall, >60 SNPs have shown robust association with CAD, the top twenty of which are reported in Table 1. A detailed list including all the remaining loci is reported elsewhere in a recent comprehensive review [
      • Assimes T.L.
      • Roberts R.
      Genetics: implications for prevention and management of coronary artery disease.
      ]. Early this year, six further loci have been described through the most updated meta-analysis [
      • Webb T.R.
      • Erdmann J.
      • Stirrups K.E.
      • Stitziel N.O.
      • Masca N.G.
      • Jansen H.
      • et al.
      Systematic evaluation of pleiotropy identifies 6 further loci associated with coronary artery disease.
      ]. Noteworthy, only a minority (~40%) of all such risk variants appears to modulate CAD risk by influencing classical risk factors like plasma lipids, diabetes, and hypertension [
      • Consortium C.A.D.
      • Deloukas P.
      • Kanoni S.
      • Willenborg C.
      • Farrall M.
      • Assimes T.L.
      • et al.
      Large-scale association analysis identifies new risk loci for coronary artery disease.
      ,
      • Myocardial Infarction Genetics C
      • Kathiresan S.
      • Voight B.F.
      • Purcell S.
      • Musunuru K.
      • Ardissino D.
      • et al.
      Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants.
      ,
      • Schunkert H.
      • Konig I.R.
      • Kathiresan S.
      • Reilly M.P.
      • Assimes T.L.
      • Holm H.
      • et al.
      Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.
      ]. This is not surprising, considering that, as mentioned above, a positive family history remains a significant predictor of CAD even after full adjustment for traditional risk factors [
      • Lloyd-Jones D.M.
      • Nam B.H.
      • D'Agostino Sr., R.B.
      • Levy D.
      • Murabito J.M.
      • Wang T.J.
      • et al.
      Parental cardiovascular disease as a risk factor for cardiovascular disease in middle-aged adults: a prospective study of parents and offspring.
      ,
      • Chow C.K.
      • Islam S.
      • Bautista L.
      • Rumboldt Z.
      • Yusufali A.
      • Xie C.
      • et al.
      Parental history and myocardial infarction risk across the world: the INTERHEART study.
      ]. Moreover, most of the risk variants identified by GWAS are located in poorly known regulatory regions [
      • Hindorff L.A.
      • Sethupathy P.
      • Junkins H.A.
      • Ramos E.M.
      • Mehta J.P.
      • Collins F.S.
      • et al.
      Potential etiologic and functional implications of genome-wide association loci for human diseases and traits.
      ], rather than in canonical genes, i.e. protein-coding sequences which in turn represent only <3% of the human genome [
      • Consortium E.P.
      • Bernstein B.E.
      • Birney E.
      • Dunham I.
      • Green E.D.
      • Gunter C.
      • et al.
      An integrated encyclopedia of DNA elements in the human genome.
      ]. According to recent breakthrough results by the ENCODE (Encyclopedia of DNA elements) project [
      • Consortium E.P.
      • Bernstein B.E.
      • Birney E.
      • Dunham I.
      • Green E.D.
      • Gunter C.
      • et al.
      An integrated encyclopedia of DNA elements in the human genome.
      ], nearly 80% of the human DNA that do not code for proteins cannot be longer considered as “junk” DNA [
      • Gibbs W.W.
      The unseen genome: gems among the junk.
      ], but rather has biochemical functions and/or is transcribed into several regulatory elements, including long noncoding RNAs, able to modulate the expression of canonical genes [
      • Morris K.V.
      • Mattick J.S.
      The rise of regulatory RNA.
      ]. A paradigm in this sense is represented by the 9p21.3 locus, which was the first one to emerge by three independent landmark GWAS published in 2007 [
      • Samani N.J.
      • Erdmann J.
      • Hall A.S.
      • Hengstenberg C.
      • Mangino M.
      • Mayer B.
      • et al.
      Genomewide association analysis of coronary artery disease.
      ,
      • McPherson R.
      • Pertsemlidis A.
      • Kavaslar N.
      • Stewart A.
      • Roberts R.
      • Cox D.R.
      • et al.
      A common allele on chromosome 9 associated with coronary heart disease.
      ,
      • Helgadottir A.
      • Thorleifsson G.
      • Manolescu A.
      • Gretarsdottir S.
      • Blondal T.
      • Jonasdottir A.
      • et al.
      A common variant on chromosome 9p21 affects the risk of myocardial infarction.
      ]. According to the most recent meta-analysis ([
      • Nikpay M.
      • Goel A.
      • Won H.H.
      • Hall L.M.
      • Willenborg C.
      • Kanoni S.
      • et al.
      A comprehensive 1,000 genomes-based genome-wide association meta-analysis of coronary artery disease.
      ]), the 9p21.3 locus remains the strongest genetic risk factor for CAD, with an impressive statistical power (P = 2 × 10−98). Indeed, the 9p21.3 genomic region appears to encode for a long noncoding RNA designated as ANRIL (antisense noncoding RNA in the INK4 locus) [
      • Holdt L.M.
      • Teupser D.
      From genotype to phenotype in human atherosclerosis—recent findings.
      ]. While the exact role of 9p21.3 risk variant(s) in promoting CAD is still not completely understood, the most recent data suggest that ANRIL influence the expression of neighboring genes (CDKN2B and/or 2A) encoding cell cycle inhibitor proteins (cyclin-dependent kinase inhibitor 2B/2A, cdkn2b, cdkn2A) expressed by several tissues including vascular smooth muscle cells [
      • Kojima Y.
      • Downing K.
      • Kundu R.
      • Miller C.
      • Dewey F.
      • Lancero H.
      • et al.
      Cyclin-dependent kinase inhibitor 2B regulates efferocytosis and atherosclerosis.
      ,
      • Visel A.
      • Zhu Y.
      • May D.
      • Afzal V.
      • Gong E.
      • Attanasio C.
      • et al.
      Targeted deletion of the 9p21 non-coding coronary artery disease risk interval in mice.
      ]. Inadequate modulation of these inhibitory proteins is likely to promote cell proliferation within the arterial walls, which in turn would contribute to the development of the atheroma [
      • Kojima Y.
      • Downing K.
      • Kundu R.
      • Miller C.
      • Dewey F.
      • Lancero H.
      • et al.
      Cyclin-dependent kinase inhibitor 2B regulates efferocytosis and atherosclerosis.
      ].
      Table 1GWAS-derived top twenty loci associated with CAD/MI.
      LocusLead SNPGene(s)Risk allele frequency (risk allele)OR

      (95% CI)
      Possible mechanism for CAD/MIMain reference
      1p13.3rs7528419CELSR2

      PSRC1

      SORT1
      0.79 (A)1.12 (1.10–1.15)Association with LDL-cholesterol levels
      • Samani N.J.
      • Erdmann J.
      • Hall A.S.
      • Hengstenberg C.
      • Mangino M.
      • Mayer B.
      • et al.
      Genomewide association analysis of coronary artery disease.
      ,
      • Myocardial Infarction Genetics C
      • Kathiresan S.
      • Voight B.F.
      • Purcell S.
      • Musunuru K.
      • Ardissino D.
      • et al.
      Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants.
      1p32.2rs11206510PCSK90.85 (T)1.08 (1.05–1.11)Dyslipidemia
      • Myocardial Infarction Genetics C
      • Kathiresan S.
      • Voight B.F.
      • Purcell S.
      • Musunuru K.
      • Ardissino D.
      • et al.
      Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants.
      1q41rs67180937MIA30.66 (C)1.08 (1.06–1.11)Lipoprotein transport, regulation of cell adhesion
      • Samani N.J.
      • Erdmann J.
      • Hall A.S.
      • Hengstenberg C.
      • Mangino M.
      • Mayer B.
      • et al.
      Genomewide association analysis of coronary artery disease.
      ,
      • Myocardial Infarction Genetics C
      • Kathiresan S.
      • Voight B.F.
      • Purcell S.
      • Musunuru K.
      • Ardissino D.
      • et al.
      Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants.
      2q33.1rs6725887WDR120.11 (C)1.14 (1.11–1.18)Unknown
      • Myocardial Infarction Genetics C
      • Kathiresan S.
      • Voight B.F.
      • Purcell S.
      • Musunuru K.
      • Ardissino D.
      • et al.
      Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants.
      3q22.3rs9818870MRAS0.14 (T)1.07 (1.04–1.10)Regulation of adhesion signaling
      • Schunkert H.
      • Konig I.R.
      • Kathiresan S.
      • Reilly M.P.
      • Assimes T.L.
      • Holm H.
      • et al.
      Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.
      ,
      • Erdmann J.
      • Grosshennig A.
      • Braund P.S.
      • Konig I.R.
      • Hengstenberg C.
      • Hall A.S.
      • et al.
      New susceptibility locus for coronary artery disease on chromosome 3q22.3.
      6p24.1rs12526453PHACTR10.83 (C)1.10 (1.06–1.13)Arterial vessel wall endothelial cells
      • Myocardial Infarction Genetics C
      • Kathiresan S.
      • Voight B.F.
      • Purcell S.
      • Musunuru K.
      • Ardissino D.
      • et al.
      Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants.
      6q26-q27Haplotype based on 4 SNPs: rs2048327, rs3127599, rs7767084, rs10755578SLC22A3-LPAL2-LPA Gene clusterIncreased Lipoprotein(a) levels
      • Schunkert H.
      • Konig I.R.
      • Kathiresan S.
      • Reilly M.P.
      • Assimes T.L.
      • Holm H.
      • et al.
      Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.
      9p21.3rs2891168CDKN2A

      CDKN2B

      ANRIL
      0.49 (G)1.21 (1.19–1.24)Regulation of cell proliferation
      • McPherson R.
      • Pertsemlidis A.
      • Kavaslar N.
      • Stewart A.
      • Roberts R.
      • Cox D.R.
      • et al.
      A common allele on chromosome 9 associated with coronary heart disease.
      ,
      • Helgadottir A.
      • Thorleifsson G.
      • Manolescu A.
      • Gretarsdottir S.
      • Blondal T.
      • Jonasdottir A.
      • et al.
      A common variant on chromosome 9p21 affects the risk of myocardial infarction.
      ,
      • Myocardial Infarction Genetics C
      • Kathiresan S.
      • Voight B.F.
      • Purcell S.
      • Musunuru K.
      • Ardissino D.
      • et al.
      Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants.
      ,
      • Wellcome Trust Case Control C
      Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls.
      9q34.2rs2519093ABO0.19 (T)1.08 (1.06–1.11)Coagulation, association with LDL cholesterol levels
      • Schunkert H.
      • Konig I.R.
      • Kathiresan S.
      • Reilly M.P.
      • Assimes T.L.
      • Holm H.
      • et al.
      Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.
      ,
      • Reilly M.P.
      • Li M.
      • He J.
      • Ferguson J.F.
      • Stylianou I.M.
      • Mehta N.N.
      • et al.
      Identification of ADAMTS7 as a novel locus for coronary atherosclerosis and association of ABO with myocardial infarction in the presence of coronary atherosclerosis: two genome-wide association studies.
      10q11.21rs1870634CXCL120.64 (G)1.08 (1.06–1.10)Stromal chemokine that regulates trafficking of bone-marrow progenitor cells toward the circulation. Role on CAD/MI unknown
      • Myocardial Infarction Genetics C
      • Kathiresan S.
      • Voight B.F.
      • Purcell S.
      • Musunuru K.
      • Ardissino D.
      • et al.
      Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants.
      11q23.3rs964184ZNF259

      APOA5/4/1

      APOC3
      0.18 (G)1.05 (1.03–1.08)Triglyceride levels
      • Schunkert H.
      • Konig I.R.
      • Kathiresan S.
      • Reilly M.P.
      • Assimes T.L.
      • Holm H.
      • et al.
      Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.
      12q24.12rs3184504SH2B30.42 (T)1.07 (1.04–1.10)Increased eosinophil count; reduced anti-inflammatory and anti-proliferative activity
      • Gudbjartsson D.F.
      • Bjornsdottir U.S.
      • Halapi E.
      • Helgadottir A.
      • Sulem P.
      • Jonsdottir G.M.
      • et al.
      Sequence variants affecting eosinophil numbers associate with asthma and myocardial infarction.
      15q25.1rs4468572ADAMTS70.59 (C)1.08 (1.06–1.10)Arterial vessel wall smooth muscle cell
      • Schunkert H.
      • Konig I.R.
      • Kathiresan S.
      • Reilly M.P.
      • Assimes T.L.
      • Holm H.
      • et al.
      Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.
      ,
      • Reilly M.P.
      • Li M.
      • He J.
      • Ferguson J.F.
      • Stylianou I.M.
      • Mehta N.N.
      • et al.
      Identification of ADAMTS7 as a novel locus for coronary atherosclerosis and association of ABO with myocardial infarction in the presence of coronary atherosclerosis: two genome-wide association studies.
      ,
      • Coronary Artery Disease Genetics C
      A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease.
      19p13.2rs56289821LDLR0.90 (G)1.14 (1.09–1.18)Dyslipidemia
      • Myocardial Infarction Genetics C
      • Kathiresan S.
      • Voight B.F.
      • Purcell S.
      • Musunuru K.
      • Ardissino D.
      • et al.
      Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants.
      21q22.11rs28451064SLC5A3

      MRPS6

      KCNE2
      0.12 (A)1.14 (1.10–1.17)Unknown
      • Myocardial Infarction Genetics C
      • Kathiresan S.
      • Voight B.F.
      • Purcell S.
      • Musunuru K.
      • Ardissino D.
      • et al.
      Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants.
      2p24.1rs515135APOB0.79 (C)1.07 (1.04–1.10)Association with LDL-cholesterol levels
      • Consortium C.A.D.
      • Deloukas P.
      • Kanoni S.
      • Willenborg C.
      • Farrall M.
      • Assimes T.L.
      • et al.
      Large-scale association analysis identifies new risk loci for coronary artery disease.
      6q26rs4252185PLG0.06 (C)1.34 (1.28–1.41)Coagulation
      • Consortium C.A.D.
      • Deloukas P.
      • Kanoni S.
      • Willenborg C.
      • Farrall M.
      • Assimes T.L.
      • et al.
      Large-scale association analysis identifies new risk loci for coronary artery disease.
      11q22.3rs2128739PDGFD0.32 (A)1.07 (1.05–1.09)Regulation of cell growth, differentiation, apoptosis
      • Coronary Artery Disease Genetics C
      A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease.
      7q32.2rs11556924ZC3HC10.69 (C)1.08 (1.05–1.10)Unknown
      • Schunkert H.
      • Konig I.R.
      • Kathiresan S.
      • Reilly M.P.
      • Assimes T.L.
      • Holm H.
      • et al.
      Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.
      19q13.11rs12976411ZNF507-LOC4006840.91 (A)1.49 (1.38–1.67)Unknown
      • Nikpay M.
      • Goel A.
      • Won H.H.
      • Hall L.M.
      • Willenborg C.
      • Kanoni S.
      • et al.
      A comprehensive 1,000 genomes-based genome-wide association meta-analysis of coronary artery disease.

      3.2 The genetic risk scores

      Because of intrinsic study methodology (see above), SNPs at 9p21.3 locus, like all GWAS-derived risk variants, are quite common in the general population. In this particular case, the MAF for the risk allele rs2891168 is 0.49, which means that near one fourth of the world population is homozygous [
      • Nikpay M.
      • Goel A.
      • Won H.H.
      • Hall L.M.
      • Willenborg C.
      • Kanoni S.
      • et al.
      A comprehensive 1,000 genomes-based genome-wide association meta-analysis of coronary artery disease.
      ]. Thus, it is not surprising that, notwithstanding the strength of the statistical association with CAD, the ensuing odds ratio (OR) for CAD of the individual 9p21.3 risk allele is low (1.21, with 95% CI 1.19–1.24 [
      • Assimes T.L.
      • Roberts R.
      Genetics: implications for prevention and management of coronary artery disease.
      ]), making it not at all useful in clinical practice when considered alone. This is true for all the GWAS-derived risk variants, whose individual ORs for CAD are in the range between 1.03 and 1.10 [
      • Assimes T.L.
      • Roberts R.
      Genetics: implications for prevention and management of coronary artery disease.
      ]. On the other hand, their frequencies make unavoidable that any given individual could carry simultaneously several risk variants. This represents the basis for calculating the genetic risk scores (GRSs) (Fig. 1), in the effort to eventually provide an effective tool for improving CAD prediction. In its simplest definition, a GRS is calculated by counting the number of “risk” alleles inherited by a given individual, each corrected for its own effect size, according to the following formula:
      GRS=nallele1×βallele1+nallele2×βallele2+nallele3×βallele3+nallelen×βallelen


      where n is the individual's genotype (0 = normal, 1 = heterozygous, 2 = homozygous) for the risk allele, and β is the effect size of the same allele (i.e. the log of the OR) derived from largest available GWAS. The resulting GRS is then used as a single variable added to classical prediction models. Several studies utilizing different GRSs (i.e. built up with different numbers and combinations of risk alleles) have shown that they are robustly associated with incident CAD, independent of classical risk factors [
      • Ganna A.
      • Magnusson P.K.
      • Pedersen N.L.
      • de Faire U.
      • Reilly M.
      • Arnlov J.
      • et al.
      Multilocus genetic risk scores for coronary heart disease prediction.
      ,
      • Krarup N.T.
      • Borglykke A.
      • Allin K.H.
      • Sandholt C.H.
      • Justesen J.M.
      • Andersson E.A.
      • et al.
      A genetic risk score of 45 coronary artery disease risk variants associates with increased risk of myocardial infarction in 6041 Danish individuals.
      ,
      • Tada H.
      • Melander O.
      • Louie J.Z.
      • Catanese J.J.
      • Rowland C.M.
      • Devlin J.J.
      • et al.
      Risk prediction by genetic risk scores for coronary heart disease is independent of self-reported family history.
      ,
      • Abraham G.
      • Havulinna A.S.
      • Bhalala O.G.
      • Byars S.G.
      • De Livera A.M.
      • Yetukuri L.
      • et al.
      Genomic prediction of coronary heart disease.
      ,
      • Joseph P.G.
      • Pare G.
      • Asma S.
      • Engert J.C.
      • Yusuf S.
      • Anand S.S.
      • et al.
      Impact of a genetic risk score on myocardial infarction risk across different ethnic populations.
      ]. However, this does not appear to translate into an actual usefulness in clinical practice. To this end, what is needed is the demonstration that incorporation of GRS into an established clinical prediction model (i.e. the Framingham Risk Score–FRS–, or ACC/AHA13 calculator [
      • Goff Jr., D.C.
      • Lloyd-Jones D.M.
      • Bennett G.
      • Coady S.
      • D'Agostino Sr., R.B.
      • Gibbons R.
      • et al.
      2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines.
      ]), is actually able to improve either discrimination (c-statistic) or reclassification [
      • Goldstein B.A.
      • Knowles J.W.
      • Salfati E.
      • Ioannidis J.P.
      • Assimes T.L.
      Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example.
      ]. With relatively few exceptions, the GRSs did not perform better than simple family history in improving individual's risk stratification after incorporation into existing clinical models [
      • Bush W.S.
      • Crawford D.C.
      Predicting incident coronary heart disease many markers at a time.
      ]. Recently, Iribarren and colleagues found that application of GRSs including 8 to 51 SNPs to a cohort of 51,954 subjects of European-ancestry improved prediction of the FRS, although the net reclassification rate was modest (5–9%) [
      • Iribarren C.
      • Lu M.
      • Jorgenson E.
      • Martinez M.
      • Lluis-Ganella C.
      • Subirana I.
      • et al.
      Clinical utility of multimarker genetic risk scores for prediction of incident coronary heart disease: a cohort study among over 51 thousand individuals of European ancestry.
      ]. Tada and colleagues evaluated an extended GRS including 50 SNPs (“GRS-50”) in 23,595 Swedish, pointing out an effect independent of family history [
      • Tada H.
      • Melander O.
      • Louie J.Z.
      • Catanese J.J.
      • Rowland C.M.
      • Devlin J.J.
      • et al.
      Risk prediction by genetic risk scores for coronary heart disease is independent of self-reported family history.
      ]. However, this is not surprising since self-reported family history in large population surveys is known to have a low accuracy and to reflect both genetic and non-genetic risk factors. A major general limitation of GWAS is that the risk variants explain only a minor fraction (no >20%) of total estimated CAD heritability [
      • Consortium C.A.D.
      • Deloukas P.
      • Kanoni S.
      • Willenborg C.
      • Farrall M.
      • Assimes T.L.
      • et al.
      Large-scale association analysis identifies new risk loci for coronary artery disease.
      ]. Current hypothesis, by analogy with recent demonstrations for other traits like height [
      • Yang J.
      • Benyamin B.
      • McEvoy B.P.
      • Gordon S.
      • Henders A.K.
      • Nyholt D.R.
      • et al.
      Common SNPs explain a large proportion of the heritability for human height.
      ], and BMI [
      • Locke A.E.
      • Kahali B.
      • Berndt S.I.
      • Justice A.E.
      • Pers T.H.
      • Day F.R.
      • et al.
      Genetic studies of body mass index yield new insights for obesity biology.
      ], suggests that the majority of “missing” heritability [
      • Maher B.
      Personal genomes: the case of the missing heritability.
      ] is hidden amongst the thousands of SNPs that did not reach genome-wide significance. Accordingly, Abraham and colleagues built up a “massive” GRS with 49,310 SNPs (“49K-GRS”), possibly reflecting the maximum available amount of genomic information, and successfully showed that it increased CAD prediction in FINRISK (n = 12,676) and Framingham Heart Study (n = 3406) prospective cohorts [
      • Abraham G.
      • Havulinna A.S.
      • Bhalala O.G.
      • Byars S.G.
      • De Livera A.M.
      • Yetukuri L.
      • et al.
      Genomic prediction of coronary heart disease.
      ]. Again, however, the overall incremental predictive power of the 49K-GRS after incorporation into FRS and ACC/AHA13 models was very modest (C-index = +1.5%), except in certain subpopulations like individuals ≥ 60 years old (C-index = +4.6–5.1%). Arguments in favor of the possible use of the GRSs come from two studies that analyzed retrospectively DNA samples from patients participating to five major clinical trials on statin therapy (JUPITER, ASCOT, WOSCOPS, CARE and PROVE-IT-TIMI 22) [
      • Mega J.L.
      • Stitziel N.O.
      • Smith J.G.
      • Chasman D.I.
      • Caulfield M.J.
      • Devlin J.J.
      • et al.
      Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials.
      ,
      • Natarajan P.
      • Young R.
      • Stitziel N.O.
      • Padmanabhan S.
      • Baber U.
      • Mehran R.
      • et al.
      Polygenic risk score identifies subgroup with higher burden of atherosclerosis and greater relative benefit from statin therapy in the primary prevention setting.
      ]. Both such analyses concordantly showed that the application of a GRS-27 [
      • Mega J.L.
      • Stitziel N.O.
      • Smith J.G.
      • Chasman D.I.
      • Caulfield M.J.
      • Devlin J.J.
      • et al.
      Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials.
      ] or a GRS-57 [
      • Natarajan P.
      • Young R.
      • Stitziel N.O.
      • Padmanabhan S.
      • Baber U.
      • Mehran R.
      • et al.
      Polygenic risk score identifies subgroup with higher burden of atherosclerosis and greater relative benefit from statin therapy in the primary prevention setting.
      ] effectively discriminated patients with the highest genetic risk, who in turn derived the maximal benefit from statins. However, these intriguing results need validation in prospective trials. Moreover, a recent survey on 55,685 subjects from four studies still confirmed the association between GRSs (including up to 50 risk variants) and incident CAD, with subjects in the top GRS quintiles having a 91% higher relative risk as compared to those in the bottom quintiles [
      • Khera A.V.
      • Emdin C.A.
      • Drake I.
      • Natarajan P.
      • Bick A.G.
      • Cook N.R.
      • et al.
      Genetic risk, adherence to a healthy lifestyle, and coronary disease.
      ]. Noteworthy, in any genetic risk category, the adherence to a healthy lifestyle was associated with a substantial risk reduction, up to nearly 50% in subjects with the highest genetic risk. Taken together, the results on GRS suggest at least two important practical lessons. First, the dream of a “perfect” prediction of CAD through the incorporation of genetic risk markers into more traditional models is likely unrealistic. The incremental benefit, if any, appears dull even with the addition of apparently robust and maximally informative markers integrating the most recent technological advances. Even though costs are consistently declining so that simultaneous genotyping of thousands of SNPs (i.e. for calculating the 49K-GRS) could be obtained with <100 €, the ensuing level of complexity makes unreliable the use of such information in daily clinical practice, particularly considering that an accurate family history (simple and inexpensive at same time) represents an excellent alternative. Second, widespread application of complex genetic tests at population level is unlikely to be cost-effective even in the future, since it is becoming evident that lifestyle factors can powerfully modify the risk of CAD regardless of individual's genetic risk profile. Thus, from a public health point of view, investing resources to promote adherence to healthy lifestyle should still remain a priority. Accordingly, there is no reason to disagree with recently updated guidelines by the European Society of Cardiology on cardiovascular disease prevention, which recommend against the use of genetic testing in clinical practice [
      • Piepoli M.F.
      • Hoes A.W.
      • Agewall S.
      • Albus C.
      • Brotons C.
      • Catapano A.L.
      • et al.
      2016 European guidelines on cardiovascular disease prevention in clinical practice: the sixth joint task force of the European society of cardiology and other societies on cardiovascular disease prevention in clinical practice (constituted by representatives of 10 societies and by invited experts) developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR).
      ].

      3.3 Familial Hypercholesterolemia

      The above mentioned rule has, however, a notable exception represented by Mendelian disorders strongly associated to premature CAD, mainly Familial Hypercholesterolemia (FH). FH is a disorder due to genetic defects in LDL-cholesterol (LDL-c) metabolism resulting in unusually high LDL-c and a markedly increased risk of early-onset CAD (for detailed reviews see [
      • Nordestgaard B.G.
      • Chapman M.J.
      • Humphries S.E.
      • Ginsberg H.N.
      • Masana L.
      • Descamps O.S.
      • et al.
      Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: consensus statement of the European Atherosclerosis Society.
      ,
      • Cuchel M.
      • Bruckert E.
      • Ginsberg H.N.
      • Raal F.J.
      • Santos R.D.
      • Hegele R.A.
      • et al.
      Homozygous familial hypercholesterolaemia: new insights and guidance for clinicians to improve detection and clinical management. A position paper from the Consensus Panel on Familial Hypercholesterolaemia of the European Atherosclerosis Society.
      ]. Homozygous FH is a rare disease with frequency variable from 1 in 1,000,000 (historical estimates) to 1 in 160,000 (most recent estimates in the Danish population) [
      • Nordestgaard B.G.
      • Chapman M.J.
      • Humphries S.E.
      • Ginsberg H.N.
      • Masana L.
      • Descamps O.S.
      • et al.
      Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: consensus statement of the European Atherosclerosis Society.
      ], in which untreated patients can have plasma LDL-c > 500 mg/dl, as well as develop xanthomas and CAD within the first two decade of life [
      • Cuchel M.
      • Bruckert E.
      • Ginsberg H.N.
      • Raal F.J.
      • Santos R.D.
      • Hegele R.A.
      • et al.
      Homozygous familial hypercholesterolaemia: new insights and guidance for clinicians to improve detection and clinical management. A position paper from the Consensus Panel on Familial Hypercholesterolaemia of the European Atherosclerosis Society.
      ]. Such extreme phenotype makes the diagnosis relatively easy. From a practical point of view, suspicion and diagnosis of heterozygous FH (which can be as common as 1 in 200 in general populations of European ancestry) is much more difficult, since LDL-c levels (generally >190 mg/dl) can overlap with other types of dyslipidemia, while retaining a substantially higher risk of developing CAD [
      • Khera A.V.
      • Won H.H.
      • Peloso G.M.
      • Lawson K.S.
      • Bartz T.M.
      • Deng X.
      • et al.
      Diagnostic yield and clinical utility of sequencing familial hypercholesterolemia genes in patients with severe hypercholesterolemia.
      ]. Notwithstanding well-established criteria for clinical diagnosis like the Dutch Lipid Clinic Network [
      • Nordestgaard B.G.
      • Chapman M.J.
      • Humphries S.E.
      • Ginsberg H.N.
      • Masana L.
      • Descamps O.S.
      • et al.
      Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: consensus statement of the European Atherosclerosis Society.
      ,
      • Umans-Eckenhausen M.A.
      • Defesche J.C.
      • Scheerder R.L.
      • Cline F.
      • Kastelein J.J.
      Tracing of patients with familial hypercholesterolemia in the Netherlands.
      ] or Simon Broome system [
      ,
      • Starr B.
      • Hadfield S.G.
      • Hutten B.A.
      • Lansberg P.J.
      • Leren T.P.
      • Damgaard D.
      • et al.
      Development of sensitive and specific age- and gender-specific low-density lipoprotein cholesterol cutoffs for diagnosis of first-degree relatives with familial hypercholesterolaemia in cascade testing.
      ] scores, heterozygous FH remains largely underdiagnosed and undertreated [
      • Nordestgaard B.G.
      • Chapman M.J.
      • Humphries S.E.
      • Ginsberg H.N.
      • Masana L.
      • Descamps O.S.
      • et al.
      Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: consensus statement of the European Atherosclerosis Society.
      ,
      • Gidding S.S.
      • Champagne M.A.
      • de Ferranti S.D.
      • Defesche J.
      • Ito M.K.
      • Knowles J.W.
      • et al.
      The agenda for familial hypercholesterolemia: a scientific statement from the American Heart Association.
      ], with important public health implications. Indeed, FH has been designated by the U.S. Centers for Disease Control Office of Public Health Genomics as one of three top level genetic disorders (the others being BRCA1/2 related hereditary breast/ovarian cancer, and Lynch syndrome) with sufficient evidence for recommend implementation of case finding via all possible strategies, including genetic testing, to significantly improve public health [
      • Bowen M.S.
      • Kolor K.
      • Dotson W.D.
      • Ned R.M.
      • Khoury M.J.
      Public health action in genomics is now needed beyond newborn screening.
      ]. Simultaneous, NGS-based, targeted sequencing of LDLR, APOB, and PCSK9, i.e. the three genes causally linked to the vast majority of FH, is now becoming widely available and cost-effective [
      • Khera A.V.
      • Won H.H.
      • Peloso G.M.
      • Lawson K.S.
      • Bartz T.M.
      • Deng X.
      • et al.
      Diagnostic yield and clinical utility of sequencing familial hypercholesterolemia genes in patients with severe hypercholesterolemia.
      ], so that national guidelines in Netherlands, Norway, and the U.K. currently recommend cascade screening using genetics and lipid profile after the identification of an index case [
      • Paynter N.P.
      • Ridker P.M.
      • Chasman D.I.
      Are genetic tests for atherosclerosis ready for routine clinical use?.
      ]. The incremental values of genetic testing in FH over family history and clinical scores include certainty of the diagnosis in many cases, reduction of burden of undiagnosed patients, and improved outcomes in patients properly recognized and treated, altogether finally resulting absolute lowering of FH-related costs [
      • Gidding S.S.
      • Champagne M.A.
      • de Ferranti S.D.
      • Defesche J.
      • Ito M.K.
      • Knowles J.W.
      • et al.
      The agenda for familial hypercholesterolemia: a scientific statement from the American Heart Association.
      ]. Noteworthy, Abul-Husn and colleagues recently applied exome sequencing to 50,726 individuals from a single U.S. health care system, showing that such genomic screening was effective in diagnosing FH patients (with an estimated prevalence of 1 in 256), most of whom were receiving inadequate lipid lowering therapy [
      • Abul-Husn N.S.
      • Manickam K.
      • Jones L.K.
      • Wright E.A.
      • Hartzel D.N.
      • Gonzaga-Jauregui C.
      • et al.
      Genetic identification of familial hypercholesterolemia within a single U.S. health care system.
      ].

      4. Pathophysiological insights and therapeutic implications

      At variance with modest results in CAD prediction, genomic techniques have substantially contributed to new acquisitions in CAD pathophysiology, with relevant practical implications in terms of drug therapy. The identification of new targets is instrumental to the development of modern “biologic” or “intelligent” drugs, through either inactivating monoclonal antibodies (mAb) [
      • Foltz I.N.
      • Karow M.
      • Wasserman S.M.
      Evolution and emergence of therapeutic monoclonal antibodies: what cardiologists need to know.
      ], or agents selectively blocking protein synthesis, i.e. antisense oligonucleotides (ASO) (Fig. 1) [
      • Goldberg A.C.
      Novel therapies and new targets of treatment for familial hypercholesterolemia.
      ,
      • Levin A.A.
      Targeting therapeutic oligonucleotides.
      ].

      4.1 Proprotein Convertase Subtilisin/Kexin type 9 (PCSK9)

      The most known and compelling example in this sense is Proprotein Convertase Subtilisin/Kexin type 9 (PCSK9), a liver-produced serin protease that accelerates the degradation of the LDL receptor [
      • Seidah N.G.
      • Awan Z.
      • Chretien M.
      • Mbikay M.
      PCSK9: a key modulator of cardiovascular health.
      ], whose genetic alterations can result in either increased CAD risk (gain of function mutations [
      • Abifadel M.
      • Varret M.
      • Rabes J.P.
      • Allard D.
      • Ouguerram K.
      • Devillers M.
      • et al.
      Mutations in PCSK9 cause autosomal dominant hypercholesterolemia.
      ]) or protection (loss of function mutations [
      • Cohen J.C.
      • Boerwinkle E.
      • Mosley Jr., T.H.
      • Hobbs H.H.
      Sequence variations in PCSK9, low LDL, and protection against coronary heart disease.
      ]). The PCSK9 story, comprehensively reviewed elsewhere [
      • Bergeron N.
      • Phan B.A.
      • Ding Y.
      • Fong A.
      • Krauss R.M.
      Proprotein convertase subtilisin/kexin type 9 inhibition: a new therapeutic mechanism for reducing cardiovascular disease risk.
      ], illustrates as only near a dozen years passed from protein/gene discovery (in 2003) to clinical trials showing the efficacy of target therapy through humanized monoclonal antibodies able to substantially lower LDL-cholesterol [
      • Natarajan P.
      • Kathiresan S.
      PCSK9 inhibitors.
      ,
      • Blom D.J.
      • Hala T.
      • Bolognese M.
      • Lillestol M.J.
      • Toth P.D.
      • Burgess L.
      • et al.
      A 52-week placebo-controlled trial of evolocumab in hyperlipidemia.
      ,
      • Nicholls S.J.
      • Puri R.
      • Anderson T.
      • Ballantyne C.M.
      • Cho L.
      • Kastelein J.J.
      • et al.
      Effect of evolocumab on progression of coronary disease in statin-treated patients: the GLAGOV randomized clinical trial.
      ,
      • Robinson J.G.
      • Farnier M.
      • Krempf M.
      • Bergeron J.
      • Luc G.
      • Averna M.
      • et al.
      Efficacy and safety of alirocumab in reducing lipids and cardiovascular events.
      ], an unprecedented fast-tracking process in cardiovascular drug development.

      4.2 Lipoprotein(a)

      A similar story can be depicted for Lipoprotein(a) (Lp(a), encoded by the LPA gene), although this LDL-like particle composed by apolipoprotein-B100 covalently bound to a distinct plasminogen-derived apolipoprotein (apolipoprotein(a)) [
      • Tsimikas S.
      A test in context: lipoprotein(a): diagnosis, prognosis, controversies, and emerging therapies.
      ] was known since 1963 [
      • Berg K.
      A new serum type system in man--the Lp system.
      ]. While a mechanistic link between Lp(a) and CAD was more than plausible [
      • Utermann G.
      The mysteries of lipoprotein(a).
      ], and well supported by association studies in different populations [
      • Sandholzer C.
      • Saha N.
      • Kark J.D.
      • Rees A.
      • Jaross W.
      • Dieplinger H.
      • et al.
      Apo(a) isoforms predict risk for coronary heart disease. A study in six populations.
      ], true causality remained unproven because of the lack of availability of drugs or other interventional strategies able to reduce Lp(a), and hence CAD risk. The scenario has recently clarified by the identification of LPA genetic variants associated with both elevated circulating Lp(a) and increased CAD risk [
      • Clarke R.
      • Peden J.F.
      • Hopewell J.C.
      • Kyriakou T.
      • Goel A.
      • Heath S.C.
      • et al.
      Genetic variants associated with Lp(a) lipoprotein level and coronary disease.
      ], particularly in prospective studies [
      • Kamstrup P.R.
      • Tybjaerg-Hansen A.
      • Steffensen R.
      • Nordestgaard B.G.
      Genetically elevated lipoprotein(a) and increased risk of myocardial infarction.
      ]. Of note, LPA mutations leading to low Lp(a) have been also described and associated to CAD protection [
      • Kyriakou T.
      • Seedorf U.
      • Goel A.
      • Hopewell J.C.
      • Clarke R.
      • Watkins H.
      • et al.
      A common LPA null allele associates with lower lipoprotein(a) levels and coronary artery disease risk.
      ]. A recent comprehensive analysis of such variants using data from both large-scale GWAS and NGS-based studies has consistently shown that one standard deviation (SD) genetically lowered is associated with a 29% lower risk of CAD [
      • Emdin C.A.
      • Khera A.V.
      • Natarajan P.
      • Klarin D.
      • Won H.H.
      • Peloso G.M.
      • et al.
      Phenotypic characterization of genetically lowered human lipoprotein(a) levels.
      ]. ASOs against LPA able to reduce circulating Lp(a) by up to 90% in healthy volunteers have been developed [
      • Viney N.J.
      • van Capelleveen J.C.
      • Geary R.S.
      • Xia S.
      • Tami J.A.
      • Yu R.Z.
      • et al.
      Antisense oligonucleotides targeting apolipoprotein(a) in people with raised lipoprotein(a): two randomised, double-blind, placebo-controlled, dose-ranging trials.
      ,
      • Graham M.J.
      • Viney N.
      • Crooke R.M.
      • Tsimikas S.
      Antisense inhibition of apolipoprotein (a) to lower plasma lipoprotein (a) levels in humans.
      ], and are currently under investigation in patients with elevated Lp(a) [
      • Tsimikas S.
      A test in context: lipoprotein(a): diagnosis, prognosis, controversies, and emerging therapies.
      ]. Anti-PCSK9 mAbs are also able to reduce Lp(a) by near 30% [
      • Raal F.J.
      • Giugliano R.P.
      • Sabatine M.S.
      • Koren M.J.
      • Langslet G.
      • Bays H.
      • et al.
      Reduction in lipoprotein(a) with PCSK9 monoclonal antibody evolocumab (AMG 145): a pooled analysis of more than 1,300 patients in 4 phase II trials.
      ], since the LDL receptor is also involved in its clearance [
      • Reyes-Soffer G.
      • Pavlyha M.
      • Ngai C.
      • Thomas T.
      • Holleran S.
      • Ramakrishnan R.
      • et al.
      Effects of PCSK9 inhibition with alirocumab on lipoprotein metabolism in healthy humans.
      ,
      • Packard C.J.
      Unpacking and understanding the impact of proprotein convertase subtilisin/kexin type 9 inhibitors on apolipoprotein B metabolism.
      ].

      4.3 Triglyceride-rich lipoproteins

      A third, impressive example of genomic-driven pathophysiological insight is represented by recent downsizing of the causal role of HDL cholesterol (HDL-C) and, on the contrary, revitalized interest in triglyceride-rich lipoproteins (TRLs) [
      • Libby P.
      Triglycerides on the rise: should we swap seats on the seesaw?.
      ]. The term TRLs designates very low-density lipoproteins (VLDL), chylomicrons, and their remnants. They contain both triglycerides and cholesterol (near 60% and 20% by mass in VLDL, respectively), as well as phospholipids and a number of proteins, including apolipoproteins C3 (ApoC3) and A5 (ApoA5) [
      • Nordestgaard B.G.
      Triglyceride-rich lipoproteins and atherosclerotic cardiovascular disease: new insights from epidemiology, genetics, and biology.
      ]. The major determinant of TRLs metabolism is represented by endothelial lipoprotein lipase (LPL), whose activity, in turn, is increased by ApoA5 and inhibited by ApoC3, as well as by circulating angiopoietin-like proteins 3 and 4 (Angptl3 and Angptl4) [
      • Kersten S.
      Physiological regulation of lipoprotein lipase.
      ] (Fig. 1). Plasma triglycerides concentration represents a proxy of TRLs, and, at population level, it is known to be inversely related with HDL-C levels [
      • Libby P.
      Triglycerides on the rise: should we swap seats on the seesaw?.
      ,
      • Nordestgaard B.G.
      Triglyceride-rich lipoproteins and atherosclerotic cardiovascular disease: new insights from epidemiology, genetics, and biology.
      ]. According to classic observational epidemiology, both high triglycerides and low HDL-C level were associated to CAD, but while the effect of triglycerides was substantially attenuated by adjusting for numerous covariates (including HDL-C), that of HDL-C appeared independent [
      • Emerging Risk Factors C
      • Di Angelantonio E.
      • Sarwar N.
      • Perry P.
      • Kaptoge S.
      • Ray K.K.
      • et al.
      Major lipids, apolipoproteins, and risk of vascular disease.
      ,
      • Triglyceride Coronary Disease Genetics C
      • Emerging Risk Factors C
      • Sarwar N.
      • Sandhu M.S.
      • Ricketts S.L.
      • Butterworth A.S.
      • et al.
      Triglyceride-mediated pathways and coronary disease: collaborative analysis of 101 studies.
      ]. This led to the commonly accepted “dogma” that HDL-C levels were causally related with CAD, with high levels being protective, while triglycerides were considered no more than bystanders [
      • Nordestgaard B.G.
      Triglyceride-rich lipoproteins and atherosclerotic cardiovascular disease: new insights from epidemiology, genetics, and biology.
      ]. Functional and pathological studies supported this view, showing that HDL particles are involved in reverse cholesterol transport from atherosclerotic plaques, where, in turn, triglycerides do not accumulate, unlike cholesterol [
      • Libby P.
      Triglycerides on the rise: should we swap seats on the seesaw?.
      ,
      • Nordestgaard B.G.
      Triglyceride-rich lipoproteins and atherosclerotic cardiovascular disease: new insights from epidemiology, genetics, and biology.
      ]. However, modern genetic studies have seriously confuted the causal role of HDL-C [
      • Couzin-Frankel J.
      Lipid biology. Why high ‘good cholesterol’ can be bad news.
      ], at least with respect to its concentration. A first Mendelian randomization (MR) study used a variant (Asn396Ser) on the LIPG gene significantly associated with increased HDL-C levels (but without effects on other lipid fractions) as a probe to test causality, but, indeed, such variant was not associated with the expected reduced risk of MI in a meta-analysis of 20 studies including >116,000 participants [
      • Voight B.F.
      • Peloso G.M.
      • Orho-Melander M.
      • Frikke-Schmidt R.
      • Barbalic M.
      • Jensen M.K.
      • et al.
      Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study.
      ]. More recently, Zanoni and colleagues [
      • Zanoni P.
      • Khetarpal S.A.
      • Larach D.B.
      • Hancock-Cerutti W.F.
      • Millar J.S.
      • Cuchel M.
      • et al.
      Rare variant in scavenger receptor BI raises HDL cholesterol and increases risk of coronary heart disease.
      ] applied to HDL-C a very useful and innovative approach, namely targeted NGS of subjects with “extreme” phenotypes, where the probability to find mutations with large functional effects is substantially increased as compared to the general population [
      • Kristiansson K.
      • Naukkarinen J.
      • Peltonen L.
      Isolated populations and complex disease gene identification.
      ]. In a relatively small group (n = 328) of subjects selected for having HDL-C levels > 95th percentile (mean level = 106.8 mg/dl) they detected a “human knock-out” homozygous for a loss of function [
      • Murray C.J.
      • Barber R.M.
      • Foreman K.J.
      • Abbasoglu Ozgoren A.
      • et al.
      DALYs GBD, Collaborators H
      Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990–2013: quantifying the epidemiological transition.
      ] variant (P376L) in the SCARB1 gene [
      • Zanoni P.
      • Khetarpal S.A.
      • Larach D.B.
      • Hancock-Cerutti W.F.
      • Millar J.S.
      • Cuchel M.
      • et al.
      Rare variant in scavenger receptor BI raises HDL cholesterol and increases risk of coronary heart disease.
      ], encoding for scavenger receptor BI, i.e. the major receptor for HDL [
      • Acton S.
      • Rigotti A.
      • Landschulz K.T.
      • Xu S.
      • Hobbs H.H.
      • Krieger M.
      Identification of scavenger receptor SR-BI as a high density lipoprotein receptor.
      ]. A number of P376L heterozygous carriers were then found in a large population including 137,995 individuals (49,846 CAD cases and 88,149 controls), that in spite of having elevated HDL-C had increased (not decreased) CAD risk [
      • Zanoni P.
      • Khetarpal S.A.
      • Larach D.B.
      • Hancock-Cerutti W.F.
      • Millar J.S.
      • Cuchel M.
      • et al.
      Rare variant in scavenger receptor BI raises HDL cholesterol and increases risk of coronary heart disease.
      ]. Finally, sequencing of the Icelandic population allowed the detection of rare mutations in the ASGR1 gene (encoding a subunit of the asialoglycoprotein receptor, involved in the homeostasis of circulating glycoproteins), which were “paradoxically” associated with both reduced HDL-C levels and reduced CAD risk [
      • Nioi P.
      • Sigurdsson A.
      • Thorleifsson G.
      • Helgason H.
      • Agustsdottir A.B.
      • Norddahl G.L.
      • et al.
      Variant ASGR1 associated with a reduced risk of coronary artery disease.
      ]. A further argument seriously questioning the “dogma” of inverse causality of HDL-C in CAD/MI is the proven futility of a drug increasing HDL-cholesterol (the CETP inhibitor dalcetrapib) in a clinical trial evaluating the risk of recurrent CVD [
      • Schwartz G.G.
      • Olsson A.G.
      • Abt M.
      • Ballantyne C.M.
      • Barter P.J.
      • Brumm J.
      • et al.
      Effects of dalcetrapib in patients with a recent acute coronary syndrome.
      ]. On the other hand, a number of NGS-based studies focusing on the main genes involving in modulation of the LPL pathway (APOA5, APOC3, ANGPTL4, and the LPL gene itself), often using the same strategy as above, i.e. initially focusing on individuals with extremely high or low plasma triglycerides levels, have yielded results univocally in favor of a causal role of TRLs in CAD (see Fig. 2 for a synopsis). Indeed, they found that carriers of mutations leading to increased LPL function (i.e. LoF mutations in APOC3 [
      • Tg, Hdl Working Group of the Exome Sequencing Project NHL
      • Blood I.
      • Crosby J.
      • Peloso G.M.
      • Auer P.L.
      • et al.
      Loss-of-function mutations in APOC3, triglycerides, and coronary disease.
      ,
      • Jorgensen A.B.
      • Frikke-Schmidt R.
      • Nordestgaard B.G.
      • Tybjaerg-Hansen A.
      Loss-of-function mutations in APOC3 and risk of ischemic vascular disease.
      ,
      • Pollin T.I.
      • Damcott C.M.
      • Shen H.
      • Ott S.H.
      • Shelton J.
      • Horenstein R.B.
      • et al.
      A null mutation in human APOC3 confers a favorable plasma lipid profile and apparent cardioprotection.
      ] and ANGPTL4 [
      • Dewey F.E.
      • Gusarova V.
      • O'Dushlaine C.
      • Gottesman O.
      • Trejos J.
      • Hunt C.
      • et al.
      Inactivating variants in ANGPTL4 and risk of coronary artery disease.
      ,
      • Myocardial Infarction G.
      • Investigators C.A.E.C.
      • Stitziel N.O.
      • Stirrups K.E.
      • Masca N.G.
      • Erdmann J.
      • et al.
      Coding variation in ANGPTL4, LPL, and SVEP1 and the risk of coronary disease.
      ]) had both low plasma triglycerides and decreased risk of CAD, while carriers of mutations leading to decreased LPL function (i.e. LoF mutations in APOA5 [
      • Do R.
      • Stitziel N.O.
      • Won H.H.
      • Jorgensen A.B.
      • Duga S.
      • Angelica Merlini P.
      • et al.
      Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction.
      ] and LPL [
      • Myocardial Infarction G.
      • Investigators C.A.E.C.
      • Stitziel N.O.
      • Stirrups K.E.
      • Masca N.G.
      • Erdmann J.
      • et al.
      Coding variation in ANGPTL4, LPL, and SVEP1 and the risk of coronary disease.
      ]) had both high plasma triglycerides and increased risk of CAD (Fig. 2). Helgadottir and colleagues took advantage from the reduced allele diversity of the Icelandic population for a comprehensive study combining whole genome sequencing, GRS, and MR approaches to infer causality of all major plasma lipid fractions commonly measured in clinical practice (LDL-C, HDL-C, triglycerides, and non-HDL-C) [
      • Helgadottir A.
      • Gretarsdottir S.
      • Thorleifsson G.
      • Hjartarson E.
      • Sigurdsson A.
      • Magnusdottir A.
      • et al.
      Variants with large effects on blood lipids and the role of cholesterol and triglycerides in coronary disease.
      ]. They found that non-HDL-C GRS associated most strongly with CAD (P = 2.7 × 10−28), and no other GRS associated with CAD after accounting for non-HDL-C. In summary, according to the recent studies using sequence variants as proxies to infer causality, the long-lasting controversy on the role of HDL-C or triglycerides in CAD appears to be eventually solved as follows: i) HDL-C concentration per se is not causally linked to CAD (although concentration does not necessarily reflect the flux of HDL particles and their potential function in promoting reverse cholesterol transport [
      • Khera A.V.
      • Ridker P.M.
      Demystifying HDL cholesterol-A “human knockout” to the rescue?.
      ]); ii) TRLs are causally linked to CAD; iii) however, the atherogenic role of TRLs is not due to triglycerides, but rather to their cholesterol content. The first practical insight is that clinicians should pay even more attention to non-HDL-C than to LDL-C [
      • Chapman M.J.
      • Ginsberg H.N.
      • Amarenco P.
      • Andreotti F.
      • Boren J.
      • Catapano A.L.
      • et al.
      Triglyceride-rich lipoproteins and high-density lipoprotein cholesterol in patients at high risk of cardiovascular disease: evidence and guidance for management.
      ], since this measure accounts for all atherogenic cholesterol-containing lipoproteins, including LDL, VLDL, intermediate-density lipoprotein, chylomicrons and their remnants, and Lp(a) [
      • Tybjaerg-Hansen A.
      The sialylation pathway and coronary artery disease.
      ,
      • Varbo A.
      • Benn M.
      • Nordestgaard B.G.
      Remnant cholesterol as a cause of ischemic heart disease: evidence, definition, measurement, atherogenicity, high risk patients, and present and future treatment.
      ]. The second is that TRLs have also to be considered a therapeutic target, for which the most promising agent appears an ASO against APOC3 [
      • Gaudet D.
      • Brisson D.
      • Tremblay K.
      • Alexander V.J.
      • Singleton W.
      • Hughes S.G.
      • et al.
      Targeting APOC3 in the familial chylomicronemia syndrome.
      ,
      • Gaudet D.
      • Alexander V.J.
      • Baker B.F.
      • Brisson D.
      • Tremblay K.
      • Singleton W.
      • et al.
      Antisense inhibition of apolipoprotein C-III in patients with hypertriglyceridemia.
      ,
      • Huynh K.
      Gene therapy. Inhibiting apoC-III synthesis in patients with hypertriglyceridaemia.
      ,
      • Taskinen M.R.
      • Boren J.
      Why is apolipoprotein CIII emerging as a novel therapeutic target to reduce the burden of cardiovascular disease?.
      ], particularly considering that plasma APOC3 levels are strong and independent predictors of total and cardiovascular mortality in patients with established CAD [
      • Olivieri O.
      • Martinelli N.
      • Girelli D.
      • Pizzolo F.
      • Friso S.
      • Beltrame F.
      • et al.
      Apolipoprotein C-III predicts cardiovascular mortality in severe coronary artery disease and is associated with an enhanced plasma thrombin generation.
      ].
      Fig. 2
      Fig. 2The LPL-APOC3-APOA5-ANGPTL4 pathway. The lipoprotein lipase (LPL), a key enzyme in reducing plasma triglycerides, is attached to the capillary endothelium by the protein GPIHBP1. LPL acts by hydrolyzing the triglycerides present in the triglyceride-rich lipoproteins (VLDL and chylomicrons), and is critically controlled by the apolipoproteins APOC3 and APOA5, as well as by circulating angiopoetin like protein 4 (ANGPTL4). APOC3 and ANGPTL4 inhibit LPL, while APOA5 has a stimulatory effect. LoF mutations in APOC3 and in ANGPTL4 are therefore associated with low plasma triglycerides and protection from CAD, while LoF mutations in APOA5 and LPL are associated with high plasma triglycerides and increased CAD risk. Such mutations, discovered through NGS, have been used as proxies to infer causality of triglyceride-rich lipoproteins in CAD, which appears mediated by their cholesterol content (see text).

      4.4 The key role of “human knock-outs”

      Of note, the three examples outlined above (anti-PCSK9, anti-Lp(a), and anti-APOC3 novel biologic therapies) well illustrate the extraordinary potential of genomics to guide efficient drug development [
      • Plenge R.M.
      • Scolnick E.M.
      • Altshuler D.
      Validating therapeutic targets through human genetics.
      ], by discerning causal pathways, as well as by identifying genetic variations that can anticipate potential efficacy and safety of targeted inhibitory compounds [
      • Stitziel N.O.
      • Kathiresan S.
      Leveraging human genetics to guide drug target discovery.
      ]. Indeed, extremely useful in this sense has been the discovery through NGS of individuals carrying rare LoF mutations in PCSK9, LPA, and APOC3 [
      • Khera A.V.
      • Kathiresan S.
      Genetics of coronary artery disease: discovery, biology and clinical translation.
      ], representing “experiment of nature” or “human knock-out” [
      • Kaiser J.
      The hunt for missing genes.
      ], that not only are protected against CAD, but also live well without a given protein.

      5. Conclusions and future perspectives

      The last decade has witnessed unprecedented advances in understanding of the genetic architecture of CAD, which appears far more complex than expected. Regarding prediction, although a number of genetic markers have been identified through GWAS and incorporated into promising genetic risk scores, for the moment their use in clinical practice cannot be recommended. On the other hand, the impressive technological progress in human genomics has already provided important insights into disease pathobiology and novel therapeutic approaches. A lot of work remains to be done, particularly regarding the loci whose mechanistic link to CAD is still unknown. These loci are of paramount interest for future studies aimed to dissect new pathways, and, possibly, new therapeutic targets. For example, virtually nothing is known about the possible mechanism underlying the strong association (P = 1.8 × 10−42) between the 6p24.1 locus (i.e. the second most often identified after the 9p21.3, containing the PHACTR1 gene encoding for phosphatase and actin regulator 1) and CAD [
      • Holdt L.M.
      • Teupser D.
      From genotype to phenotype in human atherosclerosis—recent findings.
      ]. Also, additional efforts are needed to elucidate CAD “missing heritability” [
      • Zuk O.
      • Schaffner S.F.
      • Samocha K.
      • Do R.
      • Hechter E.
      • Kathiresan S.
      • et al.
      Searching for missing heritability: designing rare variant association studies.
      ], requiring not only extremely large sample size (hundred of thousands, at minimum) and “deep” sequencing, but also “deep phenotyping”, i.e. meticulous gathering of clinical details at individual level [
      • Delude C.M.
      Deep phenotyping: the details of disease.
      ,
      • Robinson M.R.
      • Wray N.R.
      • Visscher P.M.
      Explaining additional genetic variation in complex traits.
      ]. Indeed, for example, most studies published so far have merged “CAD” and “MI” phenotypes. While instrumental to increase sample size, this approximation is intrinsically unable to dissect pathways involved in atheroma development (CAD) rather than in thrombotic complications (MI), which are expected to overlap only partially. To this end, an increasing participation of clinicians in large genomic studies, along with molecular biologists, epidemiologists, and bioinformatics, should be encouraged.

      Acknowledgments

      This work was performed (in part) in the LURM (Laboratorio Universitario Ricerca Medica) Research Center, University of Verona. This work was partially supported by the Cariverona Foundation (n. 2014.0851 and 2015.0872).

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