Defining and Controlling Severe Familial Hypercholesterolemia Raul D. Santos MD, PhD InCor-University of Sao Paulo Hospital Israelita Albert Einstein Brazil 1
Disclosure Honoraria received for consulting, speaker or researcher activities : Astra Zeneca, Amgen, Boehringer-Ingelheim, Cerenis, Eli Lilly, Genzyme, Kowa, Pfizer, Sanofi/Regeneron. 2
Familial Hypercholesterolemia: Need for Risk Stratification Elevated lifetime risk of cardiovascular disease However, heterogeneity in this risk LDL levels Other risk factors Susceptibility= subclinical disease Newer treatments PCSK9 inhibitors 6-14,000 US dollars year Mipomersen/Lomitapide US- 150-360,000 year
Higher LDL-C = Greater Risk
Cumulative LDL-C (mmol) Coronary disease & death before age 20 Untreated coronary disease before age 55/60 HOZ Untreated Treat at 10yrs Non FH Treat at 18yrs Homozygous FH Heterozygous FH 200 150 100 12.5yrs Start low dose statin Threshold for CHD Start high dose statin 35yrs 48yrs 53yrs 55yr Female sex Smoking Hypertension Diabetes Triglycerides HDL-C Lipoprotein(a) 50 0 Without FH 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 Age in years Years Age Adapted from Horton et al.
CVD risk vs. non severe FH 1.25 [95% CI: 1.05-1.51], p= 0.015 Besseling et al. Atherosclerosis 2014; 233 219-223 6
Overlap in LDL-C Between Homozygous and Heterozygous FH
Number of patients Distribution of serum total cholesterol levels in normal subjects, and heterozygous and homozygous FH patients 100 90 80 Normal Heterozygous FH Homozygous FH 70 60 50 40 30 20 10 0 0 2.6 (100) 5.2 (200) 7.8 (300) 10.3 (400) 12.9 (500) 15.5 (600) 18.1 (700) Serum cholesterol mmol/l (mg/dl) 20.7 (800) 23.3 (900) 25.8 (1000) Harada-Shiba et al. J Atheroscler Thromb 2012;19:1043-1060
Molecular Defect and LDL-C Phenotype Santos RD et al Lancet Diab Endocrinol 2016;4: 850-61
Other Risk Factors The usual suspects
Risk factors for CHD in Genotyped FH Patients Besseling et al. Atherosclerosis 2014; 233 219-223
jou r n al h o m ep ag e: w w w.el sev i er.co m /l o cat e/at h er o scl er o si s Predictors of cardiovascular events after one year of molecular screening for Familial hypercholesterolemia P~amela R.S. Silva a, *, Cinthia E. Jannes a, Julia D.C. Marsiglia a, Jose E. Krieger a, Raul D. Santos b, Alexandre C. Author's Pereira a Personal Copy 148 a Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of S~ao Paulo Medical School Hospital, S~ao Paulo, Brazil Index Cases b Lipid Clinic, Heart Institute (InCor), University ofp.r.s. S~ao Silva Paulo et Medical al. / Atherosclerosis School Hospital, 250 (2016) S~ao144e150 Paulo, Brazil Table 5 Variables associated w ith CV events in index cases presenting or not mutations after univariate and multivariate logistic regression. a r t i c l e i n f o a b s t r a c t OR a 95%CI p value c OR b 95%CI p value Mutation Article þ history: 4.35 Background 1.45e 13.07 and aims: This0.01 study reports the first year follow - up of individuals enrolled in Brazil s Age (years) Received 17 March 2016 1.02 0.99e 1.05 0.10 cascade screening program for Famili al Hypercholester olemi a (FH), Hipercol Brasil. Predict ors Gender (male) 1.93 0.83e 4.47 0.12 Received in revised form Hypertension 1.28 occur rence 0.50e 3.27 of cardiovascular 0.59(CV) events in individuals screened for FH w ere studied. Methods: Th 9 May 2016 Previous CVD 2.75 open prospective 1.17e 6.43 cohor t of0.01 individuals who w ere included in a cascade genetic screening program Accepted 11 May 2016 Tobacco consumption (current and former) 0.87 The first 0.34e prospective 2.25 follow0.77 -up w as carried out one year after patien ts received their genetic test Family Available history of online CVD 15 May 2016 1.84 0.55e 6.07 0.31 Individuals included in this study w ere index cases (probands) and relatives w ith identi fied (M þ ) Xanthelasmas 2.70 0.82e 8.86 0.10 Corneal genetic mutation s (M ). Logistic regression analysis w as perform ed to determine predictive va Keywords: arcus 7.33 2.63e 20.44 0.01 9.39 2.46e 35.82 0.01 Tendon xanthomas 2.93 for the0.76e occurrence 11.22 of CV events 0.11 censored at one-year of follow - up. Familial hypercholest erolemia TC 1.00 Cascade screening Results: 0.99e A total 1.01 of 818 subjects 0.88 w ere included, 47 first CV events w ere ascertained, w ith 14 (29.7% LDL-C 1.01 1.00e 1.02 0.01 Cardiovascular diseases fatal. For index cases, the only factor independently associated w ith increased risk of CV events w HDL-C 0.95 0.91e 0.99 0.01 0.95 0.90e 0.99 0.04 TG Cardiovascular disease predictors 1.00 presence 0.99e of1.01 corneal arcus 0.20 (OR: 9.39; 95%CI: 2.46e 35.82). There w as an inverse association of CV Index patient w ith higher HDL-cholesterol levels (OR: 0.95; 95%CI: 0.90e 0.99). For M þ relatives, risk factors ass a Univariate Logistic Regression Analysis. b Multivariate Logistic Regression Analysis (Adjusted for age, gender, w ithhdl-c, increased corneal CV arcus, events previous risk CVD). w ere diabetes mellitus (OR: 7.97; 95%CI: 2.07e 30.66) and tobacc c p value < 0.05. sumption (OR: 3.70; 95%CI: 1.09e 12.50). Conclusions: A high one-year incidence of CV events w as found in this cascade-screening coho dictors of events differed bet w een index cases and relatives and can be useful for the developm Table 6 preventive efforts in this highly susceptible group of individuals. Variables associated w ith CV events in relatives w ith positive mutations after univariate and multivariate logistic regression. Silva P et al. Atherosclerosis 2016;250:144-150 2016 Elsevier Ireland Ltd. All rights re OR a 95%CI p value c OR b 95%CI p value
Mutation þ 4.35 1.45e 13.07 0.01 Age (years) 1.02 0.99e 1.05 0.10 Gender (male) 1.93 0.83e 4.47 0.12 Hypertension 1.28 0.50e 3.27 0.59 Previous CVD 2.75 1.17e 6.43 0.01 Tobacco consumption (current and former) 0.87 0.34e 2.25 0.77 Family history of CVD 1.84 0.55e 6.07 0.31 Xanthelasmas Predictors of cardiovascular 2.70 0.82e events 8.86 after 0.10 one year of molecular Corneal arcus 7.33 2.63e 20.44 0.01 9.39 2.46e 35.82 0.01 Tendonscreening xanthomas for Familial 2.93hypercholesterolemia 0.76e 11.22 0.11 TC 1.00 0.99e 1.01 0.88 LDL-C 1.01 1.00e 1.02 0.01 HDL-CP~amela R.S. Silva a, *, Cinthia 0.95 E. Jannes a 0.91e 0.99, Julia D.C. 0.01Marsiglia 0.95, Jose E. 0.90e Krieger a 0.99, 0.04 TG 1.00 0.99e 1.01 0.20 Raul D. Santos b, Alexandre C. Pereira a a Univariate Logistic Regression Analysis. b Multivariate a Laboratory LogisticofRegression Genetics and Analysis Molecular (Adjusted Cardiology, for age, gender, Heart HDL-C, Institute corneal (InCor), arcus, University previous CVD). of S~ao Paulo Medical School Hospital, S~ao Paulo, Brazil c p value b Lipid < 0.05. Clinic, Heart Institute (InCor), University of S~ao Paulo Medical School Hospital, S~ao Paulo, Brazil Table 6 Variables associated w ith CV events in relatives w ith positive mutations after univariate and multivariate logistic regression. a r t i c l e i n f o jou r n al h o m ep ag e: w w w.el sev i er.co m /l o cat e/at h er o scl er o si s Relatives a b s t r a c t OR a 95%CI p value c OR b 95%CI p value Article history: Background and aims: This study reports the first year follow - up of individuals enrolled in Brazil s Age (years) 1.03 1.01e 1.06 0.02 Received 17 March 2016 Gender (male) 3.14 cascade 1.13e screening 8.70 program 0.02 for Famili al Hypercholester olemi a (FH), Hipercol Brasil. Predict ors Received in revised form Hypertension 4.41 occur 1.58e rence 12.29 of cardiovascular 0.01 (CV) events in individuals screened for FH w ere studied. Methods: Th Diabetes 9 May 2016 10.25 open3.65e prospective 28.82 cohor0.01 t of individuals w7.97 ho w ere included 2.07e 30.66 in a cascade genetic 0.01 screening program Previous Accepted CVD 11 May 2016 6.02 1.92e 18.89 0.01 The first prospective follow -up w as carried out one year after patien ts received their genetic test TobaccoAvailable consumption online (current 15 May and 2016 former) 5.26 1.80e 15.33 0.01 3.70 1.09e 12.50 0.03 Family history of CVD 0.67 Individuals 0.22e 2.00 included in 0.47 this study w ere index cases (probands) and relatives w ith identi fied (M þ ) Xanthelasmas 1.37 genetic 0.29emutation 6.37 s (M 0.68 ). Logistic regression analysis w as perform ed to determine predictive va Keywords: Corneal arcus 4.03 for the 1.40eoccurrence 11.57 of CV 0.01events censored at one-year of follow - up. Familial hypercholest erolemia Tendon xanthoma 1.37 0.29e 6.36 0.68 TC Cascade screening Results: A total of 818 subjects w ere included, 47 first CV events w ere ascertained, w ith 14 (29.7% 0.99 0.99e 1.01 0.99 LDL-C Cardiovascular diseases fatal. For index cases, the only factor independently associated w ith increased risk of CV events w 1.01 0.99e 1.01 0.54 HDL-C Cardiovascular disease predictors 0.97 presence 0.93e 1.02 of corneal arcus 0.28(OR: 9.39; 95%CI: 2.46e 35.82). There w as an inverse association of CV TG Index patient 0.99 w ith0.97e higher 1.01 HDL-cholesterol 0.99 levels (OR: 0.95; 95%CI: 0.90e 0.99). For M þ relatives, risk factors ass a Univariate Logistic Regression Analysis. w ith increased CV events risk w ere diabetes mellitus (OR: 7.97; 95%CI: 2.07e 30.66) and tobacc b Multivariate Logistic Regression Analysis (Adjusted for age, hypertension, sumption diabetes, (OR: previous 3.70; CVD, 95%CI: tobacco 1.09e consumption 12.50). and corneal arcus). c p value < 0.05. Conclusions: A high one-year incidence of CV events w as found in this cascade-screening coho dictors of events differed bet w een index cases and relatives and can be useful for the developm preventive efforts in this highly susceptible group of individuals. nonfatal CV events in the first year of follow -up w as more than individuals [18e 21]. Indeed, xanthelasmas and corneal arcus formation, important markers of long term exposition to high Silva P et al. Atherosclerosis 2016;250:144-150 2016 Elsevier Ireland Ltd. All rights re tw ice in M þ IC than in affect ed relatives. The occurrence of coro- levelsof
Lipoprotein(a) Levels in Familial Hypercholesterolemia : An Important Predictor of Cardiovascular Disease Independent of the Type of LDL Receptor Mutation Figure 4 Kaplan-Meier Curves for CVD-Free Survival in Subjects With FH According to Lp(a) Levels and Type of Mutation The black solid line indicates null mutations and Lp(a) levels >50 mg/dl; the black dashed line indicates null mutations and Lp(a)... Alonso R et al. Journal of the American College of Cardiology, Volume 63, Issue 19, 2014, 1982-1989
Lp(a), FH and Myocardial Infarction Risk : Prospective Data Langested A et al. Lancet Diabetes Endocrinol. 2016 Jul;4(7):577-87
Secondary vs. Primary Prevention
Secondary vs. Primary Prevention in FH and Mortality in the UK: Effects of Statins N=3382 patients (FUP 1980-2006) 370 deaths Standardized mortality ratios All aged 20 79 years CHD mortality reduced by 37% (95% CI 7 56) from 3.4 to 2.1-fold excess. Primary prevention: 48% reduction in CHD mortality from 2.0-fold excess to none Secondary prevention: 25% reduction in CHD mortality from 5.2 (95% CI 3.4 7.6) to a 3.9-fold excess (95% CI 3.2 4.7) Neil et al Eur Heart J 2008; 29:2625 2633
Incidence of recurrent coronary events in young patients with premature coronary heart disease by presence of familial hypercholesterolemia (FH; n=1369). All Acute Coronary Syndrome Nanchen D et al. Circulation. 2016;134:698-709
Advanced Subclinical Coronary Atherosclerosis
Subclinical Coronary Atherosclerosis in FH Figure 2 A CAC= 40, 90 th % B Rocha,VZ Santos RD J Am Coll Cardiol. 2013 May 28;61(21):2193. 20
Gidding S et al. Circulation. 1998;98:2580-2583
Mangili LC et al. Atherosclerosis 2016 in press
FH mutation as a risk factor?
Risk of Coronary Artery Disease in those with Elevated LDL cholesterol ( 190 mg/dl) According to Familial Hypercholesterolemia Mutation Status LDL-C> 190 mg/dl FH mutation- FH Mutation+ LDL-C < 130 and FH mutation - N CAD free controls/n CAD Case 1264 (422/842) 73 ( 8/65) 7485 (5175/2310) OR for CAD (95% CI) 6.0 (5.2-6.9) P<0.001 22.3 (10-7-53.2) P<0.001 Reference P FH mutation+ vs. - LDL-C adjusted OR for CAD (95%CI) 0.001 1.6 (1.3-2.1) p<0.001 4.2 (1.9-10.4) P<0.001 Reference P FH mutation + vs. - 0.02 Adapted from Khera A et al. JACC online 3 April 2016 doi 10.1016/j.jacc.2016.03.520
Santos RD et al Lancet Diab Endocrinol 2016;4: 850-61
Risk Conditions to Consider Older > 40 years old without treatment Smoking, Male gender Lp(a)>50 mg/dl Low-HDL-C (<1mmol/L or 40 mg/dl), Hypertension Diabetes mellitus Family history of early cardiovascular disease in first degree relatives (<55 years old in males and < 60 years old in females) Chronic kidney disease (defined as an estimated glomerular filtration rare < 60 ml/min/1.73 m 2 BMI >30 kg/m 2 Santos RD et al Lancet Diab Endocrinol 2016;4: 850-61
Severe Familial Hypercholesterolemia-IAS At presentation (untreated LDL-C) LDL C >10 mmol/l (400 mg/dl) LDL-C >8.0 mmol/l (310 mg/dl) + one high risk condition LDL-C > 5 mmol/l (190 mg/dl) + two high risk conditions Realistic goal: reduce 50% LDL-C Ideal goal: LDL-C < 2.5 mmol/l (100 mg/dl) With subclinical atherosclerosis assessment Advanced subclinical atherosclerosis Coronary: A-Coronary artery calcium (CAC) score > 100 Agatston units, or > 75 th percentile for age and gender* Realistic goal: reduce 50% Ideal goal : LDL-C < 1.8 mmol/l (70 mg/dl) B-Computed tomography angiography (CTA) with obstructions > 50% or presence of nonobstructive plaques > one vessel. Presence of clinical atherosclerotic cardiovascular disease Realistic goal: reduce LDL- C 50% Ideal goal: LDL-C < 1.8 mmol/l (70 mg/dl) Santos RD et al Lancet Diab Endocrinol 2016;4: 850-61
Treatment
Heterozygous FH New Horizons: PCSK9 Inhibitors LDL-C values < 1.8 mmol/l (70 mg/dl) in refractory FH patients Rutherford-2 1 61-66% treated with evolocumab Odyssey FH I and II 2 60-68% in those receiving alirocumab 1-Raal et al. Lancet 2015; 385: 331-40. 2-Kastelein et al. Eur Heart J 2015; 36:2996-3003.
Treatment Algorithm Santos RD et al Lancet Diab Endocrinol 2016;4: 850-61
Conclusions: Severe Familial Hypercholesterolemia Elevated lifetime risk of cardiovascular disease However, heterogeneity in this risk LDL levels Other risk factors Susceptibility= subclinical disease Previous CVD Identify highest risk patients in order to have best treatment cost-effectiveness