Early cardiovascular risk factors in South Asians

Early cardiovascular risk factors in South Asians MINTU TURAKHIA, MD MAS Instructor of Medicine, Stanford University Director of Cardiac Electrophysiology, Palo Alto VA Research Chair, South Asian Heart Center Disclosures! Research support:! VA HSR&D Career Development Award! AHA National Scientist Development Grant! VA MERIT Award IIR04-248! El Camino Hospital Foundation! No other financial disclosures mintu@stanford.edu 2 Objectives! Scope and burden of CVD in South Asians! Screening and risk assessment program at SAHC! SAHC clinical findings! Future avenues for research Case! 33-year old nonsmoking engineer presents with chest pain, anterior ST elevation, tachycardia, and rales! Angiography demonstrated 3-vessel disease with proximal LAD occlusion! EF 40%! Total cholesterol 234, LDL 156, HDL 32, triglycerides 45! BMI 25 kg/m 2! Fasting blood sugar: 187 3 4

South Asia = Indian subcontinent! India, Pakistan, Sri Lanka, Bangladesh! 20% of global population! 2.5 million on United States! Heterogeneous (language, diet, culture, lifestyle) Epidemiology! South Asians have a four-fold higher risk of MI and cardiovascular death compared to Caucasians International prevalence of CV disease (SHARE study, Lancet 2000)! South Asians: 10.7%! Europeans 5.4%! Chinese 2.4% 5 6 CHD mortality in India 2.52500 M 2.02000 M 1.51500 M 1.01000 M 0.5500 M 2584 2034 By 2010, India will bear 1592 60% of the 1461 world s 1108 CAD 1175 849 1123 burden 926 619 743 556 1990 2000 2010 2020 (# in thousands) Men Women Total Ghaffar et al. BMJ 2004; 328:807-10 Epidemiology! Younger! Prone to have MI at earlier age (< 40 years in men)! 25% of MIs before age 40; 33% before age 45! Three-fold higher risk of second MI compared to Caucasians! Sicker! Anterior infarction! More left main and multivessel disease at time of cath! Present later in the course! Higher post-mi mortality! Younger at first heart failure hospitalization! Die earlier! Traditional risk factors do not entirely account for this discrepancy 7 8

Why are South Asians at high risk?! Three possibilities 1. Excess burden of conventional risk factors 2. Greater susceptibility to similar burden of risk factors 3. Unrecognized ( emerging ) risk factors! May be genetic, environmental, or both Framingham Risk Factors! Smoking! Hypertension! High total cholesterol or LDL! Low HDL! Diabetes Mellitus! Age! Gender 9 10 Prevalence of Framingham risk 35 30 25 20 15 10 5 0 Framingham Offspring Study Asian Indians 10-year risk of 33-year old male with anterior MI and 3VD: 1 percent Smoking HTN LDL > 160 TG > 250 (Enas, Indian Heart J, 1996) Risk Factors for Early Myocardial Infarction in South Asians Compared With Individuals in Other Countries Joshi, et al with Yusuf (JAMA 2007) Context South Asians have high rates of acute myocardial infarction (AMI) at younger ages compared with individuals from other countries but the reasons for this are unclear. Objective To evaluate the association of risk factors for AMI in native South Asians, especially at younger ages, compared with individuals from other countries. Design, Setting, and Participants Standardized case-control study of 1732 cases with first AMI and 2204 controls matched by age and sex from 15 medical centers in 5 South Asian countries and 10 728 cases and 12 431 controls from other countries. Individuals were recruited to the study between February 1999 and March 2003. Main Outcome Measure Association of risk factors for AMI. Results The mean (SD) age for first AMI was lower in South Asian countries (53.0 [11.4] years) than in other countries (58.8 [12.2] years; P.001). Protective factors were lower in South Asian controls than in controls from other countries (moderate- or high-intensity exercise, 6.1% vs 21.6%; daily intake of fruits and vegetables, 26.5% vs 45.2%; alcohol consumption once/wk, 10.7% vs 26.9%). However, some harmful factors were more common in native South Asians than in individuals from other countries (elevated apolipoproteinb100/apolipoproteina-iratio,43.8%vs31.8%;historyofdiabetes,9.5%vs7.2%). Similar relative associations were found in South Asians compared with individuals from other countries for the risk factors of current and former smoking, apolipoprotein B100/ apolipoprotein A-I ratio for the top vs lowest tertile, waist-to-hip ratio for the top vs lowest tertile, history of hypertension, history of diabetes, psychosocial factors such as depression and stress at work or home, regular moderate- or high-intensity exercise, and daily intake of fruits and vegetables. Alcohol consumption was not found to be a risk factor for AMI in SouthAsians.Thecombinedoddsratioforall9riskfactorswassimilarinSouthAsians(123.3; 95% confidence interval [CI], 38.7-400.2] and in individuals from other countries (125.7; 95% CI, 88.5-178.4). The similarities in the odds ratios for the risk factors explained a high and similar degree of population attributable risk in both groups (85.8% [95% CI, 78.0%- 93.7%] vs 88.2% [95% CI, 86.3%-89.9%], respectively). When stratified by age, South Asians had more risk factors at ages younger than 60 years. After adjusting for all 9 risk factors, the predictive probability of classifying an AMI case as being younger than 40 years was similar in individuals from South Asian countries and those from other countries. Conclusion The earlier age of AMI in South Asians can be largely explained by higher risk factor levels at younger ages. JAMA. 2007;297:286-294 Author Affiliations: Department of Medicine, Gov- www.jama.com sity, Karachi, Pakistan (Dr Kazmi); Nepal Hyperten-! International case-control study; includes 5 South Asian countries! Cases: 1700 pts of South Asian origin after first MI! Controls:! Non South Asian with MI! South Asians without MI 11

Interheart study! Protective factors lower in South Asians! Exercise 6% v. 21%! Daily fruits and vegetables 26% v. 45%! Alcohol!"once/week 11% v. 27%! Some harmful factors more common! Diabetes 10% v. 7%! High ApoB100 /Apo A-I (LDL:HDL) ratio 44% v. 32%! Lower mean age of MI (53 vs 59 yrs)! Higher levels of risk factors at younger age (< 60 and < 40)! 9 conventional risk factors accounted for 86% of population-attributable risk of early MI Limitations! Few South Asian subjects drawn from Europe or North America! 14% unmeasured attributable risk in model; could misclassify 1 out of 6 South Asians! Possible added prognostic value of lipid subparticles, insulin resistance, and additional biomarkers! Epidemiology in United States not well characterized 13 14 Hospitalization Rates for CAD in California PMR = % of deaths from CAD in ethnic group % of deaths from CAD in whole population Likelihood of hospitalization (vs. White) 5 4 3 2 1 0 3.8 1.1 1.2 1.0 0.6 White Asian Indian Chinese Japanese Filipino (Palaniappan, L, Ann Epid 2004) (Palaniappan, L, Ann Epid 2004) 15 16

Prevalence of Diabetes Mellitus and Related Conditions in Asian Indians Living in the United States Rajesh Venkataraman, MD, MPH, Navin C. Nanda, MD, Gurpreet Baweja, MD, Naresh Parikh, MD, and Vishal Bhatia, MD Prevalence of Diabetes Mellitus and Related Conditions in Asian Indians Living in the United States Rajesh Venkataraman, MD, MPH, Navin C. Nanda, MD, Gurpreet Baweja, MD, Naresh Parikh, MD, and Vishal Bhatia, MD TABLE 1 Baseline Characteristics of Participants Characteristics Total (n 1,046) Diabetics (n 192) Nondiabetics (n 854) Men 51% 62.5% 51% Women 49% 37.5% 49% Mean age (yrs)* 52.8 11.3 57.2 9.5 51.9 11.4 Mean body mass index (kg/m 2 )* 26.1 4.7 26.4 4.5 26.0 4.7 Hypertension 23.7% 45.2% 18.9% Hypercholesterolemia 18.5% 27.3% 16.4% Myocardial infarction 6.5% 16.3% 4.3% Coronary artery intervention 10.7% 21% 8.4% History of dialysis 2.7% 8.4% 1.4% Stroke 2.9% 5.2% 2.2% Family history of diabetes mellitus 22.7% 53.1% 14% *Figures are mean SD. p 0.001, independent sample t test between diabetic and nondiabetic groups. p 0.05, independent sample t test between diabetic and nondiabetic groups. (Venkataraman, Am J Cardiol 2004) (Venkataraman, Am J Cardiol 2004) 17 Where is the unmet need?! More South Asians have CAD & present at an earlier age! Conventional risk factors, novel risk factors, or both?! Treated or untreated?! When does it start?! Role of socioeconomic status and access to care?! Where are the high-risk people? How can we get to them? Barriers to care! Lack of physician awareness of need for early screening and aggressive treatment in South Asians! Patients don t know to ask! No focused resource center for clients and physicians! 2005: Creation of South Asian Heart Center 19 20

The mission of the South Asian Heart Center is to reduce the high incidence of coronary disease among South Asians through a comprehensive, culturallyappropriate program incorporating education, advanced screening, lifestyle changes, and case management. Prevention Program Methodology! Easy sign-up at website for advanced screening! ASSESSMENT: Guided heart-heath risk assessment Advanced lab Brief physical exam! IDENTIFICATION: Detailed risk & risk factor stratification! MANAGEMENT: Customized risk-factor mgmt. plan & followthrough Results consultation with nurse practitioner Nutrition consultations with registered dietician Frequent follow-up over 1 year with heart health coaches Retest tracking, facilitation, communicating results 21 22 Metabolic Evaluation Metabolic Syndrome & Risk Marker Evaluation 23 24

SAHC evaluation process! Sign up online! 30-40 minute risk assessment by phone! Lab tests (12-hour fasting)! 30-40 min appointment to discuss results and recommendations (not prescription)! Medication, exercise, diet, stress reduction! Sent back to referring MD for interventions (MD emailed all reports and recommendations as well)! Nutrition appointment! Follow-up! Did you see your doctor?! Are you doing the things that were recommended? SAHC Experience: Bay Area South Asian Study! Started initial health screenings starting in 2006! 1 year ago: 800 participants! December 2008: 2100 participants! > 3500 patient encounters! Anthropomorphic, demographic, and medical information collected! Fasting blood specimen collected for cholesterol and metabolic profile screening! DNA banked for a sub-cohort that consented 25 26 Research aims! Define prevalence of metabolic syndrome and its components in cohort! Define burden of CV risk factors and metabolic syndrome in youngest participants SAHC MetS study! From Jan 2006-Dec 2008: 1445 completed screening program including laboratory testing! Lab testing: Berkeley Heart Lab panel! Fasting lipids! Glucose! Lipid subfractions! Inflammatory markers! Plasma insulin (E Flowers, in press, 2010) 27 28

Metabolic Syndrome (NCEP ATP III) Any 3 of the 5 Abdominal obesity > 102 cm for males and >88 cm for women Elevated Triglycerides >150 mg/dl Low HDL cholesterol (<40 mg/dl for men, <50 mg/dl for women) Elevated Blood Pressure (>130/85 mm Hg) Elevated fasting glucose (>110 mg/dl) Shown to markedly underestimate prevalence of Metabolic Syndrome Metabolic Syndrome (IDF) Waist Circumference (> 90 cm for men, >80 cm for women) + Any two of following Elevated Fasting Glucose >100 mg/dl Elevated Triglycerides (> 150 mg/dl) Elevated Blood Pressure ( > 130/85 mm Hg) Low HDL (<40 for men, <50 for women) Characteristics Mean ± SD or n (%) Men (n = 1012) Women (n = 433) p-value Age (years) 43 ±10 43 ±10 43 ±11 0.6 Birth country (n = 849) South Asia 763 (89) 526 (90) 237 (87) 0.6 United States 40 (5) 26 (4) 14 (5) 0.5 Married 1343 (93) 947 (94) 396 (91) 0.2 Education Less than Bachelorʼs 52 (4) 21 (<1) 31 (7) <0.05 Bachelorʼs 326 (23) 175 (17) 151 (35) <0.05 Graduate/Masterʼs 932 (65) 707 (70) 225 (52) <0.05 PhD/post-grad 132 (9) 106 (11) 25 (6) <0.05 Behaviors Current smoking 54 (4) 49 (5) 5 (1) <0.05 Former smoking 187 (13) 177 (17) 10 (2) <0.05 Family history of CVD Parent 811 (56) 560 (55) 251 (58) 0.3 Sibling (n = 678) 274 (40) 181 (39) 93 (43) 0.5 Regional data among Indians Region % Northern 22% Southern 40% Eastern 5% Western 27% Central 3% (E Flowers, in press, 2010) 32

Characteristics Mean ± SD or n (%) Men (n = 1012) Women (n = 433) p-value Age (years) Clinical variables TC (mg/dl) 43 ±10 190 ± 37 43 ±10 192 ± 37 43 ±11 185 ± 35 0.6 <0.05 LDL (mg/dl) 116 ± 31 118 ± 32 111 ± 29 <0.05 HDL (mg/dl) 45 ±12 42 ± 10 53 ± 13 <0.05 TG (mg/dl) 144 ± 93 159 ±100 110 ± 63 <0.05 Glucose (mg/dl) 90 ± 16 92 ± 18 87 ± 12 <0.05 Systolic blood pressure (mmhg) 118 ± 17 120 ± 17 113 ± 17 <0.05 Diastolic blood pressure (mmhg) 76 ± 11 78 ± 11 72 ± 11 <0.05 BMI (kg/m 2 ) 25.7 ± 3.7 25.8 ± 3.5 25.6 ± 4.1 0.3 Waist circumference (cm) 88 ± 13 91 ± 12 82 ± 12 <0.05 Metabolic syndrome 387 (27) 315 (31) 72 (17) <0.05 Gender differences (for women compared to men) Characteristic Unadjusted OR (95% CI) Adjusted* OR (95% CI) TC > 200mg/dl 0.6 (0.5, 0.8) 0.7 (0.5, 0.9) LDL > 160mg/dl 0.4 (0.2, 0.6) 0.4 (0.2, 0.6) HDL < 40mg/dl (men) < 50mg/dl (women) 1.1 (0.9, 1.3) 1.0 (0.8, 1.3) TG > 200mg/dl 0.3 (0.2, 0.4) 0.3 (0.2, 0.4) Glucose > 126 mg/dl 0.3 (0.1, 0.8) 0.3 (0.1, 0.7) Blood pressure > 140/90 0.5 (0.3, 0.7) 0.5 (0.4, 0.8) BMI > 25 0.7 (0.6, 0.9) 0.8 (0.6, 1.0) WC > 90cm (men) >80cm (women) 1.2 (0.9, 1.5) 1.3 (1.0, 1.6) *adjusted for age, smoking, and education level (E Flowers, in press, 2010) (E Flowers, in press, 2010) Relationship of HDL and HDL2b (n=798; from 2008) Clinical characteristics HDL 2b: > 20% desirable; < 10%: high risk; Only 77% of variability of HDL-2b is explained by HDL-C 44 of 216 had low HDL2b with normal HDL 1, HDL may be normal despite impaired reverse cholesterol transport 2. HDL-2b may add prognostic value, especially in borderline or low-normal HDL 35 (E Flowers, in press, 2010)

Framingham risk factors Metabolic syndrome: # criteria (ATP III) 35 30 25 20 15 Framingham Offspring Study Asian Indians 39% 26% 17% Men 27% 27% 28% Women 28% 26% 21% 17% p < 0.001 between sexes Waist > 40 M. 35 F HDL! 40M, 45F Hypertension TG " 150 Glu " 100 10 13% 5 6% 5% 0 Smoking HTN LDL > 160 TG > 250 (Enas, Indian Heart J, 1996) 0% 0 1 2 3 4 5 # of metabolic risk factors 1% 0% 37 38 Metabolic Syndrome Phenotypes n(%) Men Women p-value* n = 854 n = 589 n = 265 WC only 212 (25) 106 (18) 106 (40) <0.003 WC + HTN 63 (7) 47 (8) 16 (6) 0.3 Metabolic Syndrome Prevalence WC + HDL 102 (12) 59 (10) 43 (16) <0.003 WC + TG 65 (8) 47 (8) 18 (7) 0.5 WC + glu 30 (4) 19 (3) 11 (4) 0.5 WC + HTN + HDL 37 (4) 27 (5) 10 (4) 0.6 WC + HTN + TG 28 (3) 23 (4) 5 (2) 0.1 WC + HTN + glu 19 (2) 15 (3) 4 (2) 0.3 WC + HDL + TG 137 (16) 111 (19) 26 (10) <0.003 WC + HDL + glu 15 (2) 10 (2) 5 (2) 0.8 WC + TG + glu 22 (3) 16 (3) 6 (2) 0.7 WC + HTN + HDL + TG 55 (6) 46 (8) 9 (3) 0.02 WC + HTN + HDL + glu 10 (1) 9 (2) 1 (<1) 0.1 WC + HTN + TG + glu 13 (2) 12 (2) 1 (<1) 0.07 WC + HDL + TG + glu 22 (3) 20 (3) 2 (1) 0.02 WC + HTN + HDL +TG + glu 24 (3) 22 (4) 2 (1) 0.02 *Bonferroni corrected p-value for 16 comparisons is 0.003 *Population based sample **Convenience sample

Summary! High prevalence of metabolic syndrome (31%M, 17%F)! Very high prevalence of increased waist circumference based on IDF/WHO cutpoints (58%M, 62%F)! Prevalence of high TG much higher in men (23%M, 8%F)! Only 13% with elevated fasting glucose! HTN not as prevalent (16%M, 9%F)! Most common MetS phenotype was high WC + low HDL + high TG! Obesity, dyslipidemia markedly out of proportion to measurable insulin resistance What about young South Asians? (When does it start?)! Of 2096 participants, 678 were below age 40 at time of screening 41 NCEP/ATP III MetS Components in SAHC cohort, age < 40 Component Total Men Women Low HDL (<40 for women,<50 for men) 48.8% 47.9% 51.0% High Triglycerides (>150 mg/dl) 36.1% 46.6% 11.4% High Systolic BP (> 130mm Hg) 18.1% 20.7% 16.1% High Diastolic BP (>85 mm Hg) 16.1% 20.7% 5.5% High Waist Circumference (>102 cm for men and >88cm for women) High glucose 11.2% 10.1% 13.9% (>110mg/dL) 3.24% 3.99% 1.49% Prevalence of # of Components of Metabolic Syndrome (NCEP) Number Total Men Women 0 31.4% 26.7% 43.0% 1 30.5% 27.9% 30.5% 2 25.0% 28.8% 15.5% 3 9.4% 12.2% 2.6% 4 3.4% 4.0% 2.1% 5 0.3% 0.4% 0% Metabolic Syndrome: 13.1% of population; 16.6% of men and 4.7% of women

IDF MetS Components in SAHC cohort, age < 40 Total Men Women High Waist Circumference +0 risk factors High Waist Circumference + 1 risk factor High Waist Circumference +2 risk factors High Waist Circumference + 3 risk factors High Waist Circumference +4 risk factors 31.0% 26.1% 42.6% 34.7% 30.7% 44.1% 24.5% 30.5% 10.4% 8.11% 10.5% 2.5% 1.78% 2.3% 0.50% Prevalence of Metabolic Syndrome: 34.4% of population, 43.3% of men, 13.4% of women Lp(a) -2-3 x greater risk of MI -Primarily genetic -Associated with cardiovascular disease inhibit fibrinolysis increase LDL oxidation increase deposition of cholesterol -Lp(a) > 20 mg/dl considered abnormal Average Total Men Women Lp(a) (mg/dl) 29.2+32.2 26.1+28.4 37.7+39.7 Total Men Women Lp(a) >20 mg/dl43.4% 41.0% 50.0% Relationship of metabolic syndrome to dyslipidemia # MetS criteria 0 1 2 3 4 5 p = Total Chol LDL LDL iiia+b (%) HDL LDL:HDL HDL2B (%) TGs 196 196 187 199 191 220 NS 122 120 112 128 108 142 NS 15 19 25 27 27 34 <0.01 52 48 41 40 38 32 0.01 2.3 2.5 2.7 3.2 2.8 4.5 <0.01 18 14 11 11 9 8 <0.01 109 166 167 189 238 256 NS Relationship of metabolic syndrome to inflammatory and thrombotic biomarkers # MetS Criteria 0 1 2 3 4 5 Lp(a) Homocysteine CRP Fibrinogen 41.4 38.6 32.5 31.7 23.9 10.5 11 10.6 12 12.7 12.5 13.5 2.1 1.5 2.4 2.4 2.6 7.8 321.7 336.3 339.2 345 385.6 410.5 Adjusting for statin, niacin, folate, and B12 therapy, mean Lp(a) fell 3.39 mg/dl for each extra component of MetS, while mean homocysteine and CRP rose 0.35 umol/ml and 0.24 mg/l, respectively (for all, p < 0.001 for trend). (Divakaruni M, accepted for ACC 2010) 47 48

Conclusions! In this cohort of young- and middle-aged South Asian participants presenting for screening:! Large burden of traditional risk factors present at an early age! Consistent with Interheart (Yusuf et al), Atlanta & SHARE (Canada) studies! Occurs despite higher educational status and higher rates of private insurance and access to care! Abnormal waist circumference, LDL, HDL across all age ranges. Affected younger patients are more likely male! High prevalence of metabolic syndrome components without hyperglycemia Risk stratification and treatment of the Bay Area South Asian population is an unmet clinical need 49 Recommendations! Role of generalized advanced lipid and biomarker screening is controversial in all patients, including South Asians! South Asians adults, even age 20-40, should have a waist circumference, lipid panel, and blood pressure performed! Exercise, caloric restriction, weight loss! Lp(a) may be a useful adjunct, but prognosis and management of isolated elevated Lp(a) is unclear It s in the genes... Polymorphisms uniquely associated with CAD in South Asians:! Beta-fibrinogen (455GA, 148CT)! Factor VII (10bp promotor, R353Q; protective?)! ATP-binding cassette transporter (237indelG; 8994AG)! Platelet glycoprotein IIIa (A2 variant)! Apolipoprotein E (E3/E4 genotype)! Thrombomodulin (Ala455Val in smokers)! Endothelial nitric oxide synthase (Glu298Asp)! Tumor necrosis factor 2 (MM variant)! PECAM-1 (Leu125Val)! Cardiomyopathy (not CAD): Protein myosin binding chain PMBC3 (Nature Genetics, 2009) 51 52

Telomere shortening occurs in Asian Indian Type 2 diabetic patients. Adaikalakoteswari A, Balasubramanyam M, Mohan V. METHODS: Measure of average telomere size, in leucocyte DNA. Type 2 diabetic patients without any diabetes-related complications (n = 40) and age- and sex-matched control nondiabetic subjects (n = 40) were selected from the Chennai Urban Rural Epidemiology Study (CURES). RESULTS: Mean (+/- SE) TRF lengths of the Type 2 diabetic patients (6.01 +/- 0.2 kb) were significantly shorter than those of the control subjects (9.11 +/- 0.6 kb) (P = 0.0001). Among the biochemical parameters, only levels of TBARS showed a negative correlation with shortened telomeres in the diabetic subjects (r = -0.36; P = 0.02). However, telomere lengths were negatively correlated with insulin resistance (HOMA-IR) (r = -0.4; P = 0.01) and age (r = -0.3; P = 0.058) and positively correlated with HDL levels (r = 0.4; P = 0.01) in the control subjects. Multiple linear regression (MLR) analysis revealed diabetes to be significantly (P < 0.0001) associated with shortening of TRF lengths. Thank you CONCLUSIONS: Telomere shortening occurs in Asian Indian Type 2 diabetic patients. Diabet Med. 2005 Sep;22(9):1151-6. 54