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High prevalence of PLIN gene & Metabolic risk factors among Children initiating Antiretroviral therapy in south India P. Chandrasekaran, A. Shet, K. Ramesh,

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Presentation on theme: "High prevalence of PLIN gene & Metabolic risk factors among Children initiating Antiretroviral therapy in south India P. Chandrasekaran, A. Shet, K. Ramesh,"— Presentation transcript:

1 High prevalence of PLIN gene & Metabolic risk factors among Children initiating Antiretroviral therapy in south India P. Chandrasekaran, A. Shet, K. Ramesh, P.K.Bhavani, R. Srinivasan, G. Sanjeeva, P. Gangadevi, E. Suresh, C. Chandrasekar, C. Wanke, S. Swaminathan National Institute for Research in Tuberculosis (ICMR), India

2 Introduction Antiretroviral therapy – Overall reduction of morbidity & mortality – lead to development of Metabolic syndrome / HIV Associated Lipodystrophy Syndrome (HALS) Similar exposure to drugs, diet, socioeconomic status, not every child on ART develops HALS Host Genetic factors

3 Host Genetic factors & HALS Polymorphisms in APOA5 APOC3, APOE & CETP Perilipin gene (PLIN), major protein coating intracellular lipid droplets, modulates adipocyte lipolysis Arnedoa M et al.. Pharmacogenetics and Genomics 2007, Ordovas JM et al. Curr Opin Lipidol 2007; 18: 152 Qi L et al. Clin Genet 2004; Minor allele at PLIN (G>A) is associated with higher risk of metabolic syndrome - Higher TGL / Lower HDL-c / Higher insulin resistance No Indian Studies

4 India “HALS” study Prospective study To determine the incidence & risk factors of dyslipidemia, insulin resistance & body shape changes Children 2-12 years, initiating ART (2NRTI + 1 NNRTI) NIRT, Chennai & SJRI, B’lore

5 Objectives To assess the baseline risk factors of metabolic syndrome, namely blood lipid profile, glucose, insulin resistance and waist: hip ratio, among children before they initiate first-line antiretroviral therapy To look for the presence of polymorphisms of specific gene PLIN - associated with metabolic syndrome - in these children

6 Data collection Anthropometry, body circumferences & skinfold thickness 24-hour dietary recall and Food security Fasting blood for Serum lipids, Glucose, Insulin, high- sensitivity C-reactive protein (hs-CRP) CD4 cell count & HIV-1 viral load PLIN Gene polymorphisms RT- PCR Homeostatic model assessment-Insulin resistance (HOMA-IR) estimated using the formula [fasting glucose (mg/dL) X insulin (uU/mL)]/405

7 Study population 218 Children living with HIV infection – mean age: years (2-12years) – mean body weight : kgs – mean CD4%: 15% (1-54%) – median viral load : 179,136 copies/ml (46,090 – 574,494) 60% WHO Clinical Stage III or above 16% co-infected with Tuberculosis

8 Study population 97% through Vertical Transmission – Only 35% mothers diagnosed antenatal 61% were vaccinated up-to-date 40% households food insecure – 15% in foster-care Triple drug therapy, with 2NRTI + 1NNRTI – Regimen containing d4T : 48 / AZT :154 / ABC 16

9 Nutritional Indicators No. of Children (n=218) Percentage Stunting (HAZ < -2SD)12256% Underweight (WAZ < -2SD)12959% Wasting (WHZ < -2SD)3817% Stunting or chronic malnutrition reflects past shortage of food intake or chronic illness - negatively and irreversibly affects linear growth, organ growth & cognition Underweight – composite indicator of both past & present under nutrition (measure of MDG)

10 Risk Factors of Metabolic Syndrome 1. Fasting Blood Lipids Parameters (mg/dl)Mean (SD) (n=218) Normal Range Total Cholesterol130 (35) LDL-Cholesterol78 (28)100 – 129 HDL-cholesterol29 (11) Sr.Triglycerides142 (71) Hypocholesterolemia seen in majority of CLHIV 87% of children having low HDL-c Serum Triglycerides > 150 mg/dl seen in 37% CLHIV Waist: Hip ratio 0.96 (WNL)

11 Risk Factors of Metabolic Syndrome 2. Insulin Resistance Blood ParametersMean (SD) (n=218) Normal Range Fasting Glucose84.0 (14)60 – 110 Serum Insulin8.2 (13)5 – 20 C-reactive Protein2.0 (3.1)<3.0 low risk HOMA-IR1.8 (2.3)< 3.5 HOMA-IR > 3.5 in 13% of children at baseline hs-CRP of 3-10 mg/dl in 22% - indicators of high risk for metabolic syndrome

12 All observed genotype frequencies consistent with Hardy-Weinberg equilibrium S. NoPLIN SNPNo of Subjects Allele Frequency 1PLIN_rs (14995A>T) (A)0.36 (T) 2PLIN_rs (6209T>C) (C)0.43 (T) 3PLIN_rs (11482G>A) (G)0.33 (A) 4PLIN_rs (13041 A > G) (G)0.46 (A) NIRTICMR

13 3a. PLIN Gene Polymorphisms PLIN 11482G>A (rs894160) (n=189) ParametersGG (n=86) Mean (SD) GA + AA (n=103) Mean (SD) P value Age (years)7.2 (3)7.5 (3)0.42 Weight (kgs)17.9 (6)17.8 (6)0.95 Waist circum.52.4 (7) 0.99 Triglycerides (mg/dl) (69)156.2 (78)0.03 Tot. Cholesterol129.1 (38)127.3 (28)0.71 HDL-c (mg/dl)28.3 (11)28.2 (11)0.99 PLIN minor allele (GA+AA) associated with significant higher sr. triglycerides level at baseline

14 3b. PLIN Gene Polymorphisms PLIN 6209T>C (rs ) (n=189) ParametersTT (n=39) Mean (SD) TC + CC (n=150) Mean (SD) P value Age (years)6.4 (3)7.6 (3)0.03 Weight (kgs)16.2 (5)18.2 (6)0.07 Waist circum.51.5 (9)52.6 (6)0.47 Triglycerides (mg/dl) (62)149.8 (77)0.12 Tot. Cholesterol129.2 (31)123.1 (40)0.29 HDL-c (mg/dl)27.7 (11)28.5 (11)0.69 NIRTICMR No difference in lipid profile between variants

15 Discussion Even before ART initiation, risk factors for Metabolic syndrome seen in HIV-infected ART-naive children in South India – serum triglycerides > 150mg/dl : 81 children (37%) – HDL-cholesterol < 40mg/dl: 189 children (87%) – HOMA-IR > 3.5 : 29 children (13%) – hs-CRP 3-10mg/dl : 22% of children

16 Discussion In our cohort of CLHIV, minor allele A at PLIN G>A, which is associated with increased risk of MS, seen in 55% (103/189) of children – At baseline, among those with raised triglycerides, 68% (50/74) had minor allele A – Among those with normal TGL 46% (53/113) had minor allele A at PLIN G>A PLIN 6209T>C, PLIN13041A>G did not find any association in our cohort

17 Conclusion Despite background of food insecurity and malnutrition, substantial number of HIV-infected ART-naive children are at high risk for development of Metabolic Syndrome Given the relatively large number of carriers of genetic risk variants in this group, children with advanced disease need to be closely monitored for the development of MS, once ART is initiated Prevent long-term morbidities. Study is ongoing

18 Acknowledgements Tufts University, Boston Dr. Christine A Wanke, Dr. Jose Ordovas St. John’s Research Institute, B’lore Dr. Anita Shet Indira Gandhi Hospital, Bangalore Dr. GN Sanjeeva Ro1 AI All study participants ART centre Medical Officers


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