Jadranka Sertić

Department of Medical Biochemistry and Clinical Chemistry, School of Medicine, University of Zagreb

Department of Laboratory Diagnostics, University Hospital Center Zagreb

Zagreb, Croatia

GENETICS AND

METABOLIC DYSFUNCTION

INDO-GLOBAL HEALTHCARE SUMMIT & EXPO 2014, Hayderabad, India

METABOLIC DYSFUNCTION

Environment Genes

CARDIO-CEREBROVASCULAR DISEASE

Atherosclerosis

Obesity Dyslipidemia Diabetes

Metabolic syndrome

Hypertension

HEALTH

MS and CVD are leading cause of morbility and mortality and have genetic component, as risk of

disease and biomarcer of heath.

For genetic prediction of disease risk it is important to identify functional gene variant, polymorphism

in order to established genotype-phenotype correlation.

There are gene-gene and gene –enviroment interaction.

GENOMICS PROTEOMICS

NUTRIGENOMICS

THE WORLD OF "OMICS"

BIOMARKERS

PREDICTIVE, PREVENTIVE AND PERSONALIZED MEDICINE

Today OMNICS technologies allow detection of genetic, biochemical and other relevant biomarkers for

personalized early diagnosis, intervention and treatment.

Biomarker, gene variants is a valuable tool in the prevention of a complex multifactorial disease.

PERSONALIZED MEDICINE

BIOMARKERS: GROWING IMPACT IN LABORATORY MEDICINE

Human Genome Project

Enhanced understanding of molecular basis of disease

Genetics Genomics Proteomics: new possibilities

To predict disease onset Improvement quality of life

To individualize treatment Reduced costs of healthcare

PPPM offer great promise for the future practise of medicine. Essential components of this approach include

utilizing novel diagnostic biomarkers of disease states resulting in a improvement in quality of life and reduced

costs of healthcare

GENES AND ENVIRONMENT

The importance of gene-environment interaction is evident in the fact that its

effect will be so great that premature disease will develop

only when an individual with a high-risk genetic profile moves into a high-risk

environment.

Genetics and environmental factors

(including diet, alcohol and tobacco)

Biological and clinical data

+ lead to application of preventive

medicine in the field of obesity, MS

and CVD

For genetic prediction of disease risk, it is important to identify

functional gene variants (SNPs) in order to establish genotype-

phenotype correlation

SINGLE NUCLEOTIDE POLYMORPHISMS (SNPS)

- MOST COMMON GENE VARIANTS

There are two types of polymorphisms:

good-risk predictors - associated with health (low risk)

poor-risk predictors - related to possible development of disease

(hypercholesterolemia, hypertension, obesity, metabolic syndrome,

cardiovascular disease) (high risk)

NEW TREND IN LABORATORY MEDICINE Genomic,proteomic and nutrigenomic profiling

Genomic, proteomic and nutrigenomic profiling provides a picture of the cell and genes

variants and proteins associated with inflammatory processes, lipid homeostasis, and

hemostatic status,

as well as pathways and biological processes involved in the predisposition, interaction of

genetic risk factors, and pathophysiology of clinical entities like metabolic syndrome, obesity,

atherosclerosis and stroke.

Genetic risk factors in patients with acute ischemic stroke

University of Zagreb School of Medicine

Functional genomics and proteomics of the risk factors

of atherosclerosis

Croatian Ministry of Science

•

•

Study is part of a project:

BIOMARKERI

geni proteomici

fizikalni

metabolički

biokemijski

slikovni

fiziološki

anatomski

histološki

zračenje

GENETIC BIOMARKER AN INDICATOR OF NORMAL AND ABNORMAL BIOLOGICAL PROCESSES

AT1R PPARG

MTHFR

ADIPO

ESR

IL-6

BIOMARKERS

ACE

LPL

APOE

We investigated the possible role of gene polymorphisms of ADIPOQ, ESR1, LPL, ApoE, ACE, AT1R IL-6

and PPARG in obesity, MS and acute ischemic stroke in early adulthood

Adiponectin level and gene variablity as obesity and metabolic syndrome markers in a

young population

Gender effects of PPARG, APOE, ACE, LPL, IL-6 and AT1R gene variants on

metabolic syndrome

Genetics risk factors in patients with acute ischemic stroke: The role of PPARG,

IL-6 and AT1R

ESR1, APOE, MTHFR, ACE, IL-6 and LPL in healthy young subjects, and their effect

on biogical variables of the lipid status, hypertension and obesity,

gene - environment interaction as a predictor of early abdominal obesity and

hypertension

•

•

•

•

Genomics and proteomics of the risk

factors of atherosclerosis Croatian Ministry of Science

- obesity is a multifactorial disorder affected by genetic and dietary factors

- obesity s accepted as an important risk factor for development of certain

syndromes and many chronic diseases

- obesity has become an extensive public health concern becuse its prevalence

has increased to epidemic proportions

CONTRIBUTION OF GENE VARIANTS AND DIET TO OBESITY RISK

ESR1, APOE, MTHFR, ACE, IL-6 AND LPL IN HEALTHY YOUNG

INDIVIDUALS, AND THEIR EFFECT ON THE BIOLOGICAL

VARIABLES OF LIPID STATUS AND OBESITY

Sertić J, Juričić L, Ljubić H, Božina T, Lovrić J, Markeljević J, Jelaković B, Merkler

M, Reiner Ž. Variants of ESR1, APOE, LPL and IL-6 loci in young healthy subjects:

association with lipid status and obesity. BMC Res Notes 2009;2:203.

“ - genetic polymorphic variants could represent predictive genetic risk markers for

obesity-related metabolic disorders in young healthy subjects

- Mediteranean type of diet is also an important protective factor against

abdominal obesity ”

105 young healthy subjects aged 20 - 35 years (F 58, M 47),

participated in the study

invited to participate during routine medical check-up

family history of CVD, hypertension, obesity, medications, smoking,

diet was registered through a questionnaire

participants signed informed consent forms

study protocol was approved by the Ethics Committee

Focus of the study is on candidate genes and SNP, and their

association with biological data and demographic and

biochemical characteristics

LABORATORY MEASUREMENTS

Biochemical analyses

blood samples for biochemical analyses (total cholesterol, LDL- and HDL-

cholesterol, glucose, CRP, urate) were taken after overnight fasting

Genetic analyses included the following genes:

ESR1; TA ( 19) - short allele; > 19 repeats - long allele

APOE E2, E3, E4

MTHFR C677T

ACE; I/D

IL-6 174G>C

LPL PvuII

N= 105 young subjects Age: 25-35 Croatian origin

BMI waist/hip ratio

IL-6, ACE, LPL

PCR-RFLP

APOE, MTHFR

Real-time PCR

ESR1

Capillary electrophoresis

GENOTYPING

GENES

Genotypes have been determined by applying PCR/CE/RT-PCR

POPULATION CHARACTERISTICS: AGE, BMI

292.70 +/- 76.35 Urate (mmol/l)

5.03 +/- 0.45 Glucose (mmol/l)

1.34 +/- 1.61 CRP

2.59 +/- 0.85 LDL (mmol/l)

1.45 +/- 0.3 HDL (mmol/l)

4.53 +/- 0.96 Cholesterol (mmol/l)

1.08 +/- 0.55 Triglycerides (mmol/l)

0.81 +/- 0.8 Waist/hip ratio

103.23 +/- 8.32 Hip (cm)

83.61 +/- 12.04 Waist (cm)

23.48 +/- 3.81 BMI

175 +/- 10.53 Height

73.99 +/- 16.09 Weight

25.82 +/- 3.28 Age (yrs)

Mean +/- SD

Subjects' demographic and biochemical characteristics

Basic characteristics: age of the subjects was 25. and metabolic status ,

DIET: CONTINENTAL, MEDITERIAN, MIXED

Feature Frequencies Percent

No 78 74.3 Cardiovascular illness 4 3.8

Somatic illness

Other illnesses 14 14.3 Yes 67 63.8 Smoking No 31 29.5 No 87 82.9 With known effects on investigated features (Contraceptives)

9 3.8

Taking medications

Other medications 4 8.6 No 77 73.3 Raised hepatic enzymes Yes 19 18.1 Continental 75 71.4 Mediterranean 13 12.4

Diet

Mixed 10 9.5 No 25 23.8 Diabetes 12 11.4 Cardiovascular disease 32 30.5 Obesity 2 1.9

Positive family history

More than one 34 32.4 No 79 75.2 Hypertension (>135/85

mmHg) Yes 19 18.1

Positive familiy history was established in 32.4% of subjects.

Hypertension in 18.1%

12.4% of subjects were on Mediterrannean diet

< 25 77 73.3 25.01-30 23 21.9

BMI/km/m2

> 30.01 5 4.8 No 85 83.3 Abdominal obesity (Waist/hip

>90 (Male), >85 (Female) Yes 17 16.7

No 93 88.6 Hypertriglyceridemia (>1.7) Yes 12 11.4 No 81 77.1 Hypercholesterolemia (>5) Yes 24 22.9 No 98 93.3 Low HDL (<1.0) Yes 7 6.7 No 81 77.1 High LDL (>3) Yes 24 22.9 Normal 104 99 Glucose (>6.4) Hyperglycemia 1 1.0 < 1 61 58.1 1-3 34 32.4

CRP levels

> 3 10 9.5 No 93 88.6 Elevated urate levels (>383) Yes 12 11.4

Feature Frequencies Percent

HEALTHY YOUNG SUBJECTS – BMI, WC, CHOL.

BMI values ranging between 25 – 30 were found n 21.9% of subject

Hypertriglyceridemia was detected i 11.4% of subjects

DIFFERENCES IN WEIGHT, BMI AND WAIST OF THE

SUBJECTS WITH REGARD TO THEIR DIET TYPE

0

20

40

60

80

100

120

Weight BMI Waist

Continental Mediterranean Mixed

*

*

*

We found association between BMI and diet type – Mediterranean diet significantly different,

as a factor of environment, has considerable impact on the health of young population

Subjects on Mediterranean diet had the best results

with regard to BMI and WHR

Croatia

ASSOCIATION BETWEEN LIPID PARAMETERS AND

ESR1- AND APO E POLYMORPHISMS

Significant association was found between ESR1 (S allele) and APO E (2,3), and cholesterol

("good-risk factors")

-- Association between estrogen receptor-alfa gene polymorphisms and coronary artery

disease wth familiar hypercholesterolemia was previously reported.

Cholesterol

<5 N=81

Cholesterol

>5 N=24

OR CI Test

Alleles L 42 19 1 1-1

S 54 9 2.714 1.18- 6.26

Χ2=5.123

df = 1

p = 0.023

Genotypes LL 9 7 1 1-1 LS 24 5 3.733 0.94- 14.84

ESR1

SS 15 2 5.833 0.98- 34.44

Χ2=5.328 df = 2

p= 0.0696

Alleles 2 21 1 1 1-1 3 121 33 0.1746 0.02- 1.404

4 14 12 0.055 0.005-0.59

Χ2=12.69 df = 2

p= 0.0017

Genotypes 22 2 0 1 1-1

23 15 0 2.081e+011 9.954e+010-

4.353e+011

24 2 1 1.006e-008 0- 7.707e-008

33 47 12 1.97e-008 0-6.223e-008

34 12 9 0 0-2.319e-008

APO E

44 0 1 0 0-0

Χ2=16.28

df = 5

p= 0.006

RESULTS THAT INDICATE A RISK ASSOCIATED WITH

ABDOMINAL OBESITY

Abdominal obesity was correlated to LPL P+/-, P+/+ genotypes in significant manner

WHR /09 was found good indicator for obesity among heterozygous and homozygous subjects

for LPL genotype

Waist/hip

<0.9 (M);

<0.85 (F),

N=85

Waist/hip

>0.9 (M);

>0.85 (F),

N=17

OR CI Test

Alleles M 87 16 1 1-1

P 65 18 0.6641 0.203- 2.18

Χ2=

1.158

df = 1

p= 0.282

Genotypes MM 25 1 1 1-1

MP 37 14 0.1057 0.01-0.86

LPL

PP 14 2 0.28 0.023-3.37

Χ2=

7.984

df = 2

p = 0.018

GOOD-RISK PREDICTION IN YOUNG HEALTHY POPULATION

Environment factor:

Mediterranean diet

Genetic biomarkers:

ESR1 (TA<19)

APO E (2/3)

LPL Pvu -/-

• Results of examining correlation between weight, BMI and waist/hip ratio, and continental,

Mediterranean and mixed diet showed optimal values in subjects on Mediterranean diet

• Statistically significant correlation was detected for ESR1 short allele and cholesterol

• We also found statistically significant association of APO E 2/3 genotype with lower total- and

LDL-cholesterol levels

• Statistically significant association was observed between LPL and abdominal obesity

GENES & ENVIRONMENT: ORDER OF RELEVANCE??

"Genes load the gun, but the environment pulls the

trigger." 1921

Elliot Proctor Joslin (1869-1962)

a physician and a diabetes educator

This has recently been a very frequently used saying: would you agree that both genes and

environment are equally important?

Gender effects of PPARG, APOE, ACE, LPL, IL-6 and AT1 gene variants on metabolic

syndrome

Adiponectin gene variants and MS

Genetics risk factors in patients with acute ischemic stroke: The role of PPARG

IL-6 and AT1R

ESR1, APOE, MTHFR, ACE, IL-6 and LPL in healthy young subjects, and

their effect on biogical variables of the lipid status, hypertension and obesity •

•

•

•

Genomics and proteomics of the risk factors

of atherosclerosis Croatian Ministry of Science

Karmelić I, Lovrić J, Božina T, Ljubić H, Vogrinc Ž, Božina N, Sertić J.

Adiponectin level and gene variability are obesity and

metabolic syndrome markers in a young population.

Arch Med Res 2012;43(2):145-153.

ADIPONECTIN GENE aS A PREDICTOR OF EARLY ABDOMINAL OBESITY

The aim of the study was to establish possible correlation of adiponectin (ADIPOQ)

gene variants and peroxisome proliferator activated receptor (PPAR ) with

development of abdominal obesity, and consequently also of MS in young individuals,

as well as possible association of the variants of this gene with lipid variables.

CORRELATION OF ADIPOQ GENE POLYMORPHISMS WITH MS

Gene/polymorphism

Genotype or

allele

Subjects

without MS

N (%)

Subjects with

MS

N (%)

OR

(95% C.I.)

Pearson’s χ2 test

ADIPOQ

-11377 C>G

CC 59 (86.8) 9 (13.2) 2.93

1.26-6.81

p=0.0128

χ2= 6.523

d.f.=1; p=0.001

CG+GG 49 (64.3) +7

(70.1)

20 (29.9)

+ 5 (35.7)

C 106 (78.5) 29 (21.5) 1.63

0.87-3.05

p=0.128

χ2= 6.523 d.f.=1;

p=0.011

G 56 (69.1) 25 (30.9)

ADIPOQ

-11391 G>A

GG 76 (85.4) 13 (14.6) 3.15

1.43-6.95

p= 0.004

χ2= 8,463 d.f.=1;

p=0.004 GA+AA 38 (66.7) + 1

(33.3)

19 (33.32) + 2

(66.7)

G 115 (77.2) 34 (22.8) 1.91

1-3.65

p=0.05

χ2= 6.523 d.f.=1;

p=0.011

A 39 (65.0) 22 (35.0)

Prevalence of MS in young population is high; from 45% of subjects with increased waist circumference, 65%

also had other MS components.

Statistically significant correlation was found between ADIPOQ -11377GG and ADIPOQ -11391AA genotype,

and abdominal obesity.

CORRELATION OF ADIPOQ GENE POLYMORPHISMS WITH MS COMPONENTS

Characteristic/

ADIPOQ gene polymorphism

Genotype or allele Subjects

without MS

N (%)

Subjects with MS

N (%)

OR

(95% C.I.)

Pearson’s χ2 test

Waist circumference/

-11377 C>G

CC 39 (49.4) 27 (40.3) 5.29

0.75-2.79

p=0.017

4.68

1.19-18.34

p=0.027

χ2= 6.782; d.f.=2 p=0.03

CG 37 (46.8) 29 (43.3)

GG 3 (3.8) 11 (16.4)

C 76 (96.2) 56 (83.6) 1.36

0.78-2.37

p=0.283

Χ2= 6.6604; d.f.=1; p=0.01

G 40 (50.6) 40 (59.7)

Waist circumference/

-11391 G>A

GG 60 (75.9) 27 (40.3) 4.68

2.30-9.52

p<0.0001

χ2= 19.139; d.f.=1 p<0.001

GA+AA 18 (22.8) +1

(1.3)

38 (56.7) + 2

(3.0)

G 78 (98.7) 65 (97.0) 2.53

1.34-4.78

p=0.004

χ2=19.135;

d.f.=1 p<0.001 A 19 (24.1) 40 (59.7)

Triglycerides/

-11377 C>G

CC 58 (49.6) 9 (29.0) 6.23

2.82-13.73

p<0.0001

χ2= 6.992 d.f.=1;

p=0.008 CG + GG 50 (42.7) +9

(7.7)

22 (54.8) +5

(16.1)

C 108 (92.3) 26 (83.9) 1.54

0.80-2.99

p=0.187

χ2= 4.173; d.f.=1 p=0.041

G 59 (50.4) 22 (71.0)

Triglycerides/

-11391 G>A

GG 75 (64.1) 14 (45.2) 2.17

0.97-4.45

p=0.006

χ2= 3.663 d.f.=1

p=0.05 GA+AA 41 (30.5)

+1 (0.9)

15 (48.4)

+ 2 (6.5)

G 116 (99.1) 29 (93.5) 1.62

0.80-3.25

P=0.174

χ2= 3.668

d.f.=1

p=0.06 A 42 (35.9) 17 (54.8)

Statistically significant correlation was established between ADIPOQ -11377 G allele and hypertriglyceridemia.

ADIPOQ 11377 G and ADIPOQ -11391 A alleles have been found to be significant predictors of MS, with all its

components.

MULTIVARIATE DISCRIMINANT ANALYSIS OF MS PREDICTORS – BIOMARKER AS MODULATORS OF VISCERAL FAT ACCUMULATION???

Method: forward stepwise. Step 10; N variables in a model:8; Grouping: 2 groups (without MetS and with MetS) Wilk’s

Lambda: 0.430 approx. F (10.131)=17.364; p<0,00001

N =149

Wilks’ Lambda Partial Lambda F-remove p-value

Triglycerides (mmol/L) 0.500 0.860 21.34 <0.0001

Blood pressure 0.518 0.831 26.73 <0.0001

HDL-cholesterol (mmol/L) 0.470 0.915 12.18 0.001

ADIPOQ-11391 G>A; allele A 0.444 0.970 4.11 0.045

Glucose (mmol/L) 0.443 0.968 4.32 0.040

PPAR 2 Pro12Ala; alel C 0.442 0.973 3.67 0.058

ADIPOQ -11377 C>G; alel G 0.441 0.974 3.49 0.064

ADIPOQ -11391 G>A; alel G 0.436 0.985 1.96 0.163

Multivariate discriminant analysis was used to confirm all MS components and ADIPOQ -11391

A allele as independent MS predictors.

BIOMARKER- ADIPOQ -11391 A allele as independent MS predictors.

BIOMARKERS

Triglycerides (mmol/L)

Blood pressure

HDL-cholesterol (mmol/L)

ADIPOQ-11391 G>A; allele A

Waist circumference/

-11391 G>A Triglycerides/

-11391 G>A

Gender effects of PPARG, APOE, ACE, LPL, IL-6 and AT1 gene

variants on MS

Adiponectin gene and MS

Genetics risk factors in patients with acute ischemic stroke: The role of PPARG

and IL-6

ESR1, APOE, MTHFR, ACE, IL-6 and LPL in healthy young subjects, and

their effect on biogical variables of the lipid status, hypertension and obesity •

•

•

•

Genomics and proteomics of the risk factors

of atherosclerosis Croatian Ministry of Science

Božina T, Simić I, Lovrić J, Pećin I, Jelaković B, Sertić J, Reiner Z. Effects of

lipoprotein lipase and peroxisome proliferator-activated receptor-gamma

gene variants on metabolic syndrome traits.

Coll Antropol. 2013;37(3):801-808.

Božina T, Sertić J, Lovrić J, Jelaković B, Simić I, Reiner Z. Interaction of Genetic

Risk Factors Confers Increased Risk for Metabolic Syndrome: The Role of

Peroxisome Proliferator-Activated Receptor Genet Test Mol Biomarkers

2014; 18(1): 32-40.

GENDER-SPECIFIC EFECTS OF

PPARG, APOE, ACE, AT1R, LPL AND IL-6

GENE VARIANTS ON

METABOLIC SYNDROME TRAITS

We aimed to perform analysis of the possible role of gene polymorphisms of PPARG (Pro12Ala), ApoE

(ε2, ε3, ε4), ACE (I/D), LPL (P+/-) and IL-6 (-174G>C) in MS.

A cohort of 527 individuals (343 female, 184 male) were investigated including 263 patients with MS and

264 subjects without MS criteria.

Measurements included: fasting glucose in blood, total cholesterol, triglycerides, LDL-C, HDL-C, CRP,

blood pressure (BP), waist circumferences (WC) and measurements of weight and height for body mass

index (BMI) calculations.

Genotyping was performed for ApoE by Real-time PCR, for PPARG, LPL and IL-6 by PCR-RFLP, for ACE

by PCR based method.

• Metabolic syndrome is a cluster of modifiable risk factors including hypertension, abdominal obesity,

dyslipidemia and insulin resistance, associated with nonmodifiable risk factors, such as age, sex and genetic

background.

• PPARG (PPARG Pro12Ala (CCA – GCA) is a transcription factor with a crucial role in the expression of

key genes involved in adipogenesis, lipid and glucose metabolism, atherosclerosis, inflammation and

immunity.

• The presence of genetic variants is likely to affect expression levels of different target genes. LPL, IL-6,

ApoE and ACE.

MS

An individual with a combination of any three or more of the

following risk factors was classified as having MS:

• waist circumference, male >102 cm, female >88 cm

• TG 1.7 mmol/L

• HDL-C <1.0 in men and <1.3 mmol/L in women

• systolic blood pressure (SBP) or diastolic blood pressure (DBP)

130/85 mm Hg

• and fasting blood glucose 6.1 mmol/L

RESULTS

Patients with MS and control group did not differ significantly with respect to age and sex. Patients had significantly higher blood pressure, BMI and waist circumferences and higher levels of TG, total cholesterol, CRP and glucose and lower levels of HDL-C compared to controls.

Clinical features of study participants

Association of gene variants and components of MS in males and females

- In female group associations were found for: PPAR and LPL with BP; LPL with Chol. and LDL

- For male we found associations of: LPL variants with MS, BMI and WC;

- PPAR, LPL and apoE with BMI,

- IL-6 with CRP

Genotype: prediction - odds ratio (OR)

Feature Genotype high

n (%)

normal

n (%) OR (95% CI)

WC IL6 (controls)

GG 13 (31.7) 70 (38.0) 1

GC 18 (43.9) 94 (51.1) 1.03 (0.47-2.24)

CC 10 (24.4) 20 (10.9) 2.69 (1.03-7.05)

WC PPARγ (controls)

CC 27 (65.9) 142 (77.2) 1

CG/GG 14 (34.1) 42 (22.8) 3.86 (1.24-12.06)

TG AT1R (controls)

AA 8 (26.7) 112 (53.1) 1

AC or CC 22 (73.3) 99 (46.9) 3.11 (1.33-7.30)

Glucose AT1R (cases)

AA 3 (27.3) 115 (50.9) 1

AC 5 (45.5) 97 (42.9) 1.98 (0.46-8.48)

CC 3 (27.3) 14 (6.2) 8.21 (1.51-44.68)

•Healthy participants with IL6 CC genotype had more than 2.5 larger risk (odds) of having high waist circumference compared to those with IL6 GG genotype.

•PPAR CG or GG genotype carriers had almost 4 times larger risk (odds) of having high waist circumference compared to those with PPAR CC genotype carriers.

•Participants with AT1 AC or CC genotype were more than 3 times more likely to have high triglycerides compared to those with AT1 AA genotype.

•Participants with AT1 CC genotype had more than 8 times larger odds of having high levels of fasting blood glucose compared to those with AT1 AA genotype.

Overall predictive model for MS

Interactions / feature Genotypes cases

n (%)

controls

n(%) ORmv (95% CI) P

LPLxPPARγ / MS

LPL if PPAR CG or

GG

M/M 12 (18.5) 19 (30.2) 1

M/P or P/P 53 (81.5) 44 (69.8) 5.98 (1.46-24.47) 0.013

IL6xPPARγ / glucose

PPAR if IL6 GC/CC

CC 39 (62.9) 90 (78.3) 1

CG / GG 23 (37.1) 25 (21.7) 2.39 (1.11-5.17) 0.026

LPLxPPARγ / HDL-males

LPL if PPAR CG/GG

M/M 1 (6.3) 2 (16.7) 1

M/P or P/P 15 (93.8) 10 (83.3) 38.62 (1.72-867.06) 0.021

ACExPPARγ / BMI

PPAR if ACE DD

CC 32 (64.0) 20 (90.9)

CG / GG 18 (36.0) 2 (9.1) 9.98 (1.18-84.14) 0.034

•In the group of patients with PPARG CG or GG genotype, carriers of LPL M/P or P/P genotype have about 6 times greater risk (odds) for developing MetS compared to PPARG CC genotype carriers.

•In the group of patients with MetS carriers of combination of genotypes IL-6 -174 GC or CC with PPARG CG or GG have almost 2.5 times larger odds of having high glucose compared to PPARG CC genotype carriers.

•In the group of patients with PPAR CG or GG genotypes, those with LPL M/P or P/P genotype had 38.62 times greater risk ( odds) for low HDL cholesterol.

•In the group of patients with ACE DD genotype, those with PPAR CG or GG genotype had about 10 times greater risk for obesity.

Haplotypes :Effects of gene-gene interactions on MS syndrome traits in males

Signifikant gene interaction observed between :PPAR & APOE with cholesterol; PPARG & IL-6 with Ch.;

IL-6, PPARG, with LDL and HDL; LPL & PPAR with HDL; PPAR &APOE with CRP;LPL & ACE with CRP

Haplotypes: effects of gene-gene interactions on MS traits in females

-Signifikant gene interaction - haplotypes observed in females between :

- PPARG and LPL with Triglycerides;

- PPARG and APOE with BMI;

- ACE and APOE with BMI

Gender-based dimorphism -

PPARG and LPL- possible explanations include:

possible interaction of LPL with either sex linked genes and/or sexual

hormon effects

the effects of differentially expressed autosomal genes in male and female

differential fat distribution patterns betwen genders

differential gene-environment and gene-gene interaction

although PPAR variant show no influence on MS or its traits when tested

separetly, its inteaction with LPL variants seems to be relevant at least for

HDL-C levels in male population

transcriptional regulation – LPL promotor less efficiently transactiveited in

the presence of the PPARG Ala allele.PPARGAla /Pvu(+), 1.8 times higher

risk for lower HDL-C values in males

Gender-specific effects of PPARG, APOE, ACE, AT1R, LPL and IL-6 gene variants on metabolic syndrome traits

CONCLUSION

- gene variants of PPARG, APOE, LPL, ACE and IL-6 could be

susceptibility factors of obesity, lipid status, and glucose intolerance

- PPARG gene variant interact with target gene contribute to the

variable susceptibility to developed MS ?

-- although further studies are needed to confirm the gender specificity

of genes interaction, they interplay betwen genes and gender seems to be

significant and could point to the personalized recommendation for

prevention of metabolic and cardiovascular diseases

Linkage polymorphism of AT1R with the incidence of stroke in early

adulthood

Genetic risk factors in patients with acute ischemic

stroke:The role of PPARG and IL-6 •

•

The role of genetics markers in the

development of atherosclerosis and stroke University of Zagreb, School of Medicine

GENE VARIANTS IN THE RENIN-

ANGIOTENSIN SYSTEM AND INCREASED

RISK OF EARLY ONSET OF

ISCHEMIC STROKE

Stroke is a multifactorial atherothrombotic disease.

The renin-angiontensin system has an important role in cerebrovascular disease

through a variety of processes.

The angiotensin-converting enzyme (ACE) converts angiotensin I into

angiotensin II, which binds the angiotensin II type-1 receptor (AT1R), and is a

potent vasoconstrictor.

Both ACE and AT1R display polymorphisms that can alter their functions.

The aim of our study was to investigate ACE I/D and AT1R A1166C

polymorphisms and the risk of early onset of ischemic stroke.schemic stroke is

multifactorial disease which include interactionn among various genetic and

environmental factors

Božina T, Bazina A, Lovrić T, Poljaković Z, Sertić J.

Gene variants in the RAS and increased risk of early onset of ischemic stroke.

7th Croatian Congress of Pharmacology, Zagreb, Croatia 2014.

GENE VARIANTS IN THE RENIN-ANGIOTENSIN SYSTEM AND

INCREASED RISK OF EARLY ONSET OF

ISCHEMIC STROKE

Clinical data and genetic and biochemical parameters of 114 patients, aged 18 to

55 years, with acute ischemic stroke were analyzed.

A total of 187 controls were matched for anthropometric parameters, but

were carotid ultrasonography alterations-free, and without history of stroke

before age of 70 in two generations.

DNA was genotyped for ACE I/D and AT1R A1166C polymorphism by means of

PCR-RFLP methods.

GENE VARIANTS IN THE RENIN-ANGIOTENSIN SYSTEM AND INCREASED

RISK OF EARLY ONSET OF

ISCHEMIC STROKE

Statistically significant difference was found in prevalence of particular

AT1R genotype (P=0.004) where AA genotype was more frequent in

patient group

Participants with AT1R 1166AA genotype are two times more likely to

belong to patient group than participants with AC or CC genotypes

(OR=2.0; 95% CI:1.2-3.2)

AT1R genotypes were statistically significant associated with type of

stroke (P=0.046)

Anterior stroke was more frequent among participants with AC or CC

genotype, while posterior stroke was more frequent among participants

with AA genotype

GENE VARIANTS IN THE RENIN-ANGIOTENSIN SYSTEM

AND INCREASED RISK OF EARLY ONSET OF

ISCHEMIC STROKE

ACE I/D polymorphism did not yield a risk of ischemic stroke.

AT1R A1166C polymorphism could be risk factor for early

occurrence of stroke.

Genetic risk factors in patients with acute ischemic stroke:The

role of PPARG and IL-6

•

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The role of genetics markers in the development

of atherosclerosis and stroke University of Zagreb, School of Medicine

Linkage polymorphism of AT1R with the incidence of stroke in

early adulthood

Bazina A, Mišmaš A, Božina N, Skorić MK, Poljaković Z, Sertić J.

Genetic risk factors in patients with acute ischemic stroke:

The role of PPARG. EFNS-ENS, Istanbul, Turkey 2014.

GENETIC RISK FACTORS IN

PATIENTS WITH ACUTE ISCHEMIC

STROKE:

THE ROLE OF PPARG AND IL-6

Ischemic stroke is multifactorial disease which include interactionn among

various genetic and environmental factors

The aim of our study was to estimate possible associations of two

analyzed gene PPARG and IL-6 and their gene variability on ischemic

stroke development in in early adulthood.

Genetic risk factors in patients with acute ischemic stroke: The

role of PPARG and IL-6

Study included 301 subjects, (114 patients and 187 healthy control)

PPARG CC, IL-6 -174 GC were statistically more frequent in the

patient's group

Patients had significantly higher BMI, higher blood pressure, and higher

level of total cholesterol, LDL, triglycerides, lowered level of HDL, and

elevated level of CRP

PPARG CC and IL-6 174 GC gene polymorphism variants could be

susceptibility factors for ischemic stroke development in patient

group, particularly in males, in presence of hypertension and

elevated CRP levels

GENETICS AND METABOLIC DYSFUNCTION

GENETIC BIOMARKERS

PERSONALIZED MEDICINE

The saying: "One size fits all" is not valid any more!

Thank you for attention!

Zagreb - Croatia

Dubrovnik - Croatia