Suficiencia investigadora

1. ASSOCIATION STUDY AND
FUNCTIONAL VALIDATION OF
GENETIC MARKERS RELATED TO
NON-ALCOHOLIC FATTY LIVER
DISEASES
Angel Bardasco Blazquez
(Tutor: Ana M. Aransay, CIC bioGUNE)
0

2. ABSTRACT
Non-alcoholic fatty liver diseases (NAFLD) are the most common causes of
chronic liver disease in several western countries. Up to now, the only way to diagnose
NAFLD with certainty is liver biopsy. Therefore, the aim of the present project is to find
genetic markers that could help to develop a non-invasive diagnostic method for these
disorders. To achieve this objective we have carried out a candidate gen association
approach that yielded 6 potentially associated genes, being the first time that SLC2A1
has been associated with NAFLD. In addition, we have investigated the regulation of
those genes in liver biopsies at transcriptomic level. We have detected that all the
studied genes are regulated in NAFLD, and that the regulation is higher in advanced
stages of the disease. This suggests that the identified genes could serve as potential
markers for the diagnosis of the phases of NAFLD development.
1

3. INTRODUCTION
Non-alcoholic fatty liver disease (NAFLD) includes a wide spectrum of lesions
including steatosis (ST), non-alcoholic steatohepatitis (NASH), fatty liver and
inflammation, as well as a high number of cryptogenic cirrhoses 1. NAFLD represents
the hepatic manifestation of the metabolic syndrome with insulin resistance as a
common feature, namely, central obesity, insulin resistance, dyslipidemia and
hypertension 2, 3. ST is an accumulation of fatty acids in the liver 4 and NASH is a term
that describes a form of liver disease that is histologically indistinguishable from
4, 5
alcoholic hepatitis, but occurs in persons who do not consume excess of ethanol
(less than 40g of ethanol per week 3).
Prevalence of NAFLD
NAFLD is the most common cause of chronic liver disease in several western
countries 5 and it has been reported in all age groups including children, although the
highest prevalence is described in individuals between 40 and 60 years 3. About 75% of
obese patients have NAFLD 6 (the prevalence augments with increasing body weight 3).
In general population, the prevalence of NAFLD is estimated about 20% 7. The
prevalence of NAFLD is increasing in industrialized countries 2 due probably to social
and environmental agents like alcohol, industrial toxins and hepatotrophic viruses 5,
and also to metabolic syndromes like obesity and type 2 diabetes (T2D) 8. Nugent et al.
6
showed that patients with T2D have high risk to develop NAFLD, since NAFLD was
detected in 62% of patients with newly diagnosed T2D and T2D has been described in
34% to 75% of patients with NASH 3. Obesity and diabetes mellitus are not
predisposing factors only to develop NAFLD, but they are also potential risk factors to
develop severe hepatic fibrosis and cirrhosis 9. All of these previous mentioned factors,
hyperlidipemia and other conditions associated with insulin resistance are generally
present in patients with NAFLD 3: at the time of NASH diagnosis, up to one third of the
patients have diabetes or fasting hyperglycemia 4, between 39 and 100% are
overweighted or obese, and between 20 and 80% have abnormalities of lipid
metabolism 4.
2

4. Development and progression of NAFLD
The pathogenesis of NAFLD responds to a two-hit hypothesis. First of all, an
10
imbalance in fatty acid metabolism involves accumulation of fat in the liver
(steatosis), likely, as a result of insulin resistance and increased fat mass 5, 11. Secondly,
hepatocyte necrosis and apoptosis is driven by oxidative stress (and subsequent lipid
peroxidation), deregulated proinflammatory cytokines production by Kupffer cells
(principally the tumor necrosis factor alpha, TNFα) and hormones derived from
adipose tissue (adipocytokines) that result from efforts to compensate the altered lipid
homeostasis 1, 3, 11, 12 11. Jou et al.12 proposed that the hepatocyte death is the third and
decisive step in NAFLD pathogenesis because this event drives progression from NASH
to cirrhosis.
In the hepatic ST, vesicles of fat, predominately triglycerides, accumulate within
hepatocytes (without causing considerable hepatic inflammation) causing liver cell
5 12
death and activating mechanisms of hepatocyte regeneration . This regenerative
respond activates hepatic stellate cells to myofibroblasts, causing liver fibrosis and
expanding hepatic progenitor populations. Subsequently , several chemoattractans are
produced to recruit various types of immune cells into the liver, inducing hepatic
inflammation that drives to NASH 12. ST can progress to NASH due to hepatocyte injury
and apoptosis, and hepatic infiltration by inflammatory cells. It is unclear why some
patients who develop ST go on developing NASH while others do not 11. The next stage
could be that NASH develops to cirrhosis as a result of an incomplete repair of
metabolic liver injury 12. In most chronic liver diseases that lead to cirrhosis, there is an
increased risk of developing hepatocellular carcinoma (HCC) that is an irreversible
13
state of liver damage . Hepatocyte DNA damage and expansion of liver progenitor
cells have been demonstrated in early NASH and this suggests that NASH provides
fertile ground for neoplastic transformation of hepatocytes at several stages of
12
differentiation . Progression of simple ST to NASH increases the risk to develop
cirrhosis and consequent liver-related morbidity and mortality 12.
3

5. Figure 1. Lipid metabolism within the hepatocytes. Liver lipid content is determined
by the equilibrium of several processes: import of FFA from the adipose tissue, de
novo synthesis of FFA in hepatocytes, β-oxidation of FFAs, esterification of FFA into
triglycerides and export of triglycerides as vLDL. Hepatic ST is a consequence of
imbalance in those processes in favor of excessive triglyceride accumulation. Insulin
resistance and resulting hyperinsulinemia lead to hepatocyte lipid accumulation in
the liver by several mechanisms. In adipose tissue, insulin resistance enhances
triglyceride lipolysis and inhibits esterification of FFAs. The result is the increased
levels of circulating FFAs, which are then taken up by the liver. In hepatocytes, the
hyperinsulinemia increases the “de novo” synthesis of fatty acids and inhibits their β-
oxidation. The consequence of reduced vLDL production and triglyceride export is
the accumulation of FFAs within hepatocytes.
The normal lipid metabolism in the liver involves hepatocyte uptake and de
novo synthesis of free fatty acids (FFA), disposal of FFA via oxidation or de novo
triglyceride synthesis and export of triglycerides as a very low density lipoproteins
12
(vLDL) from hepatocytes (Figure 1) . As soon as the rate of triglyceride synthesis
overwhelms the capacity of vLDL export, triglycerides accumulate within hepatocytes
causing ST 12. When the insulin resistance occurs, hepatic FFA concentration increases
by the movement of FFA from adipocytes by lipolysis (and, consequently, increasing
hepatic import) and/or hepatic endogenous synthesis 4. Triglycerides by themselves
are not hepatotoxic but they are biomarkers of increased hepatic exposure to
potential toxic FFA. An enzyme for esterification (Acyl-coA:diacylglycerol
acylltransferase, DGAT) is required to transform FFA in triglycerides and to join vLDL12,
4

6. then, the capacity of vLDL export can be overwhelmed leading to FFA accumulation
within hepatocytes.
The molecular mechanism of the insulin resistance is complex and has not
been elucidated completely. Several molecules appear to interfere with the insulin
signaling pathway and it has been found that adiponectin plays a key role in insulin
3, 11
sensitivity . FFA and their metabolites are ligands of peroxisome proliferator-
activated receptor alpha (PPARα), a transcription factor that activates genes involved
in fatty acid oxidation. When PPARα is up-regulated, there is more FFA oxidation,
which is translated in increased oxidative stress, elimination of FFA and progression
from ST to NASH 3.
Oxidative stress
Hepatic mitochondria of patients with NASH exhibit ultrastructural lesions with
the presence of para-cristalline inclusions in the megamitochondria, while
14
mitochondria of patients with simple ST are normal . Although the mechanisms for
hepatic mitochondrial dysfunction in NASH are still unknown, it may involve lipid
peroxidation, TNFα and reactive oxygen species (ROS). TNFα increases permeability of
the mitochondrial membranes and the blocking of the electron flow from complex II to
14
complex IV . Those factors are supposed to alter mitochondrial DNA and
mitochondrial oxidative phosphorylation, producing the structural alterations
mentioned abobe3.
It has been shown that 30% of the patients with NASH have elevated ferritin
levels (marker of iron overload) 11, which plays a role in oxidative stress and may play a
15
function in pathogenesis of NASH . This iron overload generates reactive oxygen
species and subsequent lipid peroxidation. In addition, iron has harmful effects on the
mitochondria activity 11.
5

7. Diagnosis of NAFLD
Most of the diagnosis of NAFLD is done by exclusion of other liver diseases
taking into consideration parameters through a scoring system 11 like biochemical tests
based on serum markers, imaging techniques such as ultrasound, and measurement of
8, 13
liver stiffness by transient elastography . The gold standard for accurate diagnosis
of NAFLD is liver biopsy. This is the only way to distinguish between fatty liver
(steatosis) alone and NASH. There are not specific and sensitive noninvasive tests
3, 5
(there are some, but their efficiency has not been demonstrated) . The problems
with liver biopsy are that is painful, invasive and, given the increasing number of
patients with NAFLD, it is not an efficient method 8. Therefore, studies of these
diseases are limited by the inability to make a definitive diagnosis of NAFLD3.
Additionally, distinction of NASH from simple ST is important because their prognoses
and clinical management are different 8, 13. Studies that have used strict definitions for
diagnosis, including biopsies, were most often based on specific subsets of the
population (like diabetics, obese individuals, alcoholic liver diseases, etc.) and, so far,
they cannot be applied to the general population 3.
Treatment
Although there is no consensus treatment for ST and NASH, most of the applied
therapies include specific diet and exercise for weight loss and sometimes, it could be
16
enough to treat hepatic ST . It is also recommended to stop smoking and alcohol-
3
drinking during treatment . When specific diet and exercise is not enough,
pharmacological treatment should be initiated. Several drugs such as antioxidants and
3, 13
lipid-lowering drugs have been tried for the treatment of NAFLD . There is quite a
controversy about NAFLD pharmacological treatment because the response of patients
is variable and often there are important secondary effects.
6

8. Genetic of liver diseases
It has been shown that most evidences of genetic association with NAFLD
derive from family clustering analysis 2. There are different families of genes involved
in ST and NASH: genes influencing lipid metabolism, genes affecting oxidative stress,
genes coding for bacterial receptors and genes influencing extracellular matrix
synthesis and degradation 2. Modifications of those gDNA gene sequences have been
associated with liver diseases:
• The polymorphism (-493G/T) in the promotor of microsomal triglyceride
transfer protein (MTP) has been associated with NAFLD 17. This enzyme adds
triglycerides to nascent apolipoprotein B, producing vLDL. Thus, decreased
activity of MTP may lead to lipid accumulation 17.
• The (1183T/C) polymorphism in the manganese superoxide dismutase
(MnSOD), located in mitochondria and implicated in scavenging excessive
oxidative stress to hepatocytes, has been related with NAFLD 17.
• Polymorphisms (1031T/C) and (863C/A) in tumor necrosis factor alpha
(TNFα) were reported as associated with NASH in Japanese and Italian
population 18, 19. TNFα has been shown to induce insulin resistance, involved
in development of NASH.
• A SNP (V175M) in exon 8 of posphatidylethanolamine N-methyltransferase
(PEMT), that play a role in lipoprotein secretion from liver, has been seen
20
associated with NAFLD . This SNP it is a non-synonymous polymorphism
(aminoacid change: V175M) and generates a loss of function of PEMT.
• Mice exposed to a lipid rich diet developed severe NASH with fibrosis that
has been associated with overexpression of Cytochrome P450 2E1 (CYP2E1)
4
. Polymorphisms within this enzyme could be associated with risk of liver
disease.
• Mutations in gen hemochromatosis (HFE) (C282Y and H63D), related with
iron overload, have been associated with hepatic fibrosis 15.
7

9. • It was shown that polymorphism (667C/T) in the methylenetetrahydrofolate
reductase (MTHDR) has been associated with mayor risk to develop
21
hepatocellular carcinoma in patients with alcoholic cirrhosis , and some
alleles have been significantly associated with NASH 22.
23
Rubio et al. suggest that the alterations in gene expression associated with
NASH are broad and selective, and they found that many of the identified genes are
associated with mitochondrial function, insulin action and oxidative stress. Expression
of proliferator-activated receptor gamma (PPARγ) at mRNA level was significantly
24
lower in subjects with ST than in those without . Genes involved in scavenging of
reactive oxygen species (like catalase or glutathione peroxidase), as well as genes
involved in glucose (alcohol dehydrogenase 1 and glucose-6-phosphatase) and fatty
acid metabolism (like 3-hydroxy-3-,ethylglutaryl coenzyme A, mitochondrial 3-oxoacyl-
CoA thiolase and long-chain acyl-CoA synthetase) are down-regulated in NASH
25
patients . However, genes involved in protein synthesis, degradation pathways and
25
complement activation are up-regulated in NASH patients . It is interesting to
emphasize that patients with liver ST have a gene-expression pattern intermediate
23
between those patients with NASH and healthy controls . However, Rubio el al.23
described that all patients with ST do not develop NASH, and only those that have a
similar gene-expression pattern to the one associated to NASH seem to have a higher
risk to develop NASH.
Cytochrome P450 2E1 (CYP2E1) is up-regulated in patients with NASH while in
patients with ST is normal. Its activity has been associated with oxidative stress, insulin
12
resistance and hepatic lipid peroxidation . In addition, it has been seen that several
genes that are important for the mitochondrial function are down-regulated in NASH
patients 3.
8

10. Association Studies
The development of common diseases results from complex interactions
between numerous environmental factors and variation of several genes, and,
therefore, it is very interesting identifying the associated variations to understand the
biology of those diseases 26.
The Human Genome Project has deposited millions of Single Nucleotide
Polymorphisms (SNP) into public databases like dbSNP
(http://www.ncbi.nlm.nih.gov/sites/entrez) or International HapMap Project
27
(http://www.hapmap.org/) . The goal of the international HapMap Project is to
determine the common patterns of DNA sequence variation in the human genome and
to make this information freely available in the public domain. The data base contains
a map of these patterns across the genome by determining genotypes, their
28
frequencies and the degree of variability in different populations . The phase II
HapMap has characterized over 3.1 million of SNPs by genotyping 270 individuals from
four geographically diverse populations and includes 25-35% of common SNP variation
in the populations surveyed 29. In addition, HapMap Project characterized the linkage
disequilibrium (LD) patterns of different population based in the obtained genotypes.
LD means a nonrandom relationship of alleles at two or more loci that is inherited as
one single block. It is possible to do an association study of a significant proportion of
the common variation of a large number of genes that occurs in regions of high LD
where it is not necessary to genotype all SNPs within an LD-block but just one or two
26, 30
representatives of each region, which are called haplotype tag SNPs (htSNPs) .
When multiple markers in a chromosomal region are studied to assess the association
between this region and disease, a statistical analysis based on haplotypes may be
more informative than separate analyses of the individual markers 27.
Samples used for association should be selected with care:
• Case and control groups should be of the same ethnical population,
because if different population are mixed-up their different genetic
background can drive to false marker association (population
stratification) 26.
9

11. • The inclusion criteria for case and control selection should be very strict
according to their clinical parameters. The more phenotypical
information we have, the better.
The results obtained in a genetic association study should be validated by
testing the function of the associated genes within an in vivo system.
NAFLD association study at CIC bioGUNE
The present project is part of a study that is being carried out at CIC bioGUNE
for the association of genetic variations with NAFLD.
According to previous experimental studies (including knockout models,
transcriptomics, proteomics, and metabolomics), a list of candidate genes involved in
the pathogenesis of NASH was identified. Ninety two genes were considered according
to the following criteria: 62 genes were previously identified to be differentially
expressed in liver samples from patients with NASH and/or ST compared to controls 23;
17 genes are involved in hepatic One-Carbone metabolism, compromising the
methylation and folate cycles; and 13 genes had been associated to liver injury.
A total of 3,072 htSNPs were selected within those aforementioned candidate
genes based on the information available at international HapMap Project for the
European and Asian Populations.
Among all the samples obtained from the collaborative hospitals (Principe de
Asturias Hospital, Madrid, Spain; Clinic Hospital, Barcelona, Spain; Hospital de
Galdakao, Galdakao, Spain) only those with certain diagnosis for ST and/orNASH after
biopsy were genotyped. DNA from control individuals was purchased from the DNA
bank of BIOEF Foundation (Sondika, Spain). The inclusion criteria for the controls were
absence of Insulin Resistance Syndrome (no traces of hyperglycemia, hypertension or
obesity), normal liver activity tested by measuring the levels of transaminases and
Body Mass Index (BMI) ≤30 kg/m2.
10

12. A total of 69 patients and 217 controls were successfully genotyped by Golden
Gate technology following Illumina Inc.’s protocols.
Aim of the study
The general objective of CIC bioGUNE project is to find some genetic
association with non-alcoholic hepatic disease that can be used as a non-invasive
diagnosis method, following a candidate-gene association approach
The specific aim of the present work is to analyze the results of the association
study (statistics) and to test the mRNA expression level of the resulting associated
genes in liver biopsies of diagnosed individuals.
11

13. MATERIALS AND METHODS
Association study
Data obtained by GoldenGate Assay were decoded and corrected in Genome
Studio (2008 (c) Illumina, Inc. 2003-2008) software. Only good quality markers were
considered for further analysis.
Obtained genotypes and allele frequencies were compared between ST/NASH
cases and controls using PLINK Software v. 1.05. The analysis was done using allelic
test of single-marker and multi-marker association including all individuals. The data
filtering criteria were minor allele frequency (MAF) ≥ 0.01 and Hardy-Weinberg
equilibrium (HWE) ≥ 0.001.
Calculation of r2 and Gabriel et al. LD-block estimation31 were analyzed in
Haploview v. 4.1 (MAF ≥ 0.01 and HWE ≥ 0.001).
Differential expression
Total-RNA extracts were obtained from liver biopsies of control individuals, ST
and NASH patients. Human Universal Reference RNA (HUR) of Clontech (Stratagene:
740000) was used as a positive control.
Retro-transcription (RT) of samples and HUR was done following this protocol:
• 275 ng of total-RNA, 1µl of Oligo (dT) 12-18 (500µg/ml), 1µl dNTP mix
(10mM) and sterile distilled water were added per tube
• Mixture was heated at 65ºC for 5 min and contents were collected by brief
centrifugation
• 4µl of 5x First-Strand Buffer, 24µl of 0.1 M DTT and 1µl of RNaseOUTTM (40
units/µl) were added per tube
• Tubes were mixed gently and incubated at 42ºC for 2 min
12

14. • 1µl of SuperScriptTM (200 units, Invitrogen, Cat. No. 10777-019) was added
per tube and mixed
• Tubes were incubated at 42ºC for 50 min and 70ºC for 15min in order to
inactivate the enzyme
Then, 17µl of each cDNA product were diluted in 300µl of water.
cDNA of HUR was diluted as follows in order to have a standard curve of each
quantitative PCR (qPCR) reaction:
20µl of original cDNA + 400µl of distilled water
200µl of previous dilution + 200 µl of distilled water
200µl of previous dilution + 200 µl of distilled water
200µl of previous dilution + 200 µl of distilled water
200µl of previous dilution + 200 µl of distilled water
cDNA of cases and controls was analyzed in iCycler Thermal Cycler with iCycler
iQ Module developed by Bio-Rad.
Primers for measuring the mRNA expression of Cytochrome P450, family 2,
subfamily E, polypeptide 1 (CYP2E1), Serine/threonine kinase 11 (STK11), Solute carrier
family 2 (facilitated glucose transporter), member 1 (SLC2A1), Asparaginase synthetase
(ASNS) and 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR) were
purchased from Qiagen as QuantiTec® Primer Assay numbers QT01669962,
QT01008980, QT00068957, QT00084546, and QT00072156 respectively. The mRNA
expression of Glyceraldehyde-3-phosphate dehydrogenase (GADPH) and acidic
ribosomal phosphoprotein (ARP), as housekeeping genes, was analyzed using in-house
sets of primers.
For the qPCR, reactions were set in triplicates, and standard curve dilutions
were analyzed in duplicates. All reactions were done in a total volume of 20µl including
the following reagents:
13

15. For QuantiTec® Primer Assay primer sets (per tube):
1µl of EvaGreen 20x (Biotisem: 31000)
10µl of Hot Start MasterMix 2x (Metabion, mi-E8011)
2µl of Forward and Reverse primers 10X
5µl of cDNA sample
2µl of distilled water
For housekeeping genes primer sets (per tube):
1µl of EvaGreen 20x (Biotisem: 31000)
10µl of Hot Start MasterMix 2x (Metabion, mi-E8011)
0.54 µl of Forward primer 100mM
0.54 µl of Reverse primer 100mM
5µl of cDNA sample
2.92µl of distilled water
An automatic pipetting system (Eppendorff epMottion 5070) was used in order
to increase the reproducibility of the assays.The amplification cycling conditions for
the qPCR were:
• For ASNS, CYP2E1, STK11 and MTR: 40 cycles of 15s at 94ºC, 30s at 55ºC and
30s at 72ºC.
• For SLC2A1: 40 cycles of 15s at 94ºC, 30s at 61ºC and 30s at 72ºC.
• For housekeeping genes (GADPH and ARP): 40 cycles of 15s at 94ºC, 30s at 60ºC
and 30s at 72ºC.
Differential relative expression of each tested gene was estimated based on
the obtained Ct values, by the delta-delta-Ct method 32.
14

16. RESULTS
Association Study
A total of 1536 SNPs were successfully genotyped in all studied individuals (69
cases and 217 controls).
Eleven SNPs showed to be significantly associated (p < 10-4) with NAFLD for the
single-marker allelic test. These significant SNPs were located in the following genes:
Cytochrome P450, family 2, subfamily E, polypeptide 1 (CYP2E1), Smg-7 homolog,
nonsense mediated mRNA decay factor (SMG7), Solute carrier family 2 (facilitated
glucose transporter), member 1 (SLC2A1), 5-methyltetrahydrofolate-homocysteine
methyltransferase (MTR) and Serine/threonine kinase 11 (STK11) (see table 1). Seven
out of the eleven associated SNPs are located in SLC2A1 and all of them are in high LD
(figure 2).
CHR SNP gene A1 F_A F_U A2 CHISQ P Position
10 rs28969387 CYP2E1 A 0.063 0 T 27.52 1.56E-07 Exon 9
1 rs1044879 SMG7 G 0.627 0.406 C 17.43 2.98E-05 3'UTR
1 rs1770810 SLC2A1 A 0.278 0.127 G 16.4 5.13E-05 Intron
1 rs841856 SLC2A1 A 0.271 0.124 C 15.39 8.73E-05 Intron
1 rs3754255 MTR A 0.258 0.442 G 13.59 2.28E-04 Intron
19 rs7259033 STK11 G 0.33 0.521 C 12.93 3.24E-04 Intron
1 rs841858 SLC2A1 A 0.234 0.113 C 12.07 5.12E-04 Intron
1 rs4658 SLC2A1 G 0.286 0.152 C 11.71 6.23E-04 3'UTR
1 rs841848 SLC2A1 A 0.281 0.145 G 11.57 6.69E-04 Intron
1 rs3754223 SLC2A1 A 0.273 0.145 T 11.41 7.29E-04 Intron
1 rs2229682 SLC2A1 A 0.265 0.141 G 11 9.12E-04 Exon 6
-4
Table 1. Results of the single-marker analysis. Only significant (p < 10 ) SNPs are shown.
Multi-marker association was analyzed by sliding window from 2 to 10 SNPs-
windows, and p < 10-4 value was used as a threshold. This test revealed one group of 3
SNPs located in an intronic region of Asparaginase synthetase (ASNS) gene, which
resulted to be in total LD in the studied population (see table 2 and figure 2).
15

17. LOCUS gene start gene end HAPLOTYPE F_A F_U P Sliding windows
WIN1246 ASNS ASNS TAG 0.1176 0.2857 7.09E-05 rs7781469 rs4727377 rs7810919
-4
Table 2. Results of the sliding-windows analysis. Only significant (p < 10 ) windows are shown.
Figure 2. a) LD values (r2) of SLC2A1 (red color without number means 100% of LD) and b) of ASNS
significantly associated SNPs.
Differential expression
Differential expression analysis was done for all the genes represented by
several (more than one) associated SNPs with a p<10-2 (3 SNPs ofCYP2E1; 11 SNPs of
SLC2A1; 12 SNPs of MTR; 3 SNPs of STK11; 11 SNPs of ASNS. Therefore, although
rs1044879, which is a proxy of neutrophil cytosolic factor 2 (NCF2), was one of the
most significant SNPs (p=2.98 x 10-5), it was not considered for subsequent analysis
because NCF2 was represented uniquely by that polymorphism.
RT-qPCR for the 5 associated genes (CYP2E1, STK11, SLC2A1 ASNS MTR) and 2
housekeeping genes (GADPH and ARP) was carried out using the RNA extracted from
liver biopsies of a total of 5 ST and 5 NASH patients and 6 controls.
16

18. In figure 3 we represent the ratio (Cthousekeeping/Ct target gene) based on the media
Ct values obtained for each group of samples (ST, NASH and controls). These results
show that the Ct values obtained for both housekeeping genes (GADPH and ARP) were
very similar. Consequently, a media value of the 2 housekeeping Cts was used to
normalize the expression levels of the targeted genes (Figure 4).
Figure 3. mRNA expression ratio (Ct housekeeping / Ct target gene) of all the studied genes.
17

19. 32
Figure 4. Results of differential expression analysis obtained by delta-delta-Ct method .
The differential expression analysis showed that CYP2E1 has similar regulation
in controls and in ST, while it is up-regulated in NASH. We can also observe that ASNS,
STK11 and MTR are up-regulated in NASH. However, ASNS is down-regulated in ST, and
STK11 and MTR have similar expression in ST and controls. Additionally, SLC2A1 is
down-regulated in ST and NASH patients.
18

20. DISCUSSION
In association studies the possibility of false positive findings arises from a
combination of the characterization of small sample sizes, the poor description of case
and control samples, and the overestimation of the risks of genetic effects. In the
present study, the quality of the patient biological material was low and that is why
we got very small genotyping call rate of those samples, and therefore, the proportion
of the total genotyping success was very reduced (about 50%).
Among the obtained results, it is outstanding that the associated SNP located in
exon 9 of CYP2E1 (rs28969387) is a non-synonymous SNP that produces an
aminoacidic change (H457L). Structural changes or loss of function of this protein could
be related to this or other aminoacidic changes. We have seen that expression of
CYP2E1 is significantly up-regulated in NASH samples, however, it does not seem to be
altered at all in ST patients (see figure 3). Those results agree with previous studies 12
in which it is suggested that CYP2E1 could initiate oxidative stress leading to ST to
7, 12
NASH by production of reactive oxygen species (ROS) . Blocking CYP2E1 activity
prevents necroinflammatory changes in rats 4. One study by Jörn et al. 33
based in
overexpression of CYP2E1 in a hepatocyte cell line, reveals that increased CYP2E1
expression results in the down-regulation of insulin signaling, potentially contributing
to the insulin resistance associated with NAFLD. Factors related with NAFLD such as
ethanol exposure, a high-lipid and high-carbohydrate diet, fasting lost weigh and
diabetes, can increase CYP2E1 levels 4.
As shown in this study and in previous works 23, SLC2A1 is down-regulated in ST
and NASH patients (see figure 4). However, SLC2A1 has been found to be up-regulated
in obesity and diabetes patients 34, both diseases associated with NAFLD. The proper
understanding of this result could be very interesting since the oposite regulation of
SLC2A1 in ST/NASH compared to obesity/diabetes could suggest the potentiality of this
gene as a genetic marker to identify NAFLD.
4
When ST progresses to NASH, the insulin resistance occurs and in this
conditions, Cui et al.35 found over-expression of ASNS and, in addition, Sreekumar et
25
al. found general up-regulation in genes involved in protein synthesis in NASH
19

21. patients. Those data agree with our results, in which we found ASNS down-regulated in
ST while it is up-regulated in NASH (see figure 3).
36, 37
MTR enzyme has been shown down-regulated in alcoholic liver diseases
due probably to the direct effect of the alcohol in the regulation of this enzyme. In the
contrary, we saw that MTR was more expressed in the studied ST/NASH liver biopsies
than in the controls (Figure 3). This result could be understood if we consider that
NAFLD patients may drink from 0 to 40 gr of ethanol per week and we do not have this
information for the studied samples.
38
Nakau et al. suggest that lack of STK11 activity is a mechanism for HCC
38
development. In addition, STK11 plays a key role in the p53-dependent apoptosis ,
38
over-expression of STK11 in tumor cell lines results in cell cycle arrests and up-
regulation of STK11 could delay progression from NASH to HCC. What is more, STK11
phospholyration is related with an increase in expression of fatty acid synthase (FAS)
39
. Therefore, the up-regulation of this enzyme detected in the present study could be
the cause of an increasing lipid accumulation within hepatocytes in ST and NASH
patients.
It will be interesting to get the associated SNPs genotypes for the liver biopsies
where regulation of the corresponding genes was tested, in order to correlate
genotype to phenotype.
The obtained results open some new perspectives into the NAFLD research. It
will be required to describe the implications of the mentioned genes in the
pathogenesis of NAFLD, and hopefully, the resulting knowledge will even reveal some
new therapeutic targets.
20

22. CONCLUSIONS
The present project demonstrates for the first time that SLC2A1 is associated
with NAFLD, since 7 SNPs located within this gene showed significant association (p <
10-4).
Regulation of SLC2A1 in ST and NASH is opposite than in obese people. This
means that SLC2A1 could be a potential specific marker of NAFLD.
The regulation of the studied genes is always higher in NASH samples than in ST
ones. This could suggest that metabolism in NASH patients is more unbalanced than in
ST.
OUTLOOK
This project will continue first validating significant SNPs in other cohort of
case/control samples. Afterwards, functional studies of associated genes should be
carried out by either silencing down-regulated genes or over-expressing up-regulated
ones, followed by the analysis of the consequences of these regulations at genome-
wide level. The analysis of the transcriptome expression of the chosen in-vivo models
will be examined using high-throughput arrays.
Special efforts will be carried out to test that the regulation of associated genes
seen in liver biopsies is somehow reflected in the blood. This will be crucial to develop
non-invasive diagnostic tools.
AKNOWLEDGMENTS
This work was supported by a grant of Fundacion La caixa (obra social, number
BM06-227-0) coordinated by Mari Luz Martínez-Chantar. I would like to thank Ana M.
Aransay’s and Mari Luz Martinez-Chantar’s research groups for teaching me the
background, the hypothesis and the appropriate techniques that made this work
possible.
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23. REFERENCES
1. Solis Herruzo JA, Garcia Ruiz I, Perez Carreras M, Munoz Yague MT. Non-
alcoholic fatty liver disease. From insulin resistance to mitochondrial
dysfunction. Rev Esp Enferm Dig 2006;98:844-74.
2. Osterreicher CH, Brenner DA. The genetics of nonalcoholic fatty liver disease.
Ann Hepatol 2007;6:83-8.
3. Duvnjak M, Lerotic I, Barsic N, Tomasic V, Virovic Jukic L, Velagic V.
Pathogenesis and management issues for non-alcoholic fatty liver disease.
World J Gastroenterol 2007;13:4539-50.
4. Chitturi S, Farrell GC. Etiopathogenesis of nonalcoholic steatohepatitis. Semin
Liver Dis 2001;21:27-41.
5. Clark JM, Brancati FL, Diehl AM. Nonalcoholic fatty liver disease.
Gastroenterology 2002;122:1649-57.
6. Nugent C, Younossi ZM. Evaluation and management of obesity-related
nonalcoholic fatty liver disease. Nat Clin Pract Gastroenterol Hepatol
2007;4:432-41.
7. Younossi ZM, Diehl AM, Ong JP. Nonalcoholic fatty liver disease: an agenda for
clinical research. Hepatology 2002;35:746-52.
8. Castera L. Non-invasive diagnosis of steatosis and fibrosis. Diabetes Metab
2008;34:674-9.
9. Angulo P, Keach JC, Batts KP, Lindor KD. Independent predictors of liver fibrosis
in patients with nonalcoholic steatohepatitis. Hepatology 1999;30:1356-62.
10. Fong DG, Nehra V, Lindor KD, Buchman AL. Metabolic and nutritional
considerations in nonalcoholic fatty liver. Hepatology 2000;32:3-10.
11. Shifflet A, Wu GY. Non-alcoholic Steatohepatitis: An Overview. J Formos Med
Assoc 2009;108:4-12.
12. Jou J, Choi SS, Diehl AM. Mechanisms of disease progression in nonalcoholic
fatty liver disease. Semin Liver Dis 2008;28:370-9.
13. Kim CH, Younossi ZM. Nonalcoholic fatty liver disease: a manifestation of the
metabolic syndrome. Cleve Clin J Med 2008;75:721-8.
22

24. 14. Pessayre D, Fromenty B. NASH: a mitochondrial disease. J Hepatol 2005;42:928-
40.
15. Bonkovsky HL, Jawaid Q, Tortorelli K, LeClair P, Cobb J, Lambrecht RW, Banner
BF. Non-alcoholic steatohepatitis and iron: increased prevalence of mutations
of the HFE gene in non-alcoholic steatohepatitis. J Hepatol 1999;31:421-9.
16. Erickson SK. Nonalcoholic fatty liver disease (NAFLD). J Lipid Res 2008.
17. Namikawa C, Shu-Ping Z, Vyselaar JR, Nozaki Y, Nemoto Y, Ono M, Akisawa N,
Saibara T, Hiroi M, Enzan H, Onishi S. Polymorphisms of microsomal triglyceride
transfer protein gene and manganese superoxide dismutase gene in non-
alcoholic steatohepatitis. J Hepatol 2004;40:781-6.
18. Tokushige K, Takakura M, Tsuchiya-Matsushita N, Taniai M, Hashimoto E,
Shiratori K. Influence of TNF gene polymorphisms in Japanese patients with
NASH and simple steatosis. J Hepatol 2007;46:1104-10.
19. Valenti L, Fracanzani AL, Dongiovanni P, Santorelli G, Branchi A, Taioli E, Fiorelli
G, Fargion S. Tumor necrosis factor alpha promoter polymorphisms and insulin
resistance in nonalcoholic fatty liver disease. Gastroenterology 2002;122:274-
80.
20. Song J, da Costa KA, Fischer LM, Kohlmeier M, Kwock L, Wang S, Zeisel SH.
Polymorphism of the PEMT gene and susceptibility to nonalcoholic fatty liver
disease (NAFLD). FASEB J 2005;19:1266-71.
21. Saffroy R, Pham P, Chiappini F, Gross-Goupil M, Castera L, Azoulay D, Barrier A,
Samuel D, Debuire B, Lemoine A. The MTHFR 677C > T polymorphism is
associated with an increased risk of hepatocellular carcinoma in patients with
alcoholic cirrhosis. Carcinogenesis 2004;25:1443-8.
22. Sazci A, Ergul E, Aygun C, Akpinar G, Senturk O, Hulagu S.
Methylenetetrahydrofolate reductase gene polymorphisms in patients with
nonalcoholic steatohepatitis (NASH). Cell Biochem Funct 2008;26:291-6.
23. Rubio A, Guruceaga E, Vazquez-Chantada M, Sandoval J, Martinez-Cruz LA,
Segura V, Sevilla JL, Podhorski A, Corrales FJ, Torres L, Rodriguez M, Aillet F, Ariz
U, Arrieta FM, Caballeria J, Martin-Duce A, Lu SC, Martinez-Chantar ML, Mato
JM. Identification of a gene-pathway associated with non-alcoholic
steatohepatitis. J Hepatol 2007;46:708-18.
23

25. 24. Westerbacka J, Kolak M, Kiviluoto T, Arkkila P, Siren J, Hamsten A, Fisher RM,
Yki-Jarvinen H. Genes involved in fatty acid partitioning and binding, lipolysis,
monocyte/macrophage recruitment, and inflammation are overexpressed in
the human fatty liver of insulin-resistant subjects. Diabetes 2007;56:2759-65.
25. Sreekumar R, Rosado B, Rasmussen D, Charlton M. Hepatic gene expression in
histologically progressive nonalcoholic steatohepatitis. Hepatology
2003;38:244-51.
26. Wang WY, Barratt BJ, Clayton DG, Todd JA. Genome-wide association studies:
theoretical and practical concerns. Nat Rev Genet 2005;6:109-18.
27. Zhao H, Pfeiffer R, Gail MH. Haplotype analysis in population genetics and
association studies. Pharmacogenomics 2003;4:171-8.
28. The International HapMap Project. Nature 2003;426:789-96.
29. Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, Gibbs RA, Belmont JW,
Boudreau A, Hardenbol P, Leal SM, Pasternak S, Wheeler DA, Willis TD, Yu F,
Yang H, Zeng C, Gao Y, Hu H, Hu W, Li C, Lin W, Liu S, Pan H, Tang X, Wang J,
Wang W, Yu J, Zhang B, Zhang Q, Zhao H, Zhou J, Gabriel SB, Barry R,
Blumenstiel B, Camargo A, Defelice M, Faggart M, Goyette M, Gupta S, Moore
J, Nguyen H, Onofrio RC, Parkin M, Roy J, Stahl E, Winchester E, Ziaugra L,
Altshuler D, Shen Y, Yao Z, Huang W, Chu X, He Y, Jin L, Liu Y, Sun W, Wang H,
Wang Y, Xiong X, Xu L, Waye MM, Tsui SK, Xue H, Wong JT, Galver LM, Fan JB,
Gunderson K, Murray SS, Oliphant AR, Chee MS, Montpetit A, Chagnon F,
Ferretti V, Leboeuf M, Olivier JF, Phillips MS, Roumy S, Sallee C, Verner A,
Hudson TJ, Kwok PY, Cai D, Koboldt DC, Miller RD, Pawlikowska L, Taillon-Miller
P, Xiao M, Tsui LC, Mak W, Song YQ, Tam PK, Nakamura Y, Kawaguchi T,
Kitamoto T, Morizono T, Nagashima A, Ohnishi Y, Sekine A, Tanaka T, Tsunoda
T, et al. A second generation human haplotype map of over 3.1 million SNPs.
Nature 2007;449:851-61.
30. de Bakker PI, Yelensky R, Pe'er I, Gabriel SB, Daly MJ, Altshuler D. Efficiency and
power in genetic association studies. Nat Genet 2005;37:1217-23.
31. Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J,
DeFelice M, Lochner A, Faggart M, Liu-Cordero SN, Rotimi C, Adeyemo A,
24

26. Cooper R, Ward R, Lander ES, Daly MJ, Altshuler D. The structure of haplotype
blocks in the human genome. Science 2002;296:2225-9.
32. Giulietti A, Overbergh L, Valckx D, Decallonne B, Bouillon R, Mathieu C. An
overview of real-time quantitative PCR: applications to quantify cytokine gene
expression. Methods 2001;25:386-401.
33. Schattenberg JM, Wang Y, Singh R, Rigoli RM, Czaja MJ. Hepatocyte CYP2E1
overexpression and steatohepatitis lead to impaired hepatic insulin signaling. J
Biol Chem 2005;280:9887-94.
34. MacLaren R, Cui W, Simard S, Cianflone K. Influence of obesity and insulin
sensitivity on insulin signaling genes in human omental and subcutaneous
adipose tissue. J Lipid Res 2008;49:308-23.
35. Cui H, Darmanin S, Natsuisaka M, Kondo T, Asaka M, Shindoh M, Higashino F,
Hamuro J, Okada F, Kobayashi M, Nakagawa K, Koide H. Enhanced expression
of asparagine synthetase under glucose-deprived conditions protects
pancreatic cancer cells from apoptosis induced by glucose deprivation and
cisplatin. Cancer Res 2007;67:3345-55.
36. Barak AJ, Beckenhauer HC, Kharbanda KK, Tuma DJ. Chronic ethanol
consumption increases homocysteine accumulation in hepatocytes. Alcohol
2001;25:77-81.
37. Kerai MD, Waterfield CJ, Kenyon SH, Asker DS, Timbrell JA. Reversal of ethanol-
induced hepatic steatosis and lipid peroxidation by taurine: a study in rats.
Alcohol Alcohol 1999;34:529-41.
38. Nakau M, Miyoshi H, Seldin MF, Imamura M, Oshima M, Taketo MM.
Hepatocellular carcinoma caused by loss of heterozygosity in Lkb1 gene
knockout mice. Cancer Res 2002;62:4549-53.
39. Hou X, Xu S, Maitland-Toolan KA, Sato K, Jiang B, Ido Y, Lan F, Walsh K,
Wierzbicki M, Verbeuren TJ, Cohen RA, Zang M. SIRT1 regulates hepatocyte
lipid metabolism through activating AMP-activated protein kinase. J Biol Chem
2008;283:20015-26.
25