Suficiencia investigadora


Published on

Suficiencia investigadora

Published in: Education, Health & Medicine
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Suficiencia investigadora

  2. 2. ABSTRACT Non-alcoholic fatty liver diseases (NAFLD) are the most common causes ofchronic liver disease in several western countries. Up to now, the only way to diagnoseNAFLD with certainty is liver biopsy. Therefore, the aim of the present project is to findgenetic markers that could help to develop a non-invasive diagnostic method for thesedisorders. To achieve this objective we have carried out a candidate gen associationapproach that yielded 6 potentially associated genes, being the first time that SLC2A1has been associated with NAFLD. In addition, we have investigated the regulation ofthose genes in liver biopsies at transcriptomic level. We have detected that all thestudied genes are regulated in NAFLD, and that the regulation is higher in advancedstages of the disease. This suggests that the identified genes could serve as potentialmarkers for the diagnosis of the phases of NAFLD development. 1
  3. 3. INTRODUCTION Non-alcoholic fatty liver disease (NAFLD) includes a wide spectrum of lesionsincluding steatosis (ST), non-alcoholic steatohepatitis (NASH), fatty liver andinflammation, as well as a high number of cryptogenic cirrhoses 1. NAFLD representsthe hepatic manifestation of the metabolic syndrome with insulin resistance as acommon feature, namely, central obesity, insulin resistance, dyslipidemia andhypertension 2, 3. ST is an accumulation of fatty acids in the liver 4 and NASH is a termthat describes a form of liver disease that is histologically indistinguishable from 4, 5alcoholic 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 westerncountries 5 and it has been reported in all age groups including children, although thehighest prevalence is described in individuals between 40 and 60 years 3. About 75% ofobese patients have NAFLD 6 (the prevalence augments with increasing body weight 3).In general population, the prevalence of NAFLD is estimated about 20% 7. Theprevalence of NAFLD is increasing in industrialized countries 2 due probably to socialand 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 wasdetected in 62% of patients with newly diagnosed T2D and T2D has been described in34% to 75% of patients with NASH 3. Obesity and diabetes mellitus are notpredisposing factors only to develop NAFLD, but they are also potential risk factors todevelop severe hepatic fibrosis and cirrhosis 9. All of these previous mentioned factors,hyperlidipemia and other conditions associated with insulin resistance are generallypresent in patients with NAFLD 3: at the time of NASH diagnosis, up to one third of thepatients have diabetes or fasting hyperglycemia 4, between 39 and 100% areoverweighted or obese, and between 20 and 80% have abnormalities of lipidmetabolism 4. 2
  4. 4. Development and progression of NAFLD The pathogenesis of NAFLD responds to a two-hit hypothesis. First of all, an 10imbalance 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 lipidperoxidation), deregulated proinflammatory cytokines production by Kupffer cells(principally the tumor necrosis factor alpha, TNFα) and hormones derived fromadipose tissue (adipocytokines) that result from efforts to compensate the altered lipidhomeostasis 1, 3, 11, 12 11. Jou et al.12 proposed that the hepatocyte death is the third anddecisive step in NAFLD pathogenesis because this event drives progression from NASHto cirrhosis. In the hepatic ST, vesicles of fat, predominately triglycerides, accumulate withinhepatocytes (without causing considerable hepatic inflammation) causing liver cell 5 12death and activating mechanisms of hepatocyte regeneration . This regenerativerespond activates hepatic stellate cells to myofibroblasts, causing liver fibrosis andexpanding hepatic progenitor populations. Subsequently , several chemoattractans areproduced to recruit various types of immune cells into the liver, inducing hepaticinflammation that drives to NASH 12. ST can progress to NASH due to hepatocyte injuryand apoptosis, and hepatic infiltration by inflammatory cells. It is unclear why somepatients who develop ST go on developing NASH while others do not 11. The next stagecould be that NASH develops to cirrhosis as a result of an incomplete repair ofmetabolic liver injury 12. In most chronic liver diseases that lead to cirrhosis, there is anincreased risk of developing hepatocellular carcinoma (HCC) that is an irreversible 13state of liver damage . Hepatocyte DNA damage and expansion of liver progenitorcells have been demonstrated in early NASH and this suggests that NASH providesfertile ground for neoplastic transformation of hepatocytes at several stages of 12differentiation . Progression of simple ST to NASH increases the risk to developcirrhosis and consequent liver-related morbidity and mortality 12. 3
  5. 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 denovo synthesis of free fatty acids (FFA), disposal of FFA via oxidation or de novotriglyceride synthesis and export of triglycerides as a very low density lipoproteins 12(vLDL) from hepatocytes (Figure 1) . As soon as the rate of triglyceride synthesisoverwhelms the capacity of vLDL export, triglycerides accumulate within hepatocytescausing ST 12. When the insulin resistance occurs, hepatic FFA concentration increasesby the movement of FFA from adipocytes by lipolysis (and, consequently, increasinghepatic import) and/or hepatic endogenous synthesis 4. Triglycerides by themselvesare not hepatotoxic but they are biomarkers of increased hepatic exposure topotential toxic FFA. An enzyme for esterification (Acyl-coA:diacylglycerolacylltransferase, DGAT) is required to transform FFA in triglycerides and to join vLDL12, 4
  6. 6. then, the capacity of vLDL export can be overwhelmed leading to FFA accumulationwithin hepatocytes. The molecular mechanism of the insulin resistance is complex and has notbeen elucidated completely. Several molecules appear to interfere with the insulinsignaling pathway and it has been found that adiponectin plays a key role in insulin 3, 11sensitivity . FFA and their metabolites are ligands of peroxisome proliferator-activated receptor alpha (PPARα), a transcription factor that activates genes involvedin fatty acid oxidation. When PPARα is up-regulated, there is more FFA oxidation,which is translated in increased oxidative stress, elimination of FFA and progressionfrom ST to NASH 3.Oxidative stress Hepatic mitochondria of patients with NASH exhibit ultrastructural lesions withthe presence of para-cristalline inclusions in the megamitochondria, while 14mitochondria of patients with simple ST are normal . Although the mechanisms forhepatic mitochondrial dysfunction in NASH are still unknown, it may involve lipidperoxidation, TNFα and reactive oxygen species (ROS). TNFα increases permeability ofthe mitochondrial membranes and the blocking of the electron flow from complex II to 14complex IV . Those factors are supposed to alter mitochondrial DNA andmitochondrial oxidative phosphorylation, producing the structural alterationsmentioned abobe3. It has been shown that 30% of the patients with NASH have elevated ferritinlevels (marker of iron overload) 11, which plays a role in oxidative stress and may play a 15function in pathogenesis of NASH . This iron overload generates reactive oxygenspecies and subsequent lipid peroxidation. In addition, iron has harmful effects on themitochondria activity 11. 5
  7. 7. Diagnosis of NAFLD Most of the diagnosis of NAFLD is done by exclusion of other liver diseasestaking into consideration parameters through a scoring system 11 like biochemical testsbased on serum markers, imaging techniques such as ultrasound, and measurement of 8, 13liver stiffness by transient elastography . The gold standard for accurate diagnosisof 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 problemswith liver biopsy are that is painful, invasive and, given the increasing number ofpatients with NAFLD, it is not an efficient method 8. Therefore, studies of thesediseases are limited by the inability to make a definitive diagnosis of NAFLD3.Additionally, distinction of NASH from simple ST is important because their prognosesand clinical management are different 8, 13. Studies that have used strict definitions fordiagnosis, including biopsies, were most often based on specific subsets of thepopulation (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 appliedtherapies include specific diet and exercise for weight loss and sometimes, it could be 16enough to treat hepatic ST . It is also recommended to stop smoking and alcohol- 3drinking during treatment . When specific diet and exercise is not enough,pharmacological treatment should be initiated. Several drugs such as antioxidants and 3, 13lipid-lowering drugs have been tried for the treatment of NAFLD . There is quite acontroversy about NAFLD pharmacological treatment because the response of patientsis variable and often there are important secondary effects. 6
  8. 8. Genetic of liver diseases It has been shown that most evidences of genetic association with NAFLDderive from family clustering analysis 2. There are different families of genes involvedin ST and NASH: genes influencing lipid metabolism, genes affecting oxidative stress,genes coding for bacterial receptors and genes influencing extracellular matrixsynthesis and degradation 2. Modifications of those gDNA gene sequences have beenassociated 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. 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 withNASH are broad and selective, and they found that many of the identified genes areassociated with mitochondrial function, insulin action and oxidative stress. Expressionof proliferator-activated receptor gamma (PPARγ) at mRNA level was significantly 24lower in subjects with ST than in those without . Genes involved in scavenging ofreactive oxygen species (like catalase or glutathione peroxidase), as well as genesinvolved in glucose (alcohol dehydrogenase 1 and glucose-6-phosphatase) and fattyacid metabolism (like 3-hydroxy-3-,ethylglutaryl coenzyme A, mitochondrial 3-oxoacyl-CoA thiolase and long-chain acyl-CoA synthetase) are down-regulated in NASH 25patients . However, genes involved in protein synthesis, degradation pathways and 25complement activation are up-regulated in NASH patients . It is interesting toemphasize that patients with liver ST have a gene-expression pattern intermediate 23between those patients with NASH and healthy controls . However, Rubio el al.23described that all patients with ST do not develop NASH, and only those that have asimilar gene-expression pattern to the one associated to NASH seem to have a higherrisk to develop NASH. Cytochrome P450 2E1 (CYP2E1) is up-regulated in patients with NASH while inpatients with ST is normal. Its activity has been associated with oxidative stress, insulin 12resistance and hepatic lipid peroxidation . In addition, it has been seen that severalgenes that are important for the mitochondrial function are down-regulated in NASHpatients 3. 8
  10. 10. Association Studies The development of common diseases results from complex interactionsbetween numerous environmental factors and variation of several genes, and,therefore, it is very interesting identifying the associated variations to understand thebiology of those diseases 26. The Human Genome Project has deposited millions of Single NucleotidePolymorphisms (SNP) into public databases like dbSNP( or International HapMap Project 27( . The goal of the international HapMap Project is todetermine the common patterns of DNA sequence variation in the human genome andto make this information freely available in the public domain. The data base containsa map of these patterns across the genome by determining genotypes, their 28frequencies and the degree of variability in different populations . The phase IIHapMap has characterized over 3.1 million of SNPs by genotyping 270 individuals fromfour geographically diverse populations and includes 25-35% of common SNP variationin the populations surveyed 29. In addition, HapMap Project characterized the linkagedisequilibrium (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 asone single block. It is possible to do an association study of a significant proportion ofthe common variation of a large number of genes that occurs in regions of high LDwhere it is not necessary to genotype all SNPs within an LD-block but just one or two 26, 30representatives of each region, which are called haplotype tag SNPs (htSNPs) .When multiple markers in a chromosomal region are studied to assess the associationbetween this region and disease, a statistical analysis based on haplotypes may bemore 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. 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 bytesting 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 bioGUNEfor 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 inthe pathogenesis of NASH was identified. Ninety two genes were considered accordingto the following criteria: 62 genes were previously identified to be differentiallyexpressed in liver samples from patients with NASH and/or ST compared to controls 23;17 genes are involved in hepatic One-Carbone metabolism, compromising themethylation and folate cycles; and 13 genes had been associated to liver injury. A total of 3,072 htSNPs were selected within those aforementioned candidategenes based on the information available at international HapMap Project for theEuropean and Asian Populations. Among all the samples obtained from the collaborative hospitals (Principe deAsturias Hospital, Madrid, Spain; Clinic Hospital, Barcelona, Spain; Hospital deGaldakao, Galdakao, Spain) only those with certain diagnosis for ST and/orNASH afterbiopsy were genotyped. DNA from control individuals was purchased from the DNAbank of BIOEF Foundation (Sondika, Spain). The inclusion criteria for the controls wereabsence of Insulin Resistance Syndrome (no traces of hyperglycemia, hypertension orobesity), normal liver activity tested by measuring the levels of transaminases andBody Mass Index (BMI) ≤30 kg/m2. 10
  12. 12. A total of 69 patients and 217 controls were successfully genotyped by GoldenGate technology following Illumina Inc.’s protocols.Aim of the study The general objective of CIC bioGUNE project is to find some geneticassociation with non-alcoholic hepatic disease that can be used as a non-invasivediagnosis method, following a candidate-gene association approach The specific aim of the present work is to analyze the results of the associationstudy (statistics) and to test the mRNA expression level of the resulting associatedgenes in liver biopsies of diagnosed individuals. 11
  13. 13. MATERIALS AND METHODSAssociation study Data obtained by GoldenGate Assay were decoded and corrected in GenomeStudio (2008 (c) Illumina, Inc. 2003-2008) software. Only good quality markers wereconsidered for further analysis. Obtained genotypes and allele frequencies were compared between ST/NASHcases and controls using PLINK Software v. 1.05. The analysis was done using allelictest of single-marker and multi-marker association including all individuals. The datafiltering criteria were minor allele frequency (MAF) ≥ 0.01 and Hardy-Weinbergequilibrium (HWE) ≥ 0.001. Calculation of r2 and Gabriel et al. LD-block estimation31 were analyzed inHaploview v. 4.1 (MAF ≥ 0.01 and HWE ≥ 0.001).Differential expression Total-RNA extracts were obtained from liver biopsies of control individuals, STand 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. 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 eachquantitative 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 iCycleriQ 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 carrierfamily 2 (facilitated glucose transporter), member 1 (SLC2A1), Asparaginase synthetase(ASNS) and 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR) werepurchased from Qiagen as QuantiTec® Primer Assay numbers QT01669962,QT01008980, QT00068957, QT00084546, and QT00072156 respectively. The mRNAexpression of Glyceraldehyde-3-phosphate dehydrogenase (GADPH) and acidicribosomal phosphoprotein (ARP), as housekeeping genes, was analyzed using in-housesets of primers. For the qPCR, reactions were set in triplicates, and standard curve dilutionswere analyzed in duplicates. All reactions were done in a total volume of 20µl includingthe following reagents: 13
  15. 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 orderto increase the reproducibility of the assays.The amplification cycling conditions forthe 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 onthe obtained Ct values, by the delta-delta-Ct method 32. 14
  16. 16. RESULTSAssociation Study A total of 1536 SNPs were successfully genotyped in all studied individuals (69cases and 217 controls). Eleven SNPs showed to be significantly associated (p < 10-4) with NAFLD for thesingle-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 (facilitatedglucose transporter), member 1 (SLC2A1), 5-methyltetrahydrofolate-homocysteinemethyltransferase (MTR) and Serine/threonine kinase 11 (STK11) (see table 1). Sevenout 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 3UTR 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 3UTR 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 3SNPs located in an intronic region of Asparaginase synthetase (ASNS) gene, whichresulted to be in total LD in the studied population (see table 2 and figure 2). 15
  17. 17. LOCUS gene start gene end HAPLOTYPE F_A F_U P Sliding windowsWIN1246 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. 18. In figure 3 we represent the ratio (Cthousekeeping/Ct target gene) based on the mediaCt values obtained for each group of samples (ST, NASH and controls). These resultsshow that the Ct values obtained for both housekeeping genes (GADPH and ARP) werevery similar. Consequently, a media value of the 2 housekeeping Cts was used tonormalize 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. 19. 32Figure 4. Results of differential expression analysis obtained by delta-delta-Ct method . The differential expression analysis showed that CYP2E1 has similar regulationin 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, andSTK11 and MTR have similar expression in ST and controls. Additionally, SLC2A1 isdown-regulated in ST and NASH patients. 18
  20. 20. DISCUSSION In association studies the possibility of false positive findings arises from acombination of the characterization of small sample sizes, the poor description of caseand control samples, and the overestimation of the risks of genetic effects. In thepresent study, the quality of the patient biological material was low and that is whywe got very small genotyping call rate of those samples, and therefore, the proportionof the total genotyping success was very reduced (about 50%). Among the obtained results, it is outstanding that the associated SNP located inexon 9 of CYP2E1 (rs28969387) is a non-synonymous SNP that produces anaminoacidic change (H457L). Structural changes or loss of function of this protein couldbe related to this or other aminoacidic changes. We have seen that expression ofCYP2E1 is significantly up-regulated in NASH samples, however, it does not seem to bealtered at all in ST patients (see figure 3). Those results agree with previous studies 12in which it is suggested that CYP2E1 could initiate oxidative stress leading to ST to 7, 12NASH by production of reactive oxygen species (ROS) . Blocking CYP2E1 activityprevents necroinflammatory changes in rats 4. One study by Jörn et al. 33 based inoverexpression of CYP2E1 in a hepatocyte cell line, reveals that increased CYP2E1expression results in the down-regulation of insulin signaling, potentially contributingto the insulin resistance associated with NAFLD. Factors related with NAFLD such asethanol exposure, a high-lipid and high-carbohydrate diet, fasting lost weigh anddiabetes, can increase CYP2E1 levels 4. As shown in this study and in previous works 23, SLC2A1 is down-regulated in STand NASH patients (see figure 4). However, SLC2A1 has been found to be up-regulatedin obesity and diabetes patients 34, both diseases associated with NAFLD. The properunderstanding of this result could be very interesting since the oposite regulation ofSLC2A1 in ST/NASH compared to obesity/diabetes could suggest the potentiality of thisgene as a genetic marker to identify NAFLD. 4 When ST progresses to NASH, the insulin resistance occurs and in thisconditions, Cui et al.35 found over-expression of ASNS and, in addition, Sreekumar et 25al. found general up-regulation in genes involved in protein synthesis in NASH 19
  21. 21. patients. Those data agree with our results, in which we found ASNS down-regulated inST while it is up-regulated in NASH (see figure 3). 36, 37 MTR enzyme has been shown down-regulated in alcoholic liver diseasesdue probably to the direct effect of the alcohol in the regulation of this enzyme. In thecontrary, we saw that MTR was more expressed in the studied ST/NASH liver biopsiesthan in the controls (Figure 3). This result could be understood if we consider thatNAFLD patients may drink from 0 to 40 gr of ethanol per week and we do not have thisinformation for the studied samples. 38 Nakau et al. suggest that lack of STK11 activity is a mechanism for HCC 38development. In addition, STK11 plays a key role in the p53-dependent apoptosis , 38over-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, STK11phospholyration 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 bethe cause of an increasing lipid accumulation within hepatocytes in ST and NASHpatients. It will be interesting to get the associated SNPs genotypes for the liver biopsieswhere regulation of the corresponding genes was tested, in order to correlategenotype to phenotype. The obtained results open some new perspectives into the NAFLD research. Itwill be required to describe the implications of the mentioned genes in thepathogenesis of NAFLD, and hopefully, the resulting knowledge will even reveal somenew therapeutic targets. 20
  22. 22. CONCLUSIONS The present project demonstrates for the first time that SLC2A1 is associatedwith 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. Thismeans that SLC2A1 could be a potential specific marker of NAFLD. The regulation of the studied genes is always higher in NASH samples than in STones. This could suggest that metabolism in NASH patients is more unbalanced than inST.OUTLOOK This project will continue first validating significant SNPs in other cohort ofcase/control samples. Afterwards, functional studies of associated genes should becarried out by either silencing down-regulated genes or over-expressing up-regulatedones, 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 modelswill be examined using high-throughput arrays. Special efforts will be carried out to test that the regulation of associated genesseen in liver biopsies is somehow reflected in the blood. This will be crucial to developnon-invasive diagnostic tools.AKNOWLEDGMENTS This work was supported by a grant of Fundacion La caixa (obra social, numberBM06-227-0) 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 thebackground, the hypothesis and the appropriate techniques that made this workpossible. 21
  23. 23. REFERENCES1. 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. 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. 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, Peer 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. 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