Polimorfismos de nucleotídeo único (SNPs) nos genes codificadores da IL-10, TNF-α e em NFkB1 e sua associação com parâmetros clínicos, laboratoriais e de seguimento de pacientes com linfoma de Hodgkin clássico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Global pharmacogenomics: Impact of population diversity on the distribution of polymorphisms in the CYP2C cluster among Brazilians

The impact of biogeographical ancestry, self-reported 'race/color' and geographical origin on the frequency distribution of 10 CYP2C functional polymorphisms (CYP2C8*2, *3, *4, CYP2C9*2, *3, *5, *11, CYP2C19*2, *3 and *17) and their haplotypes was assessed in a representative cohort of the Brazilian population (n = 1034). TaqMan assays were used for allele discrimination at each CYP2C locus investigated. Individual proportions of European, African and Amerindian biogeographical ancestry were estimated using a panel of insertion-deletion polymorphisms. Multinomial log-linear models were applied to infer the statistical association between the CYP2C alleles and haplotypes (response variables), and biogeographical ancestry, self-reported Color and geographical origin (explanatory variables). The results showed that CYP2C19*3, CYP2C9*5 and CYP2C9*11 were rare alleles (<1%), the frequency of other variants ranged from 3.4% (CYP2C8*4) to 17.3% (CYP2C19*17). Two distinct haplotype blocks were identified: block 1 consists of three single nucleotide polymorphisms (SNPs) (CYP2C19*17, CYP2C19*2 and CYP2C9*2) and block 2 of six SNPs (CYP2C9*11, CYP2C9*3, CYP2C9*5, CYP2C8*2, CYP2C8*4 and CYP2C8*3). Diplotype analysis generated 41 haplotypes, of which eight had frequencies greater than 1% and together accounted for 96.4% of the overall genetic diversity. The distribution of CYP2C8 and CYP2C9 (but not CYP2C19) alleles, and of CYP2C haplotypes was significantly associated with self-reported Color and with the individual proportions of European and African genetic ancestry, irrespective of Color self-identification. The individual odds of having alleles CYP2C8*2, CYP2C8*3, CYP2C9*2 and CYP2C9*3, and haplotypes including these alleles, varied continuously as the proportion of European ancestry increased. Collectively, these data strongly suggest that the intrinsic heterogeneity of the Brazilian population must be acknowledged in the design and interpretation of pharmacogenomic studies of the CYP2C cluster in order to avoid spurious conclusions based on improper matching of study cohorts. This conclusion extends to other polymorphic pharmacogenes among Brazilians, and most likely to other admixed populations of the Americas. The Pharmacogenomics Journal (2012) 12, 267-276; doi: 10.1038/tpj.2010.89; published online 21 December 2010

Polymorphisms in antithrombin and in tissue factor pathway inhibitor genes are associated with recurrent pregnancy loss

Recurrent pregnancy loss (RPL) is a multifactorial condition. The effect of antithrombin (SERPINC1), protein C (PROC), thrombomodulin (THBD) and tissue factor pathway inhibitor (TFPI) single nucleotide polymorphisms (SNPs) on the risk of RPL is thus far unknown. Our objective was to determine the association of SNPs in the above mentioned genes with RPL. We included 117 non-pregnant women with three or more consecutive losses prior to 20 weeks of pregnancy without a previous history of carrying a fetus to viability, and 264 healthy fertile non-pregnant women who had at least two term deliveries and no known pregnancy losses. The PROC (rs1799809 and rs1799808), SERPINC1 (rs2227589), THBD (rs1042579) and TFPI (rs10931292, rs8176592 and rs10153820) SNPs were analysed by Real Time PCR. Genotype frequencies for PROC 2418A > G, PROC 2405C > T, THBD 1418C > T, TFPI (T-33C and TFPI C-399T) SNPs were similar in cases and controls. The carriers of SERPINC1 786A allele (GA + AA genotypes) had an increased risk for RPL (odds ratio [OR]: 1.77, 95% confidence interval [CI]: 1.05-3.00, p=0.034) while women carrying the TFPI-287C allele (TC + CC genotypes) had a protection effect on having RPL (OR: 0.46, 95% CI: 0.26 - 0.83, p=0.009). The TCC haplotype for TFPI T-33C/TFPI T-287C/TFPI C-399T SNPs was less frequent in cases (5.7%) than in controls (11.6%) (OR: 0.45, 95% CI: 0.23 - 0.90, p=0.025). In conclusion, our data indicate that SERPINC1 786G > A variant increases the risk for RPL, while TFPI T-287C variant is protective; however, further studies are required to confirm our findings.

Influence of Genomic Ancestry on the Distribution of SLCO1B1, SLCO1B3 and ABCB1 Gene Polymorphisms among Brazilians

The frequency distribution of SNPs and haplotypes in the ABCB1, SLCO1B1 and SLCO1B3 genes varies largely among continental populations. This variation can lead to biases in pharmacogenetic studies conducted in admixed populations such as those from Brazil and other Latin American countries. The aim of this study was to evaluate the influence of self-reported colour, geographical origin and genomic ancestry on distributions of the ABCB1, SLCO1B1 and SLCO1B3 polymorphisms and derived haplotypes in admixed Brazilian populations. A total of 1039 healthy adults from the north, north-east, south-east and south of Brazil were recruited for this investigation. The c.388A>G (rs2306283), c.463C>A (rs11045819) and c.521T>C (rs4149056) SNPs in the SLCO1B1 gene and c.334T>G (rs4149117) and c.699G>A (rs7311358) SNPs in the SLCO1B3 gene were determined by Taqman 5'-nuclease assays. The ABCB1 c.1236C>T (rs1128503), c.2677G>T/A (rs2032582) and c.3435C>T (rs1045642) polymorphisms were genotyped using a previously described single-base extension/termination method. The results showed that genotype and haplotype distributions are highly variable among populations of the same self-reported colour and geographical region. However, genomic ancestry showed that these associations are better explained by a continuous variable. The influence of ancestry on the distribution of alleles and haplotype frequencies was more evident in variants with large differences in allele frequencies between European and African populations. Design and interpretation of pharmacogenetic studies using these transporter genes should include genomic controls to avoid spurious conclusions based on improper matching of study cohorts from Brazilian populations and other highly admixed populations.

Association between diet and polymorphisms in individuals with statin-controlled dyslipidaemia grouped according to oxidative stress biomarkers

The objective of this study was to investigate whether differences in diet and in single-nucleotide polymorphisms (SNPs) found in paraoxonase-1 (PON-1), 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR), cholesterol ester transfer protein (CETP) and apolipoprotein E (APOE) genes, are associated with oxidative stress biomarkers and consequently with susceptibility of low-density cholesterol (LDL) to oxidation. A multivariate approach was applied to a group of 55 patients according to three biomarkers: plasma antioxidant activity, malondialdehyde and oxidized LDL (oxLDL) concentrations. Individuals classified in Cluster III showed the worst prognoses in terms of antioxidant activity and oxidative status. Individuals classified in Cluster I presented the lowest oxidative status, while individuals grouped in Cluster II presented the highest levels of antioxidant activity. No difference in nutrient intake was observed among the clusters. Significantly higher gamma- and delta-tocopherol concentrations were observed in those individuals with the highest levels of antioxidant activity. No single linear regression was statistically significant, suggesting that mutant alleles of the SNPs selected did not contribute to the differences observed in oxidative stress response. Although not statistically significant, the p value of the APO E coefficient for oxLDL response was 0.096, indicating that patients who carry the TT allele of the APO E gene tend to present lower plasma oxLDL concentrations. Therefore, the differences in oxidative stress levels observed in this study could not be attributed to diet or to the variant alleles of PON-1, CETP, HMGCR or APO E. This data supports the influence of gamma-tocopherol and delta-tocopherol on antioxidant activity, and highlights the need for further studies investigating APO E alleles and LDL oxidation.

Correlations of CTLA-4 gene polymorphisms and hepatitis C chronic infection

Background: Cytotoxic T lymphocyte-associated factor 4 (CTLA-4) functions as a negative regulator of T cell-mediated immune response. Molecular changes associated to CTLA-4 gene polymorphisms could reduce its ability to suppress and control lymphocyte proliferation. Aims: To evaluate the frequency of CTLA-4 gene polymorphisms in chronic hepatitis C virus (HCV) infected patients and correlate to clinical and histological findings. Methods: We evaluated 112 HCV-infected subjects prospectively selected and 183 healthy controls. Clinical and liver histological data were analysed. - 318C > T, A49G and CT60 CTLA-4 single-nucleotide polymorphisms (SNPs) were studied by PCR-RFLP and AT(n) polymorphism by DNA fragment analysis by capillary electrophoresis in automatic sequencer. Results: Eight AT repetitions in 3' UTR region were more frequent in HCV-infected subjects. We found a positive association of -318C and + 49G with HCV genotype 3 (P = 0.008, OR 9.13, P = 0.004, OR 2.49 respectively) and an inverse association of both alleles with HCV genotype 1 (P = 0.020, OR 0.19, P = 0.002, OR 0.38 respectively). Allele + 49G was also associated to aminotransferases quotients > 3 (qALT, P = 0.034, qAST, P = 0.041). Allele G of CT60 SNP was also associated with qAST > 3 (P = 0.012). Increased number of AT repetitions was positively associated to severe necroinflammatory activity scores in liver biopsies (P = 0.045, OR 4.62). Conclusion: CTLA-4 gene polymorphisms were associated to HCVinfection. Eight AT repetitions were more prevalent in HCV-infected subjects. - 318C and + 49G alleles were associated to genotypes 1 and 3 infections and increased number of AT repetitions in 3' UTR region favoured severe necroinflammatory activity scores in liver biopsies.

Associations of the TNF-alpha-308 G/A, IL6-174 G/C and AdipoQ 45 T/G polymorphisms with inflammatory and metabolic responses to lifestyle intervention in Brazilians at high cardiometabolic risk

Background: Cytokines secreted by the adipose tissue influence inflammation and insulin sensitivity, and lead to metabolic disturbances. How certain single-nucleotide polymorphisms (SNPs) interfere on lifestyle interventions is unclear. We assessed associations of selected SNPs with changes induced by a lifestyle intervention. Methods: This 9-month intervention on diet and physical activity included 180 Brazilians at high cardiometabolic risk, genotyped for the TNF-alpha -308 G/A, IL-6 -174 G/C and AdipoQ 45 T/G SNPs. Changes in metabolic and inflammatory variables were analyzed according to these SNPs. Individuals with at least one variant allele were grouped and compared with those with the reference genotype. Results: In the entire sample (66.7% women; mean age 56.5 +/- 11.6 years), intervention resulted in lower energy intake, higher physical activity, and improvement in anthropometry, plasma glucose, HOMA-IR, lipid profile and inflammatory markers, except for IL-6 concentrations. After intervention, only variant allele carriers of the TNF-alpha -308 G/A decreased plasma glucose, after adjusting for age and gender (OR 2.96, p = 0.025). Regarding the IL-6 -174 G/C SNP, carriers of the variant allele had a better response of lipid profile and adiponectin concentration, but only the reference genotype group decreased plasma glucose. In contrast to individuals with the reference genotype, carriers of variant allele of AdipoQ 45 T/G SNP did not change plasma glucose, apolipoprotein B, HDL-c and adiponectin concentrations in response to intervention. Conclusion: The TNF alpha -308 G/A SNP may predispose a better response of glucose metabolism to lifestyle intervention. The IL-6 -174 G/C SNP may confer a beneficial effect on lipid but not on glucose metabolism. Our findings reinforce unfavorable effects of the AdipoQ 45 T/G SNP in lipid profile and glucose metabolism after intervention in Brazilians at cardiometabolic risk. Further studies are needed to direct lifestyle intervention to subsets of individuals at cardiometabolic risk.

Toll-like receptor 1 N248S single-nucleotide polymorphism is associated with leprosy risk and regulates immune activation during mycobacterial infection

Conflicting findings about the association between leprosy and TLR1 variants N248S and I602S have been reported. Here, we performed case-control and family based studies, followed by replication in 2 case-control populations from Brazil, involving 3162 individuals. Results indicated an association between TLR1 248S and leprosy in the case-control study (SS genotype odds ratio [OR], 1.81; P = .004) and the family based study (z = 2.02; P = .05). This association was consistently replicated in other populations (combined OR, 1.51; P < .001), corroborating the finding that 248S is a susceptibility factor for leprosy. Additionally, we demonstrated that peripheral blood mononuclear cells (PBMCs) carrying 248S produce a lower tumor necrosis factor/interleukin-10 ratio when stimulated with Mycobacterium leprae but not with lipopolysaccharide or PAM3cysK4. The same effect was observed after infection of PBMCs with the Moreau strain of bacillus Calmette-Guerin but not after infection with other strains. Finally, molecular dynamics simulations indicated that the Toll-like receptor 1 structure containing 248S amino acid is different from the structure containing 248N. Our results suggest that TLR1 248S is associated with an increased risk for leprosy, consistent with its hypoimmune regulatory function.

Associations of the TNF-alpha -308 G/A, IL6 -174 G/C and AdipoQ 45 T/G polymorphisms with inflammatory and metabolic responses to lifestyle intervention in Brazilians at high cardiometabolic risk

Abstract Background Cytokines secreted by the adipose tissue influence inflammation and insulin sensitivity, and lead to metabolic disturbances. How certain single-nucleotide polymorphisms (SNPs) interfere on lifestyle interventions is unclear. We assessed associations of selected SNPs with changes induced by a lifestyle intervention. Methods This 9-month intervention on diet and physical activity included 180 Brazilians at high cardiometabolic risk, genotyped for the TNF-α -308 G/A, IL-6 -174 G/C and AdipoQ 45 T/G SNPs. Changes in metabolic and inflammatory variables were analyzed according to these SNPs. Individuals with at least one variant allele were grouped and compared with those with the reference genotype. Results In the entire sample (66.7% women; mean age 56.5 ± 11.6 years), intervention resulted in lower energy intake, higher physical activity, and improvement in anthropometry, plasma glucose, HOMA-IR, lipid profile and inflammatory markers, except for IL-6 concentrations. After intervention, only variant allele carriers of the TNF-α -308 G/A decreased plasma glucose, after adjusting for age and gender (OR 2.96, p = 0.025). Regarding the IL6 -174 G/C SNP, carriers of the variant allele had a better response of lipid profile and adiponectin concentration, but only the reference genotype group decreased plasma glucose. In contrast to individuals with the reference genotype, carriers of variant allele of AdipoQ 45 T/G SNP did not change plasma glucose, apolipoprotein B, HDL-c and adiponectin concentrations in response to intervention. Conclusion The TNFα -308 G/A SNP may predispose a better response of glucose metabolism to lifestyle intervention. The IL-6 -174 G/C SNP may confer a beneficial effect on lipid but not on glucose metabolism. Our findings reinforce unfavorable effects of the AdipoQ 45 T/G SNP in lipid profile and glucose metabolism after intervention in Brazilians at cardiometabolic risk. Further studies are needed to direct lifestyle intervention to subsets of individuals at cardiometabolic risk.

Investigating the role of single point mutations in the human proteome: a computational study

In the post genomic era with the massive production of biological data the understanding of factors affecting protein stability is one of the most important and challenging tasks for highlighting the role of mutations in relation to human maladies. The problem is at the basis of what is referred to as molecular medicine with the underlying idea that pathologies can be detailed at a molecular level. To this purpose scientific efforts focus on characterising mutations that hamper protein functions and by these affect biological processes at the basis of cell physiology. New techniques have been developed with the aim of detailing single nucleotide polymorphisms (SNPs) at large in all the human chromosomes and by this information in specific databases are exponentially increasing. Eventually mutations that can be found at the DNA level, when occurring in transcribed regions may then lead to mutated proteins and this can be a serious medical problem, largely affecting the phenotype. Bioinformatics tools are urgently needed to cope with the flood of genomic data stored in database and in order to analyse the role of SNPs at the protein level. In principle several experimental and theoretical observations are suggesting that protein stability in the solvent-protein space is responsible of the correct protein functioning. Then mutations that are found disease related during DNA analysis are often assumed to perturb protein stability as well. However so far no extensive analysis at the proteome level has investigated whether this is the case. Also computationally methods have been developed to infer whether a mutation is disease related and independently whether it affects protein stability. Therefore whether the perturbation of protein stability is related to what it is routinely referred to as a disease is still a big question mark. In this work we have tried for the first time to explore the relation among mutations at the protein level and their relevance to diseases with a large-scale computational study of the data from different databases. To this aim in the first part of the thesis for each mutation type we have derived two probabilistic indices (for 141 out of 150 possible SNPs): the perturbing index (Pp), which indicates the probability that a given mutation effects protein stability considering all the “in vitro” thermodynamic data available and the disease index (Pd), which indicates the probability of a mutation to be disease related, given all the mutations that have been clinically associated so far. We find with a robust statistics that the two indexes correlate with the exception of all the mutations that are somatic cancer related. By this each mutation of the 150 can be coded by two values that allow a direct comparison with data base information. Furthermore we also implement computational methods that starting from the protein structure is suited to predict the effect of a mutation on protein stability and find that overpasses a set of other predictors performing the same task. The predictor is based on support vector machines and takes as input protein tertiary structures. We show that the predicted data well correlate with the data from the databases. All our efforts therefore add to the SNP annotation process and more importantly found the relationship among protein stability perturbation and the human variome leading to the diseasome.

Bioinformatic methods in applied genomic research

Here I will focus on three main topics that best address and include the projects I have been working in during my three year PhD period that I have spent in different research laboratories addressing both computationally and practically important problems all related to modern molecular genomics. The first topic is the use of livestock species (pigs) as a model of obesity, a complex human dysfunction. My efforts here concern the detection and annotation of Single Nucleotide Polymorphisms. I developed a pipeline for mining human and porcine sequences. Starting from a set of human genes related with obesity the platform returns a list of annotated porcine SNPs extracted from a new set of potential obesity-genes. 565 of these SNPs were analyzed on an Illumina chip to test the involvement in obesity on a population composed by more than 500 pigs. Results will be discussed. All the computational analysis and experiments were done in collaboration with the Biocomputing group and Dr.Luca Fontanesi, respectively, under the direction of prof. Rita Casadio at the Bologna University, Italy. The second topic concerns developing a methodology, based on Factor Analysis, to simultaneously mine information from different levels of biological organization. With specific test cases we develop models of the complexity of the mRNA-miRNA molecular interaction in brain tumors measured indirectly by microarray and quantitative PCR. This work was done under the supervision of Prof. Christine Nardini, at the “CAS-MPG Partner Institute for Computational Biology” of Shangai, China (co-founded by the Max Planck Society and the Chinese Academy of Sciences jointly) The third topic concerns the development of a new method to overcome the variety of PCR technologies routinely adopted to characterize unknown flanking DNA regions of a viral integration locus of the human genome after clinical gene therapy. This new method is entirely based on next generation sequencing and it reduces the time required to detect insertion sites, decreasing the complexity of the procedure. This work was done in collaboration with the group of Dr. Manfred Schmidt at the Nationales Centrum für Tumorerkrankungen (Heidelberg, Germany) supervised by Dr. Annette Deichmann and Dr. Ali Nowrouzi. Furthermore I add as an Appendix the description of a R package for gene network reconstruction that I helped to develop for scientific usage (http://www.bioconductor.org/help/bioc-views/release/bioc/html/BUS.html).

CYP17A1 polymorphisms and clinical outcome of patients with metastatic castration-resistant prostate cancer treated with abiraterone

Background. Abiraterone acetate is a potent inhibitor of cytochrome P450 17 α-hydrolase (CYP17A1) that causes a reduction in the synthesis of testosterone in the adrenal glands, testes and tumor microenvironment. Blocking androgen production, abiraterone has been shown to prolong progression-free survival (PFS) and overall survival (OS) in patients with metastatic castration-resistant prostate cancer (CRPC) previously submitted to chemotherapy. The aim of our study was to verify the role of single nucleotide polymorphisms (SNPs) in predicting clinical outcome in CRPC patients treated with abiraterone after chemotherapy. Methods. We analyzed 48 CRPC consecutive patients treated with abiraterone after at least one chemotherapeutic regimen with docetaxel. DNA was extracted from peripheral blood and genotyped for four polymorphisms in the CYP17A1 gene (rs743572, rs10883783, rs17115100, rs284849). PFS and OS survival curves were used to identify statistical associations between haplotypes and clinical outcome. Results. Forty-eight Caucasian patients with metastatic CRPC treated with abiraterone were genotyped for polymorphisms in the CYP17A1 gene. All samples were evaluable for both sequencing and TaqMan Genotyping assay. The CRPC patients treated with abiraterone had a median PFS and OS of 7.6 months (95% CI: 4.3-10.5) and 17.6 months (95% CI: 10.5-19.0), respectively Statistical analyses highlighted a difference approaching statistical significance (log-rank test p = 0.0534) between rs10883783 and PFS. Other polymorphisms were not associated with a benefit from treatment with abiraterone. Conclusions. In our case series of 48 treated patients, rs10883783 only was identified as a possible predictive marker, results showing a trend toward statistical significance. Further analysis of this polymorphism is needed in larger series of patients to confirm our findings.

Evaluation von Nukleotidpolymorphismen für die Analyse des hämatopoetischen Spenderchimärismus auf Ebene der cDNA

Nach einer hämatopoetischen Stammzelltransplantation spielt die Zuordnung hämatopoetischer Zellen zum Spender oder Empfänger für viele transplantationsbezogene Fragestellungen eine wichtige Rolle. Unter anderem ist das Persistieren von dendritischen Zellen des Empfängers, welche allogene T-Zellen des Spenders stimulieren, ein wichtiger Schritt bei der Entstehung der akuten GVHD. Aus diesem Grund wurde in dieser Arbeit die Weiterentwicklung einer Methode angestrebt, die es uns erlaubt, die Zugehörigkeit isolierter hämatopoetischer Zellen dem Spender oder dem Empfänger zuzuordnen (Chimärismusbestimmung) und gleichzeitig Aussagen über das Ursprungsgewebe und den Aktivierungszustand der Zellen machen zu können. Hierfür nutzten wir Einzelbasenpolymorphismen (SNPs). Ziel dieser Arbeit war es, einen Pool von cDNA-kodierten SNPs zu definieren, mit dem auch HLA-identische Geschwister eindeutig unteschieden werden können. rnHierfür wurden zunächst aus publizierten Datenbanken solche SNPs ausgewählt, die in kodierenden Genabschnitten konstitutiv und gewebeunabhängig auf expremierten Genen lagen und zugleich eine hohe Heterozygotenfrequenz in der europäischen Population aufwiesen. Anhand dieser Kriterien wurden mittels der NCBI-Datenbank insgesamt eine Anzahl von 208 Polymorphismen auf 150 Genen identifiziert. Anschließend erfolgte die Gestaltung von Primerpaaren zur Amplifikation der SNP-kodierenden cDNA-Abschnitte. Diese mussten mindestens eine Intron/Exon-Grenze überspannen, um genomische DNA in der PCR ausschließen zu können. Mit Hilfe der etablierten PCR-Reaktion wurden die Gene in unterschiedlichen Geweben auf ihre Expression hin überprüft. Für 45 Gene ließ sich sowohl eine entsprechende PCR etablieren als auch deren konstitutive Expression in verschiedenen hämatopoetischen Zellen nachweisen. Zur Detektion der einzelnen SNPs in der Minisequenzierung wurden Minisequenzierungs-Sonden generiert und geprüft. Im Folgenden wurden für PCR und Minisequezierung Multiplex-Reaktionen aus vier bis sechs Reaktionen zusammengestellt. Zu diesem Zweck wurden die jeweiligen Primerinteraktionen und die unterschiedlichen Basenlängen des PCR-Produktes berücksichtigt.rnVon den 45 etablierten Einzelreaktionen waren 30 für den Multiplexansatz geeignet. Unter Anwendung dieser Multiplex-Reaktionen wurden 24 HLA-identische Geschwisterpaare (Spender und Empfänger) getestet. Zur Kontrolle erfolgte zusätzlich eine konventionelle Sequenzierung der SNP-kodierenden Bereiche auf der cDNA der jeweiligen Proben. Mit Hilfe der SNP-Kombinationen und der etablierten Methodik waren wir in der Lage alle 24 untersuchten Geschwisterpaare in zwischen sechs und 18 SNP-Systemen zu unterscheiden. rnDie Möglichkeiten, die die Analysen des Chimärismus mittels SNPs auf kodierenden Bereichen der DNA mit sich bringen, liegen nicht nur in der gleichzeitigen Bestimmung der Gewebszugehörigkeit und der Detektion des bestehenden Chimärismus sowie dessen Quantifizierung unter Anwendung einer Real-time-PCR. Vielmehr ermöglicht sie auch eine Aussage über die Genexpression der untersuchten Zelle zu machen. Dies ist insbesondere dann von Interesse, wenn geringe Zellzahlen von aus Gewebe isolierten Zellen zur Verfügung stehen. Die in dieser Arbeit etablierten Ansätze werden derzeit für eine Quantifizierung mittels real-time RCR weiterentwickelt und sollen mittelfristig insbesondere für Untersuchungen des Chimärismus von dermalen und epidermalen dendritischen Zellen der Haut und anderer Zielgewebe der GvHD verwendet werden.rn

Identification of SNPs in the cystic fibrosis interactome influencing pulmonary progression in cystic fibrosis

There is growing evidence that the great phenotypic variability in patients with cystic fibrosis (CF) not only depends on the genotype, but apart from a combination of environmental and stochastic factors predominantly also on modifier gene effects. It has been proposed that genes interacting with CF transmembrane conductance regulator (CFTR) and epithelial sodium channel (ENaC) are potential modifiers. Therefore, we assessed the impact of single-nucleotide polymorphisms (SNPs) of several of these interacters on CF disease outcome. SNPs that potentially alter gene function were genotyped in 95 well-characterized p.Phe508del homozygous CF patients. Linear mixed-effect model analysis was used to assess the relationship between sequence variants and the repeated measurements of lung function parameters. In total, we genotyped 72 SNPs in 10 genes. Twenty-five SNPs were used for statistical analysis, where we found strong associations for one SNP in PPP2R4 with the lung clearance index (P ≤ 0.01), the specific effective airway resistance (P ≤ 0.005) and the forced expiratory volume in 1 s (P ≤ 0.005). In addition, we identified one SNP in SNAP23 to be significantly associated with three lung function parameters as well as one SNP in PPP2R1A and three in KRT19 to show a significant influence on one lung function parameter each. Our findings indicate that direct interacters with CFTR, such as SNAP23, PPP2R4 and PPP2R1A, may modify the residual function of p.Phe508del-CFTR while variants in KRT19 may modulate the amount of p.Phe508del-CFTR at the apical membrane and consequently modify CF disease.

QUANTIFYING UNCERTAINTY IN GENOTYPE CALLS

Genome-wide association studies (GWAS) are used to discover genes underlying complex, heritable disorders for which less powerful study designs have failed in the past. The number of GWAS has skyrocketed recently with findings reported in top journals and the mainstream media. Mircorarrays are the genotype calling technology of choice in GWAS as they permit exploration of more than a million single nucleotide polymorphisms (SNPs)simultaneously. The starting point for the statistical analyses used by GWAS, to determine association between loci and disease, are genotype calls (AA, AB, or BB). However, the raw data, microarray probe intensities, are heavily processed before arriving at these calls. Various sophisticated statistical procedures have been proposed for transforming raw data into genotype calls. We find that variability in microarray output quality across different SNPs, different arrays, and different sample batches has substantial inuence on the accuracy of genotype calls made by existing algorithms. Failure to account for these sources of variability, GWAS run the risk of adversely affecting the quality of reported findings. In this paper we present solutions based on a multi-level mixed model. Software implementation of the method described in this paper is available as free and open source code in the crlmm R/BioConductor.