IL-10 in Human Newborns : Ontogeny of IL-10 secretion and relation to the secretion of IFN-g, immunoglobulin M, G, and A, and mononuclear cell composition in newborns

The purpose of this work was to elucidate the ontogeny of interleukin-10 (IL-10) secretion from newborn mononuclear cells (MCs), and to examine its relation to the secretion of interferon-g (IFN-g) and immunoglobulins (Igs). The initial hypothesis was that the decreased immunoglobulin (Ig) synthesis of newborn babies was the result of immature cytokine synthesis regulation, which would lead to excessive IL-10 production, leading in turn to suppressed IFN-g secretion. Altogether 57 full-term newborns and 34 adult volunteers were enrolled. Additionally, surface marker compositions of 29 premature babies were included. Enzyme-linked immunoassays were used to determine the amount of secreted IL-10, IFN-g, and Igs, and the surface marker composition of MC were analyzed with a FACScan flow cytometer. The three most important findings were: 1. Cord blood MC, including CD5+ B cells, are able to secrete IL-10. However, when compared with adults, the secretion of IL-10 was decreased. This indicates that reasons other than excessive IL-10 secretion are responsible of reduced IFN-g secretion in newborns. 2. As illustrated by the IL-10 and IFN-g secretion pattern, newborn cytokine profile was skewed towards the Th2 type. However, approximately 25% of newborns had an adult like cytokine profile with both good IL10 and IFN-g secretion, demonstrating that fullterm newborns are not an immunologically homogenous group at the time of birth. 3. There were significant differences in the surface marker composition of MCs between individual neonates. While gestational age correlated with the proportion of some MC types, it is evident that there are many other maternal and fetal factors that influence the maturity and nature of lymphocyte subpopulations in individual neonates. In conclusion, the reduced ability of neonates to secrete Ig and IFN-g is not a consequence of high IL-10 secretion. However, individual newborns differ significantly in their ability to secrete cytokines as well as Igs.

Exposure-related human cancer: Molecular changes in sinonasal cancer and lung cancer, with focus on TP53 mutations

Cancer is a leading cause of death worldwide and the total number of cancer cases continues to increase. Many cancers, for example sinonasal cancer and lung cancer, have clear external risk factors and so are potentially preventable. The occurrence of sinonasal cancer is strongly associated with wood dust exposure and the main risk factor for lung cancer is tobacco smoking. Although the molecular mechanisms involved in lung carcinogenesis have been widely studied, very little is known about the molecular changes leading to sinonasal cancer. In this work, mutations in the tumour suppressor TP53 gene in cases of sinonasal cancer and lung cancer and the associations of these mutations with exposure factors were studied. In addition, another important mechanism in many cancers, inflammation, was explored by analyzing the expression of the inflammation related enzyme, COX-2, in sinonasal cancer. The results demonstrate that TP53 mutations are frequent in sinonasal cancer and lung cancer and in both cancers they are associated with exposure. In sinonasal cancer, the occurrence of TP53 mutation significantly increased in relation to long duration and high level of exposure to wood dust. Smoking was not associated with the overall occurrence of the TP53 mutation in sinonasal cancer, but was associated with multiple TP53 mutations. Furthermore, inflammation appears to play a part in sinonasal carcinogenesis as indicated by our results showing that the expression of COX-2 was associated with adenocarcinoma type of tumours, wood dust exposure and non-smoking. In lung cancer, we detected statistically significant associations between TP53 mutations and duration of smoking, gender and histology. We also found that patients with a tumour carrying a G to T transversion, a mutation commonly found in association with tobacco smoking, had a high level of smoking-related bulky DNA adducts in their non-tumorous lung tissue. Altogether, the information on molecular changes in exposure induced cancers adds to the observations from epidemiological studies and helps to understand the role and impact of different etiological factors, which in turn can be beneficial for risk assessment and prevention.

Common and rare variants of the renin-angiotensin system and their relation to antihypertensive drug responses

Most of the diseases affecting public health, like hypertension, are multifactorial by etiology. Hypertension is influenced by genetic, life style and environmental factors. Estimation of the influence of genes to the risk of essential hypertension varies from 30 to 50%. It is plausible that in most of the cases susceptibility to hypertension is determined by the action of more than one gene. Although the exact molecular mechanism underlying essential hypertension remains obscure, several monogenic forms of hypertension have been identified. Since common genetic variations may predict, not only to susceptibility to hypertension, but also response to antihypertensive drug therapy, pharmacogenetic approaches may provide useful markers in finding relations between candidate genes and phenotypes of hypertension. The aim of this study was to identify genetic mutations and polymorphisms contributing to human hypertension, and examine their relationships to intermediate phenotypes of hypertension, such as blood pressure (BP) responses to antihypertensive drugs or biochemical laboratory values. Two groups of patients were investigated in the present study. The first group was collected from the database of patients investigated in the Hypertension Outpatient Ward, Helsinki University Central Hospital, and consisted of 399 subjects considered to have essential hypertension. Frequncies of the mutant or variant alleles were compared with those in two reference groups, healthy blood donors (n = 301) and normotensive males (n = 175). The second group of subjects with hypertension was collected prospectively. The study subjects (n=313) underwent a protocol lasting eight months, including four one-month drug treatment periods with antihypertensive medications (thiazide diuretic, β-blocker, calcium channel antagonist, and an angiotensin II receptor antagonist). BP responses and laboratory values were related to polymorphims of several candidate genes of the renin-angiotensin system (RAS). In addition, two patients with typical features of Liddle’s syndrome were screened for mutations in kidney epithelial sodium channel (ENaC) subunits. Two novel mutations causing Liddle’s syndrome were identified. The first mutation identified located in the beta-subunit of ENaC and the second mutation found located in the gamma-subunit, constituting the first identified Liddle mutation locating in the extracellular domain. This mutation showed 2-fold increase in channel activity in vitro. Three gene variants, of which two are novel, were identified in ENaC subunits. The prevalence of the variants was three times higher in hypertensive patients (9%) than in reference groups (3%). The variant carriers had increased daily urinary potassium excretion rate in relation to their renin levels compared with controls suggesting increased ENaC activity, although in vitro they did not show increased channel activity. Of the common polymorphisms of the RAS studied, angiotensin II receptor type I (AGTR1) 1166 A/C polymorphism was associated with modest changes in RAS activity. Thus, patients homozygous for the C allele tended to have increased aldosterone and decreased renin levels. In vitro functional studies using transfected HEK293 cells provided additional evidence that the AGTR1 1166 C allele may be associated with increased expression of the AGTR1. Common polymorphisms of the alpha-adducin and the RAS genes did not significantly predict BP responses to one-month monotherapies with hydroclorothiazide, bisoprolol, amlodipin, or losartan. In conclusion, two novel mutations of ENaC subunits causing Liddle’s syndrome were identified. In addition, three common ENaC polymorphisms were shown to be associated with occurrence of essential hypertension, but their exact functional and clinical consequences remain to be explored. The AGTR1 1166 C allele may modify the endocrine phenotype of hypertensive patients, when present in homozygous form. Certain widely studied polymorphisms of the ACE, angiotensinogen, AGTR1 and alpha-adducin genes did not significantly affect responses to a thiazide, β-blocker, calcium channel antagonist, and angiotensin II receptor antagonist.

Studies of the Human Transcriptome

Gene expression is one of the most critical factors influencing the phenotype of a cell. As a result of several technological advances, measuring gene expression levels has become one of the most common molecular biological measurements to study the behaviour of cells. The scientific community has produced enormous and constantly increasing collection of gene expression data from various human cells both from healthy and pathological conditions. However, while each of these studies is informative and enlighting in its own context and research setup, diverging methods and terminologies make it very challenging to integrate existing gene expression data to a more comprehensive view of human transcriptome function. On the other hand, bioinformatic science advances only through data integration and synthesis. The aim of this study was to develop biological and mathematical methods to overcome these challenges and to construct an integrated database of human transcriptome as well as to demonstrate its usage. Methods developed in this study can be divided in two distinct parts. First, the biological and medical annotation of the existing gene expression measurements needed to be encoded by systematic vocabularies. There was no single existing biomedical ontology or vocabulary suitable for this purpose. Thus, new annotation terminology was developed as a part of this work. Second part was to develop mathematical methods correcting the noise and systematic differences/errors in the data caused by various array generations. Additionally, there was a need to develop suitable computational methods for sample collection and archiving, unique sample identification, database structures, data retrieval and visualization. Bioinformatic methods were developed to analyze gene expression levels and putative functional associations of human genes by using the integrated gene expression data. Also a method to interpret individual gene expression profiles across all the healthy and pathological tissues of the reference database was developed. As a result of this work 9783 human gene expression samples measured by Affymetrix microarrays were integrated to form a unique human transcriptome resource GeneSapiens. This makes it possible to analyse expression levels of 17330 genes across 175 types of healthy and pathological human tissues. Application of this resource to interpret individual gene expression measurements allowed identification of tissue of origin with 92.0% accuracy among 44 healthy tissue types. Systematic analysis of transcriptional activity levels of 459 kinase genes was performed across 44 healthy and 55 pathological tissue types and a genome wide analysis of kinase gene co-expression networks was done. This analysis revealed biologically and medically interesting data on putative kinase gene functions in health and disease. Finally, we developed a method for alignment of gene expression profiles (AGEP) to perform analysis for individual patient samples to pinpoint gene- and pathway-specific changes in the test sample in relation to the reference transcriptome database. We also showed how large-scale gene expression data resources can be used to quantitatively characterize changes in the transcriptomic program of differentiating stem cells. Taken together, these studies indicate the power of systematic bioinformatic analyses to infer biological and medical insights from existing published datasets as well as to facilitate the interpretation of new molecular profiling data from individual patients.