Genomic microarrays in chromosomal analysis of leukemia

Chromosomal alterations in leukemia have been shown to have prognostic and predictive significance and are also important minimal residual disease (MRD) markers in the follow-up of leukemia patients. Although specific oncogenes and tumor suppressors have been discovered in some of the chromosomal alterations, the role and target genes of many alterations in leukemia remain unknown. In addition, a number of leukemia patients have a normal karyotype by standard cytogenetics, but have variability in clinical course and are often molecularly heterogeneous. Cytogenetic methods traditionally used in leukemia analysis and diagnostics; G-banding, various fluorescence in situ hybridization (FISH) techniques, and chromosomal comparative genomic hybridization (cCGH), have enormously increased knowledge about the leukemia genome, but have limitations in resolution or in genomic coverage. In the last decade, the development of microarray comparative genomic hybridization (array-CGH, aCGH) for DNA copy number analysis and the SNP microarray (SNP-array) method for simultaneous copy number and loss of heterozygosity (LOH) analysis has enabled investigation of chromosomal and gene alterations genome-wide with high resolution and high throughput. In these studies, genetic alterations were analyzed in acute myeloid leukemia (AML) and chronic lymphocytic leukemia (CLL). The aim was to screen and characterize genomic alterations that could play role in leukemia pathogenesis by using aCGH and SNP-arrays. One of the most important goals was to screen cryptic alterations in karyotypically normal leukemia patients. In addition, chromosomal changes were evaluated to narrow the target regions, to find new markers, and to obtain tumor suppressor and oncogene candidates. The work presented here shows the capability of aCGH to detect submicroscopic copy number alterations in leukemia, with information about breakpoints and genes involved in the alterations, and that genome-wide microarray analyses with aCGH and SNP-array are advantageous methods in the research and diagnosis of leukemia. The most important findings were the cryptic changes detected with aCGH in karyotypically normal AML and CLL, characterization of amplified genes in 11q marker chromosomes, detection of deletion-based mechanisms of MLL-ARHGEF12 fusion gene formation, and detection of LOH without copy number alteration in karyotypically normal AML. These alterations harbor candidate oncogenes and tumor suppressors for further studies.

Computational Methods for Detecting Large-Scale Chromosome Rearrangements in SNP Data

Large-scale chromosome rearrangements such as copy number variants (CNVs) and inversions encompass a considerable proportion of the genetic variation between human individuals. In a number of cases, they have been closely linked with various inheritable diseases. Single-nucleotide polymorphisms (SNPs) are another large part of the genetic variance between individuals. They are also typically abundant and their measuring is straightforward and cheap. This thesis presents computational means of using SNPs to detect the presence of inversions and deletions, a particular variety of CNVs. Technically, the inversion-detection algorithm detects the suppressed recombination rate between inverted and non-inverted haplotype populations whereas the deletion-detection algorithm uses the EM-algorithm to estimate the haplotype frequencies of a window with and without a deletion haplotype. As a contribution to population biology, a coalescent simulator for simulating inversion polymorphisms has been developed. Coalescent simulation is a backward-in-time method of modelling population ancestry. Technically, the simulator also models multiple crossovers by using the Counting model as the chiasma interference model. Finally, this thesis includes an experimental section. The aforementioned methods were tested on synthetic data to evaluate their power and specificity. They were also applied to the HapMap Phase II and Phase III data sets, yielding a number of candidates for previously unknown inversions, deletions and also correctly detecting known such rearrangements.

Computational Identification of Recessive Mutations in Cancers using High Throughput SNP-arrays

This thesis presents a highly sensitive genome wide search method for recessive mutations. The method is suitable for distantly related samples that are divided into phenotype positives and negatives. High throughput genotype arrays are used to identify and compare homozygous regions between the cohorts. The method is demonstrated by comparing colorectal cancer patients against unaffected references. The objective is to find homozygous regions and alleles that are more common in cancer patients. We have designed and implemented software tools to automate the data analysis from genotypes to lists of candidate genes and to their properties. The programs have been designed in respect to a pipeline architecture that allows their integration to other programs such as biological databases and copy number analysis tools. The integration of the tools is crucial as the genome wide analysis of the cohort differences produces many candidate regions not related to the studied phenotype. CohortComparator is a genotype comparison tool that detects homozygous regions and compares their loci and allele constitutions between two sets of samples. The data is visualised in chromosome specific graphs illustrating the homozygous regions and alleles of each sample. The genomic regions that may harbour recessive mutations are emphasised with different colours and a scoring scheme is given for these regions. The detection of homozygous regions, cohort comparisons and result annotations are all subjected to presumptions many of which have been parameterized in our programs. The effect of these parameters and the suitable scope of the methods have been evaluated. Samples with different resolutions can be balanced with the genotype estimates of their haplotypes and they can be used within the same study.

The Gerbera cDNA Microarray: A Tool for Large-Scale Identification of Genes Involved in Flower Development

During the past ten years, large-scale transcript analysis using microarrays has become a powerful tool to identify and predict functions for new genes. It allows simultaneous monitoring of the expression of thousands of genes and has become a routinely used tool in laboratories worldwide. Microarray analysis will, together with other functional genomics tools, take us closer to understanding the functions of all genes in genomes of living organisms. Flower development is a genetically regulated process which has mostly been studied in the traditional model species Arabidopsis thaliana, Antirrhinum majus and Petunia hybrida. The molecular mechanisms behind flower development in them are partly applicable in other plant systems. However, not all biological phenomena can be approached with just a few model systems. In order to understand and apply the knowledge to ecologically and economically important plants, other species also need to be studied. Sequencing of 17 000 ESTs from nine different cDNA libraries of the ornamental plant Gerbera hybrida made it possible to construct a cDNA microarray with 9000 probes. The probes of the microarray represent all different ESTs in the database. From the gerbera ESTs 20% were unique to gerbera while 373 were specific to the Asteraceae family of flowering plants. Gerbera has composite inflorescences with three different types of flowers that vary from each other morphologically. The marginal ray flowers are large, often pigmented and female, while the central disc flowers are smaller and more radially symmetrical perfect flowers. Intermediate trans flowers are similar to ray flowers but smaller in size. This feature together with the molecular tools applied to gerbera, make gerbera a unique system in comparison to the common model plants with only a single kind of flowers in their inflorescence. In the first part of this thesis, conditions for gerbera microarray analysis were optimised including experimental design, sample preparation and hybridization, as well as data analysis and verification. Moreover, in the first study, the flower and flower organ-specific genes were identified. After the reliability and reproducibility of the method were confirmed, the microarrays were utilized to investigate transcriptional differences between ray and disc flowers. This study revealed novel information about the morphological development as well as the transcriptional regulation of early stages of development in various flower types of gerbera. The most interesting finding was differential expression of MADS-box genes, suggesting the existence of flower type-specific regulatory complexes in the specification of different types of flowers. The gerbera microarray was further used to profile changes in expression during petal development. Gerbera ray flower petals are large, which makes them an ideal model to study organogenesis. Six different stages were compared and specifically analysed. Expression profiles of genes related to cell structure and growth implied that during stage two, cells divide, a process which is marked by expression of histones, cyclins and tubulins. Stage 4 was found to be a transition stage between cell division and expansion and by stage 6 cells had stopped division and instead underwent expansion. Interestingly, at the last analysed stage, stage 9, when cells did not grow any more, the highest number of upregulated genes was detected. The gerbera microarray is a fully-functioning tool for large-scale studies of flower development and correlation with real-time RT-PCR results show that it is also highly sensitive and reliable. Gene expression data presented here will be a source for gene expression mining or marker gene discovery in the future studies that will be performed in the Gerbera Laboratory. The publicly available data will also serve the plant research community world-wide.

Characterization of genomic diversity in extraintestinal pathogenic Escherichia coli (ExPEC) and development of a diagnostic DNA microarray for the differentiation of ExPEC isolates causing urinary tract infections

Extraintestinal pathogenic Escherichia coli (ExPEC) represent a diverse group of strains of E. coli, which infect extraintestinal sites, such as the urinary tract, the bloodstream, the meninges, the peritoneal cavity, and the lungs. Urinary tract infections (UTIs) caused by uropathogenic E. coli (UPEC), the major subgroup of ExPEC, are among the most prevalent microbial diseases world wide and a substantial burden for public health care systems. UTIs are responsible for serious morbidity and mortality in the elderly, in young children, and in immune-compromised and hospitalized patients. ExPEC strains are different, both from genetic and clinical perspectives, from commensal E. coli strains belonging to the normal intestinal flora and from intestinal pathogenic E. coli strains causing diarrhea. ExPEC strains are characterized by a broad range of alternate virulence factors, such as adhesins, toxins, and iron accumulation systems. Unlike diarrheagenic E. coli, whose distinctive virulence determinants evoke characteristic diarrheagenic symptoms and signs, ExPEC strains are exceedingly heterogeneous and are known to possess no specific virulence factors or a set of factors, which are obligatory for the infection of a certain extraintestinal site (e. g. the urinary tract). The ExPEC genomes are highly diverse mosaic structures in permanent flux. These strains have obtained a significant amount of DNA (predictably up to 25% of the genomes) through acquisition of foreign DNA from diverse related or non-related donor species by lateral transfer of mobile genetic elements, including pathogenicity islands (PAIs), plasmids, phages, transposons, and insertion elements. The ability of ExPEC strains to cause disease is mainly derived from this horizontally acquired gene pool; the extragenous DNA facilitates rapid adaptation of the pathogen to changing conditions and hence the extent of the spectrum of sites that can be infected. However, neither the amount of unique DNA in different ExPEC strains (or UPEC strains) nor the mechanisms lying behind the observed genomic mobility are known. Due to this extreme heterogeneity of the UPEC and ExPEC populations in general, the routine surveillance of ExPEC is exceedingly difficult. In this project, we presented a novel virulence gene algorithm (VGA) for the estimation of the extraintestinal virulence potential (VP, pathogenicity risk) of clinically relevant ExPECs and fecal E. coli isolates. The VGA was based on a DNA microarray specific for the ExPEC phenotype (ExPEC pathoarray). This array contained 77 DNA probes homologous with known (e.g. adhesion factors, iron accumulation systems, and toxins) and putative (e.g. genes predictably involved in adhesion, iron uptake, or in metabolic functions) ExPEC virulence determinants. In total, 25 of DNA probes homologous with known virulence factors and 36 of DNA probes representing putative extraintestinal virulence determinants were found at significantly higher frequency in virulent ExPEC isolates than in commensal E. coli strains. We showed that the ExPEC pathoarray and the VGA could be readily used for the differentiation of highly virulent ExPECs both from less virulent ExPEC clones and from commensal E. coli strains as well. Implementing the VGA in a group of unknown ExPECs (n=53) and fecal E. coli isolates (n=37), 83% of strains were correctly identified as extraintestinal virulent or commensal E. coli. Conversely, 15% of clinical ExPECs and 19% of fecal E. coli strains failed to raster into their respective pathogenic and non-pathogenic groups. Clinical data and virulence gene profiles of these strains warranted the estimated VPs; UPEC strains with atypically low risk-ratios were largely isolated from patients with certain medical history, including diabetes mellitus or catheterization, or from elderly patients. In addition, fecal E. coli strains with VPs characteristic for ExPEC were shown to represent the diagnostically important fraction of resident strains of the gut flora with a high potential of causing extraintestinal infections. Interestingly, a large fraction of DNA probes associated with the ExPEC phenotype corresponded to novel DNA sequences without any known function in UTIs and thus represented new genetic markers for the extraintestinal virulence. These DNA probes included unknown DNA sequences originating from the genomic subtractions of four clinical ExPEC isolates as well as from five novel cosmid sequences identified in the UPEC strains HE300 and JS299. The characterized cosmid sequences (pJS332, pJS448, pJS666, pJS700, and pJS706) revealed complex modular DNA structures with known and unknown DNA fragments arranged in a puzzle-like manner and integrated into the common E. coli genomic backbone. Furthermore, cosmid pJS332 of the UPEC strain HE300, which carried a chromosomal virulence gene cluster (iroBCDEN) encoding the salmochelin siderophore system, was shown to be part of a transmissible plasmid of Salmonella enterica. Taken together, the results of this project pointed towards the assumptions that first, (i) homologous recombination, even within coding genes, contributes to the observed mosaicism of ExPEC genomes and secondly, (ii) besides en block transfer of large DNA regions (e.g. chromosomal PAIs) also rearrangements of small DNA modules provide a means of genomic plasticity. The data presented in this project supplemented previous whole genome sequencing projects of E. coli and indicated that each E. coli genome displays a unique assemblage of individual mosaic structures, which enable these strains to successfully colonize and infect different anatomical sites.

Cow's milk allergy and the development of tolerance

Aims: To gain insight on the immunological processes behind cow’s milk allergy (CMA) and the development of oral tolerance. To furthermore investigate the associations of HLA II and filaggrin genotypes with humoral responses to early oral antigens. Methods: The study population was from a cohort of 6209 healthy, full-term infants who in a double-blind randomized trial received supplementary feeding at maternity hospitals (mean duration 4 days): cow’s milk (CM) formula, extensively hydrolyzed whey formula or donor breast milk. Infants who developed CM associated symptoms that subsided during elimination diet (n=223) underwent an open oral CM challenge (at mean age 7 months). The challenge was negative in 112, and in 111 it confirmed CMA, which was IgE-mediated in 83. Patients with CMA were followed until recovery, and 94 of them participated in a follow-up study at age 8-9 years. We investigated serum samples at diagnosis (mean age 7 months, n=111), one year later (19 months, n=101) and at follow-up (8.6 years, n=85). At follow-up, also 76 children randomly selected from the original cohort and without CM associated symptoms were included. We measured CM specific IgE levels with UniCAP (Phadia, Uppsala, Sweden), and β-lactoglobulin, α-casein and ovalbumin specific IgA, IgG1, IgG4 and IgG levels with enzyme-linked immunosorbent assay in sera. We applied a microarray based immunoassay to measure the binding of IgE, IgG4 and IgA serum antibodies to sequential epitopes derived from five major CM proteins at the three time points in 11 patients with active IgE-mediated CMA at age 8-9 years and in 12 patients who had recovered from IgE-mediated CMA by age 3 years. We used bioinformatic methods to analyze the microarray data. We studied T cell expression profile in peripheral blood mononuclear cell (PBMC) samples from 57 children aged 5-12 years (median 8.3): 16 with active CMA, 20 who had recovered from CMA by age 3 years, 21 non-atopic control subjects. Following in vitro β-lactoglobulin stimulation, we measured the mRNA expression in PBMCs of 12 T-cell markers (T-bet, GATA-3, IFN-γ, CTLA4, IL-10, IL-16, TGF-β, FOXP3, Nfat-C2, TIM3, TIM4, STIM-1) with quantitative real time polymerase chain reaction, and the protein expression of CD4, CD25, CD127, FoxP3 with flow cytometry. To optimally distinguish the three study groups, we performed artificial neural networks with exhaustive search for all marker combinations. For genetic associations with specific humoral responses, we analyzed 14 HLA class II haplotypes, the PTPN22 1858 SNP (R620W allele) and 5 known filaggrin null mutations from blood samples of 87 patients with CMA and 76 control subjects (age 8.0-9.3 years). Results: High IgG and IgG4 levels to β-lactoglobulin and α-casein were associated with the HLA (DR15)-DQB1*0602 haplotype in patients with CMA, but not in control subjects. Conversely, (DR1/10)-DQB1*0501 was associated with lower IgG and IgG4 levels to these CM antigens, and to ovalbumin, most significantly among control subjects. Infants with IgE-mediated CMA had lower β -lactoglobulin and α-casein specific IgG1, IgG4 and IgG levels (p<0.05) at diagnosis than infants with non-IgE-mediated CMA or control subjects. When CMA persisted beyond age 8 years, CM specific IgE levels were higher at all three time points investigated and IgE epitope binding pattern remained stable (p<0.001) compared with recovery from CMA by age 3 years. Patients with persisting CMA at 8-9 years had lower serum IgA levels to β-lactoglobulin at diagnosis (p=0.01), and lower IgG4 levels to β-lactoglobulin (p=0.04) and α-casein (p=0.05) at follow-up compared with patients who recovered by age 3 years. In early recovery, signal of IgG4 epitope binding increased while that of IgE decreased over time, and binding patterns of IgE and IgG4 overlapped. In T cell expression profile in response to β –lactoglobulin, the combination of markers FoxP3, Nfat-C2, IL-16, GATA-3 distinguished patients with persisting CMA most accurately from patients who had become tolerant and from non-atopic subjects. FoxP3 expression at both RNA and protein level was higher in children with CMA compared with non-atopic children. Conclusions: Genetic factors (the HLA II genotype) are associated with humoral responses to early food allergens. High CM specific IgE levels predict persistence of CMA. Development of tolerance is associated with higher specific IgA and IgG4 levels and lower specific IgE levels, with decreased CM epitope binding by IgE and concurrent increase in corresponding epitope binding by IgG4. Both Th2 and Treg pathways are activated upon CM antigen stimulation in patients with CMA. In the clinical management of CMA, HLA II or filaggrin genotyping are not applicable, whereas the measurement of CM specific antibodies may assist in estimating the prognosis.

Data integration from two microarray platforms identifies bi-allelic genetic inactivation of RIC8A in a breast cancer cell line

Background: Using array comparative genomic hybridization (aCGH), a large number of deleted genomic regions have been identified in human cancers. However, subsequent efforts to identify target genes selected for inactivation in these regions have often been challenging. Methods: We integrated here genome-wide copy number data with gene expression data and non-sense mediated mRNA decay rates in breast cancer cell lines to prioritize gene candidates that are likely to be tumour suppressor genes inactivated by bi-allelic genetic events. The candidates were sequenced to identify potential mutations. Results: This integrated genomic approach led to the identification of RIC8A at 11p15 as a putative candidate target gene for the genomic deletion in the ZR-75-1 breast cancer cell line. We identified a truncating mutation in this cell line, leading to loss of expression and rapid decay of the transcript. We screened 127 breast cancers for RIC8A mutations, but did not find any pathogenic mutations. No promoter hypermethylation in these tumours was detected either. However, analysis of gene expression data from breast tumours identified a small group of aggressive tumours that displayed low levels of RIC8A transcripts. qRT-PCR analysis of 38 breast tumours showed a strong association between low RIC8A expression and the presence of TP53 mutations (P = 0.006). Conclusion: We demonstrate a data integration strategy leading to the identification of RIC8A as a gene undergoing a classical double-hit genetic inactivation in a breast cancer cell line, as well as in vivo evidence of loss of RIC8A expression in a subgroup of aggressive TP53 mutant breast cancers.

Studies on Causes of Multiple Sclerosis : From Genes to Transcriptome

Multiple sclerosis (MS) is the most common cause of neurological disability in young adults, affecting more than two million people worldwide. It manifests as a chronic inflammation in the central nervous system (CNS) and causes demyelination and neurodegeneration. Depending on the location of the demyelinated plaques and axonal loss, a variety of symptoms can be observed including deficits in vision, coordination, balance and movement. With a typical age of onset at 20-40 years, the social and economic impacts of MS on lives of the patients and their families are considerable. Unfortunately the current treatments are relatively inefficient and the development of more effective treatments has been impeded by our limited understanding of the causes and pathogenesis of MS. Risk of MS is higher in biological relatives of MS patients than in the general population. Twin and adoption studies have shown that familial clustering of MS is explained by shared genetic factors rather than by shared familial environment. While the involvement of the human leukocyte antigen (HLA) genes was first discovered four decades ago, additional genetic risk factors have only recently been identified through genome-wide association studies (GWAS). Current evidence suggests that MS is a highly polygenic disease with perhaps hundreds of common variants with relatively modest effects contributing to susceptibility. Despite extensive research, the majority of these risk factors still remain to be identified. In this thesis the aim was to identify novel genes and pathways involved in MS. Using genome-wide microarray technology, gene expression levels in peripheral blood mononuclear cells (PBMC) from 12 MS patients and 15 controls were profiled and more than 600 genes with altered expression in MS were identified. Three of five selected findings, DEFA1A3, LILRA4 and TNFRSF25, were successfully replicated in an independent sample. Increased expression of DEFA1A3 in MS is a particularly interesting observation, because its elevated levels have previously been reported also in several other autoimmune diseases. A systematic review of seven microarray studies was then performed leading to identification of 229 genes, in which either decreased or increased expression in MS had been reported in at least two studies. In general there was relatively little overlap across the experiments: 11 of the 229 genes had been reported in three studies and only HSPA1A in four studies. Nevertheless, these 229 genes were associated with several immunological pathways including interleukin pathways related to type 2 and type 17 helper T cells and regulatory T cells. However, whether these pathways are involved in causing MS or related to secondary processes activated after disease onset remains to be investigated. The 229 genes were also compared with loci identified in published MS GWASs. Single nucleotide polymorphisms (SNP) in 17 of the 229 loci had been reported to be associated with MS with P-value less than 0.0001 including variants in CXCR4 and SAPS2, which were the only loci where evidence for correlation between the associated variant and gene expression was found. The CXCR4 variant was further tested for association with MS in a large case-control sample and the previously reported suggestive association was replicated (P-value is 0.0004). Finally, common genetic variants in candidate genes, which had been selected on the basis of showing association with other autoimmune diseases (MYO9B) or showing differential expression in MS in our study (DEFA1A3, LILRA4 and TNFRSF25), were tested for association with MS, but no evidence of association was found. In conclusion, through a systematic review of genome-wide expression studies in MS we have identified several promising candidate genes and pathways for future studies. In addition, we have replicated a previously suggested association of a SNP variant upstream of CXCR4 with MS. Keywords: autoimmune disease, common variant, CXCR4, DEFA1A3, HSPA1A,gene expression, genetic association, GWAS, MS, multiple sclerosis, systematic review

Microbial identification by detection of ligation probes on DNA microarray

Microbes in natural and artificial environments as well as in the human body are a key part of the functional properties of these complex systems. The presence or absence of certain microbial taxa is a correlate of functional status like risk of disease or course of metabolic processes of a microbial community. As microbes are highly diverse and mostly notcultivable, molecular markers like gene sequences are a potential basis for detection and identification of key types. The goal of this thesis was to study molecular methods for identification of microbial DNA in order to develop a tool for analysis of environmental and clinical DNA samples. Particular emphasis was placed on specificity of detection which is a major challenge when analyzing complex microbial communities. The approach taken in this study was the application and optimization of enzymatic ligation of DNA probes coupled with microarray read-out for high-throughput microbial profiling. The results show that fungal phylotypes and human papillomavirus genotypes could be accurately identified from pools of PCR amplicons generated from purified sample DNA. Approximately 1 ng/μl of sample DNA was needed for representative PCR amplification as measured by comparisons between clone sequencing and microarray. A minimum of 0,25 amol/μl of PCR amplicons was detectable from amongst 5 ng/μl of background DNA, suggesting that the detection limit of the test comprising of ligation reaction followed by microarray read-out was approximately 0,04%. Detection from sample DNA directly was shown to be feasible with probes forming a circular molecule upon ligation followed by PCR amplification of the probe. In this approach, the minimum detectable relative amount of target genome was found to be 1% of all genomes in the sample as estimated from 454 deep sequencing results. Signal-to-noise of contact printed microarrays could be improved by using an internal microarray hybridization control oligonucleotide probe together with a computational algorithm. The algorithm was based on identification of a bias in the microarray data and correction of the bias as shown by simulated and real data. The results further suggest semiquantitative detection to be possible by ligation detection, allowing estimation of target abundance in a sample. However, in practise, comprehensive sequence information of full length rRNA genes is needed to support probe design with complex samples. This study shows that DNA microarray has the potential for an accurate microbial diagnostic platform to take advantage of increasing sequence data and to replace traditional, less efficient methods that still dominate routine testing in laboratories. The data suggests that ligation reaction based microarray assay can be optimized to a degree that allows good signal-tonoise and semiquantitative detection.

Molecular diagnosis of developmental disorders

ABSTRACT Idiopathic developmental disorders (DDs) affect ~1% of the population worldwide. This being a considerable amount, efforts are being made to elucidate the disease mechanisms. One or several genetic factors cause 30-40% of DDs, and only 10% are caused by environmental factors. The remaining 50% of DD patients go undiagnosed, mostly due to a lack of diagnostic techniques. The cause in most undiagnosed cases is though to be a genetic factor or a combination of genetic and environmental factors. Despite the surge of new technologies entering the market, their implementation into diagnostic laboratories is hampered by costs, lack of information about the expected diagnostic yield, and the wide range of selection. This study evaluates new microarray methods in diagnosing idiopathic DDs, providing information about their added diagnostic value. Study I analysed 150 patients by array comparative genomic hybridization (array CGH, 44K and 244K), with a subsequent 18% diagnostic yield. These results are supported by other studies, indicating an enourmous added diagnostic value of array CGH, compared with conventional cytogenetic analysis. Nevertheless, 80% of the patients remained undiagnosed in Study I. In an effort to diagnose more patients, in Study IV the resolution was increased from 8.9 Kb of the 244K CGH array to 0.7 Kb, by using a single-nucleotide polymorphism (SNP) array. However, no additional pathogenic changes were detected in the 35 patients assessed, and thus, for diagnostic purposes, an array platform with ca 9 Kb resolution appears adequate. The recent vast increase in reports of detected aberrations and associated phenotypes has enabled characterization of several new syndromes first based on a common aberration and thereafter by delineation of common clinical characteristics. In Study II, a familial deletion at 9q22.2q22.32 with variable penetrance was described. Despite several reports of aberrations in the adjacent area at 9q associated with Gorlin syndrome, the patients in this family had a unique phenotype and did not present with the syndrome. In Study III, a familial duplication of chromosome 6p22.2 was described. The duplication caused increased expression of an important enzyme of the γ-aminobutyric acid (GABA) degradation pathway, causing oxidative stress of the brain, and thus, very likely, the mild mental retardation of these patients. These two case studies attempted to pinpoint candidate genes and to resolve the pathogenic mechanism causing the clinical characteristics of the patients. Presenting rare genetic and clinical findings to the international science and medical community enables interpretation of similar findings in other patients. The added value of molecular karyotyping in patients with idiopathic DD is evident. As a first line of testing, arrays with a median resolution of at least 9 Kb should be considered and further characterization of detected aberrations undertaken when possible. Diagnostic whole-exome sequencing may be the best option for patients who remain undiagnosed after high-resolution array analysis.

Neural stem cell characteristics affected by oncogenic pathways and in a human motoneuron disease

Neural stem cell characteristics affected by oncogenic pathways and in a human motoneuron disease Stem cells provide the self-renewing cell pool for developing or regenerating organs. The mechanisms underlying the decisions of a stem or progenitor cell to either self-renew and maintain multipotentiality or alternatively to differentiate are incompletely understood. In this thesis work, I have approached this question by investigating the role of the proto-oncogene Myc in the regulatory functions of neural progenitor cell (NPC) self-renewal, proliferation and differentiation. By using a retroviral transduction technique to create overexpression models in embryonic NPCs cultured as neurospheres, I show that activated levels of Myc increase NPC self-renewal. Furthermore, several mechanisms that regulate the activity of Myc were identified. Myc induced self-renewal is signalled through binding to the transcription factor Miz-1 as shown by the inhibited capacity of a Myc mutant (MycV394D), deficient in binding to Miz-1, to increase self-renewal in NPCs. Furthermore, overexpression of the newly identified proto-oncogene CIP2A recapitulates the effects of Myc overexpression in NPCs. Also the expression levels and in vivo expression patterns of Myc and CIP2A were linked together. CIP2A stabilizes Myc protein levels in several cancer types by inhibiting its degradation and our results suggest the same function for CIP2A in NPCs. Our results also support the conception of self-renewal and proliferation being two separately regulated cellular functions. Finally, I suggest that Myc regulates NPC self-renewal by influencing the way stem and progenitor cells react to the environmental cues that normally dictate the cellular identity of tissues containing self-renewing cells. Neurosphere cultures were also utilised in order to characterise functional defects in a human disease. Neural stem cell cultures obtained post-mortem from foetuses of lethal congenital contracture syndrome (LCCS) were used to reveal possible cell autonomous differentiation defects of patient NPCs. However, LCCS derived NPCs were able to differentiate normally in vitro although several transcriptional differences were identified by using microarray analysis. Proliferation rate of the patient NPCs was also increased as compared to NPCs of age-matched control foetuses.

Effects of dairy proteins and calcium on diet-induced obesity in mice

Diet high in dairy products is inversely associated with body mass index, risk of metabolic syndrome and prevalence of type 2 diabetes in several populations. Also a number of intervention studies support the role of increased dairy intake in the prevention and treatment of obesity. Dairy calcium has been suggested to account for the effect of dairy on body weight, but it has been repeatedly shown that the effect of dairy is superior to the effect of supplemental calcium. Dairy proteins are postulated to either enhance the effect of calcium or have an independent effect on body weight, but studies in the area are scarce. The aim of this study was to evaluate the potential of dairy proteins and calcium in the prevention and treatment of diet-induced obesity in C57Bl/6J mice. The effect of dairy proteins and calcium on the liver and adipose tissue was also investigated in order to characterise the potential mechanisms explaining the reduction of risk for metabolic syndrome and type 2 diabetes. A high-calcium diet (1.8%) in combination with dietary whey protein inhibited body weight and fat gain and accelerated body weight and fat loss in high-fat-fed C57Bl/6J mice during long-term studies of 14 to 21 weeks. α-lactalbumin, one of the major whey proteins, was the most effective whey protein fraction showing significantly accelerated weight and fat loss during energy restriction and reduced the amount of visceral fat gain during ad libitum feeding after weight loss. The microarray data suggest sensitisation of insulin signalling in the adipose tissue as a result of a calcium-rich whey protein diet. Lipidomic analysis revealed that weight loss on whey protein-based high-calcium diet was characterised by significant decreases in diabetogenic diacylglycerols and lipotoxic ceramide species. The calcium supplementation led to a small, but statistically significant decrease in fat absorption independent of the protein source of the diet. This augments, but does not fully explain the effects of the studied diets on body weight. A whey protein-containing high-calcium diet had a protective effect against a high-fat diet-induced decline of β3 adrenergic receptor expression in adipose tissue. In addition, a high-calcium diet with whey protein increased the adipose tissue leptin expression which is decreased in this obesity-prone mouse strain. These changes are likely to contribute to the inhibition of weight gain. The potential sensitisation of insulin signalling in adipose tissue together with the less lipotoxic and diabetogenic hepatic lipid profile suggest a novel mechanistic link to explain why increased dairy intake is associated with a lower prevalence of metabolic syndrome and type 2 diabetes in epidemiological studies. Taken together, the intake of a high-calcium diet with dairy proteins has a body weight lowering effect in high-fat-fed C57Bl/6J mice. High-calcium diets containing whey protein prevent weight gain and enhance weight loss, α-lactalbumin being the most effective whey protein fraction. Whey proteins and calcium have also beneficial effects on hepatic lipid profile and adipose tissue gene expression, which suggest a novel mechanistic link to explain the epidemiological findings on dairy intake and metabolic syndrome. The clinical relevance of these findings and the precise mechanisms of action remain an intriguing field of future research.

Candidate gene studies on cardiovascular traits

Cardiovascular diseases (CVD) are a major cause of death and disability in Western countries and a growing health problem in the developing world. The genetic component of both coronary heart disease (CHD) and ischemic stroke events has been established in twin studies, and the traits predisposing to CVD, such as hypertension, dyslipidemias, obesity, diabetes, and smoking behavior, are all partly hereditary. Better understanding of the pathophysiology of CVD-related traits could help to target disease prevention and clinical treatment to individuals at an especially high disease risk and provide novel pharmaceutical interventions. This thesis aimed to clarify the genetic background of CVD at a population level using large Nordic population cohorts and a candidate gene approach. The first study concentrated on the allelic diversity of the thrombomodulin (THBD) gene in two Finnish cohorts, FINRISK-92 and FINRISK-97. The results from this study implied that THBD variants do not substantially contribute to CVD risk. In the second study, three other candidate genes were added to the analyses. The study investigated the epistatic effects of coagulation factor V (F5), intercellular adhesion molecule -1 (ICAM1), protein C (PROC), and THBD in the same FINRISK cohorts. The results were encouraging; we were able to identify several single SNPs and SNP combinations associating with CVD and mortality. Interestingly, THBD variants appeared in the associating SNP combinations despite the negative results from Study I, suggesting that THBD contributes to CVD through gene-gene interactions. In the third study, upstream transcription factor -1 (USF1) was analyzed in a cohort of Swedish men. USF1 was associated with metabolic syndrome, characterized by accumulation of different CVD risk factors. A putative protective and a putative risk variant were identified. A direct association with CVD was not observed. The longitudinal nature of the study also clarified the effect of USF1 variants on CVD risk factors followed in four examinations throughout adulthood. The three studies provided valuable information on the study of complex traits, highlighting the use of large study samples, the importance of replication, and the full coverage of the major allelic variants of the target genes to assure reliable findings. Although the genetic basis of coronary heart disease and ischemic stroke remains unknown, single genetic findings may facilitate the recognition of high-risk subgroups.

Pathophysiological factors of irritable bowel syndrome, and the effects of probiotic supplementation

Gastrointestinal symptoms and impaired quality of life caused by irritable bowel syndrome (IBS) affect up to 20% of the adult population worldwide. The exact aetiology and pathophysiology of IBS are incompletely understood. Clinical studies suggest that supplementation with certain probiotics may be beneficial in IBS, but there is not enough evidence to make general recommendations. The aim of this thesis was to investigate microbiota- and mucosa-associated pathophysiological factors of IBS, and to evaluate the long-term effects of multispecies probiotic supplementation on symptoms, quality of life, intestinal microbiota and systemic inflammatory markers in IBS. The intestinal microbiota composition in IBS patients and healthy control subjects was analysed by quantitative polymerase chain reaction (qPCR). Significantly lower counts for the Clostridium coccoides and the Bifidobacterium catenulatum groups were found in IBS compared to controls. Quantitative differences also appeared in subgroup analysis based on the predominant bowel habit: diarrhoea patients harboured significantly lower numbers of Lactobacillus spp. than the constipation-predominant patients, while higher counts for Veillonella spp. were detected in constipation-predominant patients compared to healthy controls. Analysis of mucosal biopsies by a metabolomic approach revealed multiple differences between patients and controls. The most prominent finding was an upregulation of specific lipid species, principally lysophosphatidylcholines and ceramides, in IBS. The effects of multispecies probiotic supplementation with Lactobacillus rhamnosus GG, Lactobacillus rhamnosus Lc705, Propionibacterium freudenreichii subsp. shermanii JS, and Bifidobacterium breve Bb99 or Bifidobacterium animalis subsp. lactis Bb12 was evaluated in two, randomised, double-blind, placebo-controlled trials. Compared to placebo, the probiotic supplementation significantly reduced the total symptoms of IBS. No effects on bowel habit were seen. Health-related quality of life (HRQOL) is reduced in patients with IBS in comparison with the Finnish population on the whole. The probiotic supplementation improved one IBS-specific domain of quality of life (bowel symptoms), whereas no other effects on HRQOL were seen. The probiotics had no major effects on the predominant microbiota as measured by qPCR, but a microarray-based analysis suggested that the probiotic consumption stabilised the microbiota. No effects on serum sensitive-CRP or cytokines were detected. In conclusion, alterations in the microbiota composition and in the mucosal metabolite profile are potential pathophysiological factors of IBS. Multispecies probiotic supplementation alleviates the gastrointestinal symptoms of IBS, and improves the bowel symptoms domain of HRQOL. Probiotic supplementation in IBS is associated with a stabilisation of microbiota, but it does not influence systemic inflammatory markers.