Genetic analysis of chromosomal regions 2q33, 7q32 and 19q13 in multiple sclerosis susceptibility

Multiple sclerosis (MS) is an immune-mediated demyelinating disorder of the central nervous system (CNS) affecting 0.1-0.2% of Northern European descent population. MS is considered to be a multifactorial disease, both environment and genetics play a role in its pathogenesis. Despite several decades of intense research, the etiological and pathogenic mechanisms underlying MS remain still largely unknown and no curative treatment exists. The genetic architecture underlying MS is complex with multiple genes involved. The strongest and the best characterized predisposing genetic factors for MS are located, as in other immune-mediated diseases, in the major histocompatibility complex (MHC) on chromosome 6. In humans MHC is called human leukocyte antigen (HLA). Alleles of the HLA locus have been found to associate strongly with MS and remained for many years the only consistently replicable genetic associations. However, recently other genes located outside the MHC region have been proposed as strong candidates for susceptibility to MS in several studies. In this thesis a new genetic locus located on chromosome 7q32, interferon regulatory factor 5 (IRF5), was identified in the susceptibility to MS. In particular, we found that common variation of the gene was associated with the disease in three different populations, Spanish, Swedish and Finnish. We also suggested a possible functional role for one of the risk alleles with impact on the expression of the IRF5 locus. Previous studies have pointed out a possible role played by chromosome 2q33 in the susceptibility to MS and other autoimmune disorders. The work described here also investigated the involvement of this chromosomal region in MS predisposition. After the detection of genetic association with 2q33 (article-1), we extended our analysis through fine-scale single nucleotide polymorphism (SNP) mapping to define further the contribution of this genomic area to disease pathogenesis (article-4). We found a trend (p=0.04) for association to MS with an intronic SNP located in the inducible T-cell co-stimulator (ICOS) gene, an important player in the co-stimulatory pathway of the immune system. Expression analysis of ICOS revealed a novel, previously uncharacterized, alternatively spliced isoform, lacking the extracellular domain that is needed for ligand binding. The stability of the newly-identified transcript variant and its subcellular localization were analyzed. These studies indicated that the novel isoform is stable and shows different subcellular localization as compared to full-length ICOS. The novel isoform might have a regulatory function, but further studies are required to elucidate its function. Chromosome 19q13 has been previously suggested as one of the genomic areas involved in MS predisposition. In several populations, suggestive linkage signals between MS predisposition and 19q13 have been obtained. Here, we analysed the role of allelic variation in 19q13 by family based association analysis in 782 MS families collected from Finland. In this dataset, we were not able to detect any statistically significant associations, although several previously suggested markers were included to the analysis. Replication of the previous findings on the basis of linkage disequilibrium between marker allele and disease/risk allele appears notoriously difficult because of limitations such as allelic heterogeneity. Re-sequencing based approaches may be required for elucidating the role of chromosome 19q13 with MS. This thesis has resulted in the identification of a new MS susceptibility locus (IRF5) previously associated with other inflammatory or autoimmune disorders, such as SLE. IRF5 is one of the mediators of interferons biological function. In addition to providing new insight in the possible pathogenetic pathway of the disease, this finding suggests that there might be common mechanisms between different immune-mediated disorders. Furthermore the work presented here has uncovered a novel isoform of ICOS, which may play a role in regulatory mechanisms of ICOS, an important mediator of lymphocyte activation. Further work is required to uncover its functions and possible involvement of the ICOS locus in MS susceptibility.

'Mutiny on the Bounty': The genetic history of Norfolk Island reveals extreme gender-biased admixture

Background The Pacific Oceania region was one of the last regions of the world to be settled via human migration. Here we outline a settlement of this region that has given rise to a uniquely admixed population. The current Norfolk Island population has arisen from a small number of founders with mixed Caucasian and Polynesian ancestry, descendants of a famous historical event. The ‘Mutiny on the Bounty’ has been told in history books, songs and the big screen, but recently this story can be portrayed through comprehensive molecular genetics. Written history details betrayal and murder leading to the founding of Pitcairn Island by European mutineers and the Polynesian women who left Tahiti with them. Investigation of detailed genealogical records supports historical accounts. Findings Using genetics, we show distinct maternal Polynesian mitochondrial lineages in the present day population, as well as a European centric Y-chromosome phylogeny. These results comprehensively characterise the unique gender-biased admixture of this genetic isolate and further support the historical records relating to Norfolk Island. Conclusions Our results significantly refine previous population genetic studies investigating Polynesian versus Caucasian diversity in the Norfolk Island population and add information that is beneficial to future disease and gene mapping studies.

Serum bilirubin concentration is modified by UGT1A1 Haplotypes and influences risk of type-2 diabetes in the Norfolk Island Genetic Isolate

Background Located in the Pacific Ocean between Australia and New Zealand, the unique population isolate of Norfolk Island has been shown to exhibit increased prevalence of metabolic disorders (type-2 diabetes, cardiovascular disease) compared to mainland Australia. We investigated this well-established genetic isolate, utilising its unique genomic structure to increase the ability to detect related genetic markers. A pedigree-based genome-wide association study of 16 routinely collected blood-based clinical traits in 382 Norfolk Island individuals was performed. Results A striking association peak was located at chromosome 2q37.1 for both total bilirubin and direct bilirubin, with 29 SNPs reaching statistical significance (P < 1.84 × 10−7). Strong linkage disequilibrium was observed across a 200 kb region spanning the UDP-glucuronosyltransferase family, including UGT1A1, an enzyme known to metabolise bilirubin. Given the epidemiological literature suggesting negative association between CVD-risk and serum bilirubin we further explored potential associations using stepwise multivariate regression, revealing significant association between direct bilirubin concentration and type-2 diabetes risk. In the Norfolk Island cohort increased direct bilirubin was associated with a 28 % reduction in type-2 diabetes risk (OR: 0.72, 95 % CI: 0.57-0.91, P = 0.005). When adjusted for genotypic effects the overall model was validated, with the adjusted model predicting a 30 % reduction in type-2 diabetes risk with increasing direct bilirubin concentrations (OR: 0.70, 95 % CI: 0.53-0.89, P = 0.0001). Conclusions In summary, a pedigree-based GWAS of blood-based clinical traits in the Norfolk Island population has identified variants within the UDPGT family directly associated with serum bilirubin levels, which is in turn implicated with reduced risk of developing type-2 diabetes within this population.

Evaluation of a 7-gene genetic profile for athletic endurance phenotype in Ironman championship triathletes

Polygenic profiling has been proposed for elite endurance performance, using an additive model determining the proportion of optimal alleles in endurance athletes. To investigate this model’s utility for elite triathletes, we genotyped seven polymorphisms previously associated with an endurance polygenic profile (ACE Ins/Del, ACTN3 Arg577Ter, AMPD1 Gln12Ter, CKMM 1170bp/985+185bp, HFE His63Asp, GDF8 Lys153Arg and PPARGC1A Gly482Ser) in a cohort of 196 elite athletes who participated in the 2008 Kona Ironman championship triathlon. Mean performance time (PT) was not significantly different in individual marker analysis. Age, sex, and continent of origin had a significant influence on PT and were adjusted for. Only the AMPD1 endurance-optimal Gln allele was found to be significantly associated with an improvement in PT (model p=5.79 x 10-17, AMPD1 genotype p=0.01). Individual genotypes were combined into a total genotype score (TGS); TGS distribution ranged from 28.6 to 92.9, concordant with prior studies in endurance athletes (mean±SD: 60.75±12.95). TGS distribution was shifted toward higher TGS in the top 10% of athletes, though the mean TGS was not significantly different (p=0.164) and not significantly associated with PT even when adjusted for age, sex, and origin. Receiver operating characteristic curve analysis determined that TGS alone could not significantly predict athlete finishing time with discriminating sensitivity and specificity for three outcomes (less than median PT, less than mean PT, or in the top 10%), though models with the age, sex, continent of origin, and either TGS or AMPD1 genotype could. These results suggest three things: that more sophisticated genetic models may be necessary to accurately predict athlete finishing time in endurance events; that non-genetic factors such as training are hugely influential and should be included in genetic analyses to prevent confounding; and that large collaborations may be necessary to obtain sufficient sample sizes for powerful and complex analyses of endurance performance.

Prediction of individual genetic risk to prostate cancer using a polygenic score

BACKGROUND Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction. Prostate 75:1467–1474, 2015. © 2015 Wiley Periodicals, Inc.

Identification of genetic susceptibility loci for migraine

Migraine is the common cause of chronic episodic headache, affecting 12%-15% of the Caucasian population (41 million Europeans and some half a million Finns), and causes considerable loss of quality of life to its sufferers, as well as being linked to increased risk for a wide range of conditions, from depression to stroke. Migraine is the 19th most severe disease in terms of disability-adjusted life years, and 9th among women. It is characterized by attacks of headache accompanied by sensitivity to external stimuli lasting 4-72 hours, and in a third of cases by neurological aura symptoms, such as loss of vision, speech or muscle function. The underlying pathophysiology, including what triggers migraine attacks and why they occur in the first place, is largely unknown. The aim of this study was to identify genetic factors associated with the hereditary susceptibility to migraine, in order to gain a better understanding of migraine mechanisms. In this thesis, we report the results of genetic linkage and association analyses on a Finnish migraine patient collection as well as migraineurs from Australia, Denmark, Germany, Iceland and the Netherlands. Altogether we studied genetic information of nearly 7,000 migraine patients and over 50,000 population-matched controls. We also developed a new migraine analysis method called the trait component analysis, which is based on individual patient responses instead of the clinical diagnosis. Using this method, we detected a number of new genetic loci for migraine, including on chromosome 17p13 (HLOD 4.65) and 10q22-q23 (female-specific HLOD 7.68) with significant evidence of linkage, along with five other loci (2p12, 8q12, 4q28-q31, 18q12-q22, and Xp22) detected with suggestive evidence of linkage. The 10q22-q23 locus was the first genetic finding in migraine to show linkage to the same locus and markers in multiple populations, with consistent detection in six different scans. Traditionally, ion channels have been thought to play a role in migraine susceptibility, but we were able to exclude any significant role for common variants in a candidate gene study of 155 ion transport genes. This was followed up by the first genome-wide association study in migraine, conducted on 2,748 migraine patients and 10,747 matched controls followed by a replication in 3,209 patients and 40,062 controls. In this study, we found interesting results with genome-wide significance, providing targets for future genetic and functional studies. Overall, we found several promising genetic loci for migraine providing a promising base for future studies in migraine.

Conservative Design Optimization of Laminated Composite Structures Using Genetic Algorithms and Multiple Failure Criteria

This article analyzes the effect of devising a new failure envelope by the combination of the most commonly used failure criteria for the composite laminates, on the design of composite structures. The failure criteria considered for the study are maximum stress and Tsai-Wu criteria. In addition to these popular phenomenological-based failure criteria, a micromechanics-based failure criterion called failure mechanism-based failure criterion is also considered. The failure envelopes obtained by these failure criteria are superimposed over one another and a new failure envelope is constructed based on the lowest absolute values of the strengths predicted by these failure criteria. Thus, the new failure envelope so obtained is named as most conservative failure envelope. A minimum weight design of composite laminates is performed using genetic algorithms. In addition to this, the effect of stacking sequence on the minimum weight of the laminate is also studied. Results are compared for the different failure envelopes and the conservative design is evaluated, with respect to the designs obtained by using only one failure criteria. The design approach is recommended for structures where composites are the key load-carrying members such as helicopter rotor blades.

A self-adaptive migration model genetic algorithm for data mining applications

Data mining involves nontrivial process of extracting knowledge or patterns from large databases. Genetic Algorithms are efficient and robust searching and optimization methods that are used in data mining. In this paper we propose a Self-Adaptive Migration Model GA (SAMGA), where parameters of population size, the number of points of crossover and mutation rate for each population are adaptively fixed. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions and a set of actual classification datamining problems. Michigan style of classifier was used to build the classifier and the system was tested with machine learning databases of Pima Indian Diabetes database, Wisconsin Breast Cancer database and few others. The performance of our algorithm is better than others.

Genetic studies on Finnish lupus erythematosus patients with cutaneous manifestations

Lupus erythematosus (LE) is a chronic, heterogeneous autoimmune disorder with abnormal immune responses, including production of autoantibodies and immune complexes. Clinical presentations of the disease range from mild cutaneous manifestations to a more generalised systemic involvement of internal organs. Cutaneous (CLE) forms are further subclassified into discoid LE (DLE), subacute cutaneous LE (SCLE) and acute cutaneous lupus erythematosus (ACLE), and may later progress to systemic disease (SLE). Both genetic and environmental factors contribute to the disease, although the precise aetiology is still elusive. Furthermore, complex gene-gene or gene-environment interactions may result in different subphenotypes of lupus. The genetic background of CLE is poorly known and only a few genes are confirmed, while the number of robust genetic associations in SLE exceeds 30. The aim of this thesis was to characterise the recruited patients clinically, and identify genetic variants conferring susceptibility to cutaneous variants of LE. Given that cutaneous and systemic disease may share underlying genetic factors, putative CLE candidate genes for genotyping were selected among those showing strong evidence of association in SLE. The correlation between relevant clinical manifestations and risk genotypes was investigated in order to find specific subphenotype associations. In addition, epistatic interactions in SLE were studied. Finally, the role of tissue degrading matrix metalloproteinases (MMP) in LE tissue injury was explored. These studies were conducted in Finnish case-control and family cohort, and Swedish case-control cohort. The clinical picture of the patients in terms of cutaneous, haematological and immunological findings resembled that described in the contemporary literature. However, the proportion of daily smokers was very high supporting the role of smoking in disease aetiology. The results confirmed that, even though clinically distinct entities, CLE and SLE share predisposing genetic factors. For the first time it was shown that known SLE susceptibility genes IRF5 and TYK2 also increase the risk of CLE. A tendency toward gene-gene interaction between these genes was found in SLE. As a remarkable novel finding, it was observed that ITGAM polymorphisms associated even more strongly to DLE than SLE, and the risk estimates were substantially higher than those reported for SLE. Several other recently identified SLE susceptibility genes showed signs of good or modest association especially in DLE. Subphenotype analyses indicated possible associations to clinical features, but marginally significant results reflected lack of sufficient power for these studies. Thorough immunohistochemical analyses of several MMPs demonstrated a role in epidermal changes and dermal tissue remodelling in diseased skin, and suggested that targeted action using selective MMP inhibitors may reduce lupus-induced damage in inflamed tissues. In conclusion, the results provide an insight into the genetics of CLE and demonstrate that genetic predisposition is at least in part shared between cutaneous and systemic variants of LE. This doctoral study has contributed IRF5, TYK2, ITGAM and several other novel genes to the so far short list of genes implicated in CLE susceptibility. Detailed examination of the function of these genes in CLE pathogenesis warrants further studies. Furthermore, the results support the need of subphenotype analysis with sample sizes large enough to reveal possible specific disease associations in order to better understand the heterogeneous nature and clinical specificities of the disease. Comprehensive analysis of clinical data suggests that smoking is an environmental triggering factor.

Timing of puberty : Genetic regulation

In the general population, the timing of puberty is normally distributed. This variation is determined by genetic and environmental factors, but the exact mechanisms underlying these influences remain elusive. The purpose of this study was to gain insight into genetic regulation of pubertal timing. Contributions of genetic versus environmental factors to the normal variation of pubertal timing were explored in twins. Familial occurrence and inheritance patterns of constitutional delay of growth and puberty, CDGP (a variant of normal pubertal timing), were studied in pedigrees of patients with this condition. To ultimately detect genes involved in the regulation of pubertal timing, genetic loci conferring susceptibility to CDGP were mapped by linkage analysis in the same family cohort. To subdivide the overall phenotypic variance of pubertal timing into genetic and environmental components, genetic modeling based on monozygous twins sharing 100% and dizygous twins sharing 50% of their genes was used in 2309 girls and 1828 boys from the FinnTwin 12-17 study. The timing of puberty was estimated from height growth, i.e. change in the relative height between the age when pubertal growth velocity peaks in the general population and adulthood. This reflects the percentage of adult height achieved at the average peak height velocity age, and thus, pubertal timing. Boys and girls diagnosed with CDGP were gathered through medical records from six pediatric clinics in Finland. First-degree relatives of the probands were invited to participate by letter; altogether, 286 families were recruited. When possible, families were extended to include also second-, third-, or fourth-degree relatives. The timing of puberty in all family members was primarily assessed from longitudinal growth data. Delayed puberty was defined by onset of pubertal growth spurt or peak height velocity taking place 1.5 (relaxed criterion) or 2 SD (strict criterion) beyond the mean. If growth data were unavailable, pubertal timing was based on interviews. In this case, CDGP criteria were set as having undergone pubertal development more than 2 (strict criterion) or 1.5 years (relaxed criterion) later than their peers, or menarche after 15 (strict criterion) or 14 years (relaxed criterion). Familial occurrence of strict CDGP was explored in families of 124 patients (95 males and 29 females) from two clinics in Southern Finland. In linkage analysis, we used relaxed CDGP criteria; 52 families with solely growth data-based CDGP diagnoses were selected from all clinics. Based on twin data, genetic factors explain 86% and 82% of the variance of pubertal timing in girls and boys, respectively. In families, 80% of male and 76% of female probands had affected first-degree relatives, in whom CDGP was 15 times more common than the expected (2.5%). In 74% (17 of 23) of the extended families with only one affected parent, familial patterns were consistent with autosomal dominant inheritance. By using 383 multiallelic markers and subsequently fine-mapping with 25 additional markers, significant linkage for CDGP was detected to the pericentromeric region of chromosome 2, to 2p13-2q13 (multipoint HLOD 4.44, α 0.41). The findings of the large twin study imply that the vast majority of the normal variation of pubertal timing is attributed to genetic effects. Moreover, the high frequency of dominant inheritance patterns and the large number of affected relatives of CDGP patients suggest that genetic factors also markedly contribute to constitutional delay of puberty. Detection of the locus 2p13-2q13 in the pericentromeric region of chromosome 2 associating with CDGP is one step towards unraveling the genes that determine pubertal timing.