Genetic Heterogeneity in Autism Spectrum Disorders in a Population Isolate

Positional cloning has enabled hypothesis-free, genome-wide scans for genetic factors contributing to disorders or traits. Traditionally linkage analysis has been used to identify regions of interest, followed by meticulous fine mapping and candidate gene screening using association methods and finally sequencing of regions of interest. More recently, genome-wide association analysis has enabled a more direct approach to identify specific genetic variants explaining a part of the variance of the phenotype of interest. Autism spectrum disorders (ASDs) are a group of childhood onset neuropsychiatric disorders with shared core symptoms but varying severity. Although a strong genetic component has been established in ASDs, genetic susceptibility factors have largely eluded characterization. Here, we have utilized modern molecular genetic methods combined with the advantages provided by the special population structure in Finland to identify genetic risk factors for ASDs. The results of this study show that numerous genetic risk factors exist for ASDs even within a population isolate. Stratification based on clinical phenotype resulted in encouraging results, as previously identified linkage to 3p14-p24 was replicated in an independent family set of families with Asperger syndrome, but no other ASDs. Fine-mapping of the previously identified linkage peak for ASDs at 3q25-q27 revealed association between autism and a subunit of the 5-hydroxytryptamine receptor 3C (HTR3C). We also used dense, genome-wide single nucleotide polymorphism (SNP) data to characterize the population structure of Finns. We observed significant population substructure which correlates with the known history of multiple consecutive bottle-necks experienced by the Finnish population. We used this information to ascertain a genetically homogenous subset of autism families to identify possible rare, enriched risk variants using genome-wide SNP data. No rare enriched genetic risk factors were identified in this dataset, although a subset of families could be genealogically linked to form two extended pedigrees. The lack of founder mutations in this isolated population suggests that the majority of genetic risk factors are rare, de novo mutations unique to individual nuclear families. The results of this study are consistent with others in the field. The underlying genetic architecture for this group of disorders appears highly heterogeneous, with common variants accounting for only a subset of genetic risk. The majority of identified risk factors have turned out to be exceedingly rare, and only explain a subset of the genetic risk in the general population in spite of their high penetrance within individual families. The results of this study, together with other results obtained in this field, indicate that family specific linkage, homozygosity mapping and resequencing efforts are needed to identify these rare genetic risk factors.

Genetic Mechanisms Underlying Autism Spectrum Disorders

Autism is a childhood-onset developmental disorder characterized by deficits in reciprocal social interaction, verbal and non-verbal communication, and dependence on routines and rituals. It belongs to a spectrum of disorders (autism spectrum disorders, ASDs) which share core symptoms but show considerable variation in severity. The whole spectrum affects 0.6-0.7% of children worldwide, inducing a substantial public health burden and causing suffering to the affected families. Despite having a very high heritability, ASDs have shown exceptional genetic heterogeneity, which has complicated the identification of risk variants and left the etiology largely unknown. However, recent studies suggest that rare, family-specific factors contribute significantly to the genetic basis of ASDs. In this study, we investigated the role of DISC1 (Disrupted-in-schizophrenia-1) in ASDs, and identified association with markers and haplotypes previously associated with psychiatric phenotypes. We identified four polymorphic micro-RNA target sites in the 3 UTR of DISC1, and showed that hsa-miR-559 regulates DISC1 expression in vitro in an allele-specific manner. We also analyzed an extended autism pedigree with genealogical roots in Central Finland reaching back to the 17th century. To take advantage of the beneficial characteristics of population isolates to gene mapping and reduced genetic heterogeneity observed in distantly related individuals, we performed a microsatellite-based genome-wide screen for linkage and linkage disequilibrium in this pedigree. We identified a putative autism susceptibility locus on chromosome 19p13.3 and obtained further support for previously reported loci at 1q23 and 15q11-q13. To follow-up these findings, we extended our study sample from the same sub-isolate and initiated a genome-wide analysis of homozygosity and allelic sharing using high-density SNP markers. We identified a small number of haplotypes shared by different subsets of the genealogically connected cases, along with convergent biological pathways from SNP and gene expression data, which highlighted axon guidance molecules in the pathogenesis of ASDs. In conclusion, the results obtained in this thesis show that multiple distinct genetic variants are responsible for the ASD phenotype even within single pedigrees from an isolated population. We suggest that targeted resequencing of the shared haplotypes, linkage regions, and other susceptibility loci is essential to identify the causal variants. We also report a possible micro-RNA mediated regulatory mechanism, which might partially explain the wide-range neurobiological effects of the DISC1 gene.

Associations of interleukin-1 (IL-1) gene variation and IL-1 receptor antagonist phenotypes with immunological responses, metabolic dysregulation and type 2 diabetes

The upstream proinflammatory interleukin-1 (IL-1) cytokines, together with a naturally occurring IL-1 receptor antagonist (IL-1Ra), play a significant role in several diseases and physiologic conditions. The IL-1 proteins affect glucose homeostasis at multiple levels contributing to vascular injuries and metabolic dysregulations that precede diabetes. An association between IL-1 gene variations and IL-1Ra levels has been suggested, and genetic studies have reported associations with metabolic dysregulation and altered inflammatory responses. The principal aims of this study were to: 1) examine the associations of IL-1 gene variation and IL-1Ra expression in the development and persistence of thyroid antibodies in subacute thyroiditis; 2) investigate the associations of common variants in the IL-1 gene family with plasma glucose and insulin concentrations, glucose homeostasis measures and prevalent diabetes in a representative population sample; 3) investigate genetic and non-genetic determinants of IL-1Ra phenotypes in a cross-sectional setting in three independent study populations; 4) investigate in a prospective setting (a) whether variants of the IL-1 gene family are predictors for clinically incident diabetes in two population-based observational cohort studies; and (b) whether the IL-1Ra levels predict the progression of metabolic syndrome to overt diabetes during the median follow-up of 10.8 and 7.1 years. Results from on patients with subacte thyroiditis showed that the systemic IL-1Ra levels are elevated during a specific proinflammatory response and they correlated with C-reactive protein (CRP) levels. Genetic variation in the IL-1 family seemed to have an association with the appearance of thyroid peroxidase antibodies and persisting local autoimmune responses during the follow-up. Analysis of patients suffering from diabetes and metabolic traits suggested that genetic IL-1 variation and IL-1Ra play a role in glucose homeostasis and in the development of type 2 diabetes. The coding IL-1 beta SNP rs1143634 was associated with traits related to insulin resistance in cross-sectional analyses. Two haplotype variants of the IL-1 beta gene were associated with prevalent diabetes or incident diabetes in a prospective setting and both of these haplotypes were tagged by rs1143634. Three variants of the IL-1Ra gene and one of the IL-1 beta gene were consistently identified as significant, independent determinants of the IL-1Ra phenotype in two or three populations. The proportion of the phenotypic variation explained by the genetic factors was modest however, while obesity and other metabolic traits explained a larger part. Body mass index was the strongest predictor of systemic IL-1Ra concentration overall. Furthermore, the age-adjusted IL-1Ra concentrations were elevated in individuals with metabolic syndrome or diabetes when compared to those free of metabolic dysregulation. In prospective analyses the systemic IL-1Ra levels were found as independent predictors for the development of diabetes in people with metabolic syndrome even after adjustment for multiple other factors, including plasma glucose and CRP levels. The predictive power of IL-1Ra was better than that of CRP. The prospective results also provided some evidence for a role of common IL-1 alpha promoter SNP rs1800587 in the development of type 2 diabetes among men and suggested that the role may be gender specific. Likewise, common variations in the IL-1 beta coding region may have a gender specific association with diabetes development. Further research on the potential benefits of IL-1Ra measurements in identifying individuals at high risk for diabetes, who then could be targeted for specific treatment interventions, is warranted. It has been reported in the recent literature that IL-1Ra secreted from adipose tissue has beneficial effects on glucose homeostasis. Furthermore, treatment with recombinant human IL-1Ra has been shown to have a substantial therapeutic potential. The genetic results from the prospective analyses performed in this study remain inconclusive, but together with the cross-sectional analyses they suggest gender-specific effects of the IL-1 variants on the risk of diabetes. Larger studies with more extensive genotyping and resequencing may help to pinpoint the exact variants responsible and to further elucidate the biological mechanisms for the observed associations. This would improve our understanding of the pathways linking inflammation and obesity with glucose and insulin metabolism.