Examination of Genetic Components Affecting Human Obesity-Related Quantitative Traits

Obesity increases the risk for several conditions, including type 2 diabetes mellitus, cardiovascular disease, hypertension, osteoarthirits and certain types of cancer. Twin- and family studies have shown that there is a major genetic component in the determination of body mass. In recent years several technological and scientific advance have been made in obesity research. For instance, novel replicated loci have been revealed by a number of genome wide association studies. This thesis aimed to investigate the association of genetic factors and obesity-related quantitative traits. The first study investigated the role of the lactase gene in anthropometric traits. We genetically defined lactose persistence by genotyping 31 720 individuals of European descent. We found that lactase persistence was significantly correlated with weight and body mass index but not with height. In the second study we performed the largest whole genome linkage scan for body mass index to date. The sample consisted of 4401 twin families and 10 535 individuals from six European countries. We found supporting evidence for two loci (3q29 and 7q36). We observed that the heritability estimate increased substantially when additional family members were removed from the analyses, which suggests reduced environmental variance in the twin sample. In the third study we assessed metabonomic, transcriptomic and genomic variation in a Finnish population cohort of 518 individuals. We formed gene expression networks to portray pathways and showed that a set of highly correlated genes of an inflammatory pathway associated with 80 serum metabolites (of 134 quantified measures). Strong association was found, for example, with several lipoprotein subclasses. We inferred causality by using genetic variation as anchors. The expression of the network genes was found to be dependent on the circulatory metabolite concentrations.

The genetic association between personality and major depression or bipolar disorder. A polygenic score analysis using genome-wide association data

The relationship between major depressive disorder (MDD) and bipolar disorder (BD) remains controversial. Previous research has reported differences and similarities in risk factors for MDD and BD, such as predisposing personality traits. For example, high neuroticism is related to both disorders, whereas openness to experience is specific for BD. This study examined the genetic association between personality and MDD and BD by applying polygenic scores for neuroticism, extraversion, openness to experience, agreeableness and conscientiousness to both disorders. Polygenic scores reflect the weighted sum of multiple single-nucleotide polymorphism alleles associated with the trait for an individual and were based on a meta-analysis of genome-wide association studies for personality traits including 13,835 subjects. Polygenic scores were tested for MDD in the combined Genetic Association Information Network (GAIN-MDD) and MDD2000+ samples (N=8921) and for BD in the combined Systematic Treatment Enhancement Program for Bipolar Disorder and Wellcome Trust Case-Control Consortium samples (N=6329) using logistic regression analyses. At the phenotypic level, personality dimensions were associated with MDD and BD. Polygenic neuroticism scores were significantly positively associated with MDD, whereas polygenic extraversion scores were significantly positively associated with BD. The explained variance of MDD and BD, approximately 0.1%, was highly comparable to the variance explained by the polygenic personality scores in the corresponding personality traits themselves (between 0.1 and 0.4%). This indicates that the proportions of variance explained in mood disorders are at the upper limit of what could have been expected. This study suggests shared genetic risk factors for neuroticism and MDD on the one hand and for extraversion and BD on the other.

Educational attainment: A genome wide association study in 9538 Australians

BACKGROUND Correlations between Educational Attainment (EA) and measures of cognitive performance are as high as 0.8. This makes EA an attractive alternative phenotype for studies wishing to map genes affecting cognition due to the ease of collecting EA data compared to other cognitive phenotypes such as IQ. METHODOLOGY In an Australian family sample of 9538 individuals we performed a genome-wide association scan (GWAS) using the imputed genotypes of approximately 2.4 million single nucleotide polymorphisms (SNP) for a 6-point scale measure of EA. Top hits were checked for replication in an independent sample of 968 individuals. A gene-based test of association was then applied to the GWAS results. Additionally we performed prediction analyses using the GWAS results from our discovery sample to assess the percentage of EA and full scale IQ variance explained by the predicted scores. RESULTS The best SNP fell short of having a genome-wide significant p-value (p = 9.77x10(-7)). In our independent replication sample six SNPs among the top 50 hits pruned for linkage disequilibrium (r(2)<0.8) had a p-value<0.05 but only one of these SNPs survived correction for multiple testing--rs7106258 (p = 9.7*10(-4)) located in an intergenic region of chromosome 11q14.1. The gene based test results were non-significant and our prediction analyses show that the predicted scores explained little variance in EA in our replication sample. CONCLUSION While we have identified a polymorphism chromosome 11q14.1 associated with EA, further replication is warranted. Overall, the absence of genome-wide significant p-values in our large discovery sample confirmed the high polygenic architecture of EA. Only the assembly of large samples or meta-analytic efforts will be able to assess the implication of common DNA polymorphisms in the etiology of EA.

A quantitative-trait genome-wide association study of alcoholism risk in the community: findings and implications

BACKGROUND Given moderately strong genetic contributions to variation in alcoholism and heaviness of drinking (50% to 60% heritability) with high correlation of genetic influences, we have conducted a quantitative trait genome-wide association study (GWAS) for phenotypes related to alcohol use and dependence. METHODS Diagnostic interview and blood/buccal samples were obtained from sibships ascertained through the Australian Twin Registry. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed with 8754 individuals (2062 alcohol-dependent cases) selected for informativeness for alcohol use disorder and associated quantitative traits. Family-based association tests were performed for alcohol dependence, dependence factor score, and heaviness of drinking factor score, with confirmatory case-population control comparisons using an unassessed population control series of 3393 Australians with genome-wide SNP data. RESULTS No findings reached genome-wide significance (p = 8.4 x 10(-8) for this study), with lowest p value for primary phenotypes of 1.2 x 10(-7). Convergent findings for quantitative consumption and diagnostic and quantitative dependence measures suggest possible roles for a transmembrane protein gene (TMEM108) and for ANKS1A. The major finding, however, was small effect sizes estimated for individual SNPs, suggesting that hundreds of genetic variants make modest contributions (1/4% of variance or less) to alcohol dependence risk. CONCLUSIONS We conclude that: - 1) meta-analyses of consumption data may contribute usefully to gene discovery; - 2) translation of human alcoholism GWAS results to drug discovery or clinically useful prediction of risk will be challenging, and; - 3) through accumulation across studies, GWAS data may become valuable for improved genetic risk differentiation in research in biological psychiatry (e.g., prospective high-risk or resilience studies).

Search for genetic variants influencing human height

Human growth and attained height are determined by a combination of genetic and environmental effects and in modern Western societies > 80% of the observed variation in height is determined by genetic factors. Height is a fundamental human trait that is associated with many socioeconomic and psychosocial factors and health measures, however little is known of the identity of the specific genes that influence height variation in the general population. This thesis work aimed to identify the genetic variants that influence height in the general population by genome-wide linkage analysis utilizing large family samples. The study focused on analysis of three separate sets of families consisting of: 1) 1,417 individuals from 277 Finnish families (FinnHeight), 2) 8,450 individuals from 3,817 families from Australia and Europe (EUHeight) and 3) 9,306 individuals from 3,302 families from the United States (USHeight). The most significant finding in this study was found in the Finnish family sample where we a locus in the chromosomal region 1p21 was linked to adult height. Several regions showed evidence for linkage in the Australian, European and US families with 8q21 and 15q25 being the most significant. The region on 1p21 was followed up with further studies and we were able to show that the collagen 11-alpha-1 gene (COL11A1) residing at this location was associated with adult height. This association was also confirmed in an independent Finnish population cohort (Health 2000) consisting of 6,542 individuals. From this population sample, we estimated that homozygous males and females for this gene variant were 1.1 and 0.6 cm taller than the respective controls. In this thesis work we identified a gene variant in the COL11A1 gene that influences human height, although this variant alone explains only 0.1% of height variation in the Finnish population. We also demonstrated in this study that special stratification strategies such as performing sex-limited analyses, focusing on dizygous twin pairs, analyzing ethnic groups within a population separately and utilizing homogenous populations such as the Finns can improve the statistical power of finding QTL significantly. Also, we concluded from the results of this study that even though genetic effects explain a great proportion of height variance, it is likely that there are tens or even hundreds of genes with small individual effects underlying the genetic architecture of height.

Common SNPs explain a large proportion of the heritability for human height

SNPs discovered by genome-wide association studies (GWASs) account for only a small fraction of the genetic variation of complex traits in human populations. Where is the remaining heritability? We estimated the proportion of variance for human height explained by 294,831 SNPs genotyped on 3,925 unrelated individuals using a linear model analysis, and validated the estimation method with simulations based on the observed genotype data. We show that 45% of variance can be explained by considering all SNPs simultaneously. Thus, most of the heritability is not missing but has not previously been detected because the individual effects are too small to pass stringent significance tests. We provide evidence that the remaining heritability is due to incomplete linkage disequilibrium between causal variants and genotyped SNPs, exacerbated by causal variants having lower minor allele frequency than the SNPs explored to date.

A genome-wide association study of Cloninger's temperament scales: implications for the evolutionary genetics of personality

Variation in personality traits is 30-60% attributed to genetic influences. Attempts to unravel these genetic influences at the molecular level have, so far, been inconclusive. We performed the first genome-wide association study of Cloninger's temperament scales in a sample of 5117 individuals, in order to identify common genetic variants underlying variation in personality. Participants' scores on Harm Avoidance, Novelty Seeking, Reward Dependence, and Persistence were tested for association with 1,252,387 genetic markers. We also performed gene-based association tests and biological pathway analyses. No genetic variants that significantly contribute to personality variation were identified, while our sample provides over 90% power to detect variants that explain only 1% of the trait variance. This indicates that individual common genetic variants of this size or greater do not contribute to personality trait variation, which has important implications regarding the genetic architecture of personality and the evolutionary mechanisms by which heritable variation is maintained.

Common variants in the trichohyalin gene are associated with straight hair in Europeans

Hair morphology is highly differentiated between populations and among people of European ancestry. Whereas hair morphology in East Asian populations has been studied extensively, relatively little is known about the genetics of this trait in Europeans. We performed a genome-wide association scan for hair morphology (straight, wavy, curly) in three Australian samples of European descent. All three samples showed evidence of association implicating the Trichohyalin gene (TCHH), which is expressed in the developing inner root sheath of the hair follicle, and explaining approximately 6% of variance (p=1.5x10(-31)). These variants are at their highest frequency in Northern Europeans, paralleling the distribution of the straight-hair EDAR variant in Asian populations.

Genetic influences on handedness: data from 25,732 Australian and Dutch twin families

Handedness refers to a consistent asymmetry in skill or preferential use between the hands and is related to lateralization within the brain of other functions such as language. Previous twin studies of handedness have yielded inconsistent results resulting from a general lack of statistical power to find significant effects. Here we present analyses from a large international collaborative study of handedness (assessed by writing/drawing or self report) in Australian and Dutch twins and their siblings (54,270 individuals from 25,732 families). Maximum likelihood analyses incorporating the effects of known covariates (sex, year of birth and birth weight) revealed no evidence of hormonal transfer, mirror imaging or twin specific effects. There were also no differences in prevalence between zygosity groups or between twins and their singleton siblings. Consistent with previous meta-analyses, additive genetic effects accounted for about a quarter (23.64%) of the variance (95%CI 20.17, 27.09%) with the remainder accounted for by non-shared environmental influences. The implications of these findings for handedness both as a primary phenotype and as a covariate in linkage and association analyses are discussed.

Sequence variants in three loci influence monocyte counts and erythrocyte volume

Blood cells participate in vital physiological processes, and their numbers are tightly regulated so that homeostasis is maintained. Disruption of key regulatory mechanisms underlies many blood-related Mendelian diseases but also contributes to more common disorders, including atherosclerosis. We searched for quantitative trait loci (QTL) for hematology traits through a whole-genome association study, because these could provide new insights into both hemopoeitic and disease mechanisms. We tested 1.8 million variants for association with 13 hematology traits measured in 6015 individuals from the Australian and Dutch populations. These traits included hemoglobin composition, platelet counts, and red blood cell and white blood cell indices. We identified three regions of strong association that, to our knowledge, have not been previously reported in the literature. The first was located in an intergenic region of chromosome 9q31 near LPAR1, explaining 1.5% of the variation in monocyte counts (best SNP rs7023923, p=8.9x10(-14)). The second locus was located on chromosome 6p21 and associated with mean cell erythrocyte volume (rs12661667, p=1.2x10(-9), 0.7% variance explained) in a region that spanned five genes, including CCND3, a member of the D-cyclin gene family that is involved in hematopoietic stem cell expansion. The third region was also associated with erythrocyte volume and was located in an intergenic region on chromosome 6q24 (rs592423, p=5.3x10(-9), 0.6% variance explained). All three loci replicated in an independent panel of 1543 individuals (p values=0.001, 9.9x10(-5), and 7x10(-5), respectively). The identification of these QTL provides new opportunities for furthering our understanding of the mechanisms regulating hemopoietic cell fate.

Replication of the association of common rs9939609 variant of FTO with increased BMI in an Australian adult twin population but no evidence for gene by environment (G x E) interaction

OBJECTIVE: To further investigate a common variant (rs9939609) in the fat mass- and obesity-associated gene (FTO), which recent genome-wide association studies have shown to be associated with body mass index (BMI) and obesity. DESIGN: We examined the effect of this FTO variant on BMI in 3353 Australian adult male and female twins. RESULTS: The minor A allele of rs9939609 was associated with an increased BMI (P=0.0007). Each additional copy of the A allele was associated with a mean BMI increase of approximately 1.04 kg/m(2) (approximately 3.71 kg). Using variance components decomposition, we estimate that this single-nucleotide polymorphism accounts for approximately 3% of the genetic variance in BMI in our sample (approximately 2% of the total variance). By comparing intrapair variances of monozygotic twins of different genotypes we were able to perform a direct test of gene by environment (G x E) interaction in both sexes and gene by parity (G x P) interaction in women, but no evidence was found for either. CONCLUSIONS: In addition to supporting earlier findings that the rs9939609 variant in the FTO gene is associated with an increased BMI, our results indicate that the associated genetic effect does not interact with environment or parity.

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.

Quantitative Trait Loci for CD4:CD8 Lymphocyte Ratio Are Associated with Risk of Type 1 Diabetes and HIV-1 Immune Control

Abnormal expansion or depletion of particular lymphocyte subsets is associated with clinical manifestations such as HIV progression to AIDS and autoimmune disease. We sought to identify genetic predictors of lymphocyte levels and reasoned that these may play a role in immune-related diseases. We tested 2.3 million variants for association with five lymphocyte subsets, measured in 2538 individuals from the general population, including CD4+ T cells, CD8+ T cells, CD56+ natural killer (NK) cells, and the derived measure CD4:CD8 ratio. We identified two regions of strong association. The first was located in the major histocompatibility complex (MHC), with multiple SNPs strongly associated with CD4:CD8 ratio (rs2524054, p = 2.1 × 10−28). The second region was centered within a cluster of genes from the Schlafen family and was associated with NK cell levels (rs1838149, p = 6.1 × 10−14). The MHC association with CD4:CD8 replicated convincingly (p = 1.4 × 10−9) in an independent panel of 988 individuals. Conditional analyses indicate that there are two major independent quantitative trait loci (QTL) in the MHC region that regulate CD4:CD8 ratio: one is located in the class I cluster and influences CD8 levels, whereas the second is located in the class II cluster and regulates CD4 levels. Jointly, both QTL explained 8% of the variance in CD4:CD8 ratio. The class I variants are also strongly associated with durable host control of HIV, and class II variants are associated with type-1 diabetes, suggesting that genetic variation at the MHC may predispose one to immune-related diseases partly through disregulation of T cell homeostasis.

QTL for nodal root angle in sorghum (Sorghum bicolor L. Moench) co-locate with QTL for traits associated with drought adaptation.

Nodal root angle in sorghum influences vertical and horizontal root distribution in the soil profile and is thus relevant to drought adaptation. In this study, we report for the first time on the mapping of four QTL for nodal root angle (qRA) in sorghum, in addition to three QTL for root dry weight, two for shoot dry weight, and three for plant leaf area. Phenotyping was done at the six leaf stage for a mapping population (n = 141) developed by crossing two inbred sorghum lines with contrasting root angle. Nodal root angle QTL explained 58.2% of the phenotypic variance and were validated across a range of diverse inbred lines. Three of the four nodal root angle QTL showed homology to previously identified root angle QTL in rice and maize, whereas all four QTL co-located with previously identified QTL for stay-green in sorghum. A putative association between nodal root angle QTL and grain yield was identified through single marker analysis on field testing data from a subset of the mapping population grown in hybrid combination with three different tester lines. Furthermore, a putative association between nodal root angle QTL and stay-green was identified using data sets from selected sorghum nested association mapping populations segregating for root angle. The identification of nodal root angle QTL presents new opportunities for improving drought adaptation mechanisms via molecular breeding to manipulate a trait for which selection has previously been very difficult.

Finding genes for economically important traits: Brahman cattle puberty.

Age at puberty is an important component of reproductive performance in beef cattle production systems. Brahman cattle are typically late-pubertal relative to Bos taurus cattle and so it is of economic relevance to select for early age at puberty. To assist selection and elucidate the genes underlying puberty, we performed a genome-wide association study (GWAS) using the BovineSNP50 chip (similar to 54 000 polymorphisms) in Brahman bulls (n = 1105) and heifers (n = 843) and where the heifers were previously analysed in a different study. In a new attempt to generate unbiased estimates of single-nucleotide polymorphism (SNP) effects and proportion of variance explained by each SNP, the available data were halved on the basis of year and month of birth into a calibration and validation set. The traits that defined age at puberty were, in heifers, the age at which the first corpus luteum was detected (AGECL, h(2) = 0.56 +/- 0.11) and in bulls, the age at a scrotal circumference of 26 cm (AGE26, h(2) = 0.78 +/- 0.10). At puberty, heifers were on average older (751 +/- 142 days) than bulls (555 +/- 101 days), but AGECL and AGE26 were genetically correlated (r = 0.20 +/- 0.10). There were 134 SNPs associated with AGECL and 146 SNPs associated with AGE26 (P < 0.0001). From these SNPs, 32 (similar to 22%) were associated (P < 0.0001) with both traits. These top 32 SNPs were all located on Chromosome BTA 14, between 21.95 Mb and 28.4 Mb. These results suggest that the genes located in that region of BTA 14 play a role in pubertal development in Brahman cattle. There are many annotated genes underlying this region of BTA 14 and these are the subject of current research. Further, we identified a region on Chromosome X where markers were associated (P < 1.00E-8) with AGE26, but not with AGECL. Information about specific genes and markers add value to our understanding of puberty and potentially contribute to genomic selection. Therefore, identifying these genes contributing to genetic variation in AGECL and AGE26 can assist with the selection for early onset of puberty.