Inference of the genetic architecture underlying BMI and height with the use of 20,240 sibling pairs

Evidence that complex traits are highly polygenic has been presented by population-based genome-wide association studies (GWASs) through the identification of many significant variants, as well as by family-based de novo sequencing studies indicating that several traits have a large mutational target size. Here, using a third study design, we show results consistent with extreme polygenicity for body mass index (BMI) and height. On a sample of 20,240 siblings (from 9,570 nuclear families), we used a within-family method to obtain narrow-sense heritability estimates of 0.42 (SE = 0.17, p = 0.01) and 0.69 (SE = 0.14, p = 6 x 10(-)(7)) for BMI and height, respectively, after adjusting for covariates. The genomic inflation factors from locus-specific linkage analysis were 1.69 (SE = 0.21, p = 0.04) for BMI and 2.18 (SE = 0.21, p = 2 x 10(-10)) for height. This inflation is free of confounding and congruent with polygenicity, consistent with observations of ever-increasing genomic-inflation factors from GWASs with large sample sizes, implying that those signals are due to true genetic signals across the genome rather than population stratification. We also demonstrate that the distribution of the observed test statistics is consistent with both rare and common variants underlying a polygenic architecture and that previous reports of linkage signals in complex traits are probably a consequence of polygenic architecture rather than the segregation of variants with large effects. The convergent empirical evidence from GWASs, de novo studies, and within-family segregation implies that family-based sequencing studies for complex traits require very large sample sizes because the effects of causal variants are small on average.

No genetic support for a contribution of prostaglandins to the aetiology of androgenetic alopecia

MADAM, Androgenetic alopecia (AGA) is a common age-dependent trait, characterized by a progressive loss of hair from the scalp. The hair loss may commence during puberty and up to 80% of white men experience some degree of AGA during their lifetime.1 Research has established that two essential aetiological factors for AGA are a genetic predisposition and the presence of androgens (male sex hormones).1,2 A recent meta-analysis of genome-wide association studies (GWAS) has increased the number of identified loci associated with this trait at the molecular level to a total of eight.3 However, despite these successes, a large fraction of the genetic contribution remains to be identified. One way to identify further genetic loci is to combine the resource of GWAS datasets with knowledge about specific biological factors likely to be involved in the development of disease. The focused evaluation of a limited number of candidate genes in GWAS datasets avoids the necessity for extensive correction for multiple testing, which typically limits the power for detecting genetic loci at a genome-wide level.4 Because the presence of genetic association suggests that candidate genes are likely to operate early in the causative chain of events leading to the phenotype, this approach may also function to favour biological pathways for their importance in the development of AGA.

Pharmacogenetic Variation at CYP2D6, CYP2C9, and CYP2C19: Population Genetic and Forensic Aspects

Pharmacogenetics deals with genetically determined variation in drug response. In this context, three phase I drug-metabolizing enzymes, CYP2D6, CYP2C9, and CYP2C19, have a central role, affecting the metabolism of about 20-30% of clinically used drugs. Since genes coding for these enzymes in human populations exhibit high genetic polymorphism, they are of major pharmacogenetic importance. The aims of this study were to develop new genotyping methods for CYP2D6, CYP2C9, and CYP2C19 that would cover the most important genetic variants altering the enzyme activity, and, for the first time, to describe the distribution of genetic variation at these loci on global and microgeographic scales. In addition, pharmacogenetics was applied to a postmortem forensic setting to elucidate the role of genetic variation in drug intoxications, focusing mainly on cases related to tricyclic antidepressants, which are commonly involved in fatal drug poisonings in Finland. Genetic variability data were obtained by genotyping new population samples by the methods developed based on PCR and multiplex single-nucleotide primer extension reaction, as well as by collecting data from the literature. Data consisted of 138, 129, and 146 population samples for CYP2D6, CYP2C9, and CYP2C19, respectively. In addition, over 200 postmortem forensic cases were examined with respect to drug and metabolite concentrations and genotypic variation at CYP2D6 and CYP2C19. The distribution of genetic variation within and among human populations was analyzed by descriptive statistics and variance analysis and by correlating the genetic and geographic distances using Mantel tests and spatial autocorrelation. The correlation between phenotypic and genotypic variation in drug metabolism observed in postmortem cases was also analyzed statistically. The genotyping methods developed proved to be informative, technically feasible, and cost-effective. Detailed molecular analysis of CYP2D6 genetic variation in a global survey of human populations revealed that the pattern of variation was similar to those of neutral genomic markers. Most of the CYP2D6 diversity was observed within populations, and the spatial pattern of variation was best described as clinal. On the other hand, genetic variants of CYP2D6, CYP2C9, and CYP2C19 associated with altered enzymatic activity could reach extremely high frequencies in certain geographic regions. Pharmacogenetic variation may also be significantly affected by population-specific demographic histories, as seen within the Finnish population. When pharmacogenetics was applied to a postmortem forensic setting, a correlation between amitriptyline metabolic ratios and genetic variation at CYP2D6 and CYP2C19 was observed in the sample material, even in the presence of confounding factors typical for these cases. In addition, a case of doxepin-related fatal poisoning was shown to be associated with a genetic defect at CYP2D6. Each of the genes studied showed a distinct variation pattern in human populations and high frequencies of altered activity variants, which may reflect the neutral evolution and/or selective pressures caused by dietary or environmental exposure. The results are relevant also from the clinical point of view since the genetic variation at CYP2D6, CYP2C9, and CYP2C19 already has a range of clinical applications, e.g. in cancer treatment and oral anticoagulation therapy. This study revealed that pharmacogenetics may also contribute valuable information to the medicolegal investigation of sudden, unexpected deaths.

Genome-wide meta-analysis of common variant differences between men and women

The male-to-female sex ratio at birth is constant across world populations with an average of 1.06 (106 male to 100 female live births) for populations of European descent. The sex ratio is considered to be affected by numerous biological and environmental factors and to have a heritable component. The aim of this study was to investigate the presence of common allele modest effects at autosomal and chromosome X variants that could explain the observed sex ratio at birth. We conducted a large-scale genome-wide association scan (GWAS) meta-analysis across 51 studies, comprising overall 114 863 individuals (61 094 women and 53 769 men) of European ancestry and 2 623 828 common (minor allele frequency >0.05) single-nucleotide polymorphisms (SNPs). Allele frequencies were compared between men and women for directly-typed and imputed variants within each study. Forward-time simulations for unlinked, neutral, autosomal, common loci were performed under the demographic model for European populations with a fixed sex ratio and a random mating scheme to assess the probability of detecting significant allele frequency differences. We do not detect any genome-wide significant (P < 5 x 10(-8)) common SNP differences between men and women in this well-powered meta-analysis. The simulated data provided results entirely consistent with these findings. This large-scale investigation across ~115 000 individuals shows no detectable contribution from common genetic variants to the observed skew in the sex ratio. The absence of sex-specific differences is useful in guiding genetic association study design, for example when using mixed controls for sex-biased traits.

FTO genotype is associated with phenotypic variability of body mass index

There is evidence across several species for genetic control of phenotypic variation of complex traits1, 2, 3, 4, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ~170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)5, 6, 7, is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ~0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation9, 10. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.

Identification of two novel human neuronal ceroid lipofuscinosis genes

The neuronal ceroid lipofuscinoses (NCLs) are a group of mostly autosomal recessively inherited neurodegenerative disorders. The aim of this thesis was to characterize the molecular genetic bases of these, previously genetically undetermined, NCL forms. Congenital NCL is the most aggressive form of NCLs. Previously, a mutation in the cathepsin D (CTSD) gene was shown to cause congenital NCL in sheep. Based on the close resemblance of the phenotypes between congenital NCLs in sheep and human, CTSD was considered as a potential candidate gene in humans as well. When screened for mutations by sequencing, a homozygous nucleotide duplication creating a premature stop codon was identified in CTSD in one family with congenital NCL. While in vitro the overexpressed truncated mutant protein was stable although inactive, the absence of CTSD staining in brain tissue samples of patients indicated degradation of the mutant CTSD in vivo. A lack of CTSD staining was detected also in another, unrelated family with congenital NCL. These results imply that CTSD deficiency underlies congenital NCL. While initially Turkish vLINCL was considered a distinct genetic entity (CLN7), mutations in the CLN8 gene were later reported to account for the disease in a subset of Turkish patients with vLINCL. To further dissect the genetic basis of the disease, all known NCL genes were screened for homozygosity by haplotype analysis of microsatellite markers and/or sequenced in 13 mainly consanguineous, Turkish vLINCL families. Two novel, family-specific homozygous mutations were identified in the CLN6 gene. In the remaining families, all known NCL loci were excluded. To identify novel gene(s) underlying vLINCL, a genomewide single nucleotide polymorphism scan, homozygosity mapping, and positional candidate gene sequencing were performed in ten of these families. On chromosome 4q28.1-q28.2, a novel major facilitator superfamily domain containing 8 (MFSD8) gene with six family-specific homozygous mutations in vLINCL patients was identified. MFSD8 transcript was shown to be ubiquitously expressed with a complex pattern of alternative splicing. Our results suggest that MFSD8 is a novel lysosomal integral membrane protein which, as a member of the major facilitator superfamily, is predicted to function as a transporter. Identification of MFSD8 emphasizes the genetic heterogeneity of Turkish vLINCL. In families where no MFSD8 mutations were detected, additional NCL-causing genes remain to be identified. The identification of CTSD and MFSD8 increases the number of known human NCL-causing genes to eight, and is an important step towards the complete understanding of the genetic spectrum underlying NCLs. In addition, it is a starting point for dissecting the molecular mechanisms behind the associated NCLs and contributes to the challenging task of understanding the molecular pathology underlying the group of NCL disorders.

The application of DArTseq technology to pineapple

DArTseq technology is potentially the most appropriate system to discover hundreds of polymorphic genomic loci, scoring thousands of unique genomic-wide DNA fragments in one single experiment, without requiring existing DNA sequence information. The DArT complexity reduction approach in combination with Illumina short read sequencing (Hiseq2000) was applied. To test the application of DArTseq technology in pineapple, a reference population of 13 Ananas genotypes from primitive wild accessions to modern cultivars was used. In a comparison of 3 systems, the combination of restriction enzymes PstI and MseI performed the best producing 18,900 DArT markers and close to 20,000 SNPs. Based on these markers genetic relationships between the samples were identified and a dendrogram was generated. The topography of the tree corresponds with our understanding of the genetic relationships between the genotypes. Importantly, the replicated samples of all genotypes have a dissimilarity of close to 0.0 and occupy the same positions on the tree, confirming high reproducibility of the markers detected. Eventually it is planned that molecular markers will be identified that are associated with resistance to Phytophthora cinnamomi (Pc), the most economically important pathogen of pineapple in Australia, as genetic resistance is known to exist within the Ananas. Marker assisted selection can then be utilized in a pineapple breeding program to develop cultivars resistant to Pc.

ACIAR Improving Postrainy Sorghum Varieties Grain and Fodder in India

Sorghum grown in India in the post-rainy season (Rabi) relies on residual soil moisture, and the crop is commonly exposed to terminal drought stress. But there is a ready market for its high-quality grain and stover (used as fodder on dairy farms). Steps to improve productivity while maintaining quality offer an attractive opportunity for sorghum farmers to improve their incomes. Genetically improving the efficiency of using stored soil moisture is a prime target to maximise grain/stover production and quality of Rabi sorghum. This project aims to achieve this through the application of DNA sequences known as quantitative trait loci (QTLs). The project scientists will introduce marker-assisted introgression of stay-green QTLs into sorghum lines, enhancing both the quality and the quantity of grain/stover of postrainy sorghum. They will also use modelling to identify the key physiological traits involved in a higher, more stable yield across water-limited environments of India and Australia, and the key stay-green QTLs contributing to these traits. The publicly available QTL isolines lines developed in this project will be the basis of new varieties to be bred in a subsequent phase.

Development of pedigree mapping for wheat

The aim of this project is to build on the work done so far in applying pedigree mapping principals to northern adapted wheat pedigreed to identify robust QTL for quality traits.

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.

Genomic inflation factors under polygenic inheritance

Population structure, including population stratification and cryptic relatedness, can cause spurious associations in genome-wide association studies (GWAS). Usually, the scaled median or mean test statistic for association calculated from multiple single-nucleotide-polymorphisms across the genome is used to assess such effects, and 'genomic control' can be applied subsequently to adjust test statistics at individual loci by a genomic inflation factor. Published GWAS have clearly shown that there are many loci underlying genetic variation for a wide range of complex diseases and traits, implying that a substantial proportion of the genome should show inflation of the test statistic. Here, we show by theory, simulation and analysis of data that in the absence of population structure and other technical artefacts, but in the presence of polygenic inheritance, substantial genomic inflation is expected. Its magnitude depends on sample size, heritability, linkage disequilibrium structure and the number of causal variants. Our predictions are consistent with empirical observations on height in independent samples of ~4000 and ~133,000 individuals.

Association mapping

Association mapping seeks to identify marker alleles present at significantly different frequencies in cases carrying a particular disease or trait compared with controls. Genome-wide association studies are increasingly replacing candidate gene-based association studies for complex diseases, where a number of loci are likely to contribute to disease risk and the effect size of each particular risk allele is typically modest or low. Good study design is essential to the success of an association study, and factors such as the heritability of the disease under investigation, the choice of controls, statistical power, multiple testing and whether the association can be replicated need to be considered before beginning. Likewise, thorough quality control of the genotype data needs to be undertaken prior to running any association analyses. Finally, it should be kept in mind that a significant genetic association is not proof positive that a particular genetic locus causes a disease, but rather an important first step in discovering the genetic variants underlying a complex disease.

Genome-wide association study identifies a locus at 7p15.2 associated with endometriosis

Endometriosis is a common gynecological disease associated with pelvic pain and subfertility. We conducted a genome-wide association study (GWAS) in 3,194 individuals with surgically confirmed endometriosis (cases) and 7,060 controls from Australia and the UK. Polygenic predictive modeling showed significantly increased genetic loading among 1,364 cases with moderate to severe endometriosis. The strongest association signal was on 7p15.2 (rs12700667) for 'all' endometriosis (P = 2.6 x 10(-)(7), odds ratio (OR) = 1.22, 95% CI 1.13-1.32) and for moderate to severe disease (P = 1.5 x 10(-)(9), OR = 1.38, 95% CI 1.24-1.53). We replicated rs12700667 in an independent cohort from the United States of 2,392 self-reported, surgically confirmed endometriosis cases and 2,271 controls (P = 1.2 x 10(-)(3), OR = 1.17, 95% CI 1.06-1.28), resulting in a genome-wide significant P value of 1.4 x 10(-)(9) (OR = 1.20, 95% CI 1.13-1.27) for 'all' endometriosis in our combined datasets of 5,586 cases and 9,331 controls. rs12700667 is located in an intergenic region upstream of the plausible candidate genes NFE2L3 and HOXA10.

Genome-wide association study identifies a new melanoma susceptibility locus at 1q21.3

We performed a genome-wide association study of melanoma in a discovery cohort of 2,168 Australian individuals with melanoma and 4,387 control individuals. In this discovery phase, we confirm several previously characterized melanoma-associated loci at MC1R, ASIP and MTAP-CDKN2A. We selected variants at nine loci for replication in three independent case-control studies (Europe: 2,804 subjects with melanoma, 7,618 control subjects; United States 1: 1,804 subjects with melanoma, 1,026 control subjects; United States 2: 585 subjects with melanoma, 6,500 control subjects). The combined meta-analysis of all case-control studies identified a new susceptibility locus at 1q21.3 (rs7412746, P = 9.0 x 10(-11), OR in combined replication cohorts of 0.89 (95% CI 0.85-0.95)). We also show evidence suggesting that melanoma associates with 1q42.12 (rs3219090, P = 9.3 x 10(-8)). The associated variants at the 1q21.3 locus span a region with ten genes, and plausible candidate genes for melanoma susceptibility include ARNT and SETDB1. Variants at the 1q21.3 locus do not seem to be associated with human pigmentation or measures of nevus density.

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).