Loci affecting gamma-glutamyl transferase in adults and adolescents show age x SNP interaction and cardiometabolic disease associations

Serum gamma-glutamyl transferase (GGT) activity is a marker of liver disease which is also prospectively associated with the risk of all-cause mortality, cardiovascular disease, type 2 diabetes and cancers. We have discovered novel loci affecting GGT in a genome-wide association study (rs1497406 in an intergenic region of chromosome 1, P = 3.9 x 10(-8); rs944002 in C14orf73 on chromosome 14, P = 4.7 x 10(-13); rs340005 in RORA on chromosome 15, P = 2.4 x 10(-8)), and a highly significant heterogeneity between adult and adolescent results at the GGT1 locus on chromosome 22 (maximum P(HET) = 5.6 x 10(-12) at rs6519520). Pathway analysis of significant and suggestive single-nucleotide polymorphism associations showed significant overlap between genes affecting GGT and those affecting common metabolic and inflammatory diseases, and identified the hepatic nuclear factor (HNF) family as controllers of a network of genes affecting GGT. Our results reinforce the disease associations of GGT and demonstrate that control by the GGT1 locus varies with age.

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.

GWAS of butyrylcholinesterase activity identifies four novel loci, independent effects within BCHE and secondary associations with metabolic risk factors

Serum butyrylcholinesterase (BCHE) activity is associated with obesity, blood pressure and biomarkers of cardiovascular and diabetes risk. We have conducted a genome-wide association scan to discover genetic variants affecting BCHE activity, and to clarify whether the associations between BCHE activity and cardiometabolic risk factors are caused by variation in BCHE or whether BCHE variation is secondary to the metabolic abnormalities. We measured serum BCHE in adolescents and adults from three cohorts of Australian twin and family studies. The genotypes from approximately 2.4 million single-nucleotide polymorphisms (SNPs) were available in 8791 participants with BCHE measurements. We detected significant associations with BCHE activity at three independent groups of SNPs at the BCHE locus (P = 5.8 x 10(-262), 7.8 x 10(-47), 2.9 x 10(-12)) and at four other loci: RNPEP (P = 9.4 x 10(-16)), RAPH1-ABI2 (P = 4.1 x 10(-18)), UGT1A1 (P = 4.0 x 10(-8)) and an intergenic region on chromosome 8 (P = 1.4 x 10(-8)). These loci affecting BCHE activity were not associated with metabolic risk factors. On the other hand, SNPs in genes previously associated with metabolic risk had effects on BCHE activity more often than can be explained by chance. In particular, SNPs within FTO and GCKR were associated with BCHE activity, but their effects were partly mediated by body mass index and triglycerides, respectively. We conclude that variation in BCHE activity is due to multiple variants across the spectrum from uncommon/large effect to common/small effect, and partly results from (rather than causes) metabolic abnormalities.

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.

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

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.

Meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations

Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2x10(-201)), ABCG2 (p = 3.1x10(-26)), SLC17A1 (p = 3.0x10(-14)), SLC22A11 (p = 6.7x10(-14)), SLC22A12 (p = 2.0x10(-9)), SLC16A9 (p = 1.1x10(-8)), GCKR (p = 1.4x10(-9)), LRRC16A (p = 8.5x10(-9)), and near PDZK1 (p = 2.7x10(-9)). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0x10(-26)) and propionyl-L-carnitine (p = 5.0x10(-8)) concentrations, which in turn were associated with serum UA levels (p = 1.4x10(-57) and p = 8.1x10(-54), respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels.

Susceptibility locus on chromosome 1q23-25 for a schizophrenia subtype resembling deficit schizophrenia identified by latent class analysis

Context: Identifying susceptibility genes for schizophrenia may be complicated by phenotypic heterogeneity, with some evidence suggesting that phenotypic heterogeneity reflects genetic heterogeneity. Objective: To evaluate the heritability and conduct genetic linkage analyses of empirically derived, clinically homogeneous schizophrenia subtypes. Design: Latent class and linkage analysis. Setting: Taiwanese field research centers. Participants: The latent class analysis included 1236 Han Chinese individuals with DSM-IV schizophrenia. These individuals were members of a large affected-sibling-pair sample of schizophrenia (606 ascertained families), original linkage analyses of which detected a maximum logarithm of odds (LOD) of 1.8 (z = 2.88) on chromosome 10q22.3. Main Outcome Measures: Multipoint exponential LOD scores by latent class assignment and parametric heterogeneity LOD scores. Results: Latent class analyses identified 4 classes, with 2 demonstrating familial aggregation. The first (LC2) described a group with severe negative symptoms, disorganization, and pronounced functional impairment, resembling “deficit schizophrenia.” The second (LC3) described a group with minimal functional impairment, mild or absent negative symptoms, and low disorganization. Using the negative/deficit subtype, we detected genome-wide significant linkage to 1q23-25 (LOD = 3.78, empiric genome-wide P = .01). This region was not detected using the DSM-IV schizophrenia diagnosis, but has been strongly implicated in schizophrenia pathogenesis by previous linkage and association studies.Variants in the 1q region may specifically increase risk for a negative/deficit schizophrenia subtype. Alternatively, these results may reflect increased familiality/heritability of the negative class, the presence of multiple 1q schizophrenia risk genes, or a pleiotropic 1q risk locus or loci, with stronger genotype-phenotype correlation with negative/deficit symptoms. Using the second familial latent class, we identified nominally significant linkage to the original 10q peak region. Conclusion: Genetic analyses of heritable, homogeneous phenotypes may improve the power of linkage and association studies of schizophrenia and thus have relevance to the design and analysis of genome-wide association studies.

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.

Common variants in TMPRSS6 are associated with iron status and erythrocyte volume

We report a genome-wide association study to iron status. We identify an association of SNPs in TPMRSS6 to serum iron (rs855791, combined P = 1.5 x 10(-20)), transferrin saturation (combined P = 2.2 x 10(-23)) and erythrocyte mean cell volume (MCV, combined P = 1.1 x 10(-10)). We also find suggestive evidence of association with blood hemoglobin levels (combined P = 5.3 x 10(-7)). These findings demonstrate the involvement of TMPRSS6 in control of iron homeostasis and in normal erythropoiesis.

Susceptibility variants for male-pattern baldness on chromosome 20p11

We carried out a genome-wide association study in 296 individuals with male-pattern baldness (androgenetic alopecia) and 347 controls. We then investigated the 30 best SNPs in an independent replication sample and found highly significant association for five SNPs on chromosome 20p11 (rs2180439 combined P = 2.7 x 10(-15)). No interaction was detected with the X-chromosomal androgen receptor locus, suggesting that the 20p11 locus has a role in a yet-to-be-identified androgen-independent pathway.

Identification of the semaphorin receptor PLXNA2 as a candidate for susceptibility to schizophrenia

The discovery of genetic factors that contribute to schizophrenia susceptibility is a key challenge in understanding the etiology of this disease. Here, we report the identification of a novel schizophrenia candidate gene on chromosome 1q32, plexin A2 (PLXNA2), in a genome-wide association study using 320 patients with schizophrenia of European descent and 325 matched controls. Over 25,000 single-nucleotide polymorphisms (SNPs) located within approximately 14,000 genes were tested. Out of 62 markers found to be associated with disease status, the most consistent finding was observed for a candidate locus on chromosome 1q32. The marker SNP rs752016 showed suggestive association with schizophrenia (odds ratio (OR) = 1.49, P = 0.006). This result was confirmed in an independent case-control sample of European Americans (combined OR = 1.38, P = 0.035) and similar genetic effects were observed in smaller subsets of Latin Americans (OR = 1.26) and Asian Americans (OR = 1.37). Supporting evidence was also obtained from two family-based collections, one of which reached statistical significance (OR = 2.2, P = 0.02). High-density SNP mapping showed that the region of association spans approximately 60 kb of the PLXNA2 gene. Eight out of 14 SNPs genotyped showed statistically significant differences between cases and controls. These results are in accordance with previous genetic findings that identified chromosome 1q32 as a candidate region for schizophrenia. PLXNA2 is a member of the transmembrane semaphorin receptor family that is involved in axonal guidance during development and may modulate neuronal plasticity and regeneration. The PLXNA2 ligand semaphorin 3A has been shown to be upregulated in the cerebellum of individuals with schizophrenia. These observations, together with the genetic results, make PLXNA2 a likely candidate for the 1q32 schizophrenia susceptibility locus.

Next-generation sequencing: A frameshift in skeletal dysplasia gene discovery

In the last decade, huge breakthroughs in genetics - driven by new technology and different statistical approaches - have resulted in a plethora of new disease genes identified for both common and rare diseases. Massive parallel sequencing, commonly known as next-generation sequencing, is the latest advance in genetics, and has already facilitated the discovery of the molecular cause of many monogenic disorders. This article describes this new technology and reviews how this approach has been used successfully in patients with skeletal dysplasias. Moreover, this article illustrates how the study of rare diseases can inform understanding and therapeutic developments for common diseases such as osteoporosis. © International Osteoporosis Foundation and National Osteoporosis Foundation 2013.

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.

Heritability and genome-wide linkage analysis of migraine in the genetic isolate of Norfolk Island

Migraine is a common neurovascular disorder with a complex envirogenomic aetiology. In an effort to identify migraine susceptibility genes, we conducted a study of the isolated population of Norfolk Island, Australia. A large portion of the permanent inhabitants of Norfolk Island are descended from 18th Century English sailors involved in the infamous mutiny on the Bounty and their Polynesian consorts. In total, 600 subjects were recruited including a large pedigree of 377 individuals with lineage to the founders. All individuals were phenotyped for migraine using International Classification of Headache Disorders-II criterion. All subjects were genotyped for a genome-wide panel of microsatellite markers. Genotype and phenotype data for the pedigree were analysed using heritability and linkage methods implemented in the programme SOLAR. Follow-up association analysis was performed using the CLUMP programme. A total of 154 migraine cases (25%) were identified indicating the Norfolk Island population is high-risk for migraine. Heritability estimation of the 377-member pedigree indicated a significant genetic component for migraine (h2 = 0.53, P = 0.016). Linkage analysis showed peaks on chromosome 13q33.1 (P = 0.003) and chromosome 9q22.32 (P = 0.008). Association analysis of the key microsatellites in the remaining 223 unrelated Norfolk Island individuals showed evidence of association, which strengthen support for the linkage findings (P ≤ 0.05). In conclusion, a genome-wide linkage analysis and follow-up association analysis of migraine in the genetic isolate of Norfolk Island provided evidence for migraine susceptibility loci on chromosomes 9q22.22 and 13q33.1.