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

Isolated GH deficiency: mutation screening and copy number analysis of HMGA2 and CDK6 genes

OBJECTIVE

In most patients, the genetic cause of isolated GH deficiency (IGHD) is unknown. By identifying several genes associated with height variability within the normal population, three separate genome-wide association studies provided new candidate genes for human growth disorders. We selected two of them for genetic screening of our IGHD population.

AIM

We aimed to determine whether high-mobility group A2 (HMGA2) and cyclin-dependent protein kinase 6 (CDK6) are involved in the pathogenicity of IGHD.

METHODS

We directly sequenced coding regions and exon-intron boundaries of the genes HMGA2 and CDK6 in 105 Caucasian IGHD patients from the Dutch HYPOPIT study. In addition, we developed a new probe set of multiplex ligation-dependent probe amplification for both genes in order to detect copy number variations.

RESULTS

In one patient with classical IGHD phenotype, we identified a new heterozygous 20 bp deletion in the intronic region of HMGA2 (c.250-29_-9del), which was absent in the databases and healthy controls. Together, with recently published data concerning the 12q14 microdeletion syndrome, where patients with an HMGA2 haploinsufficiency had proportionate short stature, this study provides further support of the important role for HMGA2 in growth. In CDK6, we found only known polymorphisms.

CONCLUSIONS

This study provides the first report of a deletion in the HMGA2 gene that might be related to IGHD. We suggest that this gene is investigated as a second screening in patients with a classical IGHD phenotype in which mutations in classical candidate genes have been excluded.

Effect of five genetic variants associated with lung function on the risk of chronic obstructive lung disease, and their joint effects on lung function

RATIONALE

Genomic loci are associated with FEV1 or the ratio of FEV1 to FVC in population samples, but their association with chronic obstructive pulmonary disease (COPD) has not yet been proven, nor have their combined effects on lung function and COPD been studied.

OBJECTIVES

To test association with COPD of variants at five loci (TNS1, GSTCD, HTR4, AGER, and THSD4) and to evaluate joint effects on lung function and COPD of these single-nucleotide polymorphisms (SNPs), and variants at the previously reported locus near HHIP.

METHODS

By sampling from 12 population-based studies (n = 31,422), we obtained genotype data on 3,284 COPD case subjects and 17,538 control subjects for sentinel SNPs in TNS1, GSTCD, HTR4, AGER, and THSD4. In 24,648 individuals (including 2,890 COPD case subjects and 13,862 control subjects), we additionally obtained genotypes for rs12504628 near HHIP. Each allele associated with lung function decline at these six SNPs contributed to a risk score. We studied the association of the risk score to lung function and COPD.

MEASUREMENTS AND MAIN RESULTS

Association with COPD was significant for three loci (TNS1, GSTCD, and HTR4) and the previously reported HHIP locus, and suggestive and directionally consistent for AGER and TSHD4. Compared with the baseline group (7 risk alleles), carrying 10-12 risk alleles was associated with a reduction in FEV1 (β = -72.21 ml, P = 3.90 × 10(-4)) and FEV1/FVC (β = -1.53%, P = 6.35 × 10(-6)), and with COPD (odds ratio = 1.63, P = 1.46 × 10(-5)).

CONCLUSIONS

Variants in TNS1, GSTCD, and HTR4 are associated with COPD. Our highest risk score category was associated with a 1.6-fold higher COPD risk than the population average score.

Thoughts on the nature of identity: disorders of sex development and gender identity

Children with disorders of sex development have similarities to, but also marked contrasts with, children with normal anatomy but who have gender dysphoria. Understanding gender identity development in children with sex disorders will probably help us understand typical gender identity development more than in understanding gender development in children with gender identity disorder.

Identification, replication, and fine-mapping of Loci associated with adult height in individuals of african ancestry

Adult height is a classic polygenic trait of high heritability (h(2) approximately 0.8). More than 180 single nucleotide polymorphisms (SNPs), identified mostly in populations of European descent, are associated with height. These variants convey modest effects and explain approximately10% of the variance in height. Discovery efforts in other populations, while limited, have revealed loci for height not previously implicated in individuals of European ancestry. Here, we performed a meta-analysis of genome-wide association (GWA) results for adult height in 20,427 individuals of African ancestry with replication in up to 16,436 African Americans. We found two novel height loci (Xp22-rs12393627, P = 3.4×10(-12) and 2p14-rs4315565, P = 1.2×10(-8)). As a group, height associations discovered in European-ancestry samples replicate in individuals of African ancestry (P = 1.7×10(-4) for overall replication). Fine-mapping of the European height loci in African-ancestry individuals showed an enrichment of SNPs that are associated with expression of nearby genes when compared to the index European height SNPs (P<0.01). Our results highlight the utility of genetic studies in non-European populations to understand the etiology of complex human diseases and traits.

Pharmacogenomics and epilepsy: the road ahead

Epilepsy is one of the most common, serious neurological disorders, affecting an estimated 50 million people worldwide. The condition is typically treated using antiepileptic drugs of which there are 16 in widespread use. However, there are many different syndrome and seizure types within epilepsy and information guiding clinicians on the most effective drug and dose for individual patients is lacking. Further, all of the antiepileptic drugs have associated adverse reactions, some of which are severe and life-threatening. Here, we review the pharmacogenomic work to date in the context of these issues and comment on key aspects of study design that are required to speed up the identification of clinically relevant genetic factors.

A genome-wide meta-analysis of six type 1 diabetes cohorts identifies multiple associated loci

Diabetes impacts approximately 200 million people worldwide, of whom approximately 10% are affected by type 1 diabetes (T1D). The application of genome-wide association studies (GWAS) has robustly revealed dozens of genetic contributors to the pathogenesis of T1D, with the most recent meta-analysis identifying in excess of 40 loci. To identify additional genetic loci for T1D susceptibility, we examined associations in the largest meta-analysis to date between the disease and ∼2.54 million SNPs in a combined cohort of 9,934 cases and 16,956 controls. Targeted follow-up of 53 SNPs in 1,120 affected trios uncovered three new loci associated with T1D that reached genome-wide significance. The most significantly associated SNP (rs539514, P = 5.66×10⁻¹¹) resides in an intronic region of the LMO7 (LIM domain only 7) gene on 13q22. The second most significantly associated SNP (rs478222, P = 3.50×10⁻⁹) resides in an intronic region of the EFR3B (protein EFR3 homolog B) gene on 2p23; however, the region of linkage disequilibrium is approximately 800 kb and harbors additional multiple genes, including NCOA1, C2orf79, CENPO, ADCY3, DNAJC27, POMC, and DNMT3A. The third most significantly associated SNP (rs924043, P = 8.06×10⁻⁹) lies in an intergenic region on 6q27, where the region of association is approximately 900 kb and harbors multiple genes including WDR27, C6orf120, PHF10, TCTE3, C6orf208, LOC154449, DLL1, FAM120B, PSMB1, TBP, and PCD2. These latest associated regions add to the growing repertoire of gene networks predisposing to T1D.

Despite the fact that there is clearly a large genetic component to type 1 diabetes (T1D), uncovering the genes contributing to this disease has proven challenging. However, in the past three years there has been relatively major progress in this regard, with advances in genetic screening technologies allowing investigators to scan the genome for variants conferring risk for disease without prior hypotheses. Such genome-wide association studies have revealed multiple regions of the genome to be robustly and consistently associated with T1D. More recent findings have been a consequence of combining of multiple datasets from independent investigators in meta-analyses, which have more power to pick up additional variants contributing to the trait. In the current study, we describe the largest meta-analysis of T1D genome-wide genotyped datasets to date, which combines six large studies. As a consequence, we have uncovered three new signals residing at the chromosomal locations 13q22, 2p23, and 6q27, which went on to be replicated in independent sample sets. These latest associated regions add to the growing repertoire of gene networks predisposing to T1D.

Exome sequencing and subsequent association studies identify five amino acid-altering variants influencing human height

Height is a highly heritable trait that involves multiple genetic loci. To identify causal variants that influence stature, we sequenced whole exomes of four children with idiopathic short stature. Ninety-five nonsynonymous single-nucleotide polymorphisms (nsSNPs) were selected as potential candidate variants. We performed association analysis in 740 cohort individuals and identified 11 nsSNPs in 10 loci (DIS3L2, ZBTB38, FAM154A, PTCH1, TSSC4, KIF18A, GPR133, ACAN, FAM59A, and NINL) associated with adult height (P < 0.05), including five novel loci. Of these, two nsSNPs (TSSC4 and KIF18A loci) were significant at P < 0.05 in the replication study (n = 1,000) and five (ZBTB38, FAM154A, TSSC4, KIF18A, and FAM59A loci) were significant at P < 0.01 in the combined analysis (n = 1,740). Together, the five nsSNPs accounted for approximately 2.5% of the height variation. This study demonstrated the utility of next-generation sequencing in identifying genetic variants and loci associated with complex traits.

Genetic and environmental influences on growth from late childhood to adulthood: a longitudinal study of two Finnish twin cohorts

OBJECTIVES

Human growth is a complex process that remains insufficiently understood. We aimed to analyze genetic and environmental influences on growth from late childhood to early adulthood.

METHODS

Two cohorts of monozygotic and dizygotic (same sex and opposite sex) Finnish twin pairs were studied longitudinally using self-reported height at 11-12, 14, and 17 years and adult age (FinnTwin12) and at 16, 17, and 18 years and adult age (FinnTwin16). Univariate and multivariate variance component models for twin data were used.

RESULTS

From childhood to adulthood, genetic differences explained 72-81% of the variation of height in boys and 65-86% in girls. Environmental factors common to co-twins explained 5-23% of the variation of height, with the residual variation explained by environmental factors unique to each twin individual. Common environmental factors affecting height were highly correlated between the analyzed ages (0.72-0.99 and 0.91-1.00 for boys and girls, respectively). Genetic (0.58-0.99 and 0.70-0.99, respectively) and unique environmental factors (0.32-0.78 and 0.54-0.82, respectively) affecting height at different ages were more weakly, but still substantially, correlated.

CONCLUSIONS

The genetic contribution to height is strong during adolescence. The high genetic correlations detected across the ages encourage further efforts to identify genes affecting growth. Common and unique environmental factors affecting height during adolescence are also important, and further studies are necessary to identify their nature and test whether they interact with genetic factors.

Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function

Pulmonary function measures reflect respiratory health and are used in the diagnosis of chronic obstructive pulmonary disease. We tested genome-wide association with forced expiratory volume in 1 second and the ratio of forced expiratory volume in 1 second to forced vital capacity in 48,201 individuals of European ancestry with follow up of the top associations in up to an additional 46,411 individuals. We identified new regions showing association (combined P < 5 × 10(-8)) with pulmonary function in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (also known as EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1 and KCNE2. Identification of these 16 new loci may provide insight into the molecular mechanisms regulating pulmonary function and into molecular targets for future therapy to alleviate reduced lung function.

Intelligence

Individual differences in human intelligence are of interest to a wide range of psychologists and to many people outside the discipline. This overview of contributions to intelligence research covers the first decade of the twenty-first century. There is a survey of some of the major books that appeared since 2000, at different levels of expertise and from different points of view. Contributions to the phenotype of intelligence differences are discussed, as well as some contributions to causes and consequences of intelligence differences. The major causal issues covered concern the environment and genetics, and how intelligence differences are being mapped to brain differences. The major outcomes discussed are health, education, and socioeconomic status. Aging and intelligence are discussed, as are sex differences in intelligence and whether twins and singletons differ in intelligence. More generally, the degree to which intelligence has become a part of broader research in neuroscience, health, and social science is discussed.

Genome-wide association study identifies five new schizophrenia loci

We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded genome-wide significant associations with schizophrenia for seven loci, five of which are new (1p21.3, 2q32.3, 8p23.2, 8q21.3 and 10q24.32-q24.33) and two of which have been previously implicated (6p21.32-p22.1 and 18q21.2). The strongest new finding (P = 1.6 × 10(-11)) was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of neuronal development. Four other schizophrenia loci achieving genome-wide significance contain predicted targets of MIR137, suggesting MIR137-mediated dysregulation as a previously unknown etiologic mechanism in schizophrenia. In a joint analysis with a bipolar disorder sample (16,374 affected individuals and 14,044 controls), three loci reached genome-wide significance: CACNA1C (rs4765905, P = 7.0 × 10(-9)), ANK3 (rs10994359, P = 2.5 × 10(-8)) and the ITIH3-ITIH4 region (rs2239547, P = 7.8 × 10(-9)).

Experimental designs for robust detection of effects in genome-wide case-control studies

In genome-wide association studies hundreds of thousands of loci are scanned in thousands of cases and controls, with the goal of identifying genomic loci underpinning disease. This is a challenging statistical problem requiring strong evidence. Only a small proportion of the heritability of common diseases has so far been explained. This "dark matter of the genome" is a subject of much discussion. It is critical to have experimental design criteria that ensure that associations between genomic loci and phenotypes are robustly detected. To ensure associations are robustly detected we require good power (e.g., 0.8) and sufficiently strong evidence [i.e., a high Bayes factor (e.g., 10(6), meaning the data are 1 million times more likely if the association is real than if there is no association)] to overcome the low prior odds for any given marker in a genome scan to be associated with a causal locus. Power calculations are given for determining the sample sizes necessary to detect effects with the required power and Bayes factor for biallelic markers in linkage disequilibrium with causal loci in additive, dominant, and recessive genetic models. Significantly stronger evidence and larger sample sizes are required than indicated by traditional hypothesis tests and power calculations. Many reported putative effects are not robustly detected and many effects including some large moderately low-frequency effects may remain undetected. These results may explain the dark matter in the genome. The power calculations have been implemented in R and will be available in the R package ldDesign.

Defining the power limits of genome-wide association scan meta-analyses

Large-scale meta-analyses of genome-wide association scans (GWAS) have been successful in discovering common risk variants with modest and small effects. The detection of lower frequency signals will undoubtedly require concerted efforts of at least similar scale. We investigate the sample size-dictated power limits of GWAS meta-analyses, in the presence and absence of modest levels of heterogeneity and across a range of different allelic architectures. We find that data combination through large-scale collaboration is vital in the quest for complex trait susceptibility loci, but that effect size heterogeneity across meta-analyzed studies drawn from similar populations does not appear to have a profound effect on sample size requirements.

Human distal gut microbiome

The distal gut and its associated microbiota is a new frontier in the quest to understand human biology and evolution. The renaissance in this field has been partly driven by advances in sequencing technology and also by the application of a variety of 'omic' technologies in a systems biology framework. In the initial stages of understanding what constitutes the gut, culture-independent methods, primarily inventories of 16S rRNA genes, have provided a clear view of the main taxonomic groups of Bacteria in the distal gut and we are now moving towards defining the functions that reside in the distal gut microbiome. This review will explore recent advances in the area of the distal gut and the use of a variety of omic approaches to determine what constitutes this fascinating collection of microbes.

Lactase persistence and milk consumption are associated with body height in Swedish preadolescents and adolescents

BACKGROUND

Body height is a classic polygenic trait. About 80%-90% of height is inherited and 10%-20% owed to environmental factors, of which the most important ones are nutrition and diseases in preadolescents and adolescents.

OBJECTIVE

The aim of this study was to explore potential relations between the LCT (lactase) C>T-13910 polymorphism, milk consumption, and body height in a sample of Swedish preadolescents and adolescents.

DESIGN

In a cross-sectional study, using a random sample of preadolescents and adolescents (n = 597), dietary intakes were determined. Anthropometric measurements including sexual maturity (Tanner stage) and birth weight were assessed. Parental body height and socio-economic status (SES) were obtained by questionnaires. Genotyping for the LCT C>T-13910 polymorphism that renders individuals lactase persistent (LP) or lactase non-persistent (LNP) was performed by DNA sequencing. Stepwise backward multivariate linear regression was used.

RESULTS

Milk consumption was significantly and positively associated with body height (β = 0.45; 95% CI: 0.040, 0.87, p = 0.032). Adjustments were performed for sex, parental height, birth weight, body mass index (BMI), SES, and Tanner stage. This model explains 90% of the observed variance of body height (adjusted R(2) = 0.89). The presence of the -13910 T allele was positively associated with body height (β = 2.05; 95% CI: 0.18, 3.92, p = 0.032).

CONCLUSIONS

Milk consumption is positively associated with body height in preadolescents and adolescents. We show for the first time that a nutrigenetic variant might be able to explain in part phenotypic variation of body height in preadolescents and adolescents. Due to the small sample size further studies are needed.

Discovery and replication of dopamine-related gene effects on caudate volume in young and elderly populations (N=1198) using genome-wide search

The caudate is a subcortical brain structure implicated in many common neurological and psychiatric disorders. To identify specific genes associated with variations in caudate volume, structural magnetic resonance imaging and genome-wide genotypes were acquired from two large cohorts, the Alzheimer's Disease NeuroImaging Initiative (ADNI; N=734) and the Brisbane Adolescent/Young Adult Longitudinal Twin Study (BLTS; N=464). In a preliminary analysis of heritability, around 90% of the variation in caudate volume was due to genetic factors. We then conducted genome-wide association to find common variants that contribute to this relatively high heritability. Replicated genetic association was found for the right caudate volume at single-nucleotide polymorphism rs163030 in the ADNI discovery sample (P=2.36 × 10⁻⁶) and in the BLTS replication sample (P=0.012). This genetic variation accounted for 2.79 and 1.61% of the trait variance, respectively. The peak of association was found in and around two genes, WDR41 and PDE8B, involved in dopamine signaling and development. In addition, a previously identified mutation in PDE8B causes a rare autosomal-dominant type of striatal degeneration. Searching across both samples offers a rigorous way to screen for genes consistently influencing brain structure at different stages of life. Variants identified here may be relevant to common disorders affecting the caudate.

Expression of the osteoarthritis-associated gene GDF5 is modulated epigenetically by DNA methylation

GDF5 is involved in synovial joint development, maintenance and repair, and the rs143383 C/T single nucleotide polymorphism (SNP) located in the 5'UTR of GDF5 is associated, at the genome-wide significance level, with osteoarthritis susceptibility, and with other musculoskeletal phenotypes including height, congenital hip dysplasia and Achilles tendinopathy. There is a significant reduction in the expression of the disease-associated T allele relative to the C allele in synovial joint tissues, an effect influenced by a second SNP (rs143384, C/T) also within the 5'UTR. The differential allelic expression (DAE) imbalance of the C and T alleles of rs143383 varies intra- and inter-individually, suggesting that DAE may be modulated epigenetically. The C alleles of both SNPs form CpG dinucleotides that are potentially amenable to regulation by methylation. Here, we have examined whether DNA methylation regulates GDF5 expression and the allelic imbalance caused by rs143383. We observed methylation of the GDF5 promoter and 5'UTR in cell lines and joint tissues, with demethylation correlating with increased GDF5 expression. The CpG sites created by the C alleles at rs143383 and rs143384 were variably methylated, and treatment of a heterozygous cell line with a demethylating agent further increased the allelic expression imbalance between the C and T alleles. This demonstrates that the genetic effect of the rs143383 SNP on GDF5 expression is modulated epigenetically by DNA methylation. The variability in DAE of rs143383 is therefore partly accounted for by differences in DNA methylation that could influence the penetrance of this allele in susceptibility to common musculoskeletal diseases.

Genome-wide association study identifies four loci associated with eruption of permanent teeth

The sequence and timing of permanent tooth eruption is thought to be highly heritable and can have important implications for the risk of malocclusion, crowding, and periodontal disease. We conducted a genome-wide association study of number of permanent teeth erupted between age 6 and 14 years, analyzed as age-adjusted standard deviation score averaged over multiple time points, based on childhood records for 5,104 women from the Danish National Birth Cohort. Four loci showed association at P<5×10(-8) and were replicated in four independent study groups from the United States and Denmark with a total of 3,762 individuals; all combined P-values were below 10(-11). Two loci agreed with previous findings in primary tooth eruption and were also known to influence height and breast cancer, respectively. The two other loci pointed to genomic regions without any previous significant genome-wide association study results. The intronic SNP rs7924176 in ADK could be linked to gene expression in monocytes. The combined effect of the four genetic variants was most pronounced between age 10 and 12 years, where children with 6 to 8 delayed tooth eruption alleles had on average 3.5 (95% confidence interval: 2.9-4.1) fewer permanent teeth than children with 0 or 1 of these alleles.

Shared genetic architecture in the relationship between adult stature and subclinical coronary artery atherosclerosis

BACKGROUND

Short stature is associated with increased risk of coronary heart disease (CHD); although the mechanisms for this relationship are unknown, shared genetic factors have been proposed. Subclinical atherosclerosis, measured by coronary artery calcification (CAC), is associated with CHD events and represents part of the biological continuum to overt CHD. Many molecular mechanisms of CAC development are shared with bone growth. Thus, we examined whether there was evidence of shared genes (pleiotropy) between adult stature and CAC.

METHODS

877 Asymptomatic white adults (46% men) from 625 families in a community-based sample had computed tomography measures of CAC. Pleiotropy between height and CAC was determined using maximum-likelihood estimation implemented in SOLAR.

RESULTS

Adult height was significantly and inversely associated with CAC score (P = 0.01). After adjusting for age, sex and CHD risk factors, the estimated genetic correlation between height and CAC score was -0.37 and was significantly different than 0 (P = 0.001) and -1 (P < 0.001). The environmental correlation between height and CAC score was 0.60 and was significantly different than 0 (P = 0.024).

CONCLUSIONS

Further studies of shared genetic factors between height and CAC may provide important insight into the complex genetic architecture of CHD, in part through increased understanding of the molecular pathways underlying the process of both normal growth and disease development. Bivariate genetic linkage analysis may provide a powerful mechanism for identifying specific genomic regions associated with both height and CAC.

A generalizable hypothesis for the genetic architecture of disease: pleomorphic risk loci

The dominant and sometimes competing theories for the aetiology of complex human disease have been the common disease, common variant (CDCV) hypothesis, and the multiple rare variant (MRV) hypothesis. With the advent of genome wide association studies and of second-generation sequencing, we are fortunate in being able to test these ideas. The results to date suggest that these hypotheses are not mutually exclusive. Further, initial evidence suggests that both MRV and CDCV can be true at the same loci, and that other disease-related genetic mechanisms also exist at some of these loci. We propose calling these, pleomorphic risk loci, and discuss here how such loci not only offer understanding of the genetic basis of disease, but also provide mechanistic biological insight into disease processes.

Design and coverage of high throughput genotyping arrays optimized for individuals of East Asian, African American, and Latino race/ethnicity using imputation and a novel hybrid SNP selection algorithm

Four custom Axiom genotyping arrays were designed for a genome-wide association (GWA) study of 100,000 participants from the Kaiser Permanente Research Program on Genes, Environment and Health. The array optimized for individuals of European race/ethnicity was previously described. Here we detail the development of three additional microarrays optimized for individuals of East Asian, African American, and Latino race/ethnicity. For these arrays, we decreased redundancy of high-performing SNPs to increase SNP capacity. The East Asian array was designed using greedy pairwise SNP selection. However, removing SNPs from the target set based on imputation coverage is more efficient than pairwise tagging. Therefore, we developed a novel hybrid SNP selection method for the African American and Latino arrays utilizing rounds of greedy pairwise SNP selection, followed by removal from the target set of SNPs covered by imputation. The arrays provide excellent genome-wide coverage and are valuable additions for large-scale GWA studies.

Rare de novo variants associated with autism implicate a large functional network of genes involved in formation and function of synapses

Identification of complex molecular networks underlying common human phenotypes is a major challenge of modern genetics. In this study, we develop a method for network-based analysis of genetic associations (NETBAG). We use NETBAG to identify a large biological network of genes affected by rare de novo CNVs in autism. The genes forming the network are primarily related to synapse development, axon targeting, and neuron motility. The identified network is strongly related to genes previously implicated in autism and intellectual disability phenotypes. Our results are also consistent with the hypothesis that significantly stronger functional perturbations are required to trigger the autistic phenotype in females compared to males. Overall, the presented analysis of de novo variants supports the hypothesis that perturbed synaptogenesis is at the heart of autism. More generally, our study provides proof of the principle that networks underlying complex human phenotypes can be identified by a network-based functional analysis of rare genetic variants.

Genetics of rhinosinusitis

Suggestion for a potential genetic basis to chronic rhinosinusitis (CRS) is afforded by degree of inheritability suggested from family and twin studies, existence of CRS in simple mendelian diseases, and development of sinusitis as part of the phenotype of certain gene "knockout" murine models. Genetic association studies are expected to identify novel genes associated with CRS and suggest novel mechanisms implicated in disease development. Although these studies are subject to methodologic difficulties, associations of CRS and polymorphisms in more than 30 genes have been published, with single nucleotide polymorphisms in 3 (IL1A, TNFA, AOAH) replicated. While the individual risk conferred by these single nucleotide polymorphisms remains modest, taken as a group, they suggest an important implication of pathways of innate immune recognition and in regulation of downstream signaling in the development of CRS. In a demonstration of these techniques' potential to identify new targets for research, the authors present a functional investigation of LAMB1, the top-rated gene from a pooling-based genome-wide association study of CRS. Upregulation of gene expression in LAMB1 and associated laminin genes in primary epithelial cells from CRS patients implicates the extracellular matrix in development of CRS and offers a new avenue for further study.

Sequencing of high-complexity DNA pools for identification of nucleotide and structural variants in regions associated with complex traits

We have used targeted genomic sequencing of high-complexity DNA pools based on long-range PCR and deep DNA sequencing by the SOLiD technology. The method was used for sequencing of 286 kb from four chromosomal regions with quantitative trait loci (QTL) influencing blood plasma lipid and uric acid levels in DNA pools of 500 individuals from each of five European populations. The method shows very good precision in estimating allele frequencies as compared with individual genotyping of SNPs (r(2) = 0.95, P < 10(-16)). Validation shows that the method is able to identify novel SNPs and estimate their frequency in high-complexity DNA pools. In our five populations, 17% of all SNPs and 61% of structural variants are not available in the public databases. A large fraction of the novel variants show a limited geographic distribution, with 62% of the novel SNPs and 59% of novel structural variants being detected in only one of the populations. The large number of population-specific novel SNPs underscores the need for comprehensive sequencing of local populations in order to identify the causal variants of human traits.

Is life law-like?

Genes are generally assumed to be primary biological causes of biological phenotypes and their evolution. In just over a century, a research agenda that has built on Mendel's experiments and on Darwin's theory of natural selection as a law of nature has had unprecedented scientific success in isolating and characterizing many aspects of genetic causation. We revel in these successes, and yet the story is not quite so simple. The complex cooperative nature of genetic architecture and its evolution include teasingly tractable components, but much remains elusive. The proliferation of data generated in our "omics" age raises the question of whether we even have (or need) a unified theory or "law" of life, or even clear standards of inference by which to answer the question. If not, this not only has implications for the widely promulgated belief that we will soon be able to predict phenotypes like disease risk from genes, but also speaks to the limitations in the underlying science itself. Much of life seems to be characterized by ad hoc, ephemeral, contextual probabilism without proper underlying distributions. To the extent that this is true, causal effects are not asymptotically predictable, and new ways of understanding life may be required.

Next generation genome-wide association tool: design and coverage of a high-throughput European-optimized SNP array

The success of genome-wide association studies has paralleled the development of efficient genotyping technologies. We describe the development of a next-generation microarray based on the new highly-efficient Affymetrix Axiom genotyping technology that we are using to genotype individuals of European ancestry from the Kaiser Permanente Research Program on Genes, Environment and Health (RPGEH). The array contains 674,517 SNPs, and provides excellent genome-wide as well as gene-based and candidate-SNP coverage. Coverage was calculated using an approach based on imputation and cross validation. Preliminary results for the first 80,301 saliva-derived DNA samples from the RPGEH demonstrate very high quality genotypes, with sample success rates above 94% and over 98% of successful samples having SNP call rates exceeding 98%. At steady state, we have produced 462 million genotypes per week for each Axiom system. The new array provides a valuable addition to the repertoire of tools for large scale genome-wide association studies.

Novel inactivating mutations in the GH secretagogue receptor gene in patients with constitutional delay of growth and puberty

BACKGROUND

A limited number of mutations in the GH secretagogue receptor gene (GHSR) have been described in patients with short stature. Objective To analyze GHSR in idiopathic short stature (ISS) children including a subgroup of constitutional delay of growth and puberty (CDGP) patients.

SUBJECTS AND METHODS

The GHSR coding region was directly sequenced in 96 independent patients with ISS, 31 of them with CDGP, in 150 adults, and in 197 children with normal stature. The pharmacological consequences of GHSR non-synonymous variations were established using in vitro cell-based assays.

RESULTS

Five different heterozygous point variations in GHSR were identified (c.-6 G>C, c.251G>T (p.Ser84Ile), c.505G>A (p.Ala169Thr), c.545 T>C (p.Val182Ala), and c.1072G>A (p.Ala358Thr)), all in patients with CDGP. Neither these allelic variants nor any other mutations were found in 694 alleles from controls. Functional studies revealed that two of these variations (p.Ser84Ile and p.Val182Ala) result in a decrease in basal activity that was in part explained by a reduction in cell surface expression. The p.Ser84Ile mutation was also associated with a defect in ghrelin potency. These mutations were identified in two female patients with CDGP (at the age of 13 years, their height SDS were -2.4 and -2.3). Both patients had normal progression of puberty and reached normal adult height (height SDS of -0.7 and -1.4) without treatment.

CONCLUSION

This is the first report of GHSR mutations in patients with CDGP. Our data raise the intriguing possibility that abnormalities in ghrelin receptor function may influence the phenotype of individuals with CDGP.

Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association

The identification of multiple signals at individual loci could explain additional phenotypic variance (‘missing heritability’) of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work.

From Galton to GWAS: quantitative genetics of human height

Height has been studied in human genetics since the late 1800s. We review what we have learned about the genetic architecture of this trait from the resemblance between relatives and from genetic marker data. All empirical evidence points towards height being highly polygenic, with many loci contributing to variation in the population and most effect sizes appear to be small. Nevertheless, combining new genetic and genomic technologies with phenotypic measures on height on large samples facilitates new answers to old questions, including the basis of assortative mating in humans, estimation of non-additive genetic variation and partitioning between-cohort phenotypic differences into genetic and non-genetic underlying causes.

Effect of constitution on mass of individual organs and their association with metabolic rate in humans--a detailed view on allometric scaling

Resting energy expenditure (REE)-power relationships result from multiple underlying factors including weight and height. In addition, detailed body composition, including fat free mass (FFM) and its components, skeletal muscle mass and internal organs with high metabolic rates (i.e. brain, heart, liver, kidneys), are major determinants of REE. Since the mass of individual organs scales to height as well as to weight (and, thus, to constitution), the variance in these associations may also add to the variance in REE. Here we address body composition (measured by magnetic resonance imaging) and REE (assessed by indirect calorimetry) in a group of 330 healthy volunteers differing with respect to age (17–78 years), sex (61% female) and BMI (15.9–47.8 kg/m²). Using three dimensional data interpolation we found that the inter-individual variance related to scaling of organ mass to height and weight and, thus, the constitution-related variances in either FFM (model 1) or kidneys, muscle, brain and liver (model 2) explained up to 43% of the inter-individual variance in REE. These data are the first evidence that constitution adds to the complexity of REE. Since organs scale differently as weight as well as height the “fit” of organ masses within constitution should be considered as a further trait.

An examination of single nucleotide polymorphism selection prioritization strategies for tests of gene-gene interaction

BACKGROUND

Given that genome-wide association studies (GWAS) of psychiatric disorders have identified only a small number of convincingly associated variants (single nucleotide polymorphism [SNP]), there is interest in seeking additional evidence for associated variants with tests of gene-gene interaction. Comprehensive pair-wise single SNP-SNP interaction analysis is computationally intensive, and the penalty for multiple testing is severe, given the number of interactions possible. Aiming to minimize these statistical and computational burdens, we have explored approaches to prioritize SNPs for interaction analyses.

METHODS

Primary interaction analyses were performed with the Wellcome Trust Case-Control Consortium bipolar disorder GWAS (1868 cases, 2938 control subjects). Replication analyses were performed with the Genetic Association Information Network bipolar disorder dataset (1001 cases, 1033 control subjects). The SNPs were prioritized for interaction analysis that showed evidence for association that surpassed a number of nominally significant thresholds, are within genome-wide significant genes, or are within genes that are functionally related.

RESULTS

For no set of prioritized SNPs did we obtain evidence to support the hypothesis that the selection strategy identified pairs of variants that were enriched for true (statistical) interactions.

CONCLUSIONS

The SNPs prioritized according to a number of criteria do not have a raised prior probability for significant interaction that is detectable in samples of this size. We argue that the use of significance levels reflecting only the number of tests performed, as is now widely accepted for single SNP analysis, does not offer an appropriate degree of protection against the potential for GWAS studies to generate an enormous number of false positive interactions.

Delineating the Hemostaseome as an aid to individualize the analysis of the hereditary basis of thrombotic and bleeding disorders

Next-generation sequencing and genome-wide association studies represent powerful tools to identify genetic variants that confer disease risk within populations. On their own, however, they cannot provide insight into how these variants contribute to individual risk for diseases that exhibit complex inheritance, or alternatively confer health in a given individual. Even in the case of well-characterized variants that confer a significant disease risk, more healthy individuals carry the variant, with no apparent ill effect, than those who manifest disease. Access to low-cost genome sequence data promises to provide an unprecedentedly detailed view of the nature of the hereditary component of complex diseases, but requires the large-scale comparison of sequence data from individuals with and without disease to deliver a clinical calibration. The provision of informatics support remains problematic as there are currently no means to interpret the data generated. Here, we initiate this process, a prerequisite for such a study, by narrowing the focus from an entire genome to that of a single biological system. To this end, we examine the 'Hemostaseome,' and more specifically focus on DNA sequence changes pertaining to those human genes known to impact upon hemostasis and thrombosis that can be analyzed coordinately, and on an individual basis, to interrogate how specific combinations of variants act to confer disease predisposition. As a first step, we delineate known members of the Hemostaseome and explore the nature of the genetic variants that may cause disease in individuals whose hemostatic balance has become shifted toward either a prothrombotic or anticoagulant phenotype.

Heritability in the Era of Molecular Genetics: Some Thoughts for Understanding Genetic Influences on Behavioural Traits

Genetic influences on behavioural traits are ubiquitous. When behaviourism was the dominant paradigm in psychology, demonstrations of heritability of behavioural and psychological constructs provided important evidence of its limitations. Now that genetic influences on behavioural traits are generally accepted, we need to recognise the limitations of heritability as an indicator of both the aetiology and likelihood of discovering molecular genetic associations with behavioural traits. We review those limitations and conclude that quantitative genetics and genetically informative research designs are still critical to understanding the roles of gene–environment interplay in developmental processes, though not necessarily in the ways commonly discussed. Copyright © 2011 John Wiley & Sons, Ltd.

Advances in multidisciplinary and cross-species approaches to examine the neurobiology of psychiatric disorders

Current approaches to dissect the molecular neurobiology of complex neuropsychiatric disorders such as schizophrenia and major depression have been rightly criticized for failing to provide benefits to patients. Improving the translational potential of our efforts will require the development and refinement of better disease models that consider a wide variety of contributing factors, such as genetic variation, gene-by-environment interactions, endophenotype or intermediate phenotype assessment, cross species analysis, sex differences, and developmental stages. During a targeted expert meeting of the European College of Neuropsychopharmacology (ECNP) in Istanbul, we addressed the opportunities and pitfalls of current translational animal models of psychiatric disorders and agreed on a series of core guidelines and recommendations that we believe will help guiding further research in this area.

Toward knowing the whole human: next-generation sequencing for personalized medicine

The sequencing of the human genome, combined with brilliant technical advances in microarrays and computing, opened the genomic era of personalized medicine. The next generation of genomics is now being driven by massively parallel sequencers that are effectively high definition genetic analyzers capable of sequencing an entire human genome 30-times over in approximately a week for several thousand US dollars. Likewise, these next-generation sequencers, sometimes called deep sequencers, can sequence RNA transcriptomes to render unprecedented, high definition views of transcript sequence, SNP haplotypes, rare variants, splicing, exon boundaries and RNA editing. Presently, next-generation sequencing platforms can be grouped into ‘discovery’ platforms, which provide broad sequence coverage, but require days per sample, versus ‘diagnostic’ platforms, which provide a fraction of the coverage, but require only hours for sequencing. As these technologies converge, it will be possible to sequence a human genome in a matter of hours for a few hundred US dollars. While presenting considerable technical challenges in handling the massive data generated, next-generation sequencing platforms offer unparalleled opportunities for biological insights, target discovery and clinical diagnostics to accelerate personalized medicine in the coming years.

Understanding Heritability: What it is and What it is Not

Commentators generally found our exposition of the concept of heritability helpful for psychologists, suggesting that we largely accomplished our primary goal. Many provided supplemental and helpful perspectives on concepts we addressed. A few of the comments indicated that we may not have been completely successful in making clear our secondary goal, which was to outline how heritability estimates confound a plethora of influences. In this response, we thus emphasize that we do not claim that specific kinds of complexity, or, even worse, intractable complexity, pervade the genetics of behavioural traits. Rather, our claim is that genetics is riddled with complexity of many degrees and kinds, and heritability is a poor indicator of either degree or kind of underlying genetic complexity. Copyright © 2011 John Wiley & Sons, Ltd.

Detecting rare and common variants for complex traits: sibpair and odds ratio weighted sum statistics (SPWSS, ORWSS)

It is generally known that risk variants segregate together with a disease within families, but this information has not been used in the existing statistical methods for detecting rare variants. Here we introduce two weighted sum statistics that can apply to either genome-wide association data or resequencing data for identifying rare disease variants: weights calculated based on sibpairs and odd ratios, respectively. We evaluated the two methods via extensive simulations under different disease models. We compared the proposed methods with the weighted sum statistic (WSS) proposed by Madsen and Browning, keeping the same genotyping or resequencing cost. Our methods clearly demonstrate more statistical power than the WSS. In addition, we found that using sibpair information can increase power over using only unrelated samples by more than 40%. We applied our methods to the Framingham Heart Study (FHS) and Wellcome Trust Case Control Consortium (WTCCC) hypertension datasets. Although we did not identify any genes as reaching a genome-wide significance level, we found variants in the candidate gene angiotensinogen significantly associated with hypertension at P = 6.9 × 10(-4), whereas the most significant single SNP association evidence is P = 0.063. We further applied the odds ratio weighted method to the IFIH1 gene for type-1 diabetes in the WTCCC data. Our method yielded a P-value of 4.82 × 10(-4), much more significant than that obtained by haplotype-based methods. We demonstrated that family data are extremely informative in searching for rare variants underlying complex traits, and the odds ratio weighted sum statistic is more efficient than currently existing methods.

The Future of Children's Health in the Genomic Era

The effects of genomic medicine on child health promise to be profound. Medical applications will eventually include characterizing patients' genomes to detect predictive mutations for pre-symptomatic counseling where treatment exists; to search for causes of diseases of unknown etiology, and to detect carriers for prenatal counseling; to define cancer and other disease-based genomes to design individualized therapy; and to understand our microbiomes to modify these in health and disease. Rapid advances in technology and bioinformatics have reduced the cost and the time and increased the accuracy necessary to sequence whole genomes or whole exomes. However, complete understanding of disease will also require correlation of genomic information with high-quality phenotypic data. In addition, several critical ethical, psycho-social, and public policy issues will require clarity in the coming years. Ultimately these advances will improve the effectiveness of health care for children and for society.

Dog models of naturally occurring cancer

Studies using dogs provide an ideal solution to the gap in animal models for natural disease and translational medicine. This is evidenced by approximately 400 inherited disorders being characterized in domesticated dogs, most of which are relevant to humans. There are several hundred isolated populations of dogs (breeds) and each has a vastly reduced genetic variation compared with humans; this simplifies disease mapping and pharmacogenomics. Dogs age five- to eight-fold faster than do humans, share environments with their owners, are usually kept until old age and receive a high level of health care. Farseeing investigators recognized this potential and, over the past decade, have developed the necessary tools and infrastructure to utilize this powerful model of human disease, including the sequencing of the dog genome in 2005. Here, we review the nascent convergence of genetic and translational canine models of spontaneous disease, focusing on cancer.

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 ∼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 = 9.77×10⁻⁷). In our independent replication sample six SNPs among the top 50 hits pruned for linkage disequilibrium (r²<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.

MixupMapper: correcting sample mix-ups in genome-wide datasets increases power to detect small genetic effects

MOTIVATION

Sample mix-ups can arise during sample collection, handling, genotyping or data management. It is unclear how often sample mix-ups occur in genome-wide studies, as there currently are no post hoc methods that can identify these mix-ups in unrelated samples. We have therefore developed an algorithm (MixupMapper) that can both detect and correct sample mix-ups in genome-wide studies that study gene expression levels.

RESULTS

We applied MixupMapper to five publicly available human genetical genomics datasets. On average, 3% of all analyzed samples had been assigned incorrect expression phenotypes: in one of the datasets 23% of the samples had incorrect expression phenotypes. The consequences of sample mix-ups are substantial: when we corrected these sample mix-ups, we identified on average 15% more significant cis-expression quantitative trait loci (cis-eQTLs). In one dataset, we identified three times as many significant cis-eQTLs after correction. Furthermore, we show through simulations that sample mix-ups can lead to an underestimation of the explained heritability of complex traits in genome-wide association datasets.

AVAILABILITY AND IMPLEMENTATION

MixupMapper is freely available at http://www.genenetwork.nl/mixupmapper/

The stature of boys is inversely correlated to the levels of their sertoli cell hormones: do the testes restrain the maturation of boys?

The testes of preadolescent boys appear to be dormant, as they produce only trace levels of testosterone [1]. However, they release supra-adult levels of Müllerian Inhibiting Substance (MIS, anti-Müllerian hormone) and lesser levels of inhibin B (InhB), for unknown reasons [2], [3]. Boys have a variable rate of maturation, which on average is slower than girls. The height of children relative to their parents is an index of their maturity [4], [5]. We report here that a boy's level of MIS and InhB is stable over time and negatively correlates with his height and his height relative to his parent's height. This suggests that boy's with high levels of MIS and InhB are short because they are immature, rather than because they are destined to be short men. The levels of MIS and InhB in the boys did not correlate with known hormonal modulators of growth, and were additive with age and the growth hormone/IGF1 axis as predictors of a boy's height. If MIS and InhB were causal regulators of maturity, then the inter-boy differences in the levels of these hormone produces variation in maturation equivalent to 18-months of development. MIS and InhB may thus account for most of the variation in the rate of male development. If boys lacked these hormones, then an average 5-year-old boy would be over 5 cm taller than age-matched girls, making boys almost as dimorphic as men, for height. This indicates that boys have a high growth potential that is initially suppressed by their testes. The concept of the childhood testes suppressing an adult male feature appears paradoxical. However, the growth of children requires intergenerational transfer of nutrients. Consequently, the MIS/InhB slowing of male growth may have been historically advantageous, as it would minimizes any sex bias in the maternal cost of early child rearing.