New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

Detecting epistasis with restricted response patterns in pairs of biallelic loci.

Well-established examples of genetic epistasis between a pair of loci typically show characteristic patterns of phenotypic distributions in joint genotype tables. However, inferring epistasis given such data is difficult due to the lack of power in commonly used approaches, which decompose the epistatic patterns into main plus interaction effects followed by testing the interaction term. Testing additive-only or all terms may have more power, but they are sensitive to nonepistatic patterns. Alternatively, the epistatic patterns of interest can be enumerated and the best matching one is found by searching through the possibilities. Although this approach requires multiple testing correction over possible patterns, each pattern can be fitted with a regression model with just one degree of freedom and thus the overall power can still be high, if the number of possible patterns is limited. Here we compare the power of the linear decomposition and pattern search methods, by applying them to simulated data generated under several patterns of joint genotype effects with simple biological interpretations. Interaction-only tests are the least powerful; while pattern search approach is the most powerful if the range of possibilities is restricted, but still includes the true pattern.

Thirty new loci for age at menarche identified by a meta-analysis of genome-wide association studies.

To identify loci for age at menarche, we performed a meta-analysis of 32 genome-wide association studies in 87,802 women of European descent, with replication in up to 14,731 women. In addition to the known loci at LIN28B (P = 5.4 × 10⁻⁶⁰) and 9q31.2 (P = 2.2 × 10⁻³³), we identified 30 new menarche loci (all P < 5 × 10⁻⁸) and found suggestive evidence for a further 10 loci (P < 1.9 × 10⁻⁶). The new loci included four previously associated with body mass index (in or near FTO, SEC16B, TRA2B and TMEM18), three in or near other genes implicated in energy homeostasis (BSX, CRTC1 and MCHR2) and three in or near genes implicated in hormonal regulation (INHBA, PCSK2 and RXRG). Ingenuity and gene-set enrichment pathway analyses identified coenzyme A and fatty acid biosynthesis as biological processes related to menarche timing.

Genome-wide association and genetic functional studies identify autism susceptibility candidate 2 gene (AUTS2) in the regulation of alcohol consumption.

Alcohol consumption is a moderately heritable trait, but the genetic basis in humans is largely unknown, despite its clinical and societal importance. We report a genome-wide association study meta-analysis of ∼2.5 million directly genotyped or imputed SNPs with alcohol consumption (gram per day per kilogram body weight) among 12 population-based samples of European ancestry, comprising 26,316 individuals, with replication genotyping in an additional 21,185 individuals. SNP rs6943555 in autism susceptibility candidate 2 gene (AUTS2) was associated with alcohol consumption at genome-wide significance (P = 4 × 10(-8) to P = 4 × 10(-9)). We found a genotype-specific expression of AUTS2 in 96 human prefrontal cortex samples (P = 0.026) and significant (P < 0.017) differences in expression of AUTS2 in whole-brain extracts of mice selected for differences in voluntary alcohol consumption. Down-regulation of an AUTS2 homolog caused reduced alcohol sensitivity in Drosophila (P < 0.001). Our finding of a regulator of alcohol consumption adds knowledge to our understanding of genetic mechanisms influencing alcohol drinking behavior.

A genome-wide association study of early menopause and the combined impact of identified variants.

Early menopause (EM) affects up to 10% of the female population, reducing reproductive lifespan considerably. Currently, it constitutes the leading cause of infertility in the western world, affecting mainly those women who postpone their first pregnancy beyond the age of 30 years. The genetic aetiology of EM is largely unknown in the majority of cases. We have undertaken a meta-analysis of genome-wide association studies (GWASs) in 3493 EM cases and 13 598 controls from 10 independent studies. No novel genetic variants were discovered, but the 17 variants previously associated with normal age at natural menopause as a quantitative trait (QT) were also associated with EM and primary ovarian insufficiency (POI). Thus, EM has a genetic aetiology which overlaps variation in normal age at menopause and is at least partly explained by the additive effects of the same polygenic variants. The combined effect of the common variants captured by the single nucleotide polymorphism arrays was estimated to account for ∼30% of the variance in EM. The association between the combined 17 variants and the risk of EM was greater than the best validated non-genetic risk factor, smoking.

Genome-wide association analysis identifies 20 loci that influence adult height.

Adult height is a model polygenic trait, but there has been limited success in identifying the genes underlying its normal variation. To identify genetic variants influencing adult human height, we used genome-wide association data from 13,665 individuals and genotyped 39 variants in an additional 16,482 samples. We identified 20 variants associated with adult height (P < 5 x 10(-7), with 10 reaching P < 1 x 10(-10)). Combined, the 20 SNPs explain approximately 3% of height variation, with a approximately 5 cm difference between the 6.2% of people with 17 or fewer 'tall' alleles compared to the 5.5% with 27 or more 'tall' alleles. The loci we identified implicate genes in Hedgehog signaling (IHH, HHIP, PTCH1), extracellular matrix (EFEMP1, ADAMTSL3, ACAN) and cancer (CDK6, HMGA2, DLEU7) pathways, and provide new insights into human growth and developmental processes. Finally, our results provide insights into the genetic architecture of a classic quantitative trait.

Variants in MTNR1B influence fasting glucose levels.

To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 x 10(-50)) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 x 10(-15)). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 x 10(-7)) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 x 10(-57)) and GCK (rs4607517, P = 1.0 x 10(-25)) loci.

Multivariate QST-FST comparisons: a neutrality test for the evolution of the g matrix in structured populations.

Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Q(st)-F(st)) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2F(st)/(1 - F(st))G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2F(st)/(1 - F(st))] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Q(st)-F(st) comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions.

A multilevel approach to understanding circadian rhythmicity : social and sleep-dependent effects in ants and mice

Résumé françaisLa majorité des organismes vivants sont soumis à l'alternance du jour et de la nuit, conséquence de la rotation de la terre autour de son axe. Ils ont développé un système interne de mesure du temps, appelé horloge circadienne, leur permettant de s'adapter et de synchroniser leur comportement et leur physiologie aux cycles de lumière. Cette dernière est considérée comme étant le signal majeur entraînant l'horloge interne et. par conséquent, les rythmes journaliers d'éveil et de sommeil. Outre sa régulation circadienne, le sommeil est contrôlé par un processus homéostatique qui détermine son besoin. La contribution de ces deux processus dans le fonctionnement cellulaire du cerveau n'a pas encore été investiguée. La mesure de l'amplitude ainsi que de la prévalence des ondes delta de l'EEG (activité delta) constitue un index très fiable du besoin de sommeil. Il a été démontré que cette activité est génétiquement déterminée et associée à un locus de trait quantitatif situé sur le chromosome 13 de la souris.Grâce à des expériences de privation de sommeil et d'analyses de transcriptome du cerveau dans trois souches de souris présentant diverses réponses à la privation de sommeil, nous avons trouvé que Homerla, localisé dans la région d'intérêt du chromosome 13, est le meilleur marqueur du besoin de sommeil. Homerla est impliqué dans la récupération de l'hyperactivité neuronale induite par le glutamate, grâce à son effet tampon sur le calcium intracellulaire. Une fonction fondamentale du sommeil pourrait donc être de protéger le cerveau et de lui permettre de récupérer après une hyperactivité neuronale imposée par une veille prolongée.De plus, nous avons montré que 2032 transcrits sont exprimés rythmiqueraent dans le cerveau de la souris, parmi lesquels seulement 391 le restent après que les animaux aient été privés de sommeil à différents moments au cours des 24 heures. Cette observation montre clairement que la plupart des changements rythmiques au niveau du transcriptome dépendent du sommeil et non de l'horloge circadienne et souligne ainsi l'importance du sommeil dans la physiologie des mammifères.La plupart des expériences concernant les rythmes circadiens ont été réalisées sur des individus isolés en négligeant l'effet du contexte social sur les comportements circadiens. Les espèces sociales, telles que les fourmis, se caractérisent par une division du travail où une répartition des tâches s'effectue entre ses membres. De plus, certaines d'entre elles doivent être pratiquées en continu comme les soins au couvain tandis que d'autres requièrent une activité rythmique comme le fourragement. Ainsi la fourmi est un excellent modèle pour l'étude de 1 influence du contexte social sur les rythmes circadiens.A ces fins, nous avons décidé d'étudier les rythmes circadiens chez une espèce de fourmi Camponotus fellah et de caractériser au niveau moléculaire son horloge circadienne. Nous avons ainsi développé un système vidéo permettant de suivre l'activité locomotrice de tous les individus d'une colonie. Nos résultats montrent que, bien que la plupart des fourmis soient arythmiques à l'intérieur de la colonie, elles développent d'amples rythmes d'activité en isolation. De plus, ces rythmes disparaissent presque aussitôt que la fourmi est réintroduite dans la colonie. Cette rythmicité observée en isolation semble être générée par l'horloge circadienne car elle persiste en condition constante (obscurité totale). Nous avons ensuite regardé si cette apparente arythmie observée dans la colonie résultait d'un effet masquant des interactions sociales sur les rythmes circadiens d'activité. Nos résultats suggèrent que l'horloge interne est fonctionnelle dans la colonie mais que l'expression de ses rythmes au niveau comportemental est inhibée par les interactions sociales. Les analyses moléculaires du statut de l'horloge dans différents contextes sociaux sont actuellement en cours. Le contexte social semble donc un déterminant majeur du comportement circadien chez la fourmi.AbstractAlmost all living organisms on earth are subjected to the alternance of day and night re-sulting from the rotation of the earth around its axis. They have evolved with an internal timing system, termed the circadian clock, enabling them to adapt and synchronize their behavior and physiology to the daily changes in light and related environmental parame¬ters. Light is thought to be the major cue entraining the circadian clock and consequently the rhythms of rest/activity. In addition to its circadian dependent timing, sleep is reg¬ulated by a homeostatic process that determines its need. The contribution of these two processes in the cellular functioning of the brain has not yet been considered. A highly reliable index of the homeostatic process of sleep is the measure of the amplitude and prevalence of the EEG delta waves (delta activity). It has been shown that sleep need, measured by delta activity, is genetically determined and associated with a Quantitative Trait Locus (QTL) located on the mouse chromosome 13. By using sleep deprivation and brain transcriptome profiling in three inbred mouse strains showing different responses to sleep loss, we found that Homerla, localized within this QTL region is the best transcrip¬tional marker of sleep need. Interestingly Homerla is primarily involved in the recovery from glutamate-induced neuronal hyperactivity by its buffering effect on intracellular cal¬cium. A fundamental function of sleep may therefore reside in the protection and recovery of the brain from a neuronal hyperactivity imposed by prolonged wakefulness.Moreover, time course gene expression experiments showed that 2032 brain tran¬scripts present a rhythmic variation, but only 391 of those remain rhythmic when mice are sleep deprived at four time points around the clock. This finding clearly suggests that most changes in gene transcription over the day are sleep-wake dependent rather than clock dependent and underlines the importance of sleep in mammalian physiology.In the second part of this PhD, I was interested in the social influence on circadian behavior. Most experiments done in the circadian field have been performed on isolated individuals and have therefore ignored the effect of the social context on circadian behav-ior. Eusocial insect species such as ants are characterized by a division of labor: colony tasks are distributed among individuals, some of them requiring continuous activity such as nursing or rhythmic ones such as foraging. Thus ants represent a suitable model to study the influence of the social context on the circadian clock and its output rhythms.The aim of this part was to address the effect of social context on circadian rhythms in the ant species Camponotus fellah and to characterize its circadian clock at the molecu¬lar level. We therefore developed a video tracking system to follow the locomotor activity of all individuals in a colony. Our results show that most ants are arrhythmic within the colony, but develop, when subjected to social isolation, strong rhythms of activity that intriguingly disappear when individuals are reintroduced into the colony. The rhythmicity observed in isolated ants seems to be driven by the circadian clock as it persists under constant conditions (complete darkness). We then tested whether the apparent arrhyth- micity in the colony stemmed from a masking effect of social interactions on circadian rhythms. Indeed, we found that circadian clocks of ants in the colony are functional but their expression at the behavioral level is inhibited by social interactions. The molecular assessment of the circadian clock functional state in the different social context is still under investigation. Our results suggest that social context is a major determinant of circadian behavior in ants.

Multiple sclerosis risk variant HLA-DRB1*1501 associates with high expression of DRB1 gene in different human populations.

The human leukocyte antigen (HLA) DRB1*1501 has been consistently associated with multiple sclerosis (MS) in nearly all populations tested. This points to a specific antigen presentation as the pathogenic mechanism though this does not fully explain the disease association. The identification of expression quantitative trait loci (eQTL) for genes in the HLA locus poses the question of the role of gene expression in MS susceptibility. We analyzed the eQTLs in the HLA region with respect to MS-associated HLA-variants obtained from genome-wide association studies (GWAS). We found that the Tag of DRB1*1501, rs3135388 A allele, correlated with high expression of DRB1, DRB5 and DQB1 genes in a Caucasian population. In quantitative terms, the MS-risk AA genotype carriers of rs3135388 were associated with 15.7-, 5.2- and 8.3-fold higher expression of DQB1, DRB5 and DRB1, respectively, than the non-risk GG carriers. The haplotype analysis of expression-associated variants in a Spanish MS cohort revealed that high expression of DRB1 and DQB1 alone did not contribute to the disease. However, in Caucasian, Asian and African American populations, the DRB1*1501 allele was always highly expressed. In other immune related diseases such as type 1 diabetes, inflammatory bowel disease, ulcerative colitis, asthma and IgA deficiency, the best GWAS-associated HLA SNPs were also eQTLs for different HLA Class II genes. Our data suggest that the DR/DQ expression levels, together with specific structural properties of alleles, seem to be the causal effect in MS and in other immunopathologies rather than specific antigen presentation alone.

Genomic and proteomic approaches towards an understanding of sleep.

The basic functions of sleep are still unclear, however, recent advances in genomics and proteomics have begun to contribute to our understanding of both normal and pathological sleep. In this review, we focus primarily on normal sleep and wake that have been studied in model organisms such as mice. Mice have been especially valuable since many different inbred strains exist that differ in sleep-related traits, and genes can be altered by either mutagenesis or targeted approaches. Advances in QTL (Quantitative Trait Loci) analysis have also helped to identify important sleep related genes, and several other QTLs have been mapped as a first step toward finding the genes that underlie basic sleep traits. In addition to more traditional genetic approaches, the abundance of different mRNAs across sleep and wake can now be studied and compared in different brain regions much more thoroughly using microarray methods. Progress at the protein level has been more difficult, but a few studies have begun to investigate changes in proteins during sleep and wake, and we present some of our own preliminary data in this area. A knowledge of which genes and proteins control or respond to changes in sleep will not only help answer fundamental questions, but may also suggest novel drug targets for improving multiple aspects of sleep and wake.

Genome-wide association study of multiple sclerosis confirms a novel locus at 5p13.1.

Multiple Sclerosis (MS) is the most common progressive and disabling neurological condition affecting young adults in the world today. From a genetic point of view, MS is a complex disorder resulting from the combination of genetic and non-genetic factors. We aimed to identify previously unidentified loci conducting a new GWAS of Multiple Sclerosis (MS) in a sample of 296 MS cases and 801 controls from the Spanish population. Meta-analysis of our data in combination with previous GWAS was done. A total of 17 GWAS-significant SNPs, corresponding to three different loci were identified:HLA, IL2RA, and 5p13.1. All three have been previously reported as GWAS-significant. We confirmed our observation in 5p13.1 for rs9292777 using two additional independent Spanish samples to make a total of 4912 MS cases and 7498 controls (ORpooled = 0.84; 95%CI: 0.80-0.89; p = 1.36 × 10-9). This SNP differs from the one reported within this locus in a recent GWAS. Although it is unclear whether both signals are tapping the same genetic association, it seems clear that this locus plays an important role in the pathogenesis of MS.

4

Although it has long been known that genetic factors play a major role in shaping the electroencephalogram (EEG), progress on identifying the underlying genes has, until recently, been limited. Using quantitative trait loci (QTL) analyses several genomic loci affecting the sleep EEG could be mapped in the mouse. For three of these QTLs the responsible genes were identified leading to the implication of novel signaling pathways affecting EEG traits. Moreover, the insight that in the mouse the sleep-wake dependent dynamics in the expression of EEG slow waves during sleep is under strong genetic control has paved the way for candidate gene studies in humans investigating the contribution of specific polymorphism to the trait-like inter-individual differences in the susceptibility to sleep loss. Candidate gene studies in the mouse were also instrumental in establishing an alternative, noncircadian function for clock genes in the homeostatic regulation of sleep and modulating rhythmic EEG activity of thalamocortical origin. Future efforts should combine system genetics approaches in the mouse and genome-wide association studies in humans to facilitate uncovering the molecular pathways that shape brain activity.

Evidence of new risk genetic factor to systemic lupus erythematosus: the UBASH3A gene

The ubiquitin associated and Src-homology 3 (SH3) domain containing A (UBASH3a) is a suppressor of T-cell receptor signaling, underscoring antigen presentation to T-cells as a critical shared mechanism of diseases pathogenesis. The aim of the present study was to determine whether the UBASH3a gene influence the susceptibility to systemic lupus erythematosus (SLE) in Caucasian populations. We evaluated five UBASH3a polymorphisms (rs2277798, rs2277800, rs9976767, rs13048049 and rs17114930), using TaqMan® allelic discrimination assays, in a discovery cohort that included 906 SLE patients and 1165 healthy controls from Spain. The SNPs that exhibit statistical significance difference were evaluated in a German replication cohort of 360 SLE patients and 379 healthy controls. The case-control analysis in the Spanish population showed a significant association between the rs9976767 and SLE (Pc = 9.9E-03 OR = 1.21 95%CI = 1.07-1.37) and a trend of association for the rs2277798 analysis (P = 0.09 OR = 0.9 95%CI = 0.79-1.02). The replication in a German cohort and the meta-analysis confirmed that the rs9976767 (Pc = 0.02; Pc = 2.4E-04, for German cohort and meta-analysis, respectively) and rs2277798 (Pc = 0.013; Pc = 4.7E-03, for German cohort and meta-analysis, respectively) UBASH3a variants are susceptibility factors for SLE. Finally, a conditional regression analysis suggested that the most likely genetic variation responsible for the association was the rs9976767 polymorphism. Our results suggest that UBASH3a gene plays a role in the susceptibility to SLE. Moreover, our study indicates that UBASH3a can be considered as a common genetic factor in autoimmune diseases.