The protocadherin 17 gene affects cognition, personality, amygdala structure and function, synapse development and risk of major mood disorders.

Major mood disorders, which primarily include bipolar disorder and major depressive disorder, are the leading cause of disability worldwide and pose a major challenge in identifying robust risk genes. Here, we present data from independent large-scale clinical data sets (including 29 557 cases and 32 056 controls) revealing brain expressed protocadherin 17 (PCDH17) as a susceptibility gene for major mood disorders. Single-nucleotide polymorphisms (SNPs) spanning the PCDH17 region are significantly associated with major mood disorders; subjects carrying the risk allele showed impaired cognitive abilities, increased vulnerable personality features, decreased amygdala volume and altered amygdala function as compared with non-carriers. The risk allele predicted higher transcriptional levels of PCDH17 mRNA in postmortem brain samples, which is consistent with increased gene expression in patients with bipolar disorder compared with healthy subjects. Further, overexpression of PCDH17 in primary cortical neurons revealed significantly decreased spine density and abnormal dendritic morphology compared with control groups, which again is consistent with the clinical observations of reduced numbers of dendritic spines in the brains of patients with major mood disorders. Given that synaptic spines are dynamic structures which regulate neuronal plasticity and have crucial roles in myriad brain functions, this study reveals a potential underlying biological mechanism of a novel risk gene for major mood disorders involved in synaptic function and related intermediate phenotypes.

New quality measure for SNP array based CNV detection.

MOTIVATION: Only a few large systematic studies have evaluated the impact of copy number variants (CNVs) on common diseases. Several million individuals have been genotyped on single nucleotide variation arrays, which could be used for genome-wide CNVs association studies. However, CNV calls remain prone to false positives and only empirical filtering strategies exist in the literature. To overcome this issue, we defined a new quality score (QS) estimating the probability of a CNV called by PennCNV to be confirmed by other software. RESULTS: Out-of-sample comparison showed that the correlation between the consensus CNV status and the QS is twice as high as it is for any previously proposed CNV filters. ROC curves displayed an AUC higher than 0.8 and simulations showed an increase up to 20% in statistical power when using QS in comparison to other filtering strategies. Superior performance was confirmed also for alternative consensus CNV definition and through improving known CNV-trait associations. AVAILABILITY AND IMPLEMENTATION: http://goo.gl/T6yuFM CONTACT: zoltan.kutalik@unil.ch or aurelien@mace@unil.chSupplementary information: Supplementary data are available at Bioinformatics online.

CRTC2 polymorphism as a risk factor for the incidence of metabolic syndrome in patients with solid organ transplantation.

Metabolic syndrome after transplantation is a major concern following solid organ transplantation (SOT). The CREB-regulated transcription co-activator 2 (CRTC2) regulates glucose metabolism. The effect of CRTC2 polymorphisms on new-onset diabetes after transplantation (NODAT) was investigated in a discovery sample of SOT recipients (n1=197). Positive results were tested for replication in two samples from the Swiss Transplant Cohort Study (STCS, n2=1294 and n3=759). Obesity and other metabolic traits were also tested. Associations with metabolic traits in population-based samples (n4=46'186, n5=123'865, n6>100,000) were finally analyzed. In the discovery sample, CRTC2 rs8450-AA genotype was associated with NODAT, fasting blood glucose and body mass index (Pcorrected<0.05). CRTC2 rs8450-AA genotype was associated with NODAT in the second STCS replication sample (odd ratio (OR)=2.01, P=0.04). In the combined STCS replication samples, the effect of rs8450-AA genotype on NODAT was observed in patients having received SOT from a deceased donor and treated with tacrolimus (n=395, OR=2.08, P=0.02) and in non-kidney transplant recipients (OR=2.09, P=0.02). Moreover, rs8450-AA genotype was associated with overweight or obesity (n=1215, OR=1.56, P=0.02), new-onset hyperlipidemia (n=1007, OR=1.76, P=0.007), and lower high-density lipoprotein-cholesterol (n=1214, ß=-0.08, P=0.001). In the population-based samples, a proxy of rs8450G>A was significantly associated with several metabolic abnormalities. CRTC2 rs8450G>A appears to have an important role in the high prevalence of metabolic traits observed in patients with SOT. A weak association with metabolic traits was also observed in the population-based samples.

Meta-analysis of genome-wide association studies of anxiety disorders.

Anxiety disorders (ADs), namely generalized AD, panic disorder and phobias, are common, etiologically complex conditions with a partially genetic basis. Despite differing on diagnostic definitions based on clinical presentation, ADs likely represent various expressions of an underlying common diathesis of abnormal regulation of basic threat-response systems. We conducted genome-wide association analyses in nine samples of European ancestry from seven large, independent studies. To identify genetic variants contributing to genetic susceptibility shared across interview-generated DSM-based ADs, we applied two phenotypic approaches: (1) comparisons between categorical AD cases and supernormal controls, and (2) quantitative phenotypic factor scores (FS) derived from a multivariate analysis combining information across the clinical phenotypes. We used logistic and linear regression, respectively, to analyze the association between these phenotypes and genome-wide single nucleotide polymorphisms. Meta-analysis for each phenotype combined results across the nine samples for over 18 000 unrelated individuals. Each meta-analysis identified a different genome-wide significant region, with the following markers showing the strongest association: for case-control contrasts, rs1709393 located in an uncharacterized non-coding RNA locus on chromosomal band 3q12.3 (P=1.65 × 10(-8)); for FS, rs1067327 within CAMKMT encoding the calmodulin-lysine N-methyltransferase on chromosomal band 2p21 (P=2.86 × 10(-9)). Independent replication and further exploration of these findings are needed to more fully understand the role of these variants in risk and expression of ADs.

The 16p11.2 locus modulates brain structures common to autism, schizophrenia and obesity.

Anatomical structures and mechanisms linking genes to neuropsychiatric disorders are not deciphered. Reciprocal copy number variants at the 16p11.2 BP4-BP5 locus offer a unique opportunity to study the intermediate phenotypes in carriers at high risk for autism spectrum disorder (ASD) or schizophrenia (SZ). We investigated the variation in brain anatomy in 16p11.2 deletion and duplication carriers. Beyond gene dosage effects on global brain metrics, we show that the number of genomic copies negatively correlated to the gray matter volume and white matter tissue properties in cortico-subcortical regions implicated in reward, language and social cognition. Despite the near absence of ASD or SZ diagnoses in our 16p11.2 cohort, the pattern of brain anatomy changes in carriers spatially overlaps with the well-established structural abnormalities in ASD and SZ. Using measures of peripheral mRNA levels, we confirm our genomic copy number findings. This combined molecular, neuroimaging and clinical approach, applied to larger datasets, will help interpret the relative contributions of genes to neuropsychiatric conditions by measuring their effect on local brain anatomy.

Impact of common risk factors of fibrosis progression in chronic hepatitis C.

OBJECTIVE: The natural course of chronic hepatitis C varies widely. To improve the profiling of patients at risk of developing advanced liver disease, we assessed the relative contribution of factors for liver fibrosis progression in hepatitis C. DESIGN: We analysed 1461 patients with chronic hepatitis C with an estimated date of infection and at least one liver biopsy. Risk factors for accelerated fibrosis progression rate (FPR), defined as ≥ 0.13 Metavir fibrosis units per year, were identified by logistic regression. Examined factors included age at infection, sex, route of infection, HCV genotype, body mass index (BMI), significant alcohol drinking (≥ 20 g/day for ≥ 5 years), HIV coinfection and diabetes. In a subgroup of 575 patients, we assessed the impact of single nucleotide polymorphisms previously associated with fibrosis progression in genome-wide association studies. Results were expressed as attributable fraction (AF) of risk for accelerated FPR. RESULTS: Age at infection (AF 28.7%), sex (AF 8.2%), route of infection (AF 16.5%) and HCV genotype (AF 7.9%) contributed to accelerated FPR in the Swiss Hepatitis C Cohort Study, whereas significant alcohol drinking, anti-HIV, diabetes and BMI did not. In genotyped patients, variants at rs9380516 (TULP1), rs738409 (PNPLA3), rs4374383 (MERTK) (AF 19.2%) and rs910049 (major histocompatibility complex region) significantly added to the risk of accelerated FPR. Results were replicated in three additional independent cohorts, and a meta-analysis confirmed the role of age at infection, sex, route of infection, HCV genotype, rs738409, rs4374383 and rs910049 in accelerating FPR. CONCLUSIONS: Most factors accelerating liver fibrosis progression in chronic hepatitis C are unmodifiable.

The protective effect of the obesity-associated rs9939609 A variant in fat mass- and obesity-associated gene on depression.

Candidate gene and genome-wide association studies have not identified common variants, which are reliably associated with depression. The recent identification of obesity predisposing genes that are highly expressed in the brain raises the possibility of their genetic contribution to depression. As variation in the intron 1 of the fat mass- and obesity-associated (FTO) gene contributes to polygenic obesity, we assessed the possibility that FTO gene may contribute to depression in a cross-sectional multi-ethnic sample of 6561 depression cases and 21,932 controls selected from the EpiDREAM, INTERHEART, DeCC (depression case-control study) and Cohorte Lausannoise (CoLaus) studies. Major depression was defined according to DSM IV diagnostic criteria. Association analyses were performed under the additive genetic model. A meta-analysis of the four studies showed a significant inverse association between the obesity risk FTO rs9939609 A variant and depression (odds ratio=0.92 (0.89, 0.97), P=3 × 10(-4)) adjusted for age, sex, ethnicity/population structure and body-mass index (BMI) with no significant between-study heterogeneity (I(2)=0%, P=0.63). The FTO rs9939609 A variant was also associated with increased BMI in the four studies (ß 0.30 (0.08, 0.51), P=0.0064) adjusted for age, sex and ethnicity/population structure. In conclusion, we provide the first evidence that the FTO rs9939609 A variant may be associated with a lower risk of depression independently of its effect on BMI. This study highlights the potential importance of obesity predisposing genes on depression.

Penetrance of marked cognitive impairment in older male carriers of the FMR1 gene premutation.

BACKGROUND: Male carriers of the FMR1 premutation are at risk of developing the fragile X-associated tremor/ataxia syndrome (FXTAS), a newly recognised and largely under-diagnosed late onset neurodegenerative disorder. Patients affected with FXTAS primarily present with cerebellar ataxia and intention tremor. Cognitive decline has also been associated with the premutation, but the lack of data on its penetrance is a growing concern for clinicians who provide genetic counselling. METHODS: The Mattis Dementia Rating Scale (MDRS) was administered in a double blind fashion to 74 men aged 50 years or more recruited from fragile X families (35 premutation carriers and 39 intrafamilial controls) regardless of their clinical manifestation. Based on previous publications, marked cognitive impairment was defined by a score

Weight Loss Directly Influences Intermediate-Term Remission of Diabetes Mellitus After Bariatric Surgery: A Retrospective Case-Control Study.

PURPOSE: Roux en Y gastric bypass surgery (RYGB) is an effective therapy for patients with severe obesity. It induces both significant weight loss and rapid improvements of metabolic complications. This study was undertaken to better define the direct role of weight loss in the metabolic improvements. METHODS: A retrospective, case-control study of a cohort of 649 patients with obesity who underwent RYGB, comparing higher and lower responders at 2 years after surgery (n = 100 pairs). Pairs of patients were matched for age, gender, and initial BMI. The rates of remission of diabetes, hypertension, dyslipidemia, and hyperuricemia were compared using a mixed effects logistic regression analysis. RESULTS: Diabetes before surgery was present in 12/100 lower responders and 17/100 higher responders. Remission at 2 years was observed in 4/12 (33%) of lower responders, compared to 15/17 (88%) of higher responders. Thus, the odds of diabetes remission was significantly smaller in lower responders (OR = 0.067, 95% CI 0.01-0.447). A mixed model regression analysis of all the parameters for each patient showed that the odds of achieving remission of any comorbidity was significantly lower in lower responders (OR = 0.62, 95% CI = 0.39-0.97). CONCLUSION: We could demonstrate that weight loss is a significant determinant of the remission of diabetes 2 years after RYGB. These data underline the importance of weight loss in the benefits of this procedure.

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.