Regulation of Src and Csk nonreceptor tyrosine kinases in the filasterean Ministeria vibrans

ACS AuthorChoice - This is an open access article published under an ACS AuthorChoice License, which permits copying and redistribution of the article or any adaptations for non-commercial purposes.The development of the phosphotyrosine-based signaling system predated the evolution of multicellular animals. Single-celled choanoflagellates, the closest living relatives to metazoans, possess numerous tyrosine kinases, including Src family nonreceptor tyrosine kinases. Choanoflagellates also have Csk (C-terminal Src kinase), the enzyme that regulates Src in metazoans; however, choanoflagellate Csk kinases fail to repress the cognate Src. Here, we have cloned and characterized Src and Csk kinases from Ministeria vibrans, a filasterean (the sister group to metazoans and choanoflagellates). The two Src kinases (MvSrc1 and MvSrc2) are enzymatically active Src kinases, although they have low activity toward mammalian cellular proteins. Unexpectedly, MvSrc2 has significant Ser/Thr kinase activity. The Csk homologue (MvCsk) is enzymatically inactive and fails to repress MvSrc activity. We suggest that the low activity of MvCsk is due to sequences in the SH2-kinase interface, and we show that a point mutation in this region partially restores MvCsk activity. The inactivity of filasterean Csk kinases is consistent with a model in which the stringent regulation of Src family kinases arose more recently in evolution, after the split between choanoflagellates and multicellular animals. © 2014 American Chemical Society.Peer Reviewe

Heaviness, health and happiness: a cross-sectional study of 163 066 UK Biobank participants

<b>Background</b><p></p> Obesity is known to increase the risk of many diseases and reduce overall quality of life. This study examines the relationship with self-reported health (SRH) and happiness.<p></p> <b>Methods</b> <p></p>We conducted a cross-sectional study of the 163 066 UK Biobank participants who completed the happiness rating. The association between adiposity and SRH and happiness was examined using logistic regression. SRH was defined as good (excellent, good), or poor (fair, poor). Self-reported happiness was defined as happy (extremely, very, moderately) or unhappy (moderately, very, extremely). <p></p> <b>Results</b> <p></p>Poor health was reported by 44 457 (27.3%) participants. The adjusted ORs for poor health were 3.86, 2.92, 2.60 and 6.41 for the highest, compared with lowest, deciles of Body Mass Index, waist circumference, waist to hip ratio and body fat percent, respectively. The associations were stronger in men (p<0.001). Overall, 7511 (4.6%) participants felt unhappy, and only class III obese participants were more likely to feel unhappy (adjusted OR 1.33, 95% CI 1.15 to 1.53, p<0.001) but the associations differed by sex (p<0.001). Among women, there was a significant association between unhappiness and all levels of obesity. By contrast, only class III obese men had significantly increased risk and overweight and class I obese men were less likely to be unhappy. <p></p> <b>Conclusions</b><p></p>Obesity impacts adversely on happiness as well as health, but the association with unhappiness disappeared after adjustment for self-reported health, indicating this may be mediated by health. Compared with obese men, obese women are less likely to report poor health, but more likely to feel unhappy. <p></p&gt

Gender differences in the association between adiposity and probable major depression: a cross-sectional study of 140,564 UK Biobank participants

<b>Background</b><p></p> Previous studies on the association between adiposity and mood disorder have produced contradictory results, and few have used measurements other than body mass index (BMI). We examined the association between probable major depression and several measurements of adiposity: BMI, waist circumference (WC), waist-hip-ratio (WHR), and body fat percentage (BF%).<p></p> <b>Methods</b><p></p> We conducted a cross-sectional study using baseline data on the sub-group of UK Biobank participants who were assessed for mood disorder. Multivariate logistic regression models were used, adjusting for potential confounders including: demographic and life-style factors, comorbidity and psychotropic medication.<p></p> <b>Results</b><p></p> Of the 140,564 eligible participants, evidence of probable major depression was reported by 30,145 (21.5%). The fully adjusted odds ratios (OR) for obese participants were 1.16 (95% confidence interval (CI) 1.12, 1.20) using BMI, 1.15 (95% CI 1.11, 1.19) using WC, 1.09 (95% CI 1.05, 1.13) using WHR and 1.18 (95% CI 1.12, 1.25) using BF% (all p <0.001). There was a significant interaction between adiposity and gender (p = 0.001). Overweight women were at increased risk of depression with a dose response relationship across the overweight (25.0-29.9 kg/m2), obese I (30.0-34.9 kg/m2), II (35.0-39.9 kg/m2) and III (≥40.0 kg/m2) categories; fully adjusted ORs 1.14, 1.20, 1.29 and 1.48, respectively (all p < 0.001). In contrast, only obese III men had significantly increased risk of depression (OR 1.29, 95% CI 1.08, 1.54, p = 0.006).<p></p> <b>Conclusion</b><p></p> Adiposity was associated with probable major depression, irrespective of the measurement used. The association was stronger in women than men. Physicians managing overweight and obese women should be alert to this increased risk

PTB Domain-Directed Substrate Targeting in a Tyrosine Kinase from the Unicellular Choanoflagellate Monosiga brevicollis

Choanoflagellates are considered to be the closest living unicellular relatives of metazoans. The genome of the choanoflagellate Monosiga brevicollis contains a surprisingly high number and diversity of tyrosine kinases, tyrosine phosphatases, and phosphotyrosine-binding domains. Many of the tyrosine kinases possess combinations of domains that have not been observed in any multicellular organism. The role of these protein interaction domains in M. brevicollis kinase signaling is not clear. Here, we have carried out a biochemical characterization of Monosiga HMTK1, a protein containing a putative PTB domain linked to a tyrosine kinase catalytic domain. We cloned, expressed, and purified HMTK1, and we demonstrated that it possesses tyrosine kinase activity. We used immobilized peptide arrays to define a preferred ligand for the third PTB domain of HMTK1. Peptide sequences containing this ligand sequence are phosphorylated efficiently by recombinant HMTK1, suggesting that the PTB domain of HMTK1 has a role in substrate recognition analogous to the SH2 and SH3 domains of mammalian Src family kinases. We suggest that the substrate recruitment function of the noncatalytic domains of tyrosine kinases arose before their roles in autoinhibition

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods - recursive partitioning and regression - to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; Pcombined = 2.01 × 10-19 and 2.35 × 10-13, respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes. ©2007 Nature Publishing Group

Prevalence and Characteristics of Probable Major Depression and Bipolar Disorder within UK Biobank: Cross-Sectional Study of 172,751 Participants

<b>Objectives</b> UK Biobank is a landmark cohort of over 500,000 participants which will be used to investigate genetic and non-genetic risk factors for a wide range of adverse health outcomes. This is the first study to systematically assess the prevalence and validity of proposed criteria for probable mood disorders within the cohort (major depression and bipolar disorder).<p></p> <b>Methods</b> This was a descriptive epidemiological study of 172,751 individuals assessed for a lifetime history of mood disorder in relation to a range of demographic, social, lifestyle, personality and health-related factors. The main outcomes were prevalence of a probable lifetime (single) episode of major depression, probable recurrent major depressive disorder (moderate), probable recurrent major depressive disorder (severe), probable bipolar disorder and no history of mood disorder (comparison group). Outcomes were compared on age, gender, ethnicity, socioeconomic status, educational attainment, functioning, self-reported health status, current depressive symptoms, neuroticism score, smoking status and alcohol use.<p></p> <b>Results</b> Prevalence rates for probable single lifetime episode of major depression (6.4%), probable recurrent major depression (moderate) (12.2%), probable recurrent major depression (severe) (7.2%) and probable bipolar disorder (1.3%) were comparable to those found in other population studies. The proposed diagnostic criteria have promising validity, with a gradient in evidence from no mood disorder through major depression and probable bipolar disorder in terms of gender distribution, socioeconomic status, self-reported health rating, current depressive symptoms and smoking.<p></p> <b>Significance</b> The validity of our proposed criteria for probable major depression and probable bipolar disorder within this cohort are supported by these cross-sectional analyses. Our findings are likely to prove useful as a framework for a wide range of future genetic and non-genetic studies.<p></p&gt

Association of polygenic score for major depression with response to lithium in patients with bipolar disorder

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18–2.01) and European sample: OR = 1.75 (95% CI: 1.30–2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61–4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders