Characterisation of age and polarity at onset in bipolar disorder

Background Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools. Aims To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics. Method Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts. Results Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO. Conclusions AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.publishedVersio

Characterisation of age and polarity at onset in bipolar disorder

Background Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools. Aims To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics. Method Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts. Results Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO. Conclusions AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses

Assessing volatility drivers during the Covid-19 pandemic: a sectoral approach using the GARCH model

The joint work of Adams and Hass denteufel (2021) concludes that the GARCH model is appropriate to capture stock market volatility during the Covid-19 pandemic. Here, we analyse characteristics of the 11 GICS sectors and identify their volatility drivers. We include new Covid-19cases and various independent variables as variance regressors. The Covid-19 effect on stock volatility remains positive and mostly significant for pairwise combinations of independent variables but loses significance when IRis introduced. Including more than two variance regressors, the Covid-19 effect is no longer significant for any sector while IR, CPI and EPU still hold explanatory power

Evaluation of metabolic profiles of patients with anorexia nervosa at inpatient admission, short-and long-term weight regain—descriptive and pattern analysis

10.3390/metabo11010007Metabolites111Jan-2

The predicted secretomes of Monosiga brevicollis and Capsaspora owczarzaki, close unicellular relatives of metazoans, reveal new insights into the evolution of the metazoan extracellular matrix

The extracellular matrix (ECM) is a major mediator of multi-cellularity in the metazoa. Multiple ECM proteins are conserved from sponges to human, raising questions about the evolutionary origin of ECM. Choanoflagellates are the closest unicellular relatives of the metazoa and proteins with domain characteristic of metazoan ECM proteins that have been identified from the genome-predicted proteome of the choanoflagellate Monosiga brevicollis. However, a systematic analysis of M. brevicollis secretory signal peptide-containing proteins with ECM domains has been lacking. We analysed all predicted secretory signal-peptide-containing proteins of M. brevicollis for ECM domains. Nine domains that are widespread in metazoan ECM proteins are represented, with EGF, fibronectin III, laminin G, and von Willebrand Factor_A domains being the most numerous. Three proteins contain more than one category of ECM domain, however, no proteins correspond to the domain architecture of metazoan ECM proteins. The fibronectin III domains are all present within glycoside hydrolases and none contain an integrin-binding motif. Glycosaminoglycan-binding motifs identified in animal thrombospondin type 1 domains are conserved in some M. brevicollis representatives of this domain, whereas there is little evidence of conservation of glycosaminoglycan-binding motifs in the laminin G domains. The identified proteins were compared with the predicted secretory ECM domain-containing proteins of the integrin-expressing filasterean, Capsaspora owczarzaki. C. owczarzaki encodes a smaller number of secretory, ECM domain-containing proteins and only EGF, fibronectin type III and laminin G domains are represented. The M. brevicollis and C. owczarzaki proteins have distinct domain architectures and all proteins differ in their domain architecture to metazoan ECM proteins. These identifications provide a basis for future experiments to validate the extracellular location of these proteins and uncover their functions in choanoflagellates and C. owczarzaki. The data strengthen the model that ECM proteins are metazoan-specific and evolved as innovations in the last common metazoan ancestor

The CD3 Conformational Change in the gd T Cell Receptor Is Not Triggered by Antigens but Can Be Enforced to Enhance Tumor Killing

Activation of the T cell receptor (TCR) by antigen is the key step in adaptive immunity. In the ab TCR antigen induces a conformational change at the CD3 subunits (CD3 CC) that is absolutely required for abTCR activation. Here, we demonstrate that the CD3 CC is not induced by antigen stimulation of the mouse G8 or the human Vg9Vd2 gdTCR. We find that there is a fundamental difference between the activation mechanisms of the abTCR and gdTCR that map to the constant regions of the TCRab/gd heterodimers. Enforced induction of CD3 CC with a less commonly used monoclonal anti-CD3 promoted proximal gdTCR signaling but inhibited cytokine secretion. Utilizing this knowledge, we could dramatically improve in vitro tumor cell lysis by activated human gd T cells. Thus, manipulation of the CD3 CC might be exploited to improve clinical gd T cellbased immunotherapies

Characterisation of age and polarity at onset in bipolar disorder

Background Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools. Aims To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics. Method Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts. Results Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO. Conclusions AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses