A Mutation Changes Ligand Selectivity and Transmembrane Signaling Preference of the Neurokinin-1 Receptor

Abstract We studied the biochemical properties of a genetically engineered neurokinin-1 receptor (NK1R) in which two residues lying on the extracellular edge of the fourth transmembrane domain were replaced by equivalently located elements of the neurokinin-2 receptor (G166C, Y167F NK1R mutant). The mutation produced two effects. The first is enhancement of the apparent binding affinity for heterologous tachykinins (substance K and neurokinin B) and for N- or C-terminal modified analogues of substance P, but not for substance P itself, its full-length analogues, and several peptide and nonpeptide antagonists. Only two antagonists, as exceptions, were found to exhibit a diminished affinity for the mutant receptor. The second effect is a shift in NK1R preference for distinct G protein-mediated signaling pathways. NK1R-mediated phosphoinositide hydrolysis was enhanced both in transiently and permanently transfected cells, while stimulation of cAMP accumulation did not change in transient expression experiments and was reduced in permanently expressing cells. The effect of the mutation on ligand affinity was not related to any obvious structural commonality, nor to the selectivity for different neurokinin receptors or the agonistic/antagonistic nature of the ligand. However, all ligands responding to the mutation appear to share the ability to induce phosphoinositide signaling more efficiently than cAMP responses when binding to NK1R. We suggest that the mutation shifts the internal equilibria of different functional forms of NK1R. A theoretical analysis according to a multistate allosteric model suggests that the link between binding and biological changes can result from altered stability constants of substates in the conformational space of the receptor

Analysis of heterogeneity and epistasis in physiological mixed populations by combined structural equation modelling and latent class analysis

<p>Abstract</p> <p>Background</p> <p>Biological systems are interacting, molecular networks in which genetic variation contributes to phenotypic heterogeneity. This heterogeneity is traditionally modelled as a dichotomous trait (e.g. affected vs. non-affected). This is far too simplistic considering the complexity and genetic variations of such networks.</p> <p>Methods</p> <p>In this study on type 2 diabetes mellitus, heterogeneity was resolved in a latent class framework combined with structural equation modelling using phenotypic indicators of distinct physiological processes. We modelled the clinical condition "the metabolic syndrome", which is known to be a heterogeneous and polygenic condition with a clinical endpoint (type 2 diabetes mellitus). In the model presented here, genetic factors were not included and no genetic model is assumed except that genes operate in networks. The impact of stratification of the study population on genetic interaction was demonstrated by analysis of several genes previously associated with the metabolic syndrome and type 2 diabetes mellitus.</p> <p>Results</p> <p>The analysis revealed the existence of 19 distinct subpopulations with a different propensity to develop diabetes mellitus within a large healthy study population. The allocation of subjects into subpopulations was highly accurate with an entropy measure of nearly 0.9. Although very few gene variants were directly associated with metabolic syndrome in the total study sample, almost one third of all possible epistatic interactions were highly significant. In particular, the number of interactions increased after stratifying the study population, suggesting that interactions are masked in heterogenous populations. In addition, the genetic variance increased by an average of 35-fold when analysed in the subpopulations.</p> <p>Conclusion</p> <p>The major conclusions from this study are that the likelihood of detecting true association between genetic variants and complex traits increases tremendously when studied in physiological homogenous subpopulations and on inclusion of epistasis in the analysis, whereas epistasis (i.e. genetic networks) is ubiquitous and should be the basis in modelling any biological process.</p

3D facial landmarks: Inter-operator variability of manual annotation

BACKGROUND: Manual annotation of landmarks is a known source of variance, which exist in all fields of medical imaging, influencing the accuracy and interpretation of the results. However, the variability of human facial landmarks is only sparsely addressed in the current literature as opposed to e.g. the research fields of orthodontics and cephalometrics. We present a full facial 3D annotation procedure and a sparse set of manually annotated landmarks, in effort to reduce operator time and minimize the variance. METHOD: Facial scans from 36 voluntary unrelated blood donors from the Danish Blood Donor Study was randomly chosen. Six operators twice manually annotated 73 anatomical and pseudo-landmarks, using a three-step scheme producing a dense point correspondence map. We analyzed both the intra- and inter-operator variability, using mixed-model ANOVA. We then compared four sparse sets of landmarks in order to construct a dense correspondence map of the 3D scans with a minimum point variance. RESULTS: The anatomical landmarks of the eye were associated with the lowest variance, particularly the center of the pupils. Whereas points of the jaw and eyebrows have the highest variation. We see marginal variability in regards to intra-operator and portraits. Using a sparse set of landmarks (n=14), that capture the whole face, the dense point mean variance was reduced from 1.92 to 0.54 mm. CONCLUSION: The inter-operator variability was primarily associated with particular landmarks, where more leniently landmarks had the highest variability. The variables embedded in the portray and the reliability of a trained operator did only have marginal influence on the variability. Further, using 14 of the annotated landmarks we were able to reduced the variability and create a dense correspondences mesh to capture all facial features

Is an Early Age at Illness Onset in Schizophrenia Associated With Increased Genetic Susceptibility?

Background: Early age at illness onset has been viewed as an important liability marker for schizophrenia, which may be associated with an increased genetic vulnerability. A twin approach can be valuable, because it allows for the investigation of specific illness markers in individuals with a shared genetic background. Methods: We linked nationwide registers to identify a cohort of twin pairs born in Denmark from 1951 to 2000 (N = 31,524 pairs), where one or both twins had a diagnosis in the schizophrenia spectrum. We defined two groups consisting of; N = 788 twin pairs (affected with schizophrenia spectrum) and a subsample of N = 448 (affected with schizophrenia). Survival analysis was applied to investigate the effect of age at illness onset. Findings: We found that early age at illness onset compared to later onset in the first diagnosed twin can be considered a major risk factor for developing schizophrenia in the second twin. Additionally, we found that the stronger genetic component in MZ twins compared to DZ twins is manifested in the proximity of assigned diagnosis within pairs. Discussion: Early onset schizophrenia could be linked to a more severe genetic predisposition, indicating that age might be perceived as a clinical marker for genetic vulnerability for the illness

Гестационный транзиторный тиреотоксикоз

Приведены современные данные литературы о гестационном транзиторном тиреотоксикозе. Освещены особенности гормональной регуляции щитовидной железы.Modern literature data about gestation thyrotoxicosis are presented. The peculiarities of hormonal regulation of the thyroid gland are featured

A large population-based investigation into the genetics of susceptibility to gastrointestinal infections and the link between gastrointestinal infections and mental illness.

Gastrointestinal infections can be life threatening, but not much is known about the host's genetic contribution to susceptibility to gastrointestinal infections or the latter's association with psychiatric disorders. We utilized iPSYCH, a genotyped population-based sample of individuals born between 1981 and 2005 comprising 65,534 unrelated Danish individuals (45,889 diagnosed with mental disorders and 19,645 controls from a random population sample) in which all individuals were linked utilizing nationwide population-based registers to estimate the genetic contribution to susceptibility to gastrointestinal infections, identify genetic variants associated with gastrointestinal infections, and examine the link between gastrointestinal infections and psychiatric and neurodevelopmental disorders. The SNP heritability of susceptibility to gastrointestinal infections ranged from 3.7% to 6.4% on the liability scale. Significant correlations were found between gastrointestinal infections and the combined group of mental disorders (OR = 2.09; 95% CI: 1.82-2.4, P = 1.87 × 10-25). Correlations with autism spectrum disorder, attention deficit hyperactivity disorder, and depression were also significant. We identified a genome-wide significant locus associated with susceptibility to gastrointestinal infections (OR = 1.13; 95% CI: 1.08-1.18, P = 2.9 × 10-8), where the top SNP was an eQTL for the ABO gene. The risk allele was associated with reduced ABO expression, providing, for the first time, genetic evidence to support previous studies linking the O blood group to gastrointestinal infections. This study also highlights the importance of integrative work in genetics, psychiatry, infection, and epidemiology on the road to translational medicine