The Swedish Twin Registry : establishment of a biobank and other recent developments

The Swedish Twin Registry (STR) today contains more than 194,000 twins and more than 75,000 pairs have zygosity determined by an intra-pair similarity algorithm, DNA, or by being of opposite sex. Of these, approximately 20,000, 25,000, and 30,000 pairs are monozygotic, same-sex dizygotic, and opposite-sex dizygotic pairs, respectively. Since its establishment in the late 1950s, the STR has been an important epidemiological resource for the study of genetic and environmental influences on a multitude of traits, behaviors, and diseases. Following large investments in the collection of biological specimens in the past 10 years we have now established a Swedish twin biobank with DNA from 45,000 twins and blood serum from 15,000 twins, which effectively has also transformed the registry into a powerful resource for molecular studies. We here describe the main projects within which the new collections of both biological samples as well as phenotypic measures have been collected. Coverage by year of birth, zygosity determination, ethnic heterogeneity, and influences of in vitro fertilization are also described.VetenskapsrådetNIHSSFHjärt- och LungfondenAstma- och AllergiförbundetAccepte

A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model

<p>Abstract</p> <p>Background</p> <p>Bioactivity profiling using high-throughput <it>in vitro </it>assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also reduce the need for animal testing. Several public efforts are aimed at discovering patterns or classifiers in high-dimensional bioactivity space that predict tissue, organ or whole animal toxicological endpoints. Supervised machine learning is a powerful approach to discover combinatorial relationships in complex <it>in vitro/in vivo </it>datasets. We present a novel model to simulate complex chemical-toxicology data sets and use this model to evaluate the relative performance of different machine learning (ML) methods.</p> <p>Results</p> <p>The classification performance of Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Naïve Bayes (NB), Recursive Partitioning and Regression Trees (RPART), and Support Vector Machines (SVM) in the presence and absence of filter-based feature selection was analyzed using K-way cross-validation testing and independent validation on simulated <it>in vitro </it>assay data sets with varying levels of model complexity, number of irrelevant features and measurement noise. While the prediction accuracy of all ML methods decreased as non-causal (irrelevant) features were added, some ML methods performed better than others. In the limit of using a large number of features, ANN and SVM were always in the top performing set of methods while RPART and KNN (k = 5) were always in the poorest performing set. The addition of measurement noise and irrelevant features decreased the classification accuracy of all ML methods, with LDA suffering the greatest performance degradation. LDA performance is especially sensitive to the use of feature selection. Filter-based feature selection generally improved performance, most strikingly for LDA.</p> <p>Conclusion</p> <p>We have developed a novel simulation model to evaluate machine learning methods for the analysis of data sets in which in vitro bioassay data is being used to predict in vivo chemical toxicology. From our analysis, we can recommend that several ML methods, most notably SVM and ANN, are good candidates for use in real world applications in this area.</p

Caenorhabditis elegans behavioral genetics: where are the knobs?

Thousands of behavioral mutants of Caenorhabditis elegans have been studied. I suggest a set of criteria by which some genes important in the evolution of behavior might be recognized, and identify neuropeptide signaling pathways as candidates

ApoB100-LDL Acts as a Metabolic Signal from Liver to Peripheral Fat Causing Inhibition of Lipolysis in Adipocytes

International audienceBACKGROUND: Free fatty acids released from adipose tissue affect the synthesis of apolipoprotein B-containing lipoproteins and glucose metabolism in the liver. Whether there also exists a reciprocal metabolic arm affecting energy metabolism in white adipose tissue is unknown. METHODS AND FINDINGS: We investigated the effects of apoB-containing lipoproteins on catecholamine-induced lipolysis in adipocytes from subcutaneous fat cells of obese but otherwise healthy men, fat pads from mice with plasma lipoproteins containing high or intermediate levels of apoB100 or no apoB100, primary cultured adipocytes, and 3T3-L1 cells. In subcutaneous fat cells, the rate of lipolysis was inversely related to plasma apoB levels. In human primary adipocytes, LDL inhibited lipolysis in a concentration-dependent fashion. In contrast, VLDL had no effect. Lipolysis was increased in fat pads from mice lacking plasma apoB100, reduced in apoB100-only mice, and intermediate in wild-type mice. Mice lacking apoB100 also had higher oxygen consumption and lipid oxidation. In 3T3-L1 cells, apoB100-containing lipoproteins inhibited lipolysis in a dose-dependent fashion, but lipoproteins containing apoB48 had no effect. ApoB100-LDL mediated inhibition of lipolysis was abolished in fat pads of mice deficient in the LDL receptor (Ldlr(-/-)Apob(100/100)). CONCLUSIONS: Our results show that the binding of apoB100-LDL to adipocytes via the LDL receptor inhibits intracellular noradrenaline-induced lipolysis in adipocytes. Thus, apoB100-LDL is a novel signaling molecule from the liver to peripheral fat deposits that may be an important link between atherogenic dyslipidemias and facets of the metabolic syndrome

Avpr1a variant associated with preschoolers' lower altruistic behavior

10.1371/journal.pone.0025274PLoS ONE69

Generation of Induced Pluripotent Stem Cells from the Prairie Vole

The vast majority of animals mate more or less promiscuously. A few mammals, including humans, utilize more restrained mating strategies that entail a longer term affiliation with a single mating partner. Such pair bonding mating strategies have been resistant to genetic analysis because of a lack of suitable model organisms. Prairie voles are small mouse-like rodents that form enduring pair bonds in the wild as well as in the laboratory, and consequently they have been used widely to study social bonding behavior. The lack of targeted genetic approaches in this species however has restricted the study of the molecular and neural circuit basis of pair bonds. As a first step in rendering the prairie vole amenable to reverse genetics, we have generated induced pluripotent stem cell (IPSC) lines from prairie vole fibroblasts using retroviral transduction of reprogramming factors. These IPSC lines display the cellular and molecular hallmarks of IPSC cells from other organisms, including mice and humans. Moreover, the prairie vole IPSC lines have pluripotent differentiation potential since they can give rise to all three germ layers in tissue culture and in vivo. These IPSC lines can now be used to develop conditions that facilitate homologous recombination and eventually the generation of prairie voles bearing targeted genetic modifications to study the molecular and neural basis of pair bond formation

Common marmoset (Callithrix jacchus) personality, subjective well-being, hair cortisol level and AVPR1a, OPRM1, and DAT genotypes

We studied personality, subjective well-being, and hair cortisol level, in common marmosets Callithrix jacchus, a small, cooperatively breeding New World monkey, by examining their associations with one another and genotypes. Subjects were 68 males and 9 females that lived in the RIKEN Center for Life Science Technologies. Personality and subjective well-being were assessed by keeper ratings on two questionnaires, hair samples were obtained to assay cortisol level and buccal swabs were used to assess AVPR1a, OPRM1 and DAT genotypes. Three personality domains—Dominance, Sociability, and Neuroticism—were identified. Consistent with findings in other species, Sociability and Neuroticism were related to higher and lower subjective well-being, respectively. Sociability was also associated with higher hair cortisol levels. The personality domains and hair cortisol levels were heritable and associated with genotypes: the short form of AVPR1a was associated with lower Neuroticism and the AA genotype of the A111T SNP of OPRM1 was related to lower Dominance, lower Neuroticism, and higher hair cortisol level. Some genetic associations were not in directions that one would expect given findings in other species. These findings provide insights into the proximate and ultimate bases of personality in common marmosets, other primates and humans

An intrinsic vasopressin system in the olfactory bulb is involved in social recognition

Many peptides, when released as chemical messengers within the brain, have powerful influences on complex behaviours. Most strikingly, vasopressin and oxytocin, once thought of as circulating hormones whose actions were confined to peripheral organs, are now known to be released in the brain where they play fundamentally important roles in social behaviours1. In humans, disruptions of these peptide systems have been linked to several neurobehavioural disorders, including Prader-Willi syndrome, affective disorders, and obsessive-compulsive disorder, and polymorphisms of the vasopressin V1a receptor have been linked to autism2,3. Here we report that the rat olfactory bulb contains a large population of interneurones which express vasopressin, that blocking the actions of vasopressin in the olfactory bulb impairs the social recognition abilities of rats, and that vasopressin agonists and antagonists can modulate the processing of information by olfactory bulb neurones. The findings indicate that social information is processed in part by a vasopressin system intrinsic to the olfactory system

Systemic HIV and SIV latency reversal via non-canonical NF-κB signalling in vivo

Long-lasting, latently infected resting CD4+ T cells are the greatest obstacle to obtaining a cure for HIV infection, as these cells can persist despite decades of treatment with antiretroviral therapy (ART). Estimates indicate that more than 70 years of continuous, fully suppressive ART are needed to eliminate the HIV reservoir1. Alternatively, induction of HIV from its latent state could accelerate the decrease in the reservoir, thus reducing the time to eradication. Previous attempts to reactivate latent HIV in preclinical animal models and in clinical trials have measured HIV induction in the peripheral blood with minimal focus on tissue reservoirs and have had limited effect2–9. Here we show that activation of the non-canonical NF-κB signalling pathway by AZD5582 results in the induction of HIV and SIV RNA expression in the blood and tissues of ART-suppressed bone-marrow–liver–thymus (BLT) humanized mice and rhesus macaques infected with HIV and SIV, respectively. Analysis of resting CD4+ T cells from tissues after AZD5582 treatment revealed increased SIV RNA expression in the lymph nodes of macaques and robust induction of HIV in almost all tissues analysed in humanized mice, including the lymph nodes, thymus, bone marrow, liver and lung. This promising approach to latency reversal—in combination with appropriate tools for systemic clearance of persistent HIV infection—greatly increases opportunities for HIV eradication