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The phenotypic correlation between human intelligence and brain volume (BV) is considerable (r≈0.40), and has been shown to be due to shared genetic factors1. To further examine specific genetic factors driving this correlation, we present genomic analyses of the genetic overlap between intelligence and BV using genome-wide association study (GWAS) results. First, we conducted the largest BV GWAS meta-analysis to date (N=54,407 individuals), followed by functional annotation and gene-mapping. We identified 35 genomic loci (27 novel), implicating 362 genes (346 novel) and 23 biological pathways for BV. Second, we used an existing GWAS for intelligence (N=269,867 individuals2), and estimated the genetic correlation (rg) between BV and intelligence to be 0.23. We show that the rg is driven by physical overlap of GWAS hits in 5 genomic loci. We identified 67 shared genes between BV and intelligence, which are mainly involved in important signaling pathways regulating cell growth. Out of these 67 we prioritized 32 that are most likely to have functional impact. These results provide new information on the genetics of BV and provide biological insight into BV’s shared genetic etiology with intelligence.

Insomnia is the second-most prevalent mental disorder, with no sufficient treatment available. Despite a substantial role of genetic factors, only a handful of genes have been implicated and insight into the associated neurobiological pathways remains limited. Here, we use an unprecedented large genetic association sample (N=1,331,010) to allow detection of a substantial number of genetic variants and gain insight into biological functions, cell types and tissues involved in insomnia complaints. We identify 202 genome-wide significant loci implicating 956 genes through positional, eQTL and chromatin interaction mapping. We show involvement of the axonal part of neurons, of specific cortical and subcortical tissues, and of two specific cell-types in insomnia: striatal medium spiny neurons and hypothalamic neurons. These cell-types have been implicated previously in the regulation of reward processing, sleep and arousal in animal studies, but have never been genetically linked to insomnia in humans. We found weak genetic correlations with other sleep-related traits, but strong genetic correlations with psychiatric and metabolic traits. Mendelian randomization identified causal effects of insomnia on specific psychiatric and metabolic traits. Our findings reveal key brain areas and cells implicated in the neurobiology of insomnia and its related disorders, and provide novel targets for treatment.

Intelligence is highly heritable 1 and a major determinant of human health and well-being 2 . Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence 3-7 , but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders. © 2018 The Author(s).

Genetic and environmental factors interact throughout life and give rise to individual differences, i.e., individuality. The diversifying effect of environmental factors is counteracted by genetic mechanisms to yield persistence of specific features (robustness). Here, we compared robustness between cohorts of isogenic mice of eight different commonly used strains by analyzing to what extent environmental variation contributed to individuality in each of the eight genotypes, using a previously published dataset. Behavior was assessed in the home-cage, providing control over environmental factors, to reveal within-strain variability in numerous spontaneous behaviors. Indeed, despite standardization and in line with previous studies, substantial variability among mice of the same inbred strain was observed. Strikingly, across a multidimensional set of 115 behavioral parameters, several strains consistently ranked high in within-strain variability (DBA/2J, 129S1/Sv A/J and NOD/LtJ), whereas other strains ranked low (C57BL/6J and BALB/c). Strain rankings of within-strain variability in behavior were confirmed in an independent, previously published behavioral dataset using conventional behavioral tests administered to different mice from the same breeding colonies. Together, these show that genetically inbred mouse strains consistently differ in phenotypic robustness against environmental variation, suggesting that genetic factors contribute to variation in robustness.

Individuals are able to change their behavior based on its consequences, a process involving instrumental learning. Studying instrumental learning in mice can provide new insights in this elementary aspect of cognition. Conventional appetitive operant learning tasks that facilitate the study of this form of learning in mice, as well as more complex operant paradigms, require labor-intensive handling and food deprivation to motivate the animals. Here, we describe a 1-night operant learning protocol that exploits the advantages of automated home-cage testing and circumvents the interfering effects of food restriction. The task builds on behavior that is part of the spontaneous exploratory tepertoire during the days before the task. We compared the behavior of C57BL/6J, BALB/cJ and DBA/2J mice and found various differences in behavior during this task, but no differences in learning curves. BALB/cJ mice showed the largest instrumental learning response, providing a superior dynamic range and statistical power to study instrumental learning by using this protocol. Insights gained with this home-cage-based learning protocol without food restriction will be valuable for the development of other, more complex, cognitive tasks in automated home-cages. (C) 2015 Elsevier B.V. All rights reserved.

Functional genetic analyses in mice rely on efficient and in-depth characterization of the behavioral spectrum. Automated home-cage observation can provide a systematic and efficient screening method to detect unexplored, novel behavioral phenotypes. Here, we analyzed high-throughput automated home-cage data using existing and novel concepts, to detect a plethora of genetic differences in spontaneous behavior in a panel of commonly used inbred strains (129S1/SvImJ, A/J, C3H/HeJ, C57BL/6J, BALB/cJ, DBA/2J, NOD/LtJ, FVB/NJ, WSB/EiJ, PWK/PhJ and CAST/EiJ). Continuous video-tracking observations of sheltering behavior and locomotor activity were segmented into distinguishable behavioral elements, and studied at different time scales, yielding a set of 115 behavioral parameters of which 105 showed highly significant strain differences. This set of 115 parameters was highly dimensional; principal component analysis identified 26 orthogonal components with eigenvalues above one. Especially novel parameters of sheltering behavior and parameters describing aspects of motion of the mouse in the home-cage showed high genetic effect sizes. Multi-day habituation curves and patterns of behavior surrounding dark/light phase transitions showed striking strain differences, albeit with lower genetic effect sizes. This spontaneous home-cage behavior study demonstrates high dimensionality, with a strong genetic contribution to specific sets of behavioral measures. Importantly, spontaneous home-cage behavior analysis detects genetic effects that cannot be studied in conventional behavioral tests, showing that the inclusion of a few days of undisturbed, labor extensive home-cage assessment may greatly aid gene function analyses and drug target discovery.

In dit rapport analyseert het PBL de effecten van de landbouw op de leefomgeving, evenals, in bredere zin, de voortgang van de verduurzaming van het voedselsysteem. We evalueren bovendien de effectiviteit van het Nederlandse overheidsbeleid als het erom gaat die effecten te verminderen. We beschrijven de belangrijkste ontwikkelingen op dit gebied in de afgelopen twee jaar, en bouwen daarbij voort op de analyse van de verduurzaming van het voedselsysteem in de vorige Balans van de Leefomgeving en het rapport De macht van het menu (PBL 2013a) maar leggen meer nadruk op de effecten voor de fysieke leefomgeving binnen Nederland.

Lee (2012) proposes that personality research should utilise recent theories of causality. Although we agree that such theories are important, we also note that their empirical application has not been very successful to date. The reason may be that psychological systems are frequently characterised by feedback, nonlinearity and individual differences in causal structure. Such features do not preclude the application of causal modelling but do limit the usefulness of the approach for the analysis of typical personality data. To adequately investigate personality, intensive time series of repeated measurements are needed.

Introduction: The tendency to develop asthma runs in families, but whether the severity of asthma symptoms is inherited is not known. Objectives: The aim of this study was to examine whether genetic factors influence the variation in the severity of asthma. Methods: Of a sample of 21133 adult twins from the Danish Twin Registry, a total of 575 subjects (256 intact pairs and 63 single twins) who themselves and/or their co-twins reported a history of asthma at a questionnaire survey were clinically examined. The severity of asthma symptoms was graded according to a clinical interview, and markers of airway impairment and allergy were measured. Results: After adjusting for confounders, genetic factors explained 24% (10%-37%), P=0.0004, of the variation in overall asthma symptom severity, whereas non-shared environment accounted for the remaining 76% of the variation. A significant genetic component was also found for the severity of specific asthma symptoms; wheezing 12% (3%-22%), P=0.007 and shortness of breath 17% (7%-27%), P=0.0006, but not for chest tightness and cough. Asthma symptom severity correlated weakly with rhinitis severity as well as with objective markers of lung function, airway inflammation, airway responsiveness and allergic sensitization. Conclusion: The individual variation in asthma symptom severity is to some degree influenced by genetic factors, but environmental factors explain the main part of the variation. The genetic architectures underlying the severity of asthma symptoms and objectively measured asthma-related traits, respectively, seem to differ. © 2011 Blackwell Publishing Ltd.

International audience; In a context of greenhouse gas emissions, oil price rising and intermittent renewable energy sources, energy storage, and more specifically thermal energy storage is one of the best candidates to reduce and optimize the energy use of refrigerating systems. Moreover, the temperature stability and the autonomy of those systems in case of power failure, related to the use of thermal energy storage devices, is also an important factor of food quality and security enhancement. The thermal energy storage (TES) technology has already attracted a number of applications. From short-term storage in food containers to long-term storage in low temperature warehouses, the food cold chain may take a full advantage of its potential. Coupled with control strategies as predictive control approach, it can lead to a drastic reduction of energy consumption and a significant product quality enhancement.

International audience; In a context of greenhouse gas emissions, oil price rising and intermittent renewable energy sources, energy storage, and more specifically thermal energy storage is one of the best candidates to reduce and optimize the energy use of refrigerating systems. Moreover, the temperature stability and the autonomy of those systems in case of power failure, related to the use of thermal energy storage devices, is also an important factor of food quality and security enhancement. The thermal energy storage (TES) technology has already attracted a number of applications. From short-term storage in food containers to long-term storage in low temperature warehouses, food engineering should also take a full advantage of its potential. Coupled with control strategies as predictive control approach, it can lead to a drastic reduction of energy consumption and a significant product quality enhancement. Through two cases, this paper proposes to show the potential of those technologies for food applications.

For reducing energy use for cooling, alternative methods (that do not rely on electricity) are needed. Renewable cooling is based on naturally available resources such as evaporative cooling, free cooling, phase change materials, ground subcooling, solar cooling, wind cooling, night radiation & storage. The project was aimed to create innovative combinations of these renewable cooling technologies and sophisticated control systems, to design renewable climate systems for various applications, amongst which a cold store for agro produce and air conditioning for utilities. Dit onderzoeksproject is gericht op de vraag welke alternatieve koelmethoden (die geen of substantieel minder gebruik maken van fossiele energie) wereldwijd beschikbaar zijn en betekenis deze kunnen hebben in de Nederlandse situaties (uitgaande van de specifieke klimaatcondities en belangrijkste toepassingvelden). De duurzame koelmethoden zoals hier beoogd zijn bekend onder de benaming Renewable Cooling: Renewable Cooling technieken maken gebruik van 'natuurlijke processen'; daarbij wordt gebruik gemaakt van o.a. verdampingskoeling, bodemkoeling, zon, wind en koudebuffering. Dit rapport geeft een beeld van de onderzoeksaanpak en vat de belangrijkste resultaten samen.

In de rapportage wordt een overzicht gegeven van factoren die belangrijk zijn bij het verschijnen en verdwijnen van mosselbanken in de Waddenzee. Het onderzoek is gebaseerd op een review van de literatuur en jarenlange metingen op mosselbanken. Delen van het hier gerapporteerde onderzoek zijn reeds beschreven in rapporten die uitgevoerd werden in het kader van het onderzoek naar de evaluatie van het schelpdiervisserijbeleid (het EVA-II onderzoek)