New analysis method of the halo phenomenon in finite many-fermion systems. First applications to medium-mass atomic nuclei

A new analysis method to investigate halos in finite many-fermion systems is designed, as existing characterization methods are proven to be incomplete/inaccurate. A decomposition of the internal wave-function of the {$N$-body} system in terms of overlap functions allows a model-independent analysis of medium-range and asymptotic properties of the internal one-body density. The existence of a spatially decorrelated region in the density profile is related to the existence of three typical energy scales in the excitation spectrum of the {$(N-1)$-body} system. A series of model-independent measures, taking the internal density as the only input, are introduced. The new measures allow a quantification of the potential halo in terms of the average number of fermions participating to it and of its impact on the system extension. Those new "halo factors" are validated through simulations and applied to results obtained through energy density functional calculations of medium-mass nuclei. Performing spherical Hartree-Fock-Bogoliubov calculations with state-of-the-art Skyrme plus pairing functionals, a collective halo is predicted in drip-line Cr isotopes, whereas no such effect is seen in Sn isotopes.Comment: 27 Pages, 29 Figures. Accepted for publication in Phys. Rev. C back-to-back with second part (arXiv:0711.1275

The nuclear energy density functional formalism

The present document focuses on the theoretical foundations of the nuclear energy density functional (EDF) method. As such, it does not aim at reviewing the status of the field, at covering all possible ramifications of the approach or at presenting recent achievements and applications. The objective is to provide a modern account of the nuclear EDF formalism that is at variance with traditional presentations that rely, at one point or another, on a {\it Hamiltonian-based} picture. The latter is not general enough to encompass what the nuclear EDF method represents as of today. Specifically, the traditional Hamiltonian-based picture does not allow one to grasp the difficulties associated with the fact that currently available parametrizations of the energy kernel $E[g',g]$ at play in the method do not derive from a genuine Hamilton operator, would the latter be effective. The method is formulated from the outset through the most general multi-reference, i.e. beyond mean-field, implementation such that the single-reference, i.e. "mean-field", derives as a particular case. As such, a key point of the presentation provided here is to demonstrate that the multi-reference EDF method can indeed be formulated in a {\it mathematically} meaningful fashion even if $E[g',g]$ does {\it not} derive from a genuine Hamilton operator. In particular, the restoration of symmetries can be entirely formulated without making {\it any} reference to a projected state, i.e. within a genuine EDF framework. However, and as is illustrated in the present document, a mathematically meaningful formulation does not guarantee that the formalism is sound from a {\it physical} standpoint. The price at which the latter can be enforced as well in the future is eventually alluded to.Comment: 64 pages, 8 figures, submitted to Euroschool Lecture Notes in Physics Vol.IV, Christoph Scheidenberger and Marek Pfutzner editor

Genetics and beyond - the transcriptome of human monocytes and disease susceptibility

BACKGROUND: Variability of gene expression in human may link gene sequence variability and phenotypes; however, non-genetic variations, alone or in combination with genetics, may also influence expression traits and have a critical role in physiological and disease processes. METHODOLOGY/PRINCIPAL FINDINGS: To get better insight into the overall variability of gene expression, we assessed the transcriptome of circulating monocytes, a key cell involved in immunity-related diseases and atherosclerosis, in 1,490 unrelated individuals and investigated its association with >675,000 SNPs and 10 common cardiovascular risk factors. Out of 12,808 expressed genes, 2,745 expression quantitative trait loci were detected (P<5.78x10(-12)), most of them (90%) being cis-modulated. Extensive analyses showed that associations identified by genome-wide association studies of lipids, body mass index or blood pressure were rarely compatible with a mediation by monocyte expression level at the locus. At a study-wide level (P<3.9x10(-7)), 1,662 expression traits (13.0%) were significantly associated with at least one risk factor. Genome-wide interaction analyses suggested that genetic variability and risk factors mostly acted additively on gene expression. Because of the structure of correlation among expression traits, the variability of risk factors could be characterized by a limited set of independent gene expressions which may have biological and clinical relevance. For example expression traits associated with cigarette smoking were more strongly associated with carotid atherosclerosis than smoking itself. CONCLUSIONS/SIGNIFICANCE: This study demonstrates that the monocyte transcriptome is a potent integrator of genetic and non-genetic influences of relevance for disease pathophysiology and risk assessment

Integrative genomic analysis of the human immune response to influenza vaccination

Identification of the host genetic factors that contribute to variation in vaccine responsiveness may uncover important mechanisms affecting vaccine efficacy. We carried out an integrative, longitudinal study combining genetic, transcriptional, and immunologic data in humans given seasonal influenza vaccine. We identified 20 genes exhibiting a transcriptional response to vaccination, significant genotype effects on gene expression, and correlation between the transcriptional and antibody responses. The results show that variation at the level of genes involved in membrane trafficking and antigen processing significantly influences the human response to influenza vaccination. More broadly, we demonstrate that an integrative study design is an efficient alternative to existing methods for the identification of genes involved in complex traits. DOI: http://dx.doi.org/10.7554/eLife.00299.00

Statistical colocalization of monocyte gene expression and genetic risk variants for type 1 diabetes

One mechanism by which disease-associated DNA variation can alter disease risk is altering gene expression. However, linkage disequilibrium (LD) between variants, mostly single-nucleotide polymorphisms (SNPs), means it is not sufficient to show that a particular variant associates with both disease and expression, as there could be two distinct causal variants in LD. Here, we describe a formal statistical test of colocalization and apply it to type 1 diabetes (T1D)-associated regions identified mostly through genome-wide association studies and expression quantitative trait loci (eQTLs) discovered in a recently determined large monocyte expression data set from the Gutenberg Health Study (1370 individuals), with confirmation sought in an additional data set from the Cardiogenics Transcriptome Study (558 individuals). We excluded 39 out of 60 overlapping eQTLs in 49 T1D regions from possible colocalization and identified 21 coincident eQTLs, representing 21 genes in 14 distinct T1D regions. Our results reflect the importance of monocyte (and their derivatives, macrophage and dendritic cell) gene expression in human T1D and support the candidacy of several genes as causal factors in autoimmune pancreatic beta-cell destruction, including AFF3, CD226, CLECL1, DEXI, FKRP, PRKD2, RNLS, SMARCE1 and SUOX, in addition to the recently described GPR183 (EBI2) gene

Systems genetics identifies a convergent gene network for cognition and neurodevelopmental disease

Genetic determinants of cognition are poorly characterized, and their relationship to genes that confer risk for neurodevelopmental disease is unclear. Here we performed a systems-level analysis of genome-wide gene expression data to infer gene-regulatory networks conserved across species and brain regions. Two of these networks, M1 and M3, showed replicable enrichment for common genetic variants underlying healthy human cognitive abilities, including memory. Using exome sequence data from 6,871 trios, we found that M3 genes were also enriched for mutations ascertained from patients with neurodevelopmental disease generally, and intellectual disability and epileptic encephalopathy in particular. M3 consists of 150 genes whose expression is tightly developmentally regulated, but which are collectively poorly annotated for known functional pathways. These results illustrate how systems-level analyses can reveal previously unappreciated relationships between neurodevelopmental disease–associated genes in the developed human brain, and provide empirical support for a convergent gene-regulatory network influencing cognition and neurodevelopmental disease

Expression QTLs Mapping and Analysis: A Bayesian Perspective.

The aim of expression Quantitative Trait Locus (eQTL) mapping is the identification of DNA sequence variants that explain variation in gene expression. Given the recent yield of trait-associated genetic variants identified by large-scale genome-wide association analyses (GWAS), eQTL mapping has become a useful tool to understand the functional context where these variants operate and eventually narrow down functional gene targets for disease. Despite its extensive application to complex (polygenic) traits and disease, the majority of eQTL studies still rely on univariate data modeling strategies, i.e., testing for association of all transcript-marker pairs. However these "one at-a-time" strategies are (1) unable to control the number of false-positives when an intricate Linkage Disequilibrium structure is present and (2) are often underpowered to detect the full spectrum of trans-acting regulatory effects. Here we present our viewpoint on the most recent advances on eQTL mapping approaches, with a focus on Bayesian methodology. We review the advantages of the Bayesian approach over frequentist methods and provide an empirical example of polygenic eQTL mapping to illustrate the different properties of frequentist and Bayesian methods. Finally, we discuss how multivariate eQTL mapping approaches have distinctive features with respect to detection of polygenic effects, accuracy, and interpretability of the results

Integrating Genome-Wide Genetic Variations and Monocyte Expression Data Reveals Trans-Regulated Gene Modules in Humans

One major expectation from the transcriptome in humans is to characterize the biological basis of associations identified by genome-wide association studies. So far, few cis expression quantitative trait loci (eQTLs) have been reliably related to disease susceptibility. Trans-regulating mechanisms may play a more prominent role in disease susceptibility. We analyzed 12,808 genes detected in at least 5% of circulating monocyte samples from a population-based sample of 1,490 European unrelated subjects. We applied a method of extraction of expression patterns—independent component analysis—to identify sets of co-regulated genes. These patterns were then related to 675,350 SNPs to identify major trans-acting regulators. We detected three genomic regions significantly associated with co-regulated gene modules. Association of these loci with multiple expression traits was replicated in Cardiogenics, an independent study in which expression profiles of monocytes were available in 758 subjects. The locus 12q13 (lead SNP rs11171739), previously identified as a type 1 diabetes locus, was associated with a pattern including two cis eQTLs, RPS26 and SUOX, and 5 trans eQTLs, one of which (MADCAM1) is a potential candidate for mediating T1D susceptibility. The locus 12q24 (lead SNP rs653178), which has demonstrated extensive disease pleiotropy, including type 1 diabetes, hypertension, and celiac disease, was associated to a pattern strongly correlating to blood pressure level. The strongest trans eQTL in this pattern was CRIP1, a known marker of cellular proliferation in cancer. The locus 12q15 (lead SNP rs11177644) was associated with a pattern driven by two cis eQTLs, LYZ and YEATS4, and including 34 trans eQTLs, several of them tumor-related genes. This study shows that a method exploiting the structure of co-expressions among genes can help identify genomic regions involved in trans regulation of sets of genes and can provide clues for understanding the mechanisms linking genome-wide association loci to disease

Systems genetics identifies Sestrin 3 as a regulator of a proconvulsant gene network in human epileptic hippocampus

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