Multiple regression methods show great potential for rare variant association tests

The investigation of associations between rare genetic variants and diseases or phenotypes has two goals. Firstly, the identification of which genes or genomic regions are associated, and secondly, discrimination of associated variants from background noise within each region. Over the last few years, many new methods have been developed which associate genomic regions with phenotypes. However, classical methods for high-dimensional data have received little attention. Here we investigate whether several classical statistical methods for high-dimensional data: ridge regression (RR), principal components regression (PCR), partial least squares regression (PLS), a sparse version of PLS (SPLS), and the LASSO are able to detect associations with rare genetic variants. These approaches have been extensively used in statistics to identify the true associations in data sets containing many predictor variables. Using genetic variants identified in three genes that were Sanger sequenced in 1998 individuals, we simulated continuous phenotypes under several different models, and we show that these feature selection and feature extraction methods can substantially outperform several popular methods for rare variant analysis. Furthermore, these approaches can identify which variants are contributing most to the model fit, and therefore both goals of rare variant analysis can be achieved simultaneously with the use of regression regularization methods. These methods are briefly illustrated with an analysis of adiponectin levels and variants in the ADIPOQ gene.     

Development of a panel of genome-wide ancestry informative markers to study admixture throughout the Americas

Most individuals throughout the Americas are admixed descendants of Native American, European, and African ancestors. Complex historical factors have resulted in varying proportions of ancestral contributions between individuals within and among ethnic groups. We developed a panel of 446 ancestry informative markers (AIMs) optimized to estimate ancestral proportions in individuals and populations throughout Latin America. We used genome-wide data from 953 individuals from diverse African, European, and Native American populations to select AIMs optimized for each of the three main continental populations that form the basis of modern Latin American populations. We selected markers on the basis of locus-specific branch length to be informative, well distributed throughout the genome, capable of being genotyped on widely available commercial platforms, and applicable throughout the Americas by minimizing within-continent heterogeneity. We then validated the panel in samples from four admixed populations by comparing ancestry estimates based on the AIMs panel to estimates based on genome-wide association study (GWAS) data. The panel provided balanced discriminatory power among the three ancestral populations and accurate estimates of individual ancestry proportions (R2 > 0.9 for ancestral components with significant between-subject variance). Finally, we genotyped samples from 18 populations from Latin America using the AIMs panel and estimated variability in ancestry within and between these populations. This panel and its reference genotype information will be useful resources to explore population history of admixture in Latin America and to correct for the potential effects of population stratification in admixed samples in the region.     

Ubiquitination of mammalian Pex5p, the peroxisomal import receptor

Protein translocation across the peroxisomal membrane requires the concerted action of numerous peroxins. One central component of this machinery is Pex5p, the cycling receptor for matrix proteins. Pex5p recognizes newly synthesized proteins in the cytosol and promotes their translocation across the peroxisomal membrane. After this translocation step, Pex5p is recycled back into the cytosol to start a new protein transport cycle. Here, we show that mammalian Pex5p is ubiquitinated at the peroxisomal membrane. Two different types of ubiquitination were detected, one of which is thiol-sensitive, involves Cys(11) of Pex5p, and is necessary for the export of the receptor back into the cytosol. Together with mechanistic data recently described for yeast Pex5p, these findings provide strong evidence for the existence of Pex4p- and Pex22p-like proteins in mammals.     

The Evolution of Exploitation in Humans: ‘Surrounded by Strangers I Thought Were My Friends’1

Early humans were obligately social, living in nested kin groups or close associations of related individuals. Theoretical and empirical research has demonstrated that group life is characterized by both costs (e.g. increased likelihood of disease transmission) and benefits (e.g. enhanced predator defense). This paper addresses the evolution of exploitation in humans (e.g. slavery, infanticide) as a response to within‐group competition for limiting resources (e.g. food, mates), a potential cost of living in groups. Exploitation is defined as one individual's use of another for selfish ends, in particular, the acquisition and/or use of another's resources for the optimization of inclusive fitness. It is argued that exploitation is most likely to occur in relationships characterized by asymmetries such as dependence, intimacy, and/or differential access to resources. A simple mathematical treatment assesses exploitation as a facultative response to local competition among relatives, providing insights into the conditions favorable and adverse to exploitation of conspecifics. Possible applications of the formulations are discussed, including the conditions under which intraspecific exploitation may be beneficial to both actor and recipient(s). Constraints on the evolution of exploitation in humans are identified, and suggestions are made for testing hypotheses related to the differential costs and benefits of exploitation to conspecifics. Future studies may promote the mitigation of exploitation's deleterious effects in Homo sapiens, a body of research which may apply, as well, to other social mammals.     

Involvement of c-Src tyrosine kinase in SHP-1 phosphatase activation by Ang II AT2 receptors in rat fetal tissues

Angiotensin II (Ang II) AT(2) receptors are abundantly expressed in rat fetal tissues where they probably contribute to development. In the present study we examine the effects of Ang II type 2 receptor stimulation on SHP-1 activation. Ang II (10(-7) M) elicits a rapid and transient tyrosine phosphorylation of SHP-1, maximal at 1 min, in a dose-dependent form, blocked by the AT(2) antagonist, PD123319. SHP-1 phosphorylation is followed in time by tyrosine dephosphorylation of different proteins, suggesting a sequence of events. Ang II induces association of SHP-1 to AT(2) receptors as shown by co-immunoprecipitation, Western blot and binding assays. SHP-1 activity was determined in immunocomplexes obtained with either anti-AT(2) or anti-SHP-1 antibodies, after Ang II stimulation (1 min), in correlation with the maximal level of SHP-1 phosphorylation. Interestingly, following receptor stimulation (1 min) c-Src was associated to AT(2) or SHP-1 immunocomplexes. Preincubation with the c-Src inhibitor PP2 inhibited SHP-1 activation and c-Src association, thus confirming the participation of c-Src in this pathway. We demonstrated here for the first time the involvement of c-Src in SHP-1 activation via AT(2) receptors present in an ex vivo model expressing both receptor subtypes. In this model, AT(2) receptors are not constitutively associated to SHP-1 and SHP-1 is not constitutively activated. Thus, we clearly establish that SHP-1 activation, mediated by the AT(2) subtype, involves c-Src and precedes protein tyrosine dephosphorylation, in rat fetal membranes.     

Impact of selective logging on inbreeding and gene dispersal in an Amazonian tree population of Carapa guianensis Aubl

Selective logging may impact patterns of genetic diversity within populations of harvested forest tree species by increasing distances separating conspecific trees, and modifying physical and biotic features of the forest habitat. We measured levels of gene diversity, inbreeding, pollen dispersal and spatial genetic structure (SGS) of an Amazonian insect-pollinated Carapa guianensis population before and after commercial selective logging. Similar levels of gene diversity and allelic richness were found before and after logging in both the adult and the seed generations. Pre- and post-harvest outcrossing rates were high, and not significantly different from one another. We found no significant levels of biparental inbreeding either before or after logging. Low levels of pollen pool differentiation were found, and the pre- vs. post-harvest difference was not significant. Pollen dispersal distance estimates averaged between 75 m and 265 m before logging, and between 76 m and 268 m after logging, depending on the value of tree density and the dispersal model used. There were weak and similar levels of differentiation of allele frequencies in the adults and in the pollen pool, before and after logging occurred, as well as weak and similar pre- and post-harvest levels of SGS among adult trees. The large neighbourhood sizes estimated suggest high historical levels of gene flow. Overall our results indicate that there is no clear short-term genetic impact of selective logging on this population of C. guianensis.     

Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia

Introduction

Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results.

Objectives

In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH.

Methods

Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using ¹H nuclear magnetic resonance (¹H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches.

Results

The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH.

Conclusion

PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.