Using stratified linkage disequilibrium score regression we show that, in two measures of cognitive function, SNPs associated with cognitive function cluster in regions of the genome that are under evolutionary negative selective pressure. These conserved regions contained ~2.6% of the SNPs from each GWAS but accounted for ~40% of the SNP-based heritability. The results suggest that the search for causal variants associated with cognitive function, and those variants that exert a pleiotropic effect between cognitive function and health, will be facilitated by examining these enriched regions.Differences in general cognitive function have been shown to be partly heritable and to show genetic correlations with several psychiatric and physical disease states. However, to date, few single-nucleotide polymorphisms (SNPs) have demonstrated genome-wide significance, hampering efforts aimed at determining which genetic variants are most important for cognitive function and which regions drive the genetic associations between cognitive function and disease states. Here, we combine multiple large genome-wide association study (GWAS) data sets, from the CHARGE cognitive consortium ( Another method that can both increase statistical power and facilitates an understanding of how genetic variation can result in phenotypic variation is gene set analysis (GSA).10 GSA tests the hypothesis that a set of genes, united by a shared biological function11 or their previous association with another phenotype,12 jointly show an association with the phenotype of interest. The GSA method exploits phenotypes where a highly polygenic architecture is evident by summing the small effects of multiple variants located within the predefined gene set. GSA is not reliant on any single variant attaining genome-wide significance. As such, statistical power is increased as the number of statistical tests is reduced and individual weak effects are combined together to produce a stronger association signal.13This large difference between the variance explained by single-nucleotide polymorphisms (SNPs) that do reach genome-wide significance and heritability estimates derived using all tested SNPs, indicates that much of the heritability of general cognitive function lies in SNPs that have not attained genome-wide significance. Although an increase in sample size will result in an increase in the power to detect significant effects of SNPs in a genome-wide association study (GWAS),14 However, many methods assume only a single causal SNP in each of the genetic loci,15 which, along with being more likely to inflate the type 1 error rate,16 also fails to model a polygenic architecture. Other methods suffer from limitations such as requiring access to participants' genotypes,17 and other methods fail to account for linkage disequilibrium (LD) that can lead to the same SNP being counted multiple times within a single gene set.18 Here, we make use of a recently developed method, stratified linkage disequilibrium score regression,19 that requires access to only genome-wide association summary level data. This method utilizes information from each SNP in a functional category while explicitly modelling LD to show whether a category is associated with a greater proportion of the heritability of a trait than the proportion of SNPs it contains would suggest. We apply this method to the current largest GWAS on general cognitive function.4 We also examine specific tests of cognitive function using the UK Biobank data set. We search for an enrichment in the heritability found in 52 regions corresponding to functional annotations from across cell types, and 10 corresponding to cell-specific functional groups  based on the UK Biobank8 with 36 035 individuals. We next derived a heritability Z-score for both of the data sets that was defined as the heritability estimate produced by LDS regression divided by its standard error. The magnitude of the heritability Z-score is affected by three properties, sample size, SNP-based heritability and the proportion of causal variants. An increase in these three properties is associated with an increase in the heritability Z-score. This indicates that the heritability Z-score is capturing information about the genetic architecture of a trait, with traits that have sufficient power, from sample size, high heritability and a high proportion of causal variants yield the greatest heritability Z-scores.The data used for this study were the summary of GWAS statistics from the CHARGE consortium study on general cognitive function in middle and older age, which had a total of 53 949 individuals,Z-score >7, as used in Finucane et al.19 was used as evidence for a sufficient polygenic signal within the data set for use with stratified LD regression. The CHARGE data set yielded a heritability Z-score of 10.54 and in the VNR test a heritability Z-score of 9.64 was derived. This indicates that both of these data sets have sufficient power for use with stratified LDS regression.Here, a heritability 4 General cognitive function describes the statistically revealed overlap between tests of cognitive function, that is, people who do well on one type of cognitive test tend to do well on others. The cognitive tests included in the general cognitive components used by the CHARGE cognitive working group's contributing cohorts generally measure fluid cognitive functions. These are functions assessed by tests that tend to include unfamiliar materials, that do not draw upon a participant's level of general knowledge, and that tend to show a negative trend with age. Each of the CHARGE GWAS project's cohorts used a different battery of mental tests. Full details of the tests used to measure general fluid cognitive function in each of the CHARGE consortium's cohorts can be found in Davies et al.4The CHARGE cognitive working group published a GWAS of general cognitive function in 53 949 middle and older age adults.et al.8The VNR test in UK Biobank consists of a series of 13 multiple choice questions that are answered in a 2 min time period. Six of the items were verbal questions and the remaining seven were numerical. An example of a verbal question is ‘Bud is to flower as child is to?' (Possible answers: ‘Grow/Develop/Improve/Adult/Old/Do not know/Prefer not to answer'). An example numerical question is ‘If sixty is more than half of seventy-five, multiply twenty-three by three. If not subtract 15 from eighty-five. Is the answer?' (Possible answers: ‘68/69/70/71/72/Do not know/Prefer not to answer'). To some extent, these questions draw upon materials and information that the participants should be familiar with and the scores on this test are stable when comparing the means between the ages of 40 and 60 years with a linear decline evident from a comparison between the ages of 60 and 70. Genotype data were available from 36 035 individuals who had completed this test. Full details of the genotyping procedures used for this phenotype can be found in Davies 8 had test–retest correlations of 0.15 (n=19 872) and 0.54 (n=20 188), respectively; in addition, the memory score was based on one 3 × 2 grid, and the reaction time test on just four trials. In addition, neither of these two tests showed significant genetic correlations with a general factor of cognitive ability constructed using validated tests .7 The VNR test, which we used here, had 13 items, shows a greater level of test–retest reliability (r=0.65) and had a very high genetic correlation with a general factor of cognitive ability . On the basis of these findings we decided, a priori, not to include the memory or reaction time tests from our previous GWAS as they are unreliable and appear to have a very different genetic architecture from established indicators of general cognitive function.Although a composite measure of general cognitive ability would have been preferable to the use of a single test, some of the cognitive tests used in UK Biobank are of poor quality. The tests of memory and reaction time used in our previous Genome-Wide-Association Study (GWAS)1 we first examine the degree to which the VNR measure from UK Biobank overlaps genetically with general cognitive function. Genetic correlations were derived using the summary statistics from general cognitive function in CHARGE and VNR in UK Biobank sets using LD score regression.23 The same data processing pipeline was used here as by Bulik-Sullivan et al.23 where a minor allele frequency of >0.01 was used and only those SNPs found in the HapMap3 with 1000 Genomes EUR with a minor allele frequency of >0.5 were retained. The integrated_phase1_v3.20101123 was used for LDS regression. Also, Indels, structural variants and strand-ambiguous SNPs were removed. Genome-wide significant SNPs were removed, as well as SNPs with effect sizes of χ2>80, as the presence of outliers can increase the standard error in a regression model. LD scores and weights for use with the GWAS of European ancestry were downloaded from the Broad Institute (http://www.broadinstitute.org/~bulik/eur_ldscores/).Owing to the phenotypic overlap between tests of cognitive function,4 and VNR8 were analysed using stratified LD score regression, where we followed the data processing steps of Finucane et al.19 Stratified LD score regression belongs to a class of techniques that exploit the correlated nature of SNPs. Using this method, heritability can be derived by regressing SNP's association statistic (converted to a Z-score) onto its LD score. An LD score is the sum of squared correlations between the minor allele count of a SNP, with the minor allele count of every other SNP. As the correlational structure of the genome (LD) is used in deriving the heritability estimate, LD is controlled for. A full description of how this method works can be found in Finucane et al.19 This heritability estimate is then used to derive an enrichment metric defined as the proportion of heritability captured by the functional annotation over the proportion of SNPs contained within it, (Pr(h2)/Pr(SNPs)). This ratio describes whether a functional annotation contains a greater or lesser proportion of the heritability than would be predicted by the proportion of SNPs it contains, Pr(h2)/Pr(SNPs)=1. The proportion of the heritability for each category is used as the numerator, rather than the heritability of each category. This is due to Genomic Control (GC) being performed on most GWAS data sets and, as a result, the attenuation of the heritability estimate affects the total heritability and the heritability of each SNP set equally. As these are biased in the same direction and by the same amount, the proportion of heritability accounted for by each SNP set remains unaffected by the GC correction although the absolute heritability may change. Stratified LD scores were calculated from the European ancestry samples in the 1000 Genomes project (1000G) and only included the HapMap3 SNPs with a minor allele frequency of >0.05.General cognitive functionet al.19 were used. First, SNPs were assigned to a set of 24 overlapping publically available functional annotations. 24 A 100 bp window was also placed around chromatin immunoprecipitation and sequencing (ChIP-seq) peaks; the inclusion of these additional four sets resulted in a total of 52 overlapping functional SNP annotations which formed our baseline model. In addition, a further 10 sets were examined. These sets consisted of 220 cell-type-specific annotations for four histone marks , which were arranged into 10 broad categories corresponding to histone marks found in the central nervous system, immune and hematopoietic, adrenal/pancreas, cardiovascular, connective tissue, gastrointestinal, kidney, liver, skeletal muscle and other. The SNP sets examined here are not independent and the same SNP can appear in many of the sets examined here. The size of each of the SNP sets can be found in The same functional annotations as those reported in Finucane The 10 broad cell-type categories were then analysed by adding each of them to the full baseline model. This resulted in 10 additional tests, which included the baseline model and one of the 10 cell-type-specific groupings. In this way, enrichment for these cell-specific annotations was not driven by their also being a part of the baseline model. Multiple testing was controlled for by using false discovery rate correction applied to these 10 tests.rg=0.783, s.e.=0.056, P=4.63 × 10−45 indicating that many of the same genetic variants are involved in both these traits.LDS regression was first used to determine the degree of overlap between the two cognitive phenotypes used. The genetic correlation between general cognitive function and VNR was 25 SNPs that are found in evolutionarily conserved regions showed a high level of enrichment, where 2.5% of the SNPs accounted for 49.2% of the total heritability yielding an enrichment metric defined as Pr(h2)/Pr(SNPs) of 18.87 (s.e.=3.91), P=4.88 × 10−6. Note that this does not mean that the 3% of the genome accounts for 40% of the total phenotypic variance; rather, it means that, of the 30% of phenotypic variance accounted for by common SNPs, the genetic variation in the ~3% of the genome accounts for 40% of that 30%. Statistically significant enrichment was also found after a 500 bp boundary was set around these regions , and within 500 bp of H3K4me1, where 60.9% of the SNPs collectively explained 87.5% of the total heritability . SNPs located within 500 bp of repressed regions showed a significant reduction in the level of heritability they captured. These regions accounted for 71.9% of the SNPs, but only explained 44.3% of the heritability .Enrichment was also found for two of the histone marks, H3K9ac, where 46.3% of the heritability was found for 12.6% of SNPs . SNPs within 500 bp of the functional category of DNase hypersensitivity sites also demonstrated significant enrichment for general cognitive function . These regions accounted for 49.9% of the SNPs but captured 100% of the heritability (s.e.=16%). Although this does appear to be capturing the sum of the heritability present, it is not clear whether this is biologically meaningful as the inclusion of SNPs within 500 bp of this category raises the proportion of SNPs in the category from 17% to 50% indicating that the majority of the SNPs within the larger set are not at DNaseI hypersensitivity site. SNPs found within 500 bp of introns were also significantly enriched, accounting for 39% of the SNPs and 56% of the heritability of general cognitive function, P=7.45 × 10−4.Statistically significant enrichment was also found for SNPs within 500 bp of weak enhancer regions which comprised 8.9% of the SNPs, that collectively explained 38.1% of the heritability of general cognitive function . The results for the 10 tissue types can be seen in The results for the cell type enrichment analysis indicated that histones that are marked specifically in cell types of the central nervous system accounted for 14.9% of the SNPs, but 45.0% of the heritability . As was found for general cognitive function, SNPs within 500 bp of introns also showed enrichment for heritability . This category contained 39.7% of the SNP that explained 56.2% of the heritability. Unlike general cognitive function, SNPs within 500 bp of the histone mark H3K9ac showed significant enrichment, rather than only SNPs found within this annotation . This category contained 23.1% of the SNPs, which explained 58.1% of the heritability for VNR in the UK Biobank data set.The pattern of enrichment followed the same trend for VNR as for general cognitive function. Four of the five functional annotations found to be significantly enriched in general cognitive function were also enriched for VNR . For theP=2.40 × 10−5). The enrichment results for each of the 10 tissue types can be seen in As was found in general cognitive function, histone marks specifically expressed in the central nervous system were found to contain a greater proportion of heritability  GWAS data sets on cognitive function into 24 broad functional annotations and 10 tissue types. Our analysis modelled LD, and took into account overlapping categories, as well as the proportion of SNPs in each category. We make a number of contributions to understanding the genetic architecture of cognitive function.We partitioned the total heritability found in two large, genetically correlated ), whereas those that showed no enrichment at evolutionarily conserved regions were not genetically correlated with general cognitive function or the VNR test used here.7 This suggests that not only do these evolutionarily conserved regions of the genome have a greater role in cognitive functions, but they may also harbour variants with pleiotropic effects on cognitive function, health and anthropometric traits, thereby reducing what has been varyingly called system integrity, developmental stability or general evolutionary fitness.27Evolutionarily conserved regions are unlikely to be specific to cognitive function, but rather to underlie fundamental design features important for general phenotypic functioning. The evolutionarily conserved regions used in the current paper have also been examined for enrichment with several disease- and health-related phenotypes. Significant enrichment was found for body mass index, schizophrenia and high-density lipoprotein cholesterol, but not for coronary artery disease, type 2 diabetes, low-density lipoprotein cholesterol or bipolar disorder.et al.11 found that common SNPs in the N-methyl-d-aspartate receptor complex were enriched for general cognitive function in two independent groups. The N-methyl-d-aspartate receptor complex is a component within the postsynaptic density (PSD), and using comparative proteomic analysis of the human and mouse PSD it has been found that the molecular composition of the postsynaptic density was highly similar, with more than 70% of the proteins found in the human PSD being found in the mouse PSD28 indicating conservation between species. A high level of conservation has also been found between the proteins of the PSD in comparisons between human and chimp (last common ancestor (LCA)~6 million years ago), as well as between mouse and rat (LCA 20 million years ago) and between human and mouse (LCA 90 million years ago), indicating conservation or negative selection indicative of conservation across the mammalian line.29Two previous studies using GSA have found that gene sets that are conserved between species are enriched for cognitive functions. A study by Hill et al.30 used the weighted gene co-expression network analysis to identify a novel module named M3 using cortical brain tissue extracted from living humans during surgery. This module was also present in both disease-free humans and in wild-type mouse hippocampi, indicating it had been conserved between both species. In addition, this module was found to be enriched for SNPs associated with general cognitive function and memory in two independent samples. The M3 also mapped poorly onto known biology, including the PSD, differentiating it from the N-methyl-d-aspartate receptor complex finding. In the current paper, we extend the findings of Hill et al.11 and Johnson et al.30 by considering all the SNPs, not just those found within genes, and show that regions of the genome that are under negative selective pressure harbour an enriched proportion of the heritable variance for cognitive function.More recently, Johnson et al.11 and Johnson et al.30 were constructed to test specific synaptic components and networks of genes that work together. However, both of these gene sets are under selective pressure, the current paper expands on the findings of Hill et al.11 and Johnson et al.30 by showing that conserved regions, not just those found within genes, are enriched for cognitive function.The gene sets used by Hill 32 and empirical findings33 of directional dominance acting on cognitive function. Directional selection is expected in traits that are related to fitness, and indicates a systematic direction of effect across causal loci. By examining runs of homozygosity, directional dominance can be seen when the phenotype of individuals that are homozygous for multiple locations differs from those that are heterozygous. Joshi et al.33 examined runs of homozygosity in 354 224 individuals who had taken tests of cognitive ability and found that as homozygosity increased, scores on tests of cognitive ability went down, indicating selective pressure acting to increase levels of cognitive function. The present study expands on the works of Joshi et al.33 by providing evidence that the regions of the genome most sensitive to genetic variation are more likely to harbour the variants that make the greatest contributions to cognitive and health differences.These results are also consistent with both theoretical predictions,et al.34 have suggested that intronic regions are more likely to harbour genetic variation associated with normal cognitive function than exomic regions. In addition, SNPs within 500 bp of the H3K4Me1 histone mark were enriched across both cognitive phenotypes. General cognitive function has been shown to correlate highly with tests of crystallized function, and in the present study the genetic correlation with VNR was rg=0.783 indicating that many of the same SNPs are involved in both facets of cognitive function. This overlap between these two phenotypes may therefore be driven by pleiotropic variants in introns and variants found in the H3K4Me1 histone mark, along with those that are evolutionarily conserved.SNPs within 500 bp of introns also showed significant enrichment for general cognitive function and for VNR. Enrichment for this region may indicate that, although not being translated into proteins, these regions may still exert an influence on individual differences in cognitive function. Indeed, Marioni The strengths of this study include the use of the largest GWAS of general cognitive function that used established cognitive tests to measure cognitive function. We also use data from the UK Biobank study that includes over 30 000 participants genotyped and processed together using the same VNR test administered in an identical way to remove processing artefacts owing to heterogeneity in test used and their administration. In addition, the genetic data from UK Biobank were processed in a consistent manner.The limitations of this study include the VNR test used in UK Biobank not being adequately compared to validated psychometric cognitive tests. Also the low response rate in UK Biobank of 5% ref.  indicate23 That the variants here are known to be conserved within the mammalian line may also be involved in general cognitive function in other species.36 In addition, this study aids the search for plausible sets of causal variants by showing that a reduced portion of the genome comprising, only ~2.5% of the total number of SNPs, can explain around ~40% of the SNP-based heritability (which is ~30%) of cognitive function.Following partitioned heritability analysis, we report that regions of the genome under negative selective pressure make a greater contribution to the heritability of cognitive functions than their size would suggest. This indicates that causal alleles are not distributed evenly across the genome but, rather, cluster in regions that are conserved. Disease states and anthropometric traits that show genetic correlations with cognitive function tend to show enrichment in these conserved regions; on the other hand, the diseases and traits that do not show genetic correlations with cognitive function tend not to show this pattern of enrichment. Together, this suggests that conserved regions may have a central role in mammalian genetic architecture as they appear to harbour variants with pleiotropic effects between cognitive function, diseases and anthropometric traits. This suggests that understanding the function and role of variants that are under negative selection will provide a greater understanding of cognitive function as well as how cognitive function is related to other health-related traits.


Mast cells and basophils depend on aggregation of the high-affinity IgE receptor, FceRI, to initiate secretion. A variety of studies have shown that FceRI densities vary 100 fold among subjects’ basophils and it has been speculated that high densities might be responsible for unusual behaviors of the cells, notably sensitivity to certain monomeric IgE antibodies or spontaneous release. These studies experimentally examined the density dependence of spontaneous release and signaling element expression in subjects’ basophils with FceRI densities ranging from approximately 6000 to 600,000 per cell. Through the use of numerical simulation, this study examined the expectations for spontaneous receptor aggregation and aggregate persistence at densities of FceRI ranging from 5000 to 500,000. Experimentally, FceRI density was not associated with greater spontaneous histamine release even when secretion was enhanced by the inclusion of deuterium oxide in the buffers. There was also no association of 15 activating or de-activating signaling elements with FceRI density. The numerical simulations demonstrated that at densities of ≈500,000 receptors, 13% of receptors were involved in transient aggregates at any given moment but that these aggregates rarely persisted for greater than 10 milliseconds. In contrast, a weak linear antigen aggregator, with ligand affinities known to induce secretion, would generate aggregates persisting for an average of ≈60 milliseconds. These results suggest that although a high density of FceRI likely produces a large number of transient aggregates, these aggregates do not persist long enough to induce signaling that results in secretion and do not induce the cells to alter their expression of several signaling elements known to be important in regulating secretion from human basophils. The results set some boundaries on the aggregation requirements for inducing histamine release from human basophils. Allergic reactions result from the IgE-mediated (immunoglobulin E) activation of mast cells and basophils. These cells express high affinity receptor for IgE (FceRI) and bound IgE confers on these cells the ability to sense the antigenic environment of the cells. A remarkable feature of FceRI expression on basophils and mast cells is the range of possible expression. After synthesis and placement on the cell surface, the residency time of the unoccupied receptor is relatively short; 50% are returned to the inside of the cell every 24 hours. Some of these might be recycled to the cell surface but many are degraded. However, as near as can be determined, if FceRI binds IgE, it will never leave the cell surface, provided aggregation doesn’t occur. This relationship between IgE and the stability of expressed FceRI produces some remarkable levels of FceRI expression. The steady state density of FceRI in the absence of IgE is approximately 5000–10000 per cell (a number which is dependent on the synthetic rate) . It is nRegarding whether the spontaneous aggregates might matter, there are a variety of experimental results that provide some context for the question. Another property of FceRI biology is that while some form of aggregation is required to initiate signaling, it doesn’t have to be a physical crosslink –8. SimplThe question of transience is a harder to answer but two experimental observations provide some insight. First, the signaling cascade actually has differential sensitivity to the transience of the aggregate depending on the readout of activation being assessed. Notably, extremely weak crosslinkers can still drive a signaling reaction that results in gene transcription while not leading to degranulation . A seconTherefore, if the juxtaposition of FceRI molecules need not be very long or close, the question becomes, how dense do the receptors need to be to initiate spontaneous signaling? This issue may have been inadvertently addressed in studies purporting to show that monomeric IgE can induce secretion . Many suMethodology for answering the question of transience experimentally has not been developed. An alternative approach, an aggregation simulation model, was used to explore the potential for long duration spontaneous aggregates.Leukapheresis donors are approved by protocols obtained by the leukapheresis center and the cells used for purification of basophils are considered a residual waste product. The protocol for obtaining blood from the subjects that were not processed with leukapheresis was approved by the Johns Hopkins IRB and the donors provided a written approval of a consent approved by the same IRB. This specific study was encompassed by the above approvals. Written consents are saved as part of the standard record keeping for IRB-approved studies.The following were purchased: PIPES , bovine serum albumin (BSA), EGTA, EDTA, D-glucose, NaF, Na4P2O7, Na3VO4, 2-ME, NP-40, FMLP ; crystallized human serum albumin (HSA) ; fetal calf serum (FCS) and RPMI 1640 containing 25 mM HEPES and L-glutamine ; Percoll, ; Goat anti-human IgE Ab was prepared as previously described .PIPES-albumin-glucose (PAG) buffer consisted of 25 mM PIPES, 110 mM NaCl, 5 mM KCl, 0.1% glucose, and 0.003% HSA. PAGCM was PAG supplemented with 1 mM CaCl2 and 1 mM MgCl2. PAG-EDTA consisted of PAG supplemented with 4 mM EDTA .Blood was partially enriched for basophils using single-step Percoll gradients. After washing to obtain a mononuclear cell preparation, cells were resuspended PAGCM buffer (to assess histamine release). Total histamine content was obtained by lysis of the cell preparation with 1.6% perchloric acid. These experiments included two types of spontaneous release assessments. The standard measurement is in PAGCM buffer without stimulus but a second measurement included 44% deuterium oxide to replace the water in the PAGCM. D2O (deuterium oxide) is known to enhance secretion of any type of stimulation . HistamiHistamine was measured by automated fluorimetry . The perOn a separate occasion, basophils from the same subjects were analyzed for cell surface total IgE using acetate elution. An aliquot of cells was used to determine the total basophil count by alcian blue staining and the remaining cells were treated with acetate buffer, pH 3.7, to dissociate endogenous IgE. The recovered supernatant was neutralized to pH 7 and IgE concentration measured by a total IgE assay (immunoCap). A calculation of the number of IgE molecules present and the cell number allowed the cell surface IgE density to be determined . As descBasophils were purified from leukapheresis packs or from blood obtained by venipuncture. When used at high purity, they were purified to near homogeneity by sequential application of Percoll gradients, countercurrent elutriation and negative selection using the basophil purification kit  and columns from Miltenyi Biotec  . The aveThese methods and a presentation of example blots from these studies have been previously published . All samTo make predictions about the number and duration of spontaneous aggregates, a simulation of IgE/receptor associations with or without physical linkers was developed. The supporting information contains a detailed description of the methodology as appendix 1 and the relevant code framework file  for the It is reasonable to suggest that the resting mechanisms of regulation of secretion may need to track with the receptor density in order to not allow spontaneous, non antigen-induced, secretion. A starting point for determining if receptor expression has an impact on function was to determine whether there was spontaneous secretion that was dependent on the density of FceRI. This was done in 4 separate surveys. In two of these surveys, spontaneous secretion was assessed in normal buffers and in buffer replacing 44% of the water with deuterium oxide. This substitution is known to significantly augment secretion, even without stimulation . Fig 2 sIf spontaneous secretion is not dependent on receptor density, there may be changes in signaling elements that maintain a quiescent state. A first look at this issue was whether peripheral blood basophils (PBB) cultured in IL-3 or CD34-derived basophils (CD34B) cultured in IL-3 and assessed for changes in signaling species show changes related to changes in FceRI. Two kinases that can be shown to increase the signaling and secretion of basophils are the src-family kinase, lyn, and syk . HoweverA survey of the natural distribution of several signaling elements in subjects’ basophils across a spectrum of IgE densities did not reveal marked differences at the high and low end of the density spectrum for FceRI. It is also possible to derive a small amount of data from recent studies examining the change in FceRI expression during treatment of patients with omalizumab. Only 4 signaling species have been examined in peripheral blood basophils, syk, lyn, c-cbl, and cbp/PAG , an interesting issue was raised regarding the impact of high densities of FceRI on spontaneous activation of basophils or mast cells. With a 100-fold range of FceRI expression, it would be surprising if the cells didn’t accommodate the signaling apparatus for conditions that might lead to a great deal of spontaneous aggregation. One can only speculate on the precise reason basophils and mast cells accumulate so many FceRI. One plausible explanation is to prevent a parasite from inducing nonspecific IgE as a defense against specific IgE-mediated secretion as part of the host rejection mechanism. Whatever the reason, the large up-regulation presents a potential problem for the secretory apparatus.The simulations demonstrate that at the highest densities of FceRI that are observed in individuals with high IgE levels, there are a considerable number of spontaneous aggregates present. As noted previously, a variety of studies have suggested that juxtaposition need not be close  but it dThe experimental findings show that there was no relationship between FceRI density and spontaneous histamine release ± deuterium oxide. In other studies we have shown that there is also no relationship between cellular sensitivity  or maximum histamine release . In otheThe observation that there is no relationship between FceRI density and spontaneous release might suggest that the cell uses counter-balancing mechanisms to keep activation in check. One way to counter-balance the increase in receptor is to down-regulate activating signaling steps. Alternatively, up-regulation of termination mechanisms could suppress spontaneous activation. We found no evidence for either of these changes in the molecular species that have been studied in basophils and shown to be participatory during IgE-mediated activation and de-activation. However, the list is short and there remain many other signaling species that would need examination.In addition, there is no a priori reason that any single signaling element might show a correlation with FceRI density. It may be that the entire signal element network adjusts such that only small increments of change occur for any one element. With this in mind, a simple calculation was performed on the data set used for the results in In a limited pilot study of 2 patients treated with omalizumab and 2 treated with placebo, there were no notable changes in the transciptome of basophils that experienced both down-regulated FceRI during treatment and up-regulated syk expression relative to the placebo-treated group (unpublished results). Notably, there were no changes in mRNA expression for a wide variety of expressed signaling species. What is notable from studies of omalizumab treatment is that omalizumab does down-regulate FceRI expression while up-regulating syk expression . This woEven though the persistence of spontaneous aggregates is short, there are approximately 100,000 of them at any given moment on basophils with 500,000 receptors. It remains somewhat surprising that there is no notable consequence to this situation. Perhaps the fact that FceRI has no intrinsic enzymatic activity allows the system to behave this way . It woulS1 FileDescription of the aggregation simulation.(PDF)Click here for additional data file.S2 FileExcel spreadsheet.(XLSX)Click here for additional data file.S3 FileExcel spreadsheet.(XLSX)Click here for additional data file.S4 FileStandard C code; main and model code without user interface code. To relate line numbers in the appendix to the code in this file, a code editor is needed.(C)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 FigEach IgE molecule was tracked for its association with an aggregate and marked for size of the aggregate at each cycle. A record for all IgEs at each cycle was stored and later scanned for each IgE and its status with respect to aggregate size. If it was marked as in an aggregate of size ≥2 (the gray zone in (TIF)Click here for additional data file.S3 FigPanel A; results of simulation for a 13.5 (filled circles) and 20.0 (filled squares) nm center-to-center separation distance being counted as an aggregate without regard to size or persistence at a given moment. Panel B; relationship between the size of the spontaneous aggregate, the number of aggregates and density of FceRI. The numbers on the ordinate reflect the total number of aggregates .(TIF)Click here for additional data file.S4 FigPersistence for clusters/aggregates of any size larger than monomers for two center-to-center separation distances . The count is for the number of such clusters for the first 75 msec of the simulation at a total receptor density of 270,000.(TIF)Click here for additional data file.S5 Fig6 M-1 was used for the simulation.A single-site affinity of 5x10(TIF)Click here for additional data file.S6 Fig−7 M) of crosslinker (black circles), or suboptimal crosslinker (2.5x10-10 M) (green open diamonds). The histograms on the right edge of the plot show the remaining number of aggregates at times > 75 msecs. Panel B, 3 simulations, at two different densities of receptor; spontaneous aggregates at 270,000 receptors/cell (open squares), an optimal concentration (10−7 M) of crosslinker at 270,000 receptors/cell (black circles), or optimal crosslinker (10−7 M) at 13,500 receptors/cell (green open circles). The histograms on the right edge of the plot show the remaining number of aggregates at times > 75 msecs. Panel C; 2 simulations, kr (dissociation constant) = 10  or = 100 (green squares) both at 270,000 receptors/cell.Panel A, 3 simulations, all at 270,000 receptors/cell, spontaneous aggregates (open squares), an optimal concentration (10(TIF)Click here for additional data file.


M-M males had a higher density of BrdU+ cells in the ventricular zone adjacent to HVC and of EdU+ in HVC than M-F males. M birds had a higher ratio of BrdU+EdU- to EdU+ cells than M-F subjects suggesting higher survival of newer neurons in the former group. Total number of HVC DCX+ cells was lower in M-F than in M-M males. Sex differences were also dependent of the type of marker used. Several technical limitations associated with the use of these multiple markers were also identified. These results indicate that proliferation, recruitment and survival of new neurons can be independently affected by environmental conditions and effects can only be fully discerned through the use of multiple neurogenesis markers.In songbirds, neurogenesis in the song control nucleus HVC is sensitive to the hormonal and social environment but the dynamics of this process is difficult to assess with a single exogenous marker of new neurons. We simultaneously used three independent markers to investigate HVC neurogenesis in male and female canaries. Males were castrated, implanted with testosterone and housed either alone (M), with a female (M-F) or with another male (M-M) while females were implanted with 17β-estradiol and housed with a male (F-M). All subjects received injections of the two thymidine analogues, BrdU and of EdU, respectively 21 and 10 days before brain collection. Cells containing BrdU or EdU or expressing doublecortin (DCX), which labels newborn neurons, were quantified. Social context and sex differentially affected total BrdU Endogenous and exogenous markers of new neurons differentially identify neurogenesisThymidine analogues label neuronal populations born at specified momentsDoublecortin gives an integrated view of neurogenesis changes over extended periodsBrdU antibodies detect EdU-positive cells to a variable extent depending on their ageYoung and slightly older HVC neurons are differentially affected by social conditionsAdult neurogenesis was first discovered in the rat hippocampus , howeverHVC is at the crossroad of three pathways involved in the learning, maintenance and production of song–the caudal motor pathway, the anterior forebrain ‘feedback’ pathway and the auditory pathway related to the perception of species-typical auditory signals. HVC is highly plastic and sensitive to a range of modulating factors including hormones and a variety of environmental stimuli. In seasonally breeding songbirds the volume of HVC during the breeding season is 1.3 to 3 times larger than during the non-breeding season (reviewed in ). Neurog3H]-thymidine or 5-bromo-2’-deoxyuridine (BrdU) and there are a few cases when these two markers have been combined in the same study . For exudy (see ) and theudy  has been validated as a marker of neuroblasts in neurogenic regions of the songbird brain . DCX labThe social environment profoundly influences the behavior and physiology of songbirds –32. For +) neurons than females in all photoperiodic conditions that they experience during an annual cycle, i.e., irrespective of whether they are photosensitive, photostimulated or photorefractory [+ neurons than the females of their species [On the other hand, in many temperate zone songbird species, including canaries, females rarely sing and have smaller song control nuclei, including HVC, than males  even thofractory . Male br species .To investigate the mechanism mediating the sex differences and the social effects on HVC volume and neurogenesis, we compared here males housed in three conditions–alone, with a female or with a male. The females housed with a male were treated as experimental subjects as well as stimuli in order to simultaneously investigate sex differences in neurogenesis. Sex steroid concentrations were clamped at levels representative of breeding condition for each sex via subcutaneous Silastic™ implants filled with testosterone in males and with estradiol in females. This was done to distinguish between direct effects of the social conditions on HVC  and effects mediated by the possible activation by the female of the hypothalamo-pituitary-gonadal axis ,52. Givead libitum access to food (a mix of various seeds designed for canaries), grit, cuttlebone and water for drinking and bathing. A small amount of egg yolk food was additionally added approximately once a week. Their health status and food/water provision was checked daily including during weekends as required by the Belgian law on the use of experimental animals.A total of 18 canaries of the Fife fancy breed were used in this study. All birds were in their second year; they were born and had gone through a full breeding cycle in the colony maintained at the University of Antwerp, Belgium during which they had been exposed to a minor immune challenge or its control manipulation and their body temperature had been recorded between 9 and 12 months of age  as described previously by Sartor and colleagues . Each teOne day after implantation of the Silastic™ capsules, subjects were moved from their group housing cages to their respective experimental social context and the photoperiod was changed from 8L:16D to 11L:13D. During that day subjects were also injected intraperitoneally with bromodeoxyuridine  5 times with 2 hours between each injection, at a dose of 50mg/kg per injection. The first of these injections was given at the same time when birds were moved from their group housing to the experimental social conditions and other injections followed 2 hours apart. On day 12 of the experiment all subjects were injected 5 times with 5-Ethynyl-2´-deoxyuridine  at a dose equimolar to the dose of BrdU, i.e. 41.07 mg/kg EdU in 0.01M PBS, following exactly the same injection schedule as for BrdU.The social context manipulations consisted of housing birds in one of the three following conditions: testosterone-treated male housed alone , testosterone-treated male housed with another male in the same endocrine condition, i.e. treated with testosterone , testosterone-treated male housed with an estradiol treated female (M-F). In the M-F condition both birds served as experimental subjects; results of the male in the pair will be labeled M-F (n = 5) while results of female in the pair will be labeled F-M (n = 4 due to the loss on one brain). Care was taken to distribute birds from the same pre-experimental cage across different treatment groups and to ensure that birds housed together for the experiment were neither siblings nor members of a previously breeding couple. Due to time constraints, the experiment was run in 4 replicates that were started 2 days apart. Each replicate contained roughly equal numbers of birds in each of the 4 treatment groups. The subjects from one replicate were placed in adjacent cages to facilitate simultaneous behavioral observations. Subjects in one social condition were distributed randomly in the room. All subjects were in the same room in visual but not acoustic isolation from other cages. Final numbers of subjects in each group and for each dependent variable are indicated in all figures.nd day of the experiment starting from day 3, song rate of male subjects was quantified during a total of 10 min per day . Each male subject was monitored for number of songs produced for 5 minutes in the morning and 5 minutes in the afternoon. During these 5 minutes, the observer sat quietly in front of the cages and noted the number of songs produced by each male. The different birds were observed each time in a different randomized order. We operationally defined song as a vocalization longer than approximately one second in duration after at least a 500 msec period of silence.Every 2+ cells is known to cross-react with EdU [th injection birds were killed by transcardial perfusion. The perfusion, brain collection, cryoprotection and processing followed the same protocol as for the other subjects in this study. One series of brain sections obtained from these subjects were labeled for BrdU and EdU.The BrdU antibody we used  to quantify BrdUwith EdU  which coBlood samples were taken from all subjects 4 to 7 days before the experiment (baseline), 4 days after the onset of social context manipulations, and during brain collection. 30–100 μL of blood was drawn from the brachial vein, in most cases within 3 minutes of catching. Samples collected between 3 and 4 minutes did not show increased corticosterone concentrations above baseline, therefore only a few samples collected more than 4 minutes after the initial bird capture were excluded from analyses of corticosterone. Blood samples were collected into heparinized micropipettes , transferred into Eppendorf™ microtubes and stored on crushed ice. Samples were centrifuged at 9000 g for 9 minutes, the supernatant plasma was collected and stored at -80°C until further use.Before hormone enzyme immunoassays (EIA), steroids were extracted from the samples to remove potentially interfering compounds using liquid phase extraction. Spiked samples were always processed in parallel with the experimental samples to assess extraction recovery. Spiked samples consisted of the same type, amount and dilution of plasma as experimental samples but contained in addition 30,000 counts per minute (CPM) of the tritiated hormone of interest. Recovery rates (ratio of CPM recovered to CPM added) were used to correct all assay results.10 μL of plasma was diluted in 150 μL of deionized water (MilliQ) in glass test tubes, samples were kept at +4°C for 30 minutes, and 2 mL of the non-polar organic solvent dichloromethane was added. Samples were vortexed and then left immobile for 1–2 hours to allow separation of the organic and aqueous phases. The organic phase was moved to a new test tube and dried under nitrogen gas at 40°C. The dichloromethane extraction was repeated a second time and pooled extracts were kept at -20°C until the EIA assay. Average recovery rates were 80% for testosterone and 84% for corticosterone. Testosterone and corticosterone concentrations were measured using EIA kits . On the day of the assay, samples were re-suspended in 400 μL EIA buffer from the kit (including 10% ethanol in the case of testosterone) and placed on a shaker set to 1350 rpm for 1 hour. The assay was performed immediately after following instructions provided with the kit. These assays have been previously validated for measuring these hormones in avian plasma –67.2PO4.H20). The brain was extracted from the skull immediately after perfusion and post-fixed overnight in 15 mL PFA. The following day brains were cryoprotected in 30% sucrose  until they sunk to the bottom of their vial. Brains were then frozen on dry ice and stored at -80°C until further use. Brains were cut coronally into 4 series of 30 μm thick sections on a Leica CM 3050S cryostat and stored in anti-freeze  at -20°C.After 21 days of exposure to the experimental conditions, all birds were deeply anaesthetized by an injection of 0.03–0.04 mL Nembutal™  and brains were collected from all subjects after transcardial perfusion. Blood was cleared from the brain by perfusion with 200 mL PBS 0.01M, followed by 200 mL 4% paraformaldehyde  and the delimited area was measured. When a section was missing, the area was estimated by taking the average of the two sections immediately rostral and caudal to it. The volumes of nuclei were calculated by summing the areas and multiplying by 120 μm, the distance between two successive sections in the series. The volume of the nuclei in each hemisphere was calculated separately and the average of the two measures was used for statistical analyses.2O2, avidin, biotin and diaminobenzidine (DAB) were diluted in TBS. Endogenous peroxidases were blocked using 0.6% H2O2 for 20 minutes, DNA was denatured to reveal the BrdU epitope in the chromatin by incubating the tissue in 2N HCl at 37°C for 20 minutes. The pH of the tissue was then neutralized during a 10-minute incubation in 0.1M sodium borate buffer. The non-specific binding of the secondary antibody was blocked by incubation in 10% donkey serum for 30 minutes and BrdU was labeled overnight with a primary rat anti-BrdU antibody  at a concentration of 1:2000. On the next day, sections were incubated for 2 hours with donkey anti-rat biotinylated antibody , the signal was amplified by incubation for 90 minutes in ABC kit , both components A and B being used at a concentration of 1:400. The BrdU antibody binding sites were revealed using 0.04% DAB in 0.012% H2O2 for 10 minutes, which produced a brown precipitate (A second series of sections was double-labeled by immunocytochemistry for BrdU and doublecortin (DCX). Sections were washed 3 times in Tris-Buffer Saline (TBS) 0.05M at the start and between each subsequent step except prior to primary antibody incubation. All sera and antibodies were diluted in TBST (TBS + 0.1% Triton-X100), while Hcipitate .2O2, blocked for non-specific binding of the second biotinylated antibody by incubation for 15 minutes each, first in avidin then biotin solution, both at a concentration of 1:5. Sections were blocked in 10% rabbit serum and incubated for 2 hours at room temperature and then for two days at 4°C in goat anti-DCX  at a concentration of 1:200. Next, sections were incubated with 1:100 biotinylated rabbit anti-goat antibody for 2 hours, for 90 minutes in ABC kit as previously, and finally revealed for the DCX antibody binding sites with Vector SG Substrate kit  for 6 minutes, which produced a blue-gray precipitate  was used to label cells that incorporated EdU. In order to delineate the HVC area, this was combined with immunohistochemistry for Hu, a neuronal marker that has been shown in songbirds to be expressed specifically by neurons starting soon after their birth . Many neEdU-labeling was performed according to the instructions provided by the manufacturer and BrdU immunohistochemistry was started immediately after. PBS 0.01M and PBST 0.1% were used for washes and antibody/serum dilutions. The sections were washed 3 times at the start to remove the antifreeze and following each incubation. DNA was denatured to reveal the BrdU epitope in the chromatin by incubating the tissue in 2N HCl at 37°C for 20 minutes. The pH of the tissue was then neutralized during a 10-minute incubation in 0.1M sodium borate buffer. The non-specific binding of the secondary antibody was blocked by incubation in 5% goat serum with 1% bovine serum albumin for 60 minutes and BrdU was labeled overnight at 4°C with a primary rat anti-BrdU antibody  at a concentration of 1:500. Sections were then incubated with biotinylated goat anti-rat secondary Alexa Fluor-488 antibody at a concentration of 1:500 for 2 hours at room temperature . After t+DCX-, BrdU-Fusiform-DCX+, BrdU-Round-DCX+, BrdU+Fusiform-DCX+ and BrdU+Round-DCX+. The numbers of the different cell types were summed up for each HVC and the procedure was repeated on both sides of the brain and for 3–4 sections containing HVC per subject . The total from both hemispheres was then averaged for all sections of a given subject and these mean values per section were used for analysis . In addition, the BrdU+ cells in the ventricular zone (VZ) dorsal to each of these HVCs were quantified separately, as well as the length of this segment of VZ. For these counts, we only considered cells that were entirely included in the thickness of the VZ and ignored labeled cells as soon as their perikaryon had migrated out of this periventricular cellular layer.A representation of the HVC borders was drawn on paper with the help of a camera lucida and a symbol was added on the drawing for each labeled cell, categorized as following: BrdU+ cells were quantified with a Leica fluorescence microscope  connected to a digital camera (Leica DFC 3000G). A photomicrograph was taken of each HVC, as detected by the dense group of Hu+ cells , in one series at 5x magnification and was used to quantify both the area of the nucleus and the number of EdU+ cells. The area was delineated based on the limit of the brighter, larger somas of neurons in HVC compared to surrounding nidopallium. EdU+ cells were counted manually in the entire cross section of HVC on these photographs in 3 to 6 sections per subject . The EdU+ cells in the VZ dorsal to each of these HVCs were quantified separately, as well as the length of this segment of VZ, as described for BrdU and DCX cells.EdU+ and BrdU+ cells, the brain sections were visualized with a Leica fluorescence microscope  and photomicrographs were taken with a digital camera . In the cross-reactivity validation the EdU+ and BrdU+ cells in the VZ were counted on photomicrographs taken at 20x magnification on 4–6 sections from each brain. For the social context experiment brains, EdU+ and BrdU+ cells in one section of HVC were quantified on photomicrographs taken at 10x magnification.To quantify EdU2). The density of cells/mm2 was corrected by the section thickness (30 μm) to obtain a density per mm3  and this density was then multiplied by the volume of the nucleus in mm3 to obtain an estimate of the total number in the entire nucleus. HVC volumes for this calculation were obtained from quantifications in Nissl-stained sections. These numbers that are extrapolated to the entire HVC provide a useful index to compare groups within the present experiment but should not be used for comparisons with independent studies since they are not absolute and depend on several parameters of the current study such as the section thickness and microscopic depth of field with the objective that was used, not to mention the staining efficiency.Densities of cells labeled by neurogenesis markers  were obtained by dividing number of positive cells by the cross-sectional area of the HVC they had been counted in  or as number of cells per mm of VZ adjacent to HVC. Although the VZ length per section was obviously different between males and females and possibly across male groups, since a large number of the new HVC neurons seem to originate in the adjacent VZ  or STATISTICA (StatSoft). All data are presented by the mean ± standard error of the mean (SEM). Effects were considered statistically different if the p-value (two tailed for comparisons of two groups unless otherwise mentioned) for the analysis was equal to or lower than 0.05.All behavioral and morphological measures including measures of neurogenesis were analyzed by non-parametric methods as the majority of data sets were not distributed normally, as determined by the Kolmogorov-Smirnov test. For each variable, the data from the three groups of males and one group of females is displayed side by side on a single graph for each measure, however the statistical analyses were performed separately. A Kruskal-Wallis ANOVA was used to compare the three groups of males and a Mann-Whitney U test to compare the males to the females in the M-F group. When the Kruskal-Wallis ANOVA indicated a significant difference between groups, a Dunn’s Multiple Comparisons post-hoc test was performed. All analyses of the three male groups were additionally performed taking the average data per male-male dyad rather than using individual data of the two males in the dyad, in order to test whether social interactions within a dyad had a major impact on the conclusion. The results obtained in these two approaches were very similar and therefore only the latter type of analysis is reported. Corticosterone plasma concentrations were analyzed by a repeated-measures ANOVA with social context/sex and time as factors and the Bonferroni procedure was used as a post-hoc test. Linear regression was performed to correlate the number of EdUTotal numbers of songs recorded over the three weeks of observation were compared across the three male social conditions. The highest rate of singing was observed in male subjects housed alone (M) followed by males housed with another male (M-M) and then by males housed with a female, (M-F) . StatistAs expected based on previous work ,48 in th+ cells in the VZ dorsal to HVC was significantly different between three groups of males subjected to different social conditions during 21 days  = 7.47, p = 0.024; + cells in the VZ than males housed with a female, the latter was not different from males housed alone. When the number of BrdU+ cells was normalized by the length of VZ, the difference in BrdU+ cells between the three groups of males was still significant  = 6.70, p = 0.035), however a post-hoc test did not reveal any pairs of groups that were significantly different from each other + cells between males and females in the M-F group revealed no significant difference in terms of cells per section  = 7, p = 1.000), nor in terms of cells per mm of VZ  = 7, p = 1.00).The overall number of BrdU+ cells was also higher in male subjects housed with another male than the other two groups of males, but this difference did not reach significance  = 3.89, p = 0.143; + density in HVC was found  = 5, p = 0.572). The estimated number of BrdU+ cells in the entire HVC was not significantly different across male subjects in different social conditions  = 4.55, p = 0.103; Inside HVC, the density of BrdU+ cells in the VZ dorsal to HVC in males  = 1.37, p = 0.504; + cells in the VZ was normalized by the length of the VZ, no difference was still seen between different social conditions either  = 1.54, p = 0.463; + cells per section  = 0, p = 0.016; Figs No difference between treatment groups was found in the number of EdU+ cells in HVC was marginally different between social condition groups in males  = 5.87, p = 0.053; + in HVC than males housed with a female (even if this difference is not significant). No significant difference was found in this measure between sexes in equivalent social conditions  = 8.00, p = 0.730). The estimated number of EdU+ cells in the entire HVC was not different between social conditions  = 2.91, p = 0.233: The density of EdU+ and BrdU+ cells counted in segments of the VZ in the combined sections collected at both intervals after BrdU injections . These data thus suggested that it should be possible to quantify both BrdU and EdU in sections from subjects injected with both thymidine analogs by subtracting from the BrdU-positive counts the numbers of EdU-positive cells.In male canaries injected with EdU only whose brains were collected 4 or 24 hours after the last injection there was a high degree of cross-reactivity of BrdU antibody  with EdU as shown by the correlation of the number of EdU+ cells, the quantification of BrdU+ and EdU+ cells in the brains of subjects from the main experiments that had been injected with both markers identified some subjects with more EdU+ cells than BrdU+ cells. There were even social conditions where such a difference (more EdU+ than BrdU+ cells) was seen in the average counts . This suggested that at least in some cases the cross-reactivity was not as complete as expected. To further investigate this question, we double-labeled for BrdU and EdU one section through HVC from each subject of the main experiment and quantified the single-labeled and double-labeled cells in the VZ dorsal to HVC and inside HVC.Although the cross-reactivity validation showed that the BrdU antibody we used recognizes most EdU+ and BrdU+ cells across groups was similar to the quantification of these labels performed on different sets of sections as summarized in Figs + cells in the VZ and 42.8% ± 0.07% (n = 18) of EdU+ cells in HVC were also labeled by BrdU. If we assume that some of these cells were BrdU+ because they had incorporated BrdU as well as EdU, the extent of cross-reactivity would be even lower. This is however unlikely since the BrdU and EdU injections were made 11 days apart.Overall, the pattern of the single-labeled EdU+ cells truly contained BrdU only (BrdU+EdU-) by subtracting from the total BrdU+ cells the number of BrdU+EdU+ cells. Although this number is possibly an underestimate because some of the EdU+BrdU+ cells could have incorporated both compounds (an unlikely event as discussed earlier in this section), this number still provides a useful estimate of how many of the cells born at the start of the social context manipulation and had incorporated BrdU at that time survived for 21 days. This analysis revealed that males housed with a female tended to have fewer BrdU+EdU- cells than the other two groups of males both in the entire VZ , p = 0.070) and in HVC , p = 0.061; data not shown). This pattern was also present in the analysis of the density (numbers per mm or per mm2) of BrdU+EdU- cells in the VZ , p = 0.064, +EdU- cells in the brains of the females than in those of the males although these differences did not reach statistical significance.Putting this methodological limitation aside, these counts of double-labeled cells allowed us to obtain an estimate of how many BrdU+EdU- cells over EdU+ cells as a measure of how many early born compared to late born cells survived. This comparison showed a significant difference between the three groups of males in the VZ , p = 0.009, +EdU- over EdU+ cells in the VZ than males housed with a female. Males housed with a female also had a lower ratio for the VZ than the females they were housed with  = 1, p = 0.032, We also compared across groups the ratio of BrdU+ neurons in HVC was not different between social groups  = 1.07, p = 0.586; + neurons in females compared to males  = 0, p = 0.016). A similar pattern was found for round DCX+ neurons, with no difference between social treatment groups  = 0.55, p = 0.759 and a significant sex difference with higher densities in females  = 0, p = 0.016; The density of fusiform DCX+ neurons in the entire HVC was significantly different between the male social condition groups  = 7.05, p = 0.029; + neurons/HVC than males housed with another male. Males also tended to have a larger total number of fusiform DCX+ neurons in HVC than females  = 0, p = 0.056). There was a significant effect of social condition on the estimated total number of round DCX+ neurons for HVC in males  = 7.05, p = 0.029; + neurons in HVC  = 5, p = 1.000).The estimated number of fusiform DCXThe blood samples collected at the end of the experiment from male subjects were assayed for testosterone concentrations, while samples from males and females collected at all three time points were assayed for corticosterone. Testosterone concentrations in the plasma of male subjects ranged from 1.24 to 6.84 ng/mL (mean = 3.56 ng/mL) and were not different between social conditions  = 1.07, p = 0.586).2, 16 = 1.90, p = 0.182, social context: F2, 16 = 0.36, p = 0.708) nor interaction between these factors , no main effect of sex  but a significant interaction between the two factors . Post-hoc analysis showed that before social context manipulations corticosterone concentrations were higher in males than in females. Interestingly, 4 days after onset of social conditions this pattern was reversed with females having a higher concentration of corticosterone than males, although this difference was not significant.A two-way repeated-measures ANOVA of corticosterone concentrations in the three male groups with time and social context as factors did not identify any main effects . ,70. 69,7in vivo studies only when the tissue of interest will be collected within 24 hours after injection.EdU was introduced relatively recently and has proven to be very useful for studying cell proliferation (see for example –74). Its+ cells detected from the number of BrdU+ cells detected. However, when the brains from the main study, which had been injected with both thymidine analogs 10 or 21 days before brain collection respectively were labeled for EdU and BrdU, the apparent cross-reactivity of the BrdU antibody with EdU was much lower: on average only 43.7 ± 0.06% (n = 18) of EdU+ cells in the VZ and 42.8% ± 0.07% (n = 18) of EdU+ cells in HVC were also labeled by BrdU.An additional problem of EdU relates to its dose-dependent cross-reactivity with most anti-BrdU antibodies. Before initiating the main experiment presented here, a cross-reactivity test was performed with canaries that had been injected with EdU only; their brain had been collected 4 or 24 hours later and labeled for both EdU and BrdU. In this test, the cross-reactivity of our BrdU antibody  with EdU was 87.6%. Since this number was close to 100%, we assumed that we would be able to calculate the number of cells containing BrdU in sections of brains injected with both EdU and BrdU by subtracting the number of EdUThis apparent decrease in cross-reactivity is possibly due to the fact that while at 24 hours most cells that had incorporated EdU had survived, 10 days later the cells that had incorporated a large amount of EdU had died and only those that had incorporated a smaller amount of EdU were still surviving. While the detection of EdU with the EdU kit is very sensitive and powerful, the detection of the low concentration of EdU in these cells by the BrdU antibody might give a weaker signal that was not detectable during quantification. An additional factor potentially decreasing the amount of EdU in cells at 10 days compared to at 24 hours post injection is that some cells had undergone their final division after multiple divisions of a progenitor that had incorporated EdU, each division further diluting the label.The simultaneous use of these two thymidine analogs is thus bound to result in significant problems that relate to the toxicity of EdU, limiting its use to label cell proliferation just before tissue collection, and to its cross reactivity with most anti-BrdU antibodies . We had + neurons density in female canaries. These diverging effects on density and total number of newborn neurons in HVC probably relates to the fact that the growth of HVC is due not only to an increase in neuron number but also to changes in soma size and spacing of neurons. The two types of measures of neurogenesis are thus not necessarily correlated and this raises the question of which measure better relates to functional outcomes such as memory formation or production of specific song features. Although many interesting hypotheses have been proposed about the function of adult neurogenesis such as its role in song learning or song perception, a recent critical review  has poiiew (see ).Compared to isolated males, the males housed with a female had a reduced rate of singing, a phenomenon that has been described in other songbird species including canaries . In the The number of subjects per group was reduced in the present experiment due to technical problems such as the loss of Silastic™ implants and this limited the statistical power of the study. However, the patterns of differences between groups clearly indicated that the way the three populations of newborn neurons labeled by BrdU, EdU and DCX were affected was not always equivalent. In a first step we quantified the BrdU and EdU labels separately on different sets of brain sections. Inside HVC both the EdU and BrdU density/total numbers per HVC tended to be higher in the M-M condition than in the other two groups even if group differences did not reach statistical significance in many cases see Figs  and 4. TWe additionally quantified BrdU and EdU cells in the putative site where many (most?) HVC new neurons are born: the VZ dorsal of HVC –78. Alth+EdU- cells  provided a more precise measure of cells that had incorporated BrdU by excluding from the total the BrdU cells that were also positive for EdU. The pattern for these BrdUU- cells  was soments Figs  and 4. M+ neurons was not different across social conditions in males, however the estimated number of fusiform and round DCX neurons for the entire HVC was numerically lower in males housed with a female than the other two groups of males, although this difference was significant only for the comparison of fusiform cells between the M-M and M-F groups , of HVC volumes and to some extent in the numbers of DCX+ neurons in the entire HVC but not in the densities or total numbers of EdU+ cells (presumably younger neurons) nor in measures of total BrdU+ cells that are contaminated by EdU cross-reactivity. This would suggest that singing activity affects the survival of new neurons but only does so after a minimal amount of time that would, based on the current data, definitely need to be longer than 10 days. It has been suggested in mammals [+ cells that were about 10 days of age at brain collection had not yet reached the sensitive period when the social context can affect their survival. Alternatively, the toxicity of EdU means that a large number of labeled cells must have died before brain collection and it is conceivable that those cells that survived constitute a sub-population that is less or not sensitive to the social environment.Singing activity in M-M males was intermediate between activity in the M and M-F groups. Overall the ratio of BrdUs in HVC . It is i mammals ,43 and i mammals ,42 that + neurons [Males housed with a female also had somewhat smaller HVC volumes and reduced levels of singing compared to other males, although this difference was only significant for the songs produced by males alone versus males housed with a female. There was also a lower rate of putative neuronal proliferation and survival in males housed with a female as detected by several measures which contrasts with previous studies that had identified effects in the opposite direction based on measures of HVC volumes or counts of DCX neurons ,35,39. MThe effects of the social environment can indeed be complex. Our previous work showed that males housed with a female had a larger HVC than males housed with another male ,39 but tWe also wondered whether the multiple manipulations performed in this but not in previous studies  had potentially induced a stress preventing the positive effect of female presence. Assays of plasma corticosterone provided however no evidence for this interpretation: concentrations of this steroid were similar in the three male groups and, if anything, decreased in M-F males in the course of the experiment.Another difference between this study and previous studies concerns the photoperiod the birds were exposed to. We kept birds under an 11L:13D photoperiod that insures they do not become photorefractory during the experiment, while previous studies identifying a positive effects of females on HVC were performed under an 16L:8D photoperiod ,39,80. I+ and EdU+ cells were both similar in the two sexes  but not with EdU that was injected only 10 days before tissue collection and thus labeled comparatively younger cells. This sex difference concerning BrdU+EdU- cells and DCX+ neurons but not EdU+ cells could be taken as evidence suggesting that female neurons are recruited and/or survive in HVC comparatively longer than male neurons. Unpublished data from our lab indeed suggested that newborn neurons in the HVC of females mature more slowly than in the male HVC, taking longer to down-regulate DCX [It is interesting to note that sex differences in HVC neurogenesis favoring females were detected with markers related to relatively older neurons .These results, despite their limited power related to small final sample sizes, demonstrate that the use of multiple markers is a very useful tool to understand the complexities of environmental influences on HVC neurogenesis. A limited number of endogenous markers have been validated for use in songbirds, including doublecortin that is particularly useful because it is neuron-specific and discriminates two different stages of neuroblast development, especially when combined with different analogues of thymidine which enable us to follow the trajectories of newborn neuron populations born at a specific time relative to the treatments administrated. Technical problems are however associated with the simultaneous use of multiple thymidine analogs including cross-reactivity in their detection and potential toxicity of EdU that should only be used as a marker of proliferation and injected less than 24 hours before brain collection. Even with these limitations, the present data suggest that proliferation, recruitment and survival of new neurons can be independently affected by environmental conditions with DCX providing cumulative information not necessarily reflected in measures of single new populations (BrdUS1 Table(XLSX)Click here for additional data file.


Retirement is a key life event, which is associated with changes in physical activity, however, there is limited evidence with regard to changes in physical activity that take place in post-retirement years. The aim of this study was to examine how leisure-time physical activity changes shortly after the transition to retirement and during the post-retirement years.n = 7332, response rate 83%) and phase 3 in 2012 . Disability retirees and those under the age of 50 at baseline were excluded. This yielded 2902 participants. Most of the participants (79%) were women. The mean age of the participants was 54.4 in phase 1. Negative binomial models for repeated measurements with generalized estimating equations (GEE) were used to calculate the incidence rate ratios (IRR) and 95% confidence intervals (CI). These indicated the changes in time spent in self-reported leisure-time physical activity among the retired compared with the continuously employed.The phase 1 data were collected in 2000–2002  among 40–60-year-old employees of the City of Helsinki, Finland. Phase 2 was carried out in 2007 , and 948 during the second period (phases 2–3). Change in physical activity was positive among those who retired during the first  and second  periods compared to the continuously employed. During the second period, there was little difference between those who had retired during the first one  and the continuously employed.The transition to statutory retirement was associated with an immediate increase in leisure-time physical activity, which nevertheless diminished during post-retirement years. Physical inactivity is common worldwide especially among people in older age groups, and activity tends to decrease as people get older. Almost 50 % of people 60 years and older are inactive in Europe , 2. InacChanges in physical activity during the life course are associated with major life events and transitions, such as graduation, getting married, becoming a parent or retiring . PreviouIt has been shown in previous studies, that changes in physical activity are also associated with socioeconomic position , 13, andThe present study continues our earlier research , which rn = 6245) of the participants took part in all three surveys. Non-response and attrition analyses showed that the data sufficiently represent the target population [This study is based on Helsinki Health Study (HHS) cohort data. The baseline (phase 1) surveys were sent by mail to all employees of the City of Helsinki aged 40, 45, 50, 55 and 60 in 2000, 2001 and 2002. Phase 2 and phase 3 questionnaire surveys were conducted in 2007 and 2012 respectively. There were 8960 respondents in phase 1 (response rate 68%), 7332 in phase 2 (response ate 83%) and 6814 in phase 3 (response rate 78%). Seventy per cent (pulation . Eighty pulation .n = 3702) because there were only a few retirees in this age group. We excluded those who retired on special grounds such as disability (n = 731) because the association between retirement and changes in physical activity is likely to differ in disability compared with statutory retirement. We also excluded those who were outside employment due to other reasons than retirement during the follow up (n = 102) and those with missing values in physical activity variables, retirement status or other covariates (n = 266).We included 2902 participants in our analysis, having excluded those who were under 50 years old in phase 1 ((continuously employed), those who retired in the first follow-up period between phase 1 and phase 2 (Retired1) and those who retired in the second follow up period between phase 2 and phase 3 (Retired2). Because we measured leisure-time physical activity for the whole of the preceding year we considered those who retired within six months of responding to the survey still to be in employment.Retirement status was classified in three groups. Those who continued working during the entire follow-up time We used the same question to measure leisure-time physical activity (including commuting) in all three phases. The participants were asked how many hours a week, on average, they had spent on physical activity during the past year, on four grades of intensity equivalent to walking, brisk walking, running and jogging. The minutes spent on moderate to vigorous leisure-time physical activity were calculated by summing up the time spent on each intensity grade. The main analyses focused on the changes in time (minutes/week) spent on leisure-time physical activity. For descriptive purposes we calculated metabolic equivalent (MET) hours by multiplying the MET values of each intensity grade  and summGender, age, socioeconomic position (SEP) during phase 1 and time-variant marital status, smoking, limiting long-standing illness (LLI) and body mass index (BMI) were used as covariates. We dichotomized limiting longstanding illness (LLI) to those who reported a longstanding illness and that restricted working or other daily tasks and to those who did not. BMI was calculated by dividing the self-reported weight of the participants by their self-reported height in metres squared. Occupational socioeconomic position was classified in four groups: managers and professionals, semi-professionals, routine non-manual workers and manual workers. Marital status was classified as single, married or cohabiting, and divorced or widowed. Smoking status was divided into non-smokers and smokers based on self-reported regular smoking.p = 0.2) and women and men were pooled for the analyses. We performed the analyses with SPSS version 22 for Windows.We used comparison of means and cross tabulations to describe the study variables. Negative binomial regression models for repeated measurements with generalized estimating equations (GEE) were used to calculate the incidence rate ratios (IRR) and their 95% confidence intervals (CI) for the changes in physical activity among the Retired1 and Retired2 groups compared with the continuously employed. Time in minutes per week was used as the outcome variable and the interaction between the phase and the retirement group was examined as a predictor. We adjusted the different covariates in three models. In the first model we adjusted for gender and age, in the second model also for SEP and time-variant marital status and the third for BMI and LLI, as well. There was no significant gender interaction  in the Retired1 group than among the continuously employed following adjustment for age and gender Table . FurtherThe increase in physical activity in the Retired2 group during the second period was not as notable as in the Retired1 group during the first period. There was also a decrease in physical activity among the continuously employed during the second period, however. Thus, the differences between the retired group and the continuously employed were similar during both periods (Table1 & Fig. Our results indicate a modest increase in leisure-time physical activity after the transition to statutory retirement, but this increase does not necessarily persist over a longer period. Retirement led to an immediate positive change in physical activity in both retirement groups compared to the continuously employed, although the increases in time were only 15 and 33 min. The increase in physical activity at the time of retirement was larger in absolute numbers in the Retired1 than in the Retired2 group, but the relative difference from the continuously employed was similar. This similarity implies that the association between the transition to retirement and physical activity reported in our earlier study  was not The increase in leisure-time physical activity associated with the transition to retirement does not seem to persist. The higher activity level achieved after retirement reported in the present study was not maintained in that the time spent on leisure-time physical activity decreased among the Retired1 group over the years following retirement. However, members of this group maintained a similar level of activity as those in the continuously employed group, hence the increase in physical activity associated with the transition to retirement might partly even out the decrease associated with age. This is new evidence with regard to the association between the transition to retirement and leisure-time physical activity: several previous studies , 7, 8 meOne study  examinedThe average level of leisure-time physical activity among the participants was high at around 300 min per week during phase 1, thus the changes in time spent on such activity were quite modest in both absolute and relative terms. The changes in time spent in LTPA reported in other studies have varied. One study reported 2 h  increaseWe focused only on leisure-time physical activity in this study. As work-related physical activity stops after retirement the total amount of physical activity may also decrease. One study  reportedOur question on physical activity included commuting physical activity, and the probable decrease in commuting physical activity after retirement is a potential cause of bias in our results. However, our findings are more likely to be conservative compared to studies that do not incorporate commuting activity, the loss of which after retirement counteracts the increases in leisure-time physical activity. Another limitation is that, we lack measurement of work related physical activity which is lost after retirement. Second, we used self-reported data on employment status and physical activity. It has been shown that self-reported measurements of physical activity may be overestimated. The questionnaire we used has not been validated, but similar questions have proved to be valid and reliable in comparison with a detailed interview . MoreoveThe strengths of the study include the extensive, longitudinal, prospective dataset, and the fact that all the participants were employed and able to work during phase 1. The longitudinal data collected at three time points enabled us to extend the evidence from previous studies by examining the changes in physical activity in post-retirement years as well as the change after the transition to retirement during the two consecutive follow-up periods.Statutory retirement was associated with a short-term increase in leisure-time physical activity. However, the increase in leisure-time physical activity associated with retirement may slow down or delay the decrease in physical activity seen as people age. The results highlight the need not only to encourage people to increase their physical activity after retirement, but also to help retirees to maintain their physical activity levels in the longer term.