Explore the vast range of titles available.

1. Understanding individual-level variation in response to the environment is fundamental to understanding life-history evolution and population dynamics. Telomeres, the protective caps at the ends of chromosomes, shorten in response to oxidative stress, and telomere shortening is correlated with reduced survival and life span. Investigating telomere dynamics may help us quantify individual variation in the costs experienced from social and ecological factors, and enhance our understanding of the dynamics of natural populations. 2. Here, we study spatio-temporal variation in lifelong telomere dynamics in the Seychelles warbler, Acrocephalus sechellensis. We combine long-term life history and ecological data with a large longitudinal dataset of mean telomere lengths, consisting of 1,808 samples from 22 cohorts born between 1993 and 2014. We provide a detailed analysis of how telomere dynamics vary over individual life spans and cohorts, and with spatio-temporal variation in the social and ecological environment. 3. We found that telomere length decreases with cross-sectional and longitudinal measures of age, and most rapidly very early in life. However, both cross-sectional and longitudinal data suggested that against this overall pattern of shortening, bouts of telomere length increase occur in some individuals. Using a large number of repeated measurements we show statistically that these increases are unlikely to be explained solely by qPCR measurement error. 4. Telomere length varied markedly among cohorts. Telomere length was positively associated with temporal variation in island-wide insect abundance—a key resource for the insectivorous Seychelles warbler—suggesting that the costs associated with living in harsher environments can be studied by investigating telomere dynamics. We also found evidence for sex-specific relationships between telomeres and tarsus length, potentially reflecting differential costs of growth. 5. Our long-term data show that in a natural population, telomere dynamics vary in a complex manner over individual life spans, and across space and time. Variance in telomere dynamics among individuals is the product of a wide array of genetic, parental and environmental factors. Explaining this variation more fully will require the integration of comprehensive long-term ecological and genetic data from multiple populations and species.

The processes of developmental stability, canalization, and phenotypic plasticity have ecological and evolutionary significance, and been studied extensively, but mostly separately and thus the relationships between them are not straightforward. Our objective was to better integrate these processes in the context of temporally heterogeneous environments. We did this by investigating the effects of early experience with temporal heterogeneity in water availability on associations between developmental stability, canalization, and phenotypic plasticity. We subjected eight plant species to a first round of alternating inundation and drought vs. constantly moderate water treatments (heterogeneous experience) and a second round of water conditions (to test plasticity). We measured fluctuating asymmetry (FA) in leaf size, intra‐ and inter‐individual variation (CVintra and CVinter), and plasticity (PI) in traits and analyzed correlations between these variables across all species. Results showed little correlations between FA, CVintra and PI, several positive correlations between FA and CVinter in more stressful conditions, especially in as well as positive correlations between CVinter and PI initially and negative correlations between them later. These suggested the complexity of these relationships, which can depend on whether plasticity occurs. Greater inter‐individual variation will more likely cooperate with plasticity before or during plastic response, whereas higher canalization may reflect phenotypic convergence. Both higher FA and CVintra can reflect faster growth, while CVintra may also reflect plant growth stage, and the two mechanisms should cooperate in response to environmental challenges. The complexity of these relationships suggests plants deal with environmental variation in elaborate and integrative ways which can be affected by many factors. Decreased canalization may promote plastic responses in traits before or during the induction of plasticity, whereas canalization may reflect phenotypic convergence after plastic responses.

Rare genetic DNA repair deficiency syndromes can cause immunodeficiency, neurological disorders, and cancer. In the general population, inter‐individual variation in DNA repair capacity (DRC) influences susceptibility to cancer and age‐related diseases. Genome‐wide association studies and functional analyses indicate that defects in multiple DNA repair pathways jointly increase disease risk, but previous technologies do not permit comprehensive population‐level analysis. Fluorescence multiplex host cell reactivation (FM‐HCR) assays now allow direct quantification of DRC across six major DNA repair pathways. DRC is assessed in phytohemagglutinin‐stimulated primary lymphocytes from 56 healthy individuals, with reproducibility validated in 10 individuals across up to five independent blood draws. Generalized analytical pipelines are developed to systematically correct batch effects and experimental confounders. Significant inter‐individual variation is observed across 10 reporter assays measuring distinct repair processes, with weak correlations between pathways suggesting independent disease susceptibility contribution. A complementary pipeline analyzing comet repair kinetics allows integration with previously reported comet data from the same individuals. This study underscores the sensitivity of FM‐HCR assays in detecting subtle biological differences and establishes standardized methodologies for population research. The findings and open‐source tools advance precision health by enabling comprehensive exploration of genetic and environmental determinants of DRC, supporting targeted interventions to maintain genomic integrity. Susceptibility to the health effects of DNA damage depends on a person's ability to repair DNA damage, but DNA repair has been difficult to measure in populations. A functional assay called FM‐HCR is used to measure DNA repair in 6 major pathways across 56 individuals. It is found that each pathway varies substantially and independently across individuals.

A central problem in infection biology is understanding why two individuals exposed to identical infections have different outcomes. We have developed an experimental model where genetically identical, co-housed Drosophila given identical systemic infections experience different outcomes, with some individuals succumbing to acute infection while others control the pathogen as an asymptomatic persistent infection. We found that differences in bacterial burden at the time of death did not explain the two outcomes of infection. Inter-individual variation in survival stems from variation in within-host bacterial growth, which is determined by the immune response. We developed a model that captures bacterial growth dynamics and identifies key factors that predict the infection outcome: the rate of bacterial proliferation and the time required for the host to establish an effective immunological control. Our results provide a framework for studying the individual host-pathogen parameters governing the progression of infection and lead ultimately to life or death. Sick individuals do not all respond to an infection in the same way. One individual may experience mild symptoms and recover easily, while another may suffer devastating illness or even death. A number of factors are often assumed to account for these differences, including the sex, age and genes of the individuals, and differences in the environments the individuals have been exposed to. However, random variations in how an individual’s immune system interacts with the infection could also play an important role in recovery. Duneau et al. have now studied how genetically identical fruit flies who were raised in the same environment respond to different bacterial infections. This enabled them to develop a mathematical model that describes how a bacterial infection develops in an individual. In an initial phase, the bacteria proliferate freely. If the immune defenses activate in time to control the infection, the number of bacteria in the fly decreases to a constant level and the infection enters a long-term, or chronic, phase. The sooner this happens the more likely it is that the fly will survive. If the immune control happens too late, the infection enters a terminal phase and the fly will die once the number of bacteria increases to a certain level. The model therefore reveals that the precise time at which the immune system takes control of the bacterial population – termed the “Time to Control” – determines the outcome of the infection. Duneau et al. confirmed this by injecting bacteria into identical flies. A small variation in the Time to Control was sometimes the difference between a fly living or dying. Understanding what controls this apparently random variation is key to understanding infection and potentially developing more efficient treatments for a wide range of diseases – not just those caused by bacteria, but also those caused by viruses and parasites, like HIV and malaria.

Background Individual genotypes at specific loci can result in different patterns of DNA methylation. These methylation quantitative trait loci (meQTLs) influence methylation across extended genomic regions and may underlie direct SNP associations or gene-environment interactions. We hypothesized that the detection of meQTLs varies with ancestral population, developmental stage, and tissue type. We explored this by analyzing seven datasets that varied by ancestry (African American vs. Caucasian), developmental stage (neonate vs. adult), and tissue type (blood vs. four regions of postmortem brain) with genome-wide DNA methylation and SNP data. We tested for meQTLs by constructing linear regression models of methylation levels at each CpG site on SNP genotypes within 50 kb under an additive model controlling for multiple tests. Results Most meQTLs mapped to intronic regions, although a limited number appeared to occur in synonymous or nonsynonymous coding SNPs. We saw significant overlap of meQTLs between ancestral groups, developmental stages, and tissue types, with the highest rates of overlap within the four brain regions. Compared with a random group of SNPs with comparable frequencies, meQTLs were more likely to be 1) represented among the most associated SNPs in the WTCCC bipolar disorder results and 2) located in microRNA binding sites. Conclusions These data give us insight into how SNPs impact gene regulation and support the notion that peripheral blood may be a reliable correlate of physiological processes in other tissues.

Background Major depressive disorder (MDD) shows large heterogeneity of symptoms between patients, but within patients, particular symptom clusters may show similar trajectories. While symptom clusters and networks have mostly been studied using cross-sectional designs, temporal dynamics of symptoms within patients may yield information that facilitates personalized medicine. Here, we aim to cluster depressive symptom dynamics through dynamic time warping (DTW) analysis. Methods The 17-item Hamilton Rating Scale for Depression (HRSD-17) was administered every 2 weeks for a median of 11 weeks in 255 depressed inpatients. The DTW analysis modeled the temporal dynamics of each pair of individual HRSD-17 items within each patient (i.e., 69,360 calculated “DTW distances”). Subsequently, hierarchical clustering and network models were estimated based on similarities in symptom dynamics both within each patient and at the group level. Results The sample had a mean age of 51 (SD 15.4), and 64.7% were female. Clusters and networks based on symptom dynamics markedly differed across patients. At the group level, five dynamic symptom clusters emerged, which differed from a previously published cross-sectional network. Patients who showed treatment response or remission had the shortest average DTW distance, indicating denser networks with more synchronous symptom trajectories. Conclusions Symptom dynamics over time can be clustered and visualized using DTW. DTW represents a promising new approach for studying symptom dynamics with the potential to facilitate personalized psychiatric care.

The needs of offspring change as they develop. Thus, parents should concomitantly change their investment based on the age-related needs of the offspring as they mature. Due to the high costs of parental care, it is optimal for parents to exhibit a shift from intense caregiving of young offspring to promoting independence in older offspring. Yet, the neural mechanisms that underlie shifts in parental behavior are poorly understood, and little is known about how the parental brain responds to offspring of different ages. To elucidate mechanisms that relate to shifts in parental behavior as offspring develop, we examined behavioral and neural responses of male and female prairie voles (Microtus ochrogaster), a biparental rodent, to interactions with offspring at different stages of development (ranging from neonatal to weaning age). Importantly, in biparental species, males and females may adjust their behavior differentially as offspring develop. Because the nonapeptides, vasopressin (VP) and oxytocin (OT), are well known for modulating aspects of parental care, we focused on functional activity of distinct VP and OT cell groups within the maternal and paternal brain in response to separation from, reunion (after a brief period of separation) with, or no separation from offspring of different ages. We found several differences in the neural responses of individual VP and OT cell groups that varied based on the age of pups and sex of the parent. Hypothalamic VP neurons exhibit similar functional responses in both mothers and fathers. However, hypothalamic and amygdalar OT neurons exhibit differential functional responses to being separated from pups based on the sex of the parent. Our results also reveal that the developmental stage of offspring significantly impacts neural function within OT, but not VP, cell groups of both mothers and fathers. These findings provide insight into the functional plastic capabilities of the nonapeptide system, specifically in relation to parental behavior. Identifying neural mechanisms that exhibit functional plasticity can elucidate one way in which animals are able to shift behavior on relatively short timescales in order to exhibit the most context-appropriate and adaptive behaviors.

PurposeExtensive inter-individual variability exists in the production of flavan-3-ol metabolites. Preliminary metabolic phenotypes (metabotypes) have been defined, but there is no consensus on the existence of metabotypes associated with the catabolism of catechins and proanthocyanidins. This study aims at elucidating the presence of different metabotypes in the urinary excretion of main flavan-3-ol colonic metabolites after consumption of cranberry products and at assessing the impact of the statistical technique used for metabotyping.MethodsData on urinary concentrations of phenyl-γ-valerolactones and 3-(hydroxyphenyl)propanoic acid derivatives from two human interventions has been used. Different multivariate statistics, principal component analysis (PCA), cluster analysis, and partial least square-discriminant analysis (PLS-DA), have been considered.ResultsData pre-treatment plays a major role on resulting PCA models. Cluster analysis based on k-means and a final consensus algorithm lead to quantitative-based models, while the expectation–maximization algorithm and clustering according to principal component scores yield metabotypes characterized by quali-quantitative differences in the excretion of colonic metabolites. PLS-DA, together with univariate analyses, has served to validate the urinary metabotypes in the production of flavan-3-ol metabolites and to confirm the robustness of the methodological approach.ConclusionsThis work proposes a methodological workflow for metabotype definition and highlights the importance of data pre-treatment and clustering methods on the final outcomes for a given dataset. It represents an additional step toward the understanding of the inter-individual variability in flavan-3-ol metabolism.Trial registrationThe acute study was registered at clinicaltrials.gov as NCT02517775, August 7, 2015; the chronic study was registered at clinicaltrials.gov as NCT02764749, May 6, 2016.

Background Although the genomes of monozygotic twins are practically identical, their methylomes may evolve divergently throughout their lifetime as a consequence of factors such as the environment or aging. Particularly for young and healthy monozygotic twins, DNA methylation divergence, if any, may be restricted to stochastic processes occurring post-twinning during embryonic development and early life. However, to what extent such stochastic mechanisms can systematically provide a stable source of inter-individual epigenetic variation remains uncertain until now. Results We enriched for inter-individual stochastic variation by using an equivalence testing-based statistical approach on whole blood methylation microarray data from healthy adolescent monozygotic twins. As a result, we identified 333 CpGs displaying similarly large methylation variation between monozygotic co-twins and unrelated individuals. Although their methylation variation surpasses measurement error and is stable in a short timescale, susceptibility to aging is apparent in the long term. Additionally, 46% of these CpGs were replicated in adipose tissue. The identified sites are significantly enriched at the clustered protocadherin loci, known for stochastic methylation in developing neurons. We also confirmed an enrichment in monozygotic twin DNA methylation discordance at these loci in whole genome bisulfite sequencing data from blood and adipose tissue. Conclusions We have isolated a component of stochastic methylation variation, distinct from genetic influence, measurement error, and epigenetic drift. Biomarkers enriched in this component may serve in the future as the basis for universal epigenetic fingerprinting, relevant for instance in the discrimination of monozygotic twin individuals in forensic applications, currently impossible with standard DNA profiling.

Twenty years ago, Albert Bennett published a paper in the influential book New directions in ecological physiology arguing that individual variation was an 'underutilized resource'. In this paper, I review our state of knowledge of the magnitude, mechanisms and functional significance of phenotypic variation, plasticity and flexibility in endocrine systems, and argue for a renewed focus on inter-individual variability. This will provide challenges to conventional wisdom in endocrinology itself, e.g. re-evaluation of relatively simple, but unresolved questions such as structure-function relationships among hormones, binding globulins and receptors, and the functional significance of absolute versus relative hormone titres. However, there are also abundant opportunities for endocrinologists to contribute solid mechanistic understanding to key questions in evolutionary biology, e.g. how endocrine regulation is involved in evolution of complex suites of traits, or how hormone pleiotropy regulates trade-offs among life-history traits. This will require endocrinologists to embrace the raw material of adaptation (heritable, individual variation and phenotypic plasticity) and to take advantage of conceptual approaches widely used in evolutionary biology (selection studies, reaction norms, concepts of evolutionary design) as well as a more explicit focus on the endocrine basis of life-history traits that are of primary interest to evolutionary biologists (cf. behavioural endocrinology).