Temporal change in the genetic structure between and within cohorts of a marine fish,Diplodus sargus,induced by a large variance in individual reproductive success

Temporal changes at 16 allozyme loci in the Diplodus sargus population of Banyuls-sur-Mer (Mediterranean Sea, France) were monitored. Temporal genetic variation within a single population was examined over two temporal scales: (i) among three year-classes sampled at the same age, and (ii) within a single year-class sampled three times over a two-year period. We observed a significant change in the genotypic structure within the same cohort during the first two years following settlement and before recruitment into the adult population. In addition, comparison of year-classes showed that cohorts differed significantly one year after settlement, whereas they became similar later on before recruitment into the adult population. The observed changes in the genetic structure within and between year-classes may be the result of complex selective processes or genetic drift. Linkage disequilibrium and genetic relatedness data suggest that these changes are due to large variation in reproductive success, followed by homogenization through adult movement. Overall, these results demonstrated a rapid genetic change within a population.     

Design and Analysis of Multiple Events Case–Control Studies

Summary In case–control research where there are multiple case groups, standard analyses fail to make use of all available information. Multiple events case–control (MECC) studies provide a new approach to sampling from a cohort and are useful when it is desired to study multiple types of events in the cohort. In this design, subjects in the cohort who develop any event of interest are sampled, as well as a fraction of the remaining subjects. We show that a simple case–control analysis of data arising from MECC studies is biased and develop three general estimating‐equation‐based approaches to analyzing data from these studies. We conduct simulation studies to compare the efficiency of the various MECC analyses with each other and with the corresponding conventional analyses. It is shown that the gain in efficiency by using the new design is substantial in many situations. We demonstrate the application of our approach to a nested case–control study of the effect of oral sodium phosphate use on chronic kidney injury with multiple case definitions.     

Macrophage inhibitory cytokine‐1 (MIC‐1/GDF15): a new marker of all‐cause mortality

Macrophage inhibitory cytokine‐1 (MIC‐1/GDF15) is a member of the TGF‐b superfamily, previously studied in cancer and inflammation. In addition to regulating body weight, MIC‐1/GDF15 may be used to predict mortality and/or disease course in cancer, cardiovascular disease (CVD), chronic renal and heart failure, as well as pulmonary embolism. These data suggested that MIC‐1/GDF15 may be a marker of all‐cause mortality. To determine whether serum MIC‐1/GDF15 estimation is a predictor of all‐cause mortality, we examined a cohort of 876 male subjects aged 35–80 years, selected from the Swedish Population Registry, and followed them for overall mortality. Serum MIC‐1/GDF15 levels were determined for all subjects from samples taken at study entry. A second (independent) cohort of 324 same‐sex twins (69% female) from the Swedish Twin Registry was similarly examined. All the twins had telomere length measured and 183 had serum levels of interleukin 6 (IL‐6) and C‐reactive protein (CRP) available. Patients were followed for up to 14 years and had cause‐specific and all‐cause mortality determined. Serum MIC‐1/GDF15 levels predicted mortality in the all‐male cohort with an adjusted odds ratio (OR) of death of 3.38 (95%CI 1.38–8.26). This finding was validated in the twin cohort. Serum MIC‐1/GDF15 remained an independent predictor of mortality when further adjusted for telomere length, IL‐6 and CRP. Additionally, serum MIC‐1/GDF15 levels were directly correlated with survival time independently of genetic background. Serum MIC‐1/GDF15 is a novel predictor of all‐cause mortality.     

Breeding experience and population density affect the ability of a songbird to respond to future climate variation

Predicting how populations respond to climate change requires an understanding of whether individuals or cohorts within populations vary in their response to climate variation. We used mixed-effects models on a song sparrow (Melospiza melodia) population in British Columbia, Canada, to examine differences among females and cohorts in their average breeding date and breeding date plasticity in response to the El Niño Southern Oscillation. Climatic variables, age and population density were strong predictors of timing of breeding, but we also found considerable variation among individual females and cohorts. Within cohorts, females differed markedly in their breeding date and cohorts also differed in their average breeding date and breeding date plasticity. The plasticity of a cohort appeared to be due primarily to an interaction between the environmental conditions (climate and density) experienced at different ages rather than innate inter-cohort differences. Cohorts that expressed higher plasticity in breeding date experienced warmer El Niño springs in their second or third breeding season, suggesting that prior experience affects how well individuals responded to abnormal climatic conditions. Cohorts born into lower density populations also expressed higher plasticity in breeding date. Interactions between age, experience and environmental conditions have been reported previously for long-lived taxa. Our current results indicate that similar effects operate in a short-lived, temperate songbird.     

Changes in growth and maturation parameters of Pacific sardine Sardinops sagax collected off California during a period of stock recovery from 1994 to 2010

Whether fluctuation in density influenced the growth and maturation variables of three aggregated cohorts (fish born during the 1986–1993, 1996–2003 and 2004–2008 periods) of Pacific sardine Sardinops sagax caeruleus collected off the Californian coast from 2004 to 2010 was investigated. Using a von Bertalanffy mixed‐effects model with aggregated cohorts as covariates, estimated growth rate significantly covaried with aggregated cohorts. Growth rate (K) was modelled as a fixed effect and estimated to be 0·264 ± 0·015 (±s.e ). Statistical contrasts among aggregated cohorts showed that the 1996–2003 cohorts had a significantly lower growth rate than the other two aggregated cohorts. The theoretical age at length zero (t₀) and the standard length at infinity (L_S∞) were modelled as random effects, and were estimated to be ?2·885 ± 0·259 (±s.e ) and 273·13 ± 6·533 mm (±s.e ). The relation of ovary‐free mass at length was significantly different among the three aggregated cohorts, with the allometric coefficient estimated to be 2·850 ± 0·013 (±s.e ) for the S. sagax population. The age‐at‐length trajectory of S. sagax born between 1986 and 2008 showed strong density dependence effects on somatic growth rates. In contrast to the density‐dependent nature of growth, the probability to be mature at‐size or at‐age was not significantly affected by aggregated cohort density. The size and the age‐at‐50% maturity were estimated to be 150·92 mm and 0·56 years, respectively. Stock migration, natural fluctuations in biomass and removal of older and larger S. sagax by fishing might have been interplaying factors controlling growth parameters during 1986–2010.     

Automated Assay of Telomere Length Measurement and Informatics for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort

The Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH) Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort includes DNA specimens extracted from saliva samples of 110,266 individuals. Because of its relationship to aging, telomere length measurement was considered an important biomarker to develop on these subjects. To assay relative telomere length (TL) on this large cohort over a short time period, we created a novel high throughput robotic system for TL analysis and informatics. Samples were run in triplicate, along with control samples, in a randomized design. As part of quality control, we determined the within-sample variability and employed thresholds for the elimination of outlying measurements. Of 106,902 samples assayed, 105,539 (98.7%) passed all quality control (QC) measures. As expected, TL in general showed a decline with age and a sex difference. While telomeres showed a negative correlation with age up to 75 years, in those older than 75 years, age positively correlated with longer telomeres, indicative of an association of longer telomeres with more years of survival in those older than 75. Furthermore, while females in general had longer telomeres than males, this difference was significant only for those older than age 50. An additional novel finding was that the variance of TL between individuals increased with age. This study establishes reliable assay and analysis methodologies for measurement of TL in large, population-based human studies. The GERA cohort represents the largest currently available such resource, linked to comprehensive electronic health and genotype data for analysis.     

Helicobacter pylori and the birth cohort effect: evidence for stabilized colonization rates in childhood

Background: The prevalence of Helicobacter pylori has declined over recent decades in developed countries. The increasing prevalence with age is largely because of a birth cohort effect. We previously observed a decline in H. pylori prevalence in 6‐ to 8‐year‐old Dutch children from 19% in 1978 to 9% in 1993. Knowledge about birth‐cohort‐related H. pylori prevalence is relevant as a predictor for the future incidence of H. pylori‐associated conditions. Aim: The aim of this study was to investigate whether the birth cohort effect of H. pylori observed between 1978 and 1993 continued in subsequent years. Methods: Anti‐H. pylori IgG antibodies and anti‐CagA IgG antibodies were determined in serum samples obtained in 2005/2006 from 545 Dutch children aged 7–9 years who participated in the Prevention and Incidence of Asthma and Mite Allergy birth cohort. The H. pylori and CagA antibodies were determined by enzyme‐linked immunosorbent assays that have been extensively validated in children, with a 94% sensitivity for H. pylori colonization and a 92.5% sensitivity for colonization with a cagA‐positive strain. Results: Of the 545 children (M/F 300/245), most (91.5%) were of Dutch descent. The H. pylori positivity rate was 9% (95% CI 6.6–11.4%). The prevalence of CagA antibodies was 0.9% (95% CI 0.1–1.6%). No significant differences were demonstrated in H. pylori and cagA prevalence in relation to gender or ethnicity. Conclusion: The prevalence of H. pylori in childhood has remained stable in the Netherlands from 1993 to 2005, suggesting a stabilization of the previously decreasing trend in subsequent birth cohorts. This finding may reflect stabilization in determinants such as family size, housing, and hygienic conditions (or offset by day care). If confirmed in other populations in developed countries, it implies that colonization with H. pylori will remain common in the coming decades. Remarkably however, the rate of colonization with cagA⁺H. pylori strains has become very low, consistent with prior observations that cagA⁺ strains are disappearing in Western countries.     

Case-control and case-only designs with genotype and family history data: estimating relative risk, residual familial aggregation, and cumulative risk

In case-control studies of inherited diseases, participating subjects (probands) are often interviewed to collect detailed data about disease history and age-at-onset information in their family members. Genotype data are typically collected from the probands, but not from their relatives. In this article, we introduce an approach that combines case-control analysis of data on the probands with kin-cohort analysis of disease history data on relatives. Assuming a marginally specified multivariate survival model for joint risk of disease among family members, we describe methods for estimating relative risk, cumulative risk, and residual familial aggregation. We also describe a variation of the methodology that can be used for kin-cohort analysis of the family history data from a sample of genotyped cases only. We perform simulation studies to assess performance of the proposed methodologies with correct and mis-specified models for familial aggregation. We illustrate the proposed methodologies by estimating the risk of breast cancer from BRCA1/2 mutations using data from the Washington Ashkenazi Study.