A role for the actin cytoskeleton in cell death and aging in yeast

Several determinants of aging, including metabolic capacity and genetic stability, are recognized in both yeast and humans. However, many aspects of the pathways leading to cell death remain to be elucidated. Here we report a role for the actin cytoskeleton both in cell death and in promoting longevity. We have analyzed yeast strains expressing mutants with either increased or decreased actin dynamics. We show that decreased actin dynamics causes depolarization of the mitochondrial membrane and an increase in reactive oxygen species (ROS) production, resulting in cell death. Important, however, is the demonstration that increasing actin dynamics, either by a specific actin allele or by deletion of a gene encoding the actin-bundling protein Scp1p, can increase lifespan by over 65%. Increased longevity appears to be due to these cells producing lower than wild-type levels of ROS. Homology between Scp1p and mammalian SM22/transgelin, which itself has been isolated in senescence screens, suggests a conserved mechanism linking aging to actin stability.     

Association of a Body Mass Index Genetic Risk Score with Growth throughout Childhood and Adolescence

Background

While the number of established genetic variants associated with adult body mass index (BMI) is growing, the relationships between these variants and growth during childhood are yet to be fully characterised. We examined the association between validated adult BMI associated single nucleotide polymorphisms (SNPs) and growth trajectories across childhood. We investigated the timing of onset of the genetic effect and whether it was sex specific.

Methods

Children from the ALSPAC and Raine birth cohorts were used for analysis (n = 9,328). Genotype data from 32 adult BMI associated SNPs were investigated individually and as an allelic score. Linear mixed effects models with smoothing splines were used for longitudinal modelling of the growth parameters and measures of adiposity peak and rebound were derived.

Results

The allelic score was associated with BMI growth throughout childhood, explaining 0.58% of the total variance in BMI in females and 0.44% in males. The allelic score was associated with higher BMI at the adiposity peak (females  =  0.0163 kg/m² per allele, males  =  0.0123 kg/m² per allele) and earlier age (-0.0362 years per allele in males and females) and higher BMI (0.0332 kg/m² per allele in females and 0.0364 kg/m² per allele in males) at the adiposity rebound. No gene:sex interactions were detected for BMI growth.

Conclusions

This study suggests that known adult genetic determinants of BMI have observable effects on growth from early childhood, and is consistent with the hypothesis that genetic determinants of adult susceptibility to obesity act from early childhood and develop over the life course.     

Genetic Determinants of Height Growth Assessed Longitudinally from Infancy to Adulthood in the Northern Finland Birth Cohort 1966

Recent genome-wide association (GWA) studies have identified dozens of common variants associated with adult height. However, it is unknown how these variants influence height growth during childhood. We derived peak height velocity in infancy (PHV1) and puberty (PHV2) and timing of pubertal height growth spurt from parametric growth curves fitted to longitudinal height growth data to test their association with known height variants. The study consisted of N=3,538 singletons from the prospective Northern Finland Birth Cohort 1966 with genotype data and frequent height measurements (on average 20 measurements per person) from 0–20 years. Twenty-six of the 48 variants tested associated with adult height (p<0.05, adjusted for sex and principal components) in this sample, all in the same direction as in previous GWA scans. Seven SNPs in or near the genes HHIP, DLEU7, UQCC, SF3B4/SV2A, LCORL, and HIST1H1D associated with PHV1 and five SNPs in or near SOCS2, SF3B4/SV2A, C17orf67, CABLES1, and DOT1L with PHV2 (p<0.05). We formally tested variants for interaction with age (infancy versus puberty) and found biologically meaningful evidence for an age-dependent effect for the SNP in SOCS2 (p=0.0030) and for the SNP in HHIP (p=0.045). We did not have similar prior evidence for the association between height variants and timing of pubertal height growth spurt as we had for PHVs, and none of the associations were statistically significant after correction for multiple testing. The fact that in this sample, less than half of the variants associated with adult height had a measurable effect on PHV1 or PHV2 is likely to reflect limited power to detect these associations in this dataset. Our study is the first genetic association analysis on longitudinal height growth in a prospective cohort from birth to adulthood and gives grounding for future research on the genetic regulation of human height during different periods of growth.     

Vitamin D levels and risk of type 1 diabetes: A Mendelian randomization study

BackgroundVitamin D deficiency has been associated with type 1 diabetes in observational studies, but evidence from randomized controlled trials (RCTs) is lacking. The aim of this study was to test whether genetically decreased vitamin D levels are causally associated with type 1 diabetes using Mendelian randomization (MR).Methods and findingsFor our two-sample MR study, we selected as instruments single nucleotide polymorphisms (SNPs) that are strongly associated with 25-hydroxyvitamin D (25OHD) levels in a large vitamin D genome-wide association study (GWAS) on 443,734 Europeans and obtained their corresponding effect estimates on type 1 diabetes risk from a large meta-analysis of 12 type 1 diabetes GWAS studies (Ntot = 24,063, 9,358 cases, and 15,705 controls). In addition to the main analysis using inverse variance weighted MR, we applied 3 additional methods to control for pleiotropy (MR-Egger, weighted median, and mode-based estimate) and compared the respective MR estimates. We also undertook sensitivity analyses excluding SNPs with potential pleiotropic effects. We identified 69 lead independent common SNPs to be genome-wide significant for 25OHD, explaining 3.1% of the variance in 25OHD levels. MR analyses suggested that a 1 standard deviation (SD) decrease in standardized natural log-transformed 25OHD (corresponding to a 29-nmol/l change in 25OHD levels in vitamin D–insufficient individuals) was not associated with an increase in type 1 diabetes risk (inverse-variance weighted (IVW) MR odds ratio (OR) = 1.09, 95% CI: 0.86 to 1.40, p = 0.48). We obtained similar results using the 3 pleiotropy robust MR methods and in sensitivity analyses excluding SNPs associated with serum lipid levels, body composition, blood traits, and type 2 diabetes. Our findings indicate that decreased vitamin D levels did not have a substantial impact on risk of type 1 diabetes in the populations studied. Study limitations include an inability to exclude the existence of smaller associations and a lack of evidence from non-European populations.ConclusionsOur findings suggest that 25OHD levels are unlikely to have a large effect on risk of type 1 diabetes, but larger MR studies or RCTs are needed to investigate small effects.

Despoina Manousaki and co-workers investigate vitamin D levels and risk of type I diabetes.     

Directly modelling population dynamics in the South American Arid Diagonal using 14C dates

Large anthropogenic ¹⁴C datasets are widely used to generate summed probability distributions (SPDs) as a proxy for past human population levels. However, SPDs are a poor proxy when datasets are small, bearing little relationship to true population dynamics. Instead, more robust inferences can be achieved by directly modelling the population and assessing the model likelihood given the data. We introduce the R package ADMUR which uses a continuous piecewise linear (CPL) model of population change, calculates the model likelihood given a ¹⁴C dataset, estimates credible intervals using Markov chain Monte Carlo, applies a goodness-of-fit test, and uses the Schwarz Criterion to compare CPL models. We demonstrate the efficacy of this method using toy data, showing that spurious dynamics are avoided when sample sizes are small, and true population dynamics are recovered as sample sizes increase. Finally, we use an improved ¹⁴C dataset for the South American Arid Diagonal to compare CPL modelling to current simulation methods, and identify three Holocene phases when population trajectory estimates changed from rapid initial growth of 4.15% per generation to a decline of 0.05% per generation between 10 821 and 7055 yr BP, then gently grew at 0.58% per generation until 2500 yr BP.This article is part of the theme issue ‘Cross-disciplinary approaches to prehistoric demography’.