First effects of rising amyloid-β in transgenic mouse brain: synaptic transmission and gene expression.

Detecting and treating Alzheimer's disease, before cognitive deficits occur, has become the health challenge of our time. The earliest known event in Alzheimer's disease is rising amyloid-β. Previous studies have suggested that effects on synaptic transmission may precede plaque deposition. Here we report how relative levels of different soluble amyloid-β peptides in hippocampus, preceding plaque deposition, relate to synaptic and genomic changes. Immunoprecipitation-mass spectrometry was used to measure the early rise of different amyloid-β peptides in a mouse model of increasing amyloid-β ('TASTPM', transgenic for familial Alzheimer's disease genes APP/PSEN1). In the third postnatal week, several amyloid-β peptides were above the limit of detection, including amyloid-β40, amyloid-β38 and amyloid-β42 with an intensity ratio of 6:3:2, respectively. By 2 months amyloid-β levels had only increased by 50% and although the ratio of the different peptides remained constant, the first changes in synaptic currents, compared to wild-type mice could be detected with patch-clamp recordings. Between 2 and 4 months old, levels of amyloid-β40 rose by ∼7-fold, but amyloid-β42 rose by 25-fold, increasing the amyloid-β42:amyloid-β40 ratio to 1:1. Only at 4 months did plaque deposition become detectable and only in some mice; however, synaptic changes were evident in all hippocampal fields. These changes included increased glutamate release probability (P < 0.001, n = 7-9; consistent with the proposed physiological effect of amyloid-β) and loss of spontaneous action potential-mediated activity in the cornu ammonis 1 (CA1) and dentate gyrus regions of the hippocampus (P < 0.001, n = 7). Hence synaptic changes occur when the amyloid-β levels and amyloid-β42:amyloid-β40 ratio are still low compared to those necessary for plaque deposition. Genome-wide microarray analysis revealed changes in gene expression at 2-4 months including synaptic genes being strongly affected but often showing significant changes only by 4 months. We thus demonstrate that, in a mouse model of rising amyloid-β, the initial deposition of plaques does not occur until several months after the first amyloid-β becomes detectable but coincides with a rapid acceleration in the rise of amyloid-β levels and the amyloid-β42:amyloid-β40 ratio. Prior to acceleration, however, there is already a pronounced synaptic dysfunction, reflected as changes in synaptic transmission and altered gene expression, indicating that restoring synaptic function early in the disease progression may represent the earliest possible target for intervention in the onset of Alzheimer's disease

Effect of weight loss, with or without exercise, on body composition and sex hormones in postmenopausal women: the SHAPE-2 trial

Introduction Physical inactivity and overweight are risk factors for postmenopausal breast cancer. The effect of physical activity may be partially mediated by concordant weight loss. We studied the effect on serum sex hormones, which are known to be associated with postmenopausal breast cancer risk, that is attributable to exercise by comparing randomly obtained equivalent weight loss by following a hypocaloric diet only or mainly by exercise. Methods Overweight, insufficiently active women were randomised to a diet (N = 97), mainly exercise (N = 98) or control group (N = 48). The goal of both interventions was to achieve 5–6 kg of weight loss by following a calorie-restricted diet or an intensive exercise programme combined with only a small caloric restriction. Primary outcomes after 16 weeks were serum sex hormones and sex hormone-binding globulin (SHBG). Body fat and lean mass were measured by dual-energy X-ray absorptiometry. Results Both the diet (−4.9 kg) and mainly exercise (−5.5 kg) groups achieved the target weight loss. Loss of body fat was significantly greater with exercise versus diet (difference −1.4 kg, P < 0.001). In the mainly exercise arm, the reduction in free testosterone was statistically significantly greater than that of the diet arm (treatment effect ratio [TER] 0.92, P = 0.043), and the results were suggestive of a difference for androstenedione (TER 0.90, P = 0.064) and SHBG (TER 1.05, P = 0.070). Compared with the control arm, beneficial effects were seen with both interventions, diet and mainly exercise, respectively, on oestradiol (TER 0.86, P = 0.025; TER 0.83, P = 0.007), free oestradiol (TER 0.80, P = 0.002; TER 0.77, P < 0.001), SHBG (TER 1.14; TER 1.21, both P < 0.001) and free testosterone (TER 0.91, P = 0.069; TER = 0.84, P = 0.001). After adjustment for changes in body fat, intervention effects attenuated or disappeared. Conclusions Weight loss with both interventions resulted in favourable effects on serum sex hormones, which have been shown to be associated with a decrease in postmenopausal breast cancer risk. Weight loss induced mainly by exercise additionally resulted in maintenance of lean mass, greater fitness, greater fat loss and a larger effect on (some) sex hormones. The greater fat loss likely explains the observed larger effects on sex hormone

The poly-omics of ageing through individual-based metabolic modelling

Abstract Background Ageing can be classified in two different ways, chronological ageing and biological ageing. While chronological age is a measure of the time that has passed since birth, biological (also known as transcriptomic) ageing is defined by how time and the environment affect an individual in comparison to other individuals of the same chronological age. Recent research studies have shown that transcriptomic age is associated with certain genes, and that each of those genes has an effect size. Using these effect sizes we can calculate the transcriptomic age of an individual from their age-associated gene expression levels. The limitation of this approach is that it does not consider how these changes in gene expression affect the metabolism of individuals and hence their observable cellular phenotype. Results We propose a method based on poly-omic constraint-based models and machine learning in order to further the understanding of transcriptomic ageing. We use normalised CD4 T-cell gene expression data from peripheral blood mononuclear cells in 499 healthy individuals to create individual metabolic models. These models are then combined with a transcriptomic age predictor and chronological age to provide new insights into the differences between transcriptomic and chronological ageing. As a result, we propose a novel metabolic age predictor. Conclusions We show that our poly-omic predictors provide a more detailed analysis of transcriptomic ageing compared to gene-based approaches, and represent a basis for furthering our knowledge of the ageing mechanisms in human cells

Integrative genomic analysis implicates limited peripheral adipose storage capacity in the pathogenesis of human insulin resistance.

Insulin resistance is a key mediator of obesity-related cardiometabolic disease, yet the mechanisms underlying this link remain obscure. Using an integrative genomic approach, we identify 53 genomic regions associated with insulin resistance phenotypes (higher fasting insulin levels adjusted for BMI, lower HDL cholesterol levels and higher triglyceride levels) and provide evidence that their link with higher cardiometabolic risk is underpinned by an association with lower adipose mass in peripheral compartments. Using these 53 loci, we show a polygenic contribution to familial partial lipodystrophy type 1, a severe form of insulin resistance, and highlight shared molecular mechanisms in common/mild and rare/severe insulin resistance. Population-level genetic analyses combined with experiments in cellular models implicate CCDC92, DNAH10 and L3MBTL3 as previously unrecognized molecules influencing adipocyte differentiation. Our findings support the notion that limited storage capacity of peripheral adipose tissue is an important etiological component in insulin-resistant cardiometabolic disease and highlight genes and mechanisms underpinning this link.This study was funded by the UK Medical Research Council through grants MC_UU_12015/1, MC_PC_13046, MC_PC_13048 and MR/L00002/1. This work was supported by the MRC Metabolic Diseases Unit (MC_UU_12012/5) and the Cambridge NIHR Biomedical Research Centre and EU/EFPIA Innovative Medicines Initiative Joint Undertaking (EMIF grant 115372). Funding for the InterAct project was provided by the EU FP6 program (grant LSHM_CT_2006_037197). This work was funded, in part, through an EFSD Rising Star award to R.A.S. supported by Novo Nordisk. D.B.S. is supported by Wellcome Trust grant 107064. M.I.M. is a Wellcome Trust Senior Investigator and is supported by the following grants from the Wellcome Trust: 090532 and 098381. M.v.d.B. is supported by a Novo Nordisk postdoctoral fellowship run in partnership with the University of Oxford. I.B. is supported by Wellcome Trust grant WT098051. S.O'R. acknowledges funding from the Wellcome Trust (Wellcome Trust Senior Investigator Award 095515/Z/11/Z and Wellcome Trust Strategic Award 100574/Z/12/Z)

The macrophage at the intersection of immunity and metabolism in obesity

Obesity is a worldwide pandemic representing one of the major challenges that societies face around the globe. Identifying the mechanisms involved in its development and propagation will help the development of preventative and therapeutic strategies that may help control its rising rates