Bivariate genetic modelling of the response to an oral glucose tolerance challenge: A gene x environment interaction approach

AIMS/HYPOTHESIS: Twin and family studies have shown the importance of genetic factors influencing fasting and 2 h glucose and insulin levels. However, the genetics of the physiological response to a glucose load has not been thoroughly investigated. METHODS: We studied 580 monozygotic and 1,937 dizygotic British female twins from the Twins UK Registry. The effects of genetic and environmental factors on fasting and 2 h glucose and insulin levels were estimated using univariate genetic modelling. Bivariate model fitting was used to investigate the glucose and insulin responses to a glucose load, i.e. an OGTT. RESULTS: The genetic effect on fasting and 2 h glucose and insulin levels ranged between 40% and 56% after adjustment for age and BMI. Exposure to a glucose load resulted in the emergence of novel genetic effects on 2 h glucose independent of the fasting level, accounting for about 55% of its heritability. For 2 h insulin, the effect of the same genes that already influenced fasting insulin was amplified by about 30%. CONCLUSIONS/INTERPRETATION: Exposure to a glucose challenge uncovers new genetic variance for glucose and amplifies the effects of genes that already influence the fasting insulin level. Finding the genes acting on 2 h glucose independently of fasting glucose may offer new aetiological insight into the risk of cardiovascular events and death from all causes

Defective WNT signaling may protect from articular cartilage deterioration - a quantitative MRI study on subjects with a heterozygous WNT1 mutation

Objective: WNT signaling is of key importance in chondrogenesis and defective WNT signaling may contribute to the pathogenesis of osteoarthritis and other cartilage diseases. Biochemical composition of articular cartilage in patients with aberrant WNT signaling has not been studied. Our objective was to assess the knee articular cartilage in WNT1 mutation-positive individuals using a 3.0T MRI unit to measure cartilage thickness, relaxation times, and texture features. Design: Cohort comprised mutation-positive (N = 13; age 17-76 years) and mutation-negative (N = 13; 16-77 years) subjects from two Finnish families with autosomal dominant WNT1 osteoporosis due to a heterozygous missense mutation c.652T>G (p.C218G) in WNT1. All subjects were imaged with a 3.0T MRI unit and assessed for cartilage thickness, T2 and T1 rho relaxation times, and T2 texture features contrast, dissimilarity and homogeneity of T2 relaxation time maps in six regions of interest (ROIs) in the tibiofemoral cartilage. Results: All three texture features showed opposing trends with age between the groups in the medial tibiofemoral cartilage (P = 0.020-0.085 for the difference of the regression coefficients), the mutation-positive individuals showing signs of cartilage preservation. No significant differences were observed in the lateral tibiofemoral cartilage. Cartilage thickness and means of T2 relaxation time did not differ between groups. Means of T1r relaxation time were significantly different in one ROI but the regression analysis displayed no differences. Conclusions: Our results show less age-related cartilage deterioration in the WNT1 mutation-positive than the mutation-negative subjects. This suggests, that the WNT1 mutation may alter cartilage turnover and even have a potential cartilage-preserving effect. (C) 2019 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.Peer reviewe

Dynamic calcium-mediated stress response and recovery signatures in the fungal pathogen, Candida albicans

Acknowledgements AB conceived the project and wrote the manuscript. CVG conceived the experimental design. SW designed the GCaMP reporter. AM, KL, LV-M, SC and TB constructed strains and optimised imaging. MF developed the image analysis software. CVG and CP carried out the microfluidics experiments and imaging analysis. NG assisted with preparation of the manuscript. PS, SN and DMR developed and undertook the theoretical data analysis and contributed to the interpretation of the results. Funding AB, CG and TB were funded by the Wellcome Trust [Grant number 206412/A/17/Z]. AB and DR were supported by a Wellcome Trust Institutional Strategic Support Award (WT204909/Z/16/Z). CP was funded by a University of Exeter studentship (113516). This work was also supported by a Royal Society URF (UF080611), an MRC NIRG (G0900211/90671) and the MRC-Centre for Medical Mycology at the University of Exeter (MR/N006364/2). DR was funded by the Medical Research Council (MR/P022405/1). SN was supported by the Medical Research Council via the GW4 BioMed2 DTP (MR/W006308/1). MCA was supported by a European Commission ITN ‘FungiBrain’ studentship (607963). LL and SC were funded by a Wellcome Trust Institutional Strategic Support Award to the University of Aberdeen. NG acknowledges support of Wellcome Trust Investigator, Collaborative, Equipment, Strategic and Biomedical Resource awards (101873, 200208, 215599, 224323). NG and AB thank the MRC (MR/M026663/2) for support. This study/research is funded by the National Institute for Health and Care Research (NIHR) Exeter Biomedical Research Centre (BRC). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.Peer reviewedPublisher PD

Genetic influences on the insulin response of the beta cell to different secretagogues

Aims/hypothesis: The aim of the present study was to estimate the heritability of the beta cell insulin response to glucose and to glucose combined with glucagon-like peptide-1 (GLP-1) or with GLP-1 plus arginine. Methods: This was a twin-family study that included 54 families from the Netherlands Twin Register. The participants were healthy twin pairs and their siblings of the same sex, aged 20 to 50 years. Insulin response of the beta cell was assessed by a modified hyperglycaemic clamp with additional GLP-1 and arginine. Insulin sensitivity index (ISI) was assessed by the euglycaemic-hyperinsulinaemic clamp. Multivariate structural equation modelling was used to obtain heritabilities and the genetic factors underlying individual differences in BMI, ISI and secretory responses of the beta cell. Results: The heritability of insulin levels in response to glucose was 52% and 77% for the first and second phase, respectively, 53% in response to glucose+GLP-1 and 80% in response to an additional arginine bolus. Insulin responses to the administration of glucose, glucose+GLP-1 and glucose+GLP-1+arginine were highly correlated (0.62<r<0.79). Heritability of BMI and ISI was 74% and 60% respectively. The genetic factors that influenced BMI and ISI explained about half of the heritability of insulin levels in response to the three secretagogues. The other half was due to genetic factors specific to the beta cell. Conclusions/interpretation: In healthy adults, genetic factors explain most of the individual differences in the secretory capacity of the beta cell. These genetic influences are partly independent from the genes that influence BMI and ISI. © 2009 Springer-Verlag

High-throughput muscle fiber typing from RNA sequencing data

Background Skeletal muscle fiber type distribution has implications for human health, muscle function, and performance. This knowledge has been gathered using labor-intensive and costly methodology that limited these studies. Here, we present a method based on muscle tissue RNA sequencing data (totRNAseq) to estimate the distribution of skeletal muscle fiber types from frozen human samples, allowing for a larger number of individuals to be tested. Methods By using single-nuclei RNA sequencing (snRNAseq) data as a reference, cluster expression signatures were produced by averaging gene expression of cluster gene markers and then applying these to totRNAseq data and inferring muscle fiber nuclei type via linear matrix decomposition. This estimate was then compared with fiber type distribution measured by ATPase staining or myosin heavy chain protein isoform distribution of 62 muscle samples in two independent cohorts (n = 39 and 22). Results The correlation between the sequencing-based method and the other two were rATPas = 0.44 [0.13–0.67], [95% CI], and rmyosin = 0.83 [0.61–0.93], with p = 5.70 × 10–3 and 2.00 × 10–6, respectively. The deconvolution inference of fiber type composition was accurate even for very low totRNAseq sequencing depths, i.e., down to an average of ~ 10,000 paired-end reads. Conclusions This new method (https://github.com/OlaHanssonLab/PredictFiberType) consequently allows for measurement of fiber type distribution of a larger number of samples using totRNAseq in a cost and labor-efficient way. It is now feasible to study the association between fiber type distribution and e.g. health outcomes in large well-powered studies.journal articl

High-throughput muscle fiber typing from RNA sequencing data

Background: Skeletal muscle fiber type distribution has implications for human health, muscle function, and performance. This knowledge has been gathered using labor-intensive and costly methodology that limited these studies. Here, we present a method based on muscle tissue RNA sequencing data (totRNAseq) to estimate the distribution of skeletal muscle fiber types from frozen human samples, allowing for a larger number of individuals to be tested. Methods: By using single-nuclei RNA sequencing (snRNAseq) data as a reference, cluster expression signatures were produced by averaging gene expression of cluster gene markers and then applying these to totRNAseq data and inferring muscle fiber nuclei type via linear matrix decomposition. This estimate was then compared with fiber type distribution measured by ATPase staining or myosin heavy chain protein isoform distribution of 62 muscle samples in two independent cohorts (n = 39 and 22). Results: The correlation between the sequencing-based method and the other two were r(ATpas) = 0.44 [0.13-0.67], [95% CI], and r(myosin) = 0.83 [0.61-0.93], with p = 5.70 x 10(-3) and 2.00 x 10(-6), respectively. The deconvolution inference of fiber type composition was accurate even for very low totRNAseq sequencing depths, i.e., down to an average of similar to 10,000 paired-end reads. Conclusions: This new method (https://github.com/OlaHanssonLab/PredictFiberType) consequently allows for measurement of fiber type distribution of a larger number of samples using totRNAseq in a cost and labor-efficient way. It is now feasible to study the association between fiber type distribution and e.g. health outcomes in large well-powered studies.Peer reviewe

The consequences of niche and physiological differentiation of archaeal and bacterial ammonia oxidisers for nitrous oxide emissions

The authors are members of the Nitrous Oxide Research Alliance (NORA), a Marie Skłodowska-Curie ITN and research project under the EU's seventh framework program (FP7). GN is funded by the AXA Research Fund and CGR by a Royal Society University Research Fellowship (UF150571) and a Natural Environment Research Council (NERC) Standard Grant (NE/K016342/1). The authors would like to thank Dr Robin Walker and the SRUC Craibstone Estate (Aberdeen) for access to the agricultural plots, Dr Alex Douglas for statistical advice and Philipp Schleusner for assisting microcosm construction and sampling.Peer reviewedPublisher PD