Biology subjects

Adamski, J.

Publications and source records attributed to Adamski, J..

4 recordsLinked to original sources

bioRxiv2018

Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: an overview of the data from the epidemiological studies within the IMI DIRECT Consortium

Abstract/SummaryO_ST_ABSBackground and aimsC_ST_ABSUnderstanding the aetiology, clinical presentation and prognosis of type 2 diabetes (T2D) and optimizing its treatment might be facilitated by biomarkers that help predict a persons susceptibility to the risk factors that cause diabetes or its complications, or response to treatment. The IMI DIRECT (Diabetes Research on Patient Stratification) Study is a European Union (EU) Innovative Medicines Initiative (IMI) project that seeks to test these hypotheses in two recently established epidemiological cohorts. Here, we describe the characteristics of these cohorts at baseline and at the first main follow-up examination (18-months).\n\nMaterials and methodsFrom a sampling-frame of 24,682 European-ancestry adults in whom detailed health information was available, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm and enrolled into a prospective cohort study (n=2127) undertaken at four study centres across Europe (Cohort 1: prediabetes). We also recruited people from clinical registries with recently diagnosed T2D (n=789) into a second cohort study (Cohort 2: diabetes). The two cohorts were studied in parallel with matched protocols. Endogenous insulin secretion and insulin sensitivity were modelled from frequently sampled 75g oral glucose tolerance (OGTT) in Cohort 1 and with mixed-meal tolerance tests (MMTT) in Cohort 2. Additional metabolic biochemistry was determined using blood samples taken when fasted and during the tolerance tests. Body composition was assessed using MRI and lifestyle measures through self-report and objective methods.\n\nResultsUsing ADA-2011 glycaemic categories, 33% (n=693) of Cohort 1 (prediabetes) had normal glucose regulation (NGR), and 67% (n=1419) had impaired glucose regulation (IGR). 76% of the cohort was male, age=62(6.2) years; BMI=27.9(4.0) kg/m2; fasting glucose=5.7(0.6) mmol/l; 2-hr glucose=5.9(1.6) mmol/l [mean(SD)]. At follow-up, 18.6(1.4) months after baseline, fasting glucose=5.8(0.6) mmol/l; 2-hr OGTT glucose=6.1(1.7) mmol/l [mean(SD)]. In Cohort 2 (diabetes): 65% (n=508) were lifestyle treated (LS) and 35% (n=271) were lifestyle + metformin treated (LS+MET). 58% of the cohort was male, age=62(8.1) years; BMI=30.5(5.0) kg/m2; fasting glucose=7.2(1.4)mmol/l; 2-hr glucose=8.6(2.8) mmol/l [mean(SD)]. At follow-up, 18.2(0.6) months after baseline, fasting glucose=7.8(1.8) mmol/l; 2-hr MMTT glucose=9.5(3.3) mmol/l [mean(SD)].\n\nConclusionThe epidemiological IMI DIRECT cohorts are the most intensely characterised prospective studies of glycaemic deterioration to date. Data from these cohorts help illustrate the heterogeneous characteristics of people at risk of or with T2D, highlighting the rationale for biomarker stratification of the disease - the primary objective of the IMI DIRECT consortium.\n\nAbbreviations

epidemiology↗

bioRxiv2018

Unraveling rice tolerance mechanisms against Schizotetranychus oryzae mite infestation

Infestation of Schizotetranychus oryzae (Acari: Tetranychidae) causes great losses in rice productivity. Infestation in Puita INTA-CL cultivar reduced the number of seeds/plant, percentage of full seeds, 1,000 seeds weight, and seed length, whereas infestation in IRGA423 increased 1,000 seeds weight and seed length. Reduction in seed weight/plant caused by infestation was higher in Puita INTA-CL than IRGA423. Thus, Puita INTA-CL was established as susceptible, and IRGA423 as tolerant to S. oryzae infestation. Photosynthetic parameters were less affected by infestation in IRGA423 than in Puita INTA-CL. Infestation also caused accumulation of H2O2, decreased cell membrane integrity and accelerated senescence in leaves of Puita INTA-CL, while leaves of IRGA423 presented higher levels of phenolics compounds. Using proteomic analysis, we identified proteins related to plant defense, such as jasmonate synthesis, and related to other mechanisms of tolerance such as oxidative stress, photosynthesis, and DNA structure maintenance, more abundant in IRGA423 after seven days of infestation. We detected higher levels of silicon (as amorphous silica cells) in leaves of infested IRGA423 plants compared to Puita INTA-CL, an element previously linked to plant defense. Our data shows that IRGA423 presents tolerance to S. oryzae infestation, and that multiple mechanisms might be employed by this cultivar.\n\nHighlightThis is the first report evaluating the defense responses (tolerance and susceptiblity) of two contrasting rice cultivars to Schizotetranychus oryzae mite infestation.

plant biology↗

bioRxiv2017

Low-level mitochondrial heteroplasmy modulates DNA replication, glucose metabolism and lifespan in mice

Mutations in mitochondrial DNA (mtDNA) lead to heteroplasmy, i.e. the intracellular coexistence of wild-type and mutant mtDNA strands, which impact a wide spectrum of diseases but also physiological processes, including endurance exercise performance in athletes. However, the phenotypic consequences of limited levels of naturally-arising heteroplasmy have not been experimentally studied to date. We hence generated a conplastic mouse strain carrying the mitochondrial genome of a AKR/J mouse strain (B6-mtAKR) together with a C57BL/6J nuclear genomic background, leading to >20% heteroplasmy in the origin of light-strand DNA replication (OriL). These conplastic mice demonstrate a shorter lifespan as well as dysregulation of multiple metabolic pathways, culminating in impaired glucose metabolism, compared to wild-type C57BL/6J mice carrying lower levels of heteroplasmy. Our results indicate that physiologically relevant differences in mtDNA heteroplasmy levels at a single, functionally important site impair metabolic health and lifespan in mice.\n\nHighlightsO_LIWe identify heteroplasmy of the adenine-repeat variation (9 to 13A) in nt5172 in the origin of light-strand DNA replication (OriL) in inbred mice.\nC_LIO_LIB6-mtAKR mice carry >20% 12A heteroplasmy in the OriL, while B6 mice carry only [~] 10% heteroplasmy.\nC_LIO_LIThe level of 12A heteroplasmy correlates to mtDNA copy number, glucose metabolism, and lifespan in mice.\nC_LIO_LIGiven the established role of mtDNA heteroplasmy in regards to endurance exercise performance in athletes, these findings may impact our understanding of metabolism and aging in humans.\nC_LI

genetics↗

bioRxiv2016

Network based conditional genome wide association analysis of human metabolomics

BackgroundGenome-wide association studies (GWAS) have identified hundreds of loci influencing complex human traits, however, their biological mechanism of action remains mostly unknown. Recent accumulation of functional genomics ( omics) including metabolomics data opens up opportunities to provide a new insight into the functional role of specific changes in the genome. Functional genomic data are characterized by high dimensionality, presence of (strong) statistical dependencies between traits, and, potentially, complex genetic control. Therefore, analysis of such data asks for development of specific statistical genetic methods.\n\nResultsWe propose a network-based, conditional approach to evaluate the impact of genetic variants on omics phenotypes (conditional GWAS, cGWAS). For each trait of interest, based on biological network, we select a set of other traits to be used as covariates in GWAS. The network could be reconstructed either from biological pathway databases or directly from the data. We evaluated our approach using data from a population-based KORA study (n=1,784, 1.7 M SNPs) with measured metabolomics data (151 metabolites) and demonstrated that our approach allows for identification of up to five additional loci not detected by conventional GWAS. We show that this gain in power is achieved through increased precision of genetic effect estimates, and in presence of specific contra-intuitive pleiotropic scenarios (when genetic and environmental sources of covariance are acting in opposite manner). We justify existence of such scenarios, and discuss possible applications of our method beyond metabolomics.\n\nConclusionsWe demonstrate that in context of metabolomics network-based, conditional genome-wide association analysis is able to dramatically increase power of identification of loci with specific contra-intuitive pleiotropic architecture. Our method has modest computational costs, can utilize summary level GWAS data, and is applicable to other omics data types. We anticipate that application of our method to new and existing data sets will facilitate progress in understanding genetic bases of control of molecular and complex phenotypes.\n\nShort abstractWe propose a network-based, conditional approach for genome-wide analysis of multivariate omics phenotypes. Our methods can incorporate prior biological knowledge about biological pathways from external sources. We evaluated our approach using metabolomics data and demonstrated that our approach has bigger power and allows for identification of additional loci. We show that gain in power is achieved through increased precision of genetic effect estimates, and in presence of specific contra-intuitive pleiotropic scenarios (when genetic and environmental sources of covariance are acting in opposite manner). We justify existence of such scenarios, and discuss possible applications of our method beyond metabolomics.

genomics↗