Showing papers by "University of Turku published in 2016"
TL;DR: In this article, the authors used a Bayesian hierarchical model to estimate trends in diabetes prevalence, defined as fasting plasma glucose of 7.0 mmol/L or higher, or history of diagnosis with diabetes, or use of insulin or oral hypoglycaemic drugs in 200 countries and territories in 21 regions, by sex and from 1980 to 2014.
2,782 citations
Harvard University1, Broad Institute2, University of California, Los Angeles3, VU University Medical Center4, VU University Amsterdam5, North Carolina State University6, University of North Carolina at Chapel Hill7, Karolinska Institutet8, University of Tampere9, University of Turku10, Turku University Hospital11, University of Eastern Finland12
TL;DR: A powerful strategy that integrates gene expression measurements with summary association statistics from large-scale genome-wide association studies (GWAS) to identify genes whose cis-regulated expression is associated with complex traits is introduced.
Abstract: Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance of one or multiple proteins. Here we introduce a powerful strategy that integrates gene expression measurements with summary association statistics from large-scale genome-wide association studies (GWAS) to identify genes whose cis-regulated expression is associated with complex traits. We leverage expression imputation from genetic data to perform a transcriptome-wide association study (TWAS) to identify significant expression-trait associations. We applied our approaches to expression data from blood and adipose tissue measured in ∼ 3,000 individuals overall. We imputed gene expression into GWAS data from over 900,000 phenotype measurements to identify 69 new genes significantly associated with obesity-related traits (BMI, lipids and height). Many of these genes are associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits.
1,473 citations
Stanford University1, Icahn School of Medicine at Mount Sinai2, Indiana University3, Memorial Sloan Kettering Cancer Center4, Mayo Clinic5, National Institutes of Health6, University of Utah7, Fred Hutchinson Cancer Research Center8, Johns Hopkins University9, NorthShore University HealthSystem10, University of Michigan11, University of North Carolina at Chapel Hill12, University of Turku13, Translational Genomics Research Institute14, Wayne State University15, University of Paris16, Cancer Council Victoria17, University of Melbourne18, University of Ulm19, University of Southern California20, Karolinska Institutet21, Northwestern University22, McGill University23, LSU Health Sciences Center New Orleans24
TL;DR: This work developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, LRT, GERP, SiPhy, phyloP, and phastCons.
Abstract: The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p −12 ) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies
1,295 citations
TL;DR: In this article, the results of a genome-wide association study (GWAS) for educational attainment were reported, showing that single-nucleotide polymorphisms associated with educational attainment disproportionately occur in genomic regions regulating gene expression in the fetal brain.
Abstract: Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.
1,102 citations
TL;DR: In this paper, a suite of developing theoretical tools is reviewed, with which recent progress on this problem has been based, and a more refined, non-Markovian, treatment is necessary.
Abstract: An ongoing theme in quantum physics is the interaction of small quantum systems with an environment. If that environment has many degrees of freedom and is weakly coupled, it can often be reasonable to treat its decohering effect on the small system using a ``memoryless,'' or Markovian description. This Colloquium shows that for many phenomena a more refined, non-Markovian, treatment is necessary. The suite of developing theoretical tools is reviewed, with which recent progress on this problem has been based.
1,007 citations
Smithsonian Institution1, Sun Yat-sen University2, University of California, Berkeley3, Naturalis4, Paris-Sorbonne University5, Universidade Federal de Minas Gerais6, University of Vermont7, Federal University of Western Pará8, University of Florida9, James Cook University10, Duke University11, University of Bonn12, University of Neuchâtel13, University of Turku14, University of Alaska Fairbanks15, Missouri Botanical Garden16, National Taiwan University17, Museum of New Zealand Te Papa Tongarewa18, National University of Río Cuarto19, University of Arizona20, Council of Agriculture21, Kaohsiung Medical University22, Chongqing Normal University23, Universidade Federal de Juiz de Fora24, Nanjing Forestry University25, Iowa State University26, Complutense University of Madrid27, University of Kansas28, Denison University29, University of Zurich30
TL;DR: A modern, comprehensive classification for lycophytes and ferns, down to the genus level, utilizing a community‐based approach, that uses monophyly as the primary criterion for the recognition of taxa, but also aims to preserve existing taxa and circumscriptions that are both widely accepted and consistent with the understanding of pteridophyte phylogeny.
Abstract: Phylogeny has long informed pteridophyte classification. As our ability to infer evolutionary trees has improved, classifications aimed at recognizing natural groups have become increasingly predic ...
971 citations
National Research Council1, Ghent University2, University of Sassari3, Institut national de la recherche agronomique4, ANSES5, Complutense University of Madrid6, Namik Kemal University7, University of Hohenheim8, Université catholique de Louvain9, Technical University of Denmark10, University of Turku11
TL;DR: The results of a collaborative integrated work which aims to characterize the trichothecene genotypes of strains from three Fusarium species, collected over the period 2000–2013 and to enhance the standardization of epidemiological data collection were described.
Abstract: Fusarium species, particularly Fusarium graminearum and F. culmorum, are the main cause of trichothecene type B contamination in cereals. Data on the distribution of Fusarium trichothecene genotypes in cereals in Europe are scattered in time and space. Furthermore, a common core set of related variables (sampling method, host cultivar, previous crop, etc.) that would allow more effective analysis of factors influencing the spatial and temporal population distribution, is lacking. Consequently, based on the available data, it is difficult to identify factors influencing chemotype distribution and spread at the European level. Here we describe the results of a collaborative integrated work which aims (1) to characterize the trichothecene genotypes of strains from three Fusarium species, collected over the period 2000–2013 and (2) to enhance the standardization of epidemiological data collection. Information on host plant, country of origin, sampling location, year of sampling and previous crop of 1147 F. graminearum, 479 F. culmorum, and 3 F. cortaderiae strains obtained from 17 European countries was compiled and a map of trichothecene type B genotype distribution was plotted for each species. All information on the strains was collected in a freely accessible and updatable database (www.catalogueeu.luxmcc.lu), which will serve as a starting point for epidemiological analysis of potential spatial and temporal trichothecene genotype shifts in Europe. The analysis of the currently available European dataset showed that in F. graminearum, the predominant genotype was 15-acetyldeoxynivalenol (15-ADON) (82.9%), followed by 3-acetyldeoxynivalenol (3-ADON) (13.6%), and nivalenol (NIV) (3.5%). In F. culmorum, the prevalent genotype was 3-ADON (59.9%), while the NIV genotype accounted for the remaining 40.1%. Both, geographical and temporal patterns of trichothecene genotypes distribution were identified.
936 citations
TL;DR: It is shown that Bacteroides LPS is structurally distinct from E. coli LPS and inhibits innate immune signaling and endotoxin tolerance, and that early colonization by immunologically silencing microbiota may preclude aspects of immune education.
879 citations
Aysu Okbay1, Bart M. L. Baselmans2, Jan-Emmanuel De Neve3, Patrick Turley4 +213 more•Institutions (65)
TL;DR: In this paper, the authors conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n= 161,460), and neuroticism(n = 170,911).
Abstract: Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.
796 citations
TL;DR: It is proposed that the stepwise microbial gut colonisation process may be initiated already prenatally by a distinct microbiota in the placenta and amniotic fluid, and the link between the mother and the offspring is continued after birth by microbes present in breast milk.
Abstract: Interaction with intestinal microbes in infancy has a profound impact on health and disease in later life through programming of immune and metabolic pathways. We collected maternal faeces, placenta, amniotic fluid, colostrum, meconium and infant faeces samples from 15 mother-infant pairs in an effort to rigorously investigate prenatal and neonatal microbial transfer and gut colonisation. To ensure sterile sampling, only deliveries at full term by elective caesarean section were studied. Microbiota composition and activity assessment by conventional bacterial culture, 16S rRNA gene pyrosequencing, quantitative PCR, and denaturing gradient gel electrophoresis revealed that the placenta and amniotic fluid harbour a distinct microbiota characterised by low richness, low diversity and the predominance of Proteobacteria. Shared features between the microbiota detected in the placenta and amniotic fluid and in infant meconium suggest microbial transfer at the foeto-maternal interface. At the age of 3–4 days, the infant gut microbiota composition begins to resemble that detected in colostrum. Based on these data, we propose that the stepwise microbial gut colonisation process may be initiated already prenatally by a distinct microbiota in the placenta and amniotic fluid. The link between the mother and the offspring is continued after birth by microbes present in breast milk.
753 citations
University of Helsinki1, University of Oulu2, University of Turku3, University of Tampere4, Turku University Hospital5, Hannover Medical School6, University of Cambridge7, Netherlands Cancer Institute8, Institute of Cancer Research9, University of Melbourne10, University of Erlangen-Nuremberg11, University of California, Los Angeles12, University of London13, King's College London14, Wellcome Trust Centre for Human Genetics15, Heidelberg University16, German Cancer Research Center17, French Institute of Health and Medical Research18, Copenhagen University Hospital19, University of Copenhagen20, Beckman Research Institute21, University of California, Irvine22, Technische Universität München23, University of Cologne24, University of Tübingen25, Bosch26, Ruhr University Bochum27, Karolinska Institutet28, University of Eastern Finland29, QIMR Berghofer Medical Research Institute30, Katholieke Universiteit Leuven31, University of Hamburg32, Mayo Clinic33, Cancer Council Victoria34, University of Southern California35, Laval University36, The Breast Cancer Research Foundation37, Oslo University Hospital38, Vanderbilt University39, Oulu University Hospital40, Lunenfeld-Tanenbaum Research Institute41, University of Toronto42, Leiden University Medical Center43, Erasmus University Rotterdam44, Erasmus University Medical Center45, University of Sheffield46, Pontifical Xavierian University47, Pomeranian Medical University48
TL;DR: It is suggested that loss-of-function mutations in RAD 51B are rare, but common variation at the RAD51B region is significantly associated with familial breast cancer risk.
Abstract: Common variation on 14q24.1, close to RAD51B, has been associated with breast cancer: rs999737 and rs2588809 with the risk of female breast cancer and rs1314913 with the risk of male breast cancer. The aim of this study was to investigate the role of RAD51B variants in breast cancer predisposition, particularly in the context of familial breast cancer in Finland. We sequenced the coding region of RAD51B in 168 Finnish breast cancer patients from the Helsinki region for identification of possible recurrent founder mutations. In addition, we studied the known rs999737, rs2588809, and rs1314913 SNPs and RAD51B haplotypes in 44,791 breast cancer cases and 43,583 controls from 40 studies participating in the Breast Cancer Association Consortium (BCAC) that were genotyped on a custom chip (iCOGS). We identified one putatively pathogenic missense mutation c.541C>T among the Finnish cancer patients and subsequently genotyped the mutation in additional breast cancer cases (n = 5259) and population controls (n = 3586) from Finland and Belarus. No significant association with breast cancer risk was seen in the meta-analysis of the Finnish datasets or in the large BCAC dataset. The association with previously identified risk variants rs999737, rs2588809, and rs1314913 was replicated among all breast cancer cases and also among familial cases in the BCAC dataset. The most significant association was observed for the haplotype carrying the risk-alleles of all the three SNPs both among all cases (odds ratio (OR): 1.15, 95% confidence interval (CI): 1.11-1.19, P = 8.88 x 10-16) and among familial cases (OR: 1.24, 95% CI: 1.16-1.32, P = 6.19 x 10-11), compared to the haplotype with the respective protective alleles. Our results suggest that loss-of-function mutations in RAD51B are rare, but common variation at the RAD51B region is significantly associated with familial breast cancer risk.
Erasmus University Rotterdam1, Leiden University Medical Center2, University of Oulu3, VU University Amsterdam4, University of Tartu5, University of Tampere6, University of Helsinki7, National Institutes of Health8, University of Eastern Finland9, Harvard University10, Indiana University11, Oulu University Hospital12, Turku University Hospital13, University of Turku14
TL;DR: The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism and strengthens the argument for safe LPA-targeted intervention to reduce cardiovascular risk.
Abstract: Genome-wide association studies have identified numerous loci linked with complex diseases, for which the molecular mechanisms remain largely unclear. Comprehensive molecular profiling of circulating metabolites captures highly heritable traits, which can help to uncover metabolic pathophysiology underlying established disease variants. We conduct an extended genome-wide association study of genetic influences on 123 circulating metabolic traits quantified by nuclear magnetic resonance metabolomics from up to 24,925 individuals and identify eight novel loci for amino acids, pyruvate and fatty acids. The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism. Genetic fine mapping and Mendelian randomization uncover wide-spread causal effects of lipoprotein(a) on overall lipoprotein metabolism and we assess potential pleiotropic consequences of genetically elevated lipoprotein(a) on diverse morbidities via electronic health-care records. Our findings strengthen the argument for safe LPA-targeted intervention to reduce cardiovascular risk.
TL;DR: A detailed assessment of the chemistry of Mn oxides by considering how their bulk and nanoscale properties contribute to their effectiveness as water-oxidizing catalysts and the issue of Mn complexes decomposing to Mn oxide is provided.
Abstract: All cyanobacteria, algae, and plants use a similar water-oxidizing catalyst for water oxidation. This catalyst is housed in Photosystem II, a membrane-protein complex that functions as a light-driven water oxidase in oxygenic photosynthesis. Water oxidation is also an important reaction in artificial photosynthesis because it has the potential to provide cheap electrons from water for hydrogen production or for the reduction of carbon dioxide on an industrial scale. The water-oxidizing complex of Photosystem II is a Mn–Ca cluster that oxidizes water with a low overpotential and high turnover frequency number of up to 25–90 molecules of O2 released per second. In this Review, we discuss the atomic structure of the Mn–Ca cluster of the Photosystem II water-oxidizing complex from the viewpoint that the underlying mechanism can be informative when designing artificial water-oxidizing catalysts. This is followed by consideration of functional Mn-based model complexes for water oxidation and the issue of Mn com...
University of Maryland, Baltimore1, Harvard University2, University of Florence3, University of Toulouse4, Catholic University of the Sacred Heart5, Université catholique de Louvain6, Katholieke Universiteit Leuven7, Yeshiva University8, University of Turku9, Memorial Hospital of South Bend10, University of California, San Francisco11, University of Barcelona12, Group Health Cooperative13, Seoul National University14, University of Minnesota15, California Pacific Medical Center16, French Institute of Health and Medical Research17, Johns Hopkins University18, University of Ferrara19
TL;DR: The association between poor performance on SPPB and all-cause mortality remained highly consistent independent of follow-up length, subsets of participants, geographic area, and age of the population.
Abstract: The Short Physical Performance Battery (SPPB) is a well-established tool to assess lower extremity physical performance status. Its predictive ability for all-cause mortality has been sparsely reported, but with conflicting results in different subsets of participants. The aim of this study was to perform a meta-analysis investigating the relationship between SPPB score and all-cause mortality. Articles were searched in MEDLINE, the Cochrane Library, Google Scholar, and BioMed Central between July and September 2015 and updated in January 2016. Inclusion criteria were observational studies; >50 participants; stratification of population according to SPPB value; data on all-cause mortality; English language publications. Twenty-four articles were selected from available evidence. Data of interest (i.e., clinical characteristics, information after stratification of the sample into four SPPB groups [0–3, 4–6, 7–9, 10–12]) were retrieved from the articles and/or obtained by the study authors. The odds ratio (OR) and/or hazard ratio (HR) was obtained for all-cause mortality according to SPPB category (with SPPB scores 10–12 considered as reference) with adjustment for age, sex, and body mass index. Standardized data were obtained for 17 studies (n = 16,534, mean age 76 ± 3 years). As compared to SPPB scores 10–12, values of 0–3 (OR 3.25, 95%CI 2.86–3.79), 4–6 (OR 2.14, 95%CI 1.92–2.39), and 7–9 (OR 1.50, 95%CI 1.32–1.71) were each associated with an increased risk of all-cause mortality. The association between poor performance on SPPB and all-cause mortality remained highly consistent independent of follow-up length, subsets of participants, geographic area, and age of the population. Random effects meta-regression showed that OR for all-cause mortality with SPPB values 7–9 was higher in the younger population, diabetics, and men. An SPPB score lower than 10 is predictive of all-cause mortality. The systematic implementation of the SPPB in clinical practice settings may provide useful prognostic information about the risk of all-cause mortality. Moreover, the SPPB could be used as a surrogate endpoint of all-cause mortality in trials needing to quantify benefit and health improvements of specific treatments or rehabilitation programs. The study protocol was published on PROSPERO (CRD42015024916).
Harvard University1, Broad Institute2, Oslo University Hospital3, University of Oslo4, University of Helsinki5, University of Tartu6, Boston Children's Hospital7, Illumina8, Brigham and Women's Hospital9, Charité10, deCODE genetics11, Medical Research Council12, VU University Amsterdam13, Leiden University14, Helsinki University Central Hospital15, University of Tübingen16, Ludwig Maximilian University of Munich17, Karolinska Institutet18, QIMR Berghofer Medical Research Institute19, University of Ulm20, University of Oulu21, King's College London22, Erasmus University Medical Center23, University of Tampere24, University of Duisburg-Essen25, Washington University in St. Louis26, University Medical Center Groningen27, Wellcome Trust Sanger Institute28, University of Oxford29, John Radcliffe Hospital30, Max Planck Society31, University of Kiel32, Technische Universität München33, National Institutes of Health34, Norwegian Institute of Public Health35, University of Copenhagen36, Lundbeck37, Mental Health Services38, University of Turku39, Turku University Hospital40, University of Hamburg41, St George's, University of London42, University of Iceland43, Queensland University of Technology44
TL;DR: For example, the authors identified 44 independent single-nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 × 10−8) that mapped to 38 distinct genomic loci, including 28 loci not previously reported and a locus that to date is the first to be identified on chromosome X.
Abstract: Migraine is a debilitating neurological disorder affecting around one in seven people worldwide, but its molecular mechanisms remain poorly understood. There is some debate about whether migraine is a disease of vascular dysfunction or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association (GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we carried out a genetic study of migraine on 59,674 affected subjects and 316,078 controls from 22 GWA studies. We identified 44 independent single-nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 × 10−8) that mapped to 38 distinct genomic loci, including 28 loci not previously reported and a locus that to our knowledge is the first to be identified on chromosome X. In subsequent computational analyses, the identified loci showed enrichment for genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular etiologies.
TL;DR: In the absolute rigidity range ∼60 to ∼500 GV, the antiproton p[over ¯], proton p, and positron e^{+} fluxes are found to have nearly identical rigidity dependence and the electron e^{-} flux exhibits a different rigidity dependent.
Abstract: A precision measurement by AMS of the antiproton flux and the antiproton-to-proton flux ratio in
primary cosmic rays in the absolute rigidity range from 1 to 450 GV is presented based on 3.49 × 105
antiproton events and 2.42 × 109 proton events. The fluxes and flux ratios of charged elementary particles
in cosmic rays are also presented. In the absolute rigidity range ∼60 to ∼500 GV, the antiproton ¯p, proton
p, and positron eþ fluxes are found to have nearly identical rigidity dependence and the electron e− flux
exhibits a different rigidity dependence. Below 60 GV, the ( ¯ p=p), ( ¯ p=eþ), and (p=eþ) flux ratios each
reaches a maximum. From ∼60 to ∼500 GV, the ( ¯ p=p), ( ¯ p=eþ), and (p=eþ) flux ratios show no rigidity
dependence. These are new observations of the properties of elementary particles in the cosmos.
TL;DR: In this paper, the MAGIC-I camera and its trigger system were replaced with a new one for low and medium zenith angles to assess the key performance parameters of MAGIC stereo system for point-like sources with Crab Nebula-like spectrum.
TL;DR: A meta-analysis of genome-wide association studies for estimated glomerular filtration rate suggests that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways.
Abstract: Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways.
Food and Drug Administration1, University of Birmingham2, Colorado State University3, Cornell University4, University of Barcelona5, University of Alberta6, University of Turku7, Leiden University8, Edith Cowan University9, Markey Cancer Center10, Research Triangle Park11, University of Luxembourg12, King Abdulaziz University13, University of California, Davis14, Duke University15
TL;DR: The narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature, expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis.
Abstract: Metabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or “-omics” level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person’s metabolic state provides a close representation of that individual’s overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates. We anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and stratification of patients based on metabolic pathways impacted; (4) reveal biomarkers for drug response phenotypes, providing an effective means to predict variation in a subject’s response to treatment (pharmacometabolomics); (5) define a metabotype for each specific genotype, offering a functional read-out for genetic variants: (6) provide a means to monitor response and recurrence of diseases, such as cancers: (7) describe the molecular landscape in human performance applications and extreme environments. Importantly, sophisticated metabolomic analytical platforms and informatics tools have recently been developed that make it possible to measure thousands of metabolites in blood, other body fluids, and tissues. Such tools also enable more robust analysis of response to treatment. New insights have been gained about mechanisms of diseases, including neuropsychiatric disorders, cardiovascular disease, cancers, diabetes and a range of pathologies. A series of ground breaking studies supported by National Institute of Health (NIH) through the Pharmacometabolomics Research Network and its partnership with the Pharmacogenomics Research Network illustrate how a patient’s metabotype at baseline, prior to treatment, during treatment, and post-treatment, can inform about treatment outcomes and variations in responsiveness to drugs (e.g., statins, antidepressants, antihypertensives and antiplatelet therapies). These studies along with several others also exemplify how metabolomics data can complement and inform genetic data in defining ethnic, sex, and gender basis for variation in responses to treatment, which illustrates how pharmacometabolomics and pharmacogenomics are complementary and powerful tools for precision medicine. Our metabolomics community believes that inclusion of metabolomics data in precision medicine initiatives is timely and will provide an extremely valuable layer of data that compliments and informs other data obtained by these important initiatives. Our Metabolomics Society, through its “Precision Medicine and Pharmacometabolomics Task Group”, with input from our metabolomics community at large, has developed this White Paper where we discuss the value and approaches for including metabolomics data in large precision medicine initiatives. This White Paper offers recommendations for the selection of state of-the-art metabolomics platforms and approaches that offer the widest biochemical coverage, considers critical sample collection and preservation, as well as standardization of measurements, among other important topics. We anticipate that our metabolomics community will have representation in large precision medicine initiatives to provide input with regard to sample acquisition/preservation, selection of optimal omics technologies, and key issues regarding data collection, interpretation, and dissemination. We strongly recommend the collection and biobanking of samples for precision medicine initiatives that will take into consideration needs for large-scale metabolic phenotyping studies.
TL;DR: Net protection of SGLT2 inhibitors against cardiovascular outcomes and death is suggested, driven by findings for empagliflozin (the only S GLT2 inhibitor for which data from a dedicated long-term cardiovascular safety trial have been reported), although results for the other drugs in the class were not clearly different.
Momoko Horikoshi1, Robin N Beaumont2, Felix R. Day3, Nicole M. Warrington4 +182 more•Institutions (55)
TL;DR: In this paper, the authors performed a meta-analysis of birth weight in 153,781 individuals, identifying 60 loci where fetal genotype was associated with birth weight (P < 5.5×10−8).
Abstract: Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease1. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10−8). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (Rg = −0.22, P = 5.5 × 10−13), T2D (Rg = −0.27, P = 1.1 × 10−6) and coronary artery disease (Rg = −0.30, P = 6.5 × 10−9). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10−4). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.
TL;DR: In this article, the authors provide a systematic synthesis of 144 studies that identify the proximate and underlying drivers of landscape change across Europe and find that land abandonment/extensification is the most prominent (62% of cases) among multiple proximate drivers.
TL;DR: The second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function, was conducted by as mentioned in this paper. But the results of the CAFA2 assessment are limited.
Abstract: BACKGROUND: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. RESULTS: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. CONCLUSIONS: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.
TL;DR: In this paper, a meta-analysis on the effects of agroforestry on ecosystem service provision and on biodiversity levels was conducted, and the results revealed an overall positive effect.
TL;DR: Brain regions contributing most to the classification accuracy included medial and inferior lateral prefrontal cortices, frontal pole, precentral and postcentral gyri, precuneus, and posterior cingulate cortex, suggesting a direct link between activity in these brain regions and the subjective emotional experience.
Abstract: Categorical models of emotions posit neurally and physiologically distinct human basic emotions. We tested this assumption by using multivariate pattern analysis (MVPA) to classify brain activity patterns of 6 basic emotions (disgust, fear, happiness, sadness, anger, and surprise) in 3 experiments. Emotions were induced with short movies or mental imagery during functional magnetic resonance imaging. MVPA accurately classified emotions induced by both methods, and the classification generalized from one induction condition to another and across individuals. Brain regions contributing most to the classification accuracy included medial and inferior lateral prefrontal cortices, frontal pole, precentral and postcentral gyri, precuneus, and posterior cingulate cortex. Thus, specific neural signatures across these regions hold representations of different emotional states in multimodal fashion, independently of how the emotions are induced. Similarity of subjective experiences between emotions was associated with similarity of neural patterns for the same emotions, suggesting a direct link between activity in these brain regions and the subjective emotional experience.
TL;DR: In this paper, the rigidity dependence of the boron to carbon flux ratio (B/C) is studied and a detailed variation with rigidity of the B=C spectral index is reported for the first time.
Abstract: Knowledge of the rigidity dependence of the boron to carbon flux ratio (B/C) is important in
understanding the propagation of cosmic rays. The precise measurement of the B=C ratio from 1.9 GV to
2.6 TV, based on 2.3 million boron and 8.3 million carbon nuclei collected by AMS during the first 5 years
of operation, is presented. The detailed variation with rigidity of the B=C spectral index is reported for the
first time. The B=C ratio does not show any significant structures in contrast to many cosmic ray models
that require such structures at high rigidities. Remarkably, above 65 GV, the B=C ratio is well described by
a single power law RΔ with index Δ ¼ −0.333 + 0.014ðfitÞ + 0.005ðsystÞ, in good agreement with the
Kolmogorov theory of turbulence which predicts Δ ¼ −1=3 asymptotically.
TL;DR: In this article, the sky localization of the first observed compact binary merger is presented, where the authors describe the low-latency analysis of the LIGO data and present a sky localization map.
Abstract: A gravitational-wave (GW) transient was identified in data recorded by the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) detectors on 2015 September 14. The event, initially designated G184098 and later given the name GW150914, is described in detail elsewhere. By prior arrangement, preliminary estimates of the time, significance, and sky location of the event were shared with 63 teams of observers covering radio, optical, near-infrared, X-ray, and gamma-ray wavelengths with ground- and space-based facilities. In this Letter we describe the low-latency analysis of the GW data and present the sky localization of the first observed compact binary merger. We summarize the follow-up observations reported by 25 teams via private Gamma-ray Coordinates Network circulars, giving an overview of the participating facilities, the GW sky localization coverage, the timeline, and depth of the observations. As this event turned out to be a binary black hole merger, there is little expectation of a detectable electromagnetic (EM) signature. Nevertheless, this first broadband campaign to search for a counterpart of an Advanced LIGO source represents a milestone and highlights the broad capabilities of the transient astronomy community and the observing strategies that have been developed to pursue neutron star binary merger events. Detailed investigations of the EM data and results of the EM follow-up campaign are being disseminated in papers by the individual teams.
TL;DR: Current challenges and possibilities to sustainably increase the biomass production are described and future technologies to further enhance biofuel production directly from sunlight are highlighted.
Abstract: Roadmaps towards sustainable bioeconomy, including the production of biofuels, in many EU countries mostly rely on biomass use. However, although biomass is renewable, the efficiency of biomass production is too low to be able to fully replace the fossil fuels. The use of land for fuel production also introduces ethical problems in increasing the food price. Harvesting solar energy by the photosynthetic machinery of plants and autotrophic microorganisms is the basis for all biomass production. This paper describes current challenges and possibilities to sustainably increase the biomass production and highlights future technologies to further enhance biofuel production directly from sunlight. The biggest scientific breakthroughs are expected to rely on a new technology called “synthetic biology”, which makes engineering of biological systems possible. It will enable direct conversion of solar energy to a fuel from inexhaustible raw materials: sun light, water and CO2. In the future, such solar biofuels are expected to be produced in engineered photosynthetic microorganisms or in completely synthetic living factories.
Yale University1, Massachusetts Institute of Technology2, University of Chicago3, Heidelberg University4, University of Turin5, University of Cambridge6, University of Turku7, University of Copenhagen8, University of Hawaii9, Hungarian Academy of Sciences10, Eötvös Loránd University11, University of La Laguna12, Spanish National Research Council13, University of Texas at Austin14, Polish Academy of Sciences15, University of Bern16, Ames Research Center17, Adler Planetarium18, Cornell University19, University of Helsinki20, University of Oxford21, Finnish Meteorological Institute22, ETH Zurich23, California Institute of Technology24
TL;DR: In this paper, the authors made use of data from the first public release of the WASP data (Butters et al. 2010) as provided by the NASA Exoplanet Archive, which is operated by the California Institute of Technology under contract with the National Aeronautics and Space Administration under the ERC grant number 279973.
Abstract: TSB acknowledges support provided through NASA grant ADAP12-0172 and ADAP14-0245. MCW and GMK acknowledge the support of the European Union through ERC grant number 279973. The authors acknowledge support from the Hungarian Research Grants OTKA K-109276, OTKA K-113117, the Lendulet-2009 and Lendulet-2012 Program (LP2012-31) of the Hungarian Academy of Sciences, the Hungarian National Research, Development and Innovation Office – NKFIH K-115709, and the ESA PECS Contract No. 4000110889/14/NL/NDe. This work was supported by the Momentum grant of the MTA CSFK Lendulet Disc Research Group. GH acknowledges support by the Polish NCN grant 2011/01/B/ST9/05448. Based on observations made with the NOT, operated by the Nordic Optical Telescope Scientific Association at the Observatorio del Roque de los Muchachos, La Palma, Spain, of the Instituto de Astrofisica de Canarias. This research made use of The DASCH project; we are also grateful for partial support from NSF grants AST-0407380, AST-0909073, and AST-1313370. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreements no. 269194 (IRSES/ASK) and no. 312844 (SPACEINN). We thank Scott Dahm, Julie Rivera, and the Keck Observatory staff for their assistance with these observations. This research was supported in part by NSF grant AST-0909222 awarded to M. Liu. The authors wish to recognize and acknowledge the very significant cultural role and reverence that the summit of Mauna Kea has always had within the indigenous Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain. KS gratefully acknowledges support from Swiss National Science Foundation Grant PP00P2_138979/1. HJD and DN acknowledge support by grant AYA2012-39346-C02-02 of the Spanish Secretary of State for R&D&i (MINECO). This paper makes use of data from the first public release of the WASP data (Butters et al. 2010) as provided by the WASP consortium and services at the NASA Exoplanet Archive, which is operated by the California Institute of Technology, under contract with the National Aeronautics and Space Administration under the Exoplanet Exploration Program. This publication makes use of data products from the Wide-field Infrared Survey Explorer, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, and NEOWISE, which is a project of the Jet Propulsion Laboratory/California Institute of Technology. WISE and NEOWISE are funded by the National Aeronautics and Space Administration. This research made use of the SIMBAD and VIZIER Astronomical Databases, operated at CDS, Strasbourg, France (http://cdsweb.u-strasbg.fr/), and of NASA's Astrophysics Data System.
University of Amsterdam1, University of Southampton2, Massachusetts Institute of Technology3, INAF4, Technische Universität Darmstadt5, University of Illinois at Urbana–Champaign6, University of Maryland, College Park7, University of Alberta8, University of Arizona9, Leiden University10, University of Turku11, University of Tennessee12, Spanish National Research Council13
TL;DR: In this paper, the authors used waveform modeling to determine the equation of state at supranuclear densities inside neutron stars by measuring the radius of neutron stars with different masses to accuracies of a few percent.
Abstract: One of the primary science goals of the next generation of hard x-ray timing instruments is to determine the equation of state of matter at supranuclear densities inside neutron stars by measuring the radius of neutron stars with different masses to accuracies of a few percent. Three main techniques can be used to achieve this goal. The first involves waveform modeling. The flux observed from a hotspot on the neutron star surface offset from the rotational pole will be modulated by the star’s rotation, and this periodic modulation at the spin frequency is called a pulsation. As the photons propagate through the curved spacetime of the star, information about mass and radius is encoded into the shape of the waveform (pulse profile) via special and general-relativistic effects. Using pulsations from known sources (which have hotspots that develop either during thermonuclear bursts or due to channeled accretion) it is possible to obtain tight constraints on mass and radius. The second technique involves characterizing the spin distribution of accreting neutron stars. A large collecting area enables highly sensitive searches for weak or intermittent pulsations (which yield spin) from the many accreting neutron stars whose spin rates are not yet known. The most rapidly rotating stars provide a clean constraint, since the limiting spin rate where the equatorial surface velocity is comparable to the local orbital velocity, at which mass shedding occurs, is a function of mass and radius. However, the overall spin distribution also provides a guide to the torque mechanisms in operation and the moment of inertia, both of which can depend sensitively on dense matter physics. The third technique is to search for quasiperiodic oscillations in x-ray flux associated with global seismic vibrations of magnetars (the most highly magnetized neutron stars), triggered by magnetic explosions. The vibrational frequencies depend on stellar parameters including the dense matter equation of state, and large-area x-ray timing instruments would provide much improved detection capability. An illustration is given of how these complementary x-ray timing techniques can be used to constrain the dense matter equation of state and the results that might be expected from a 10 m2 instrument are discussed. Also discussed are how the results from such a facility would compare to other astronomical investigations of neutron star properties.